WorldWideScience

Sample records for ladar based object

  1. ALLFlight: detection of moving objects in IR and ladar images

    Science.gov (United States)

    Doehler, H.-U.; Peinecke, Niklas; Lueken, Thomas; Schmerwitz, Sven

    2013-05-01

    Supporting a helicopter pilot during landing and takeoff in degraded visual environment (DVE) is one of the challenges within DLR's project ALLFlight (Assisted Low Level Flight and Landing on Unprepared Landing Sites). Different types of sensors (TV, Infrared, mmW radar and laser radar) are mounted onto DLR's research helicopter FHS (flying helicopter simulator) for gathering different sensor data of the surrounding world. A high performance computer cluster architecture acquires and fuses all the information to get one single comprehensive description of the outside situation. While both TV and IR cameras deliver images with frame rates of 25 Hz or 30 Hz, Ladar and mmW radar provide georeferenced sensor data with only 2 Hz or even less. Therefore, it takes several seconds to detect or even track potential moving obstacle candidates in mmW or Ladar sequences. Especially if the helicopter is flying with higher speed, it is very important to minimize the detection time of obstacles in order to initiate a re-planning of the helicopter's mission timely. Applying feature extraction algorithms on IR images in combination with data fusion algorithms of extracted features and Ladar data can decrease the detection time appreciably. Based on real data from flight tests, the paper describes applied feature extraction methods for moving object detection, as well as data fusion techniques for combining features from TV/IR and Ladar data.

  2. Supercomputer-based advanced ladar imaging simulator (ALIS)

    Science.gov (United States)

    Smith, Duane D.; Nichols, Terry L.; Gatt, Philip; Lee, Kotik K.; Sicking, Charles; Seida, Steven B.; Coker, Charles F.; Perry, Kimberly M.; Coker, Jason S.

    2004-01-01

    The Advanced Ladar Imaging Simulator (ALIS) is a comprehensive multi-dimensional laser radar system simulator that models complex atmospheric scenes combined with high-resolution solid object scenes. The primary functions of ALIS are to serve as a laser radar sensor design tool, data product generator for exploitation, and a decision aid for implementing system designs. This paper focuses on the software structure of the simulator and the challenges that it presents. The ambient atmospheric scene generation is augmented with built-in approximate plume models or with external large-scale Navier-Stokes computational fluid dynamics plume models. The mixed atmosphere and solid object scene is generated via an adaptively meshed, over-sampled voxel representation predicated jointly on the sensor capabilities and scene complexity. To our knowledge, ALIS goes beyond previous ladar simulators with detailed atmospheric turbulence effects and time-dependent plume dispersion models for direct and coherent detection frequency-agile transceivers. ALIS models a wide range of ladar architectures, treating laser coherence properties, receiver electronics noise/transfer functions, and electronics/photon statistical noise. It provides complex amplitude ladar echo "range cubes" (all range reports along a given line-of-sight) for the composite atmosphere-solid scene. The model complexity and its capability to process large (>109) voxel count scenes is accommodated with a portable, scalable software architecture that supports single processors to fine-grained parallel supercomputers.

  3. Development features of atmospheric LD ladar based on the CW-FM-range-finding principles

    Science.gov (United States)

    Agishev, Ravil R.; Comeron, Adolfo; Duch, Lluis; Sagdiev, Rafael K.; Dios, Victor F.; Cifuentes, Jose Carlos; Lopez, Miguel Angel

    2004-02-01

    Elements of spectroscopic continuous-wave, frequency-modulated ladar (CW-FM-ladar) concept based on principles of both CW-FM-range-finding and modulation spectroscopy, and also on modern techniques of optical signal transmission, reception and processing are presented. Features of heterodyning methods for ladar echo-signal reception are considered. The comparison of CW-FM-ladar with CW-FM-range-finder and incoherent pulse lidar is carried out. Estimations of the achievable signal-to-noise ratio, the operation range and the range resolution are performed using frequency-dependent parameters of the transmitting and receiving subsystems. Preliminary experimental results on the range-finding subsystem characteristics of the CW-FM-laser diode (LD)-ladar are discussed.

  4. Precision and Accuracy Testing of FMCW Ladar Based Length Metrology

    CERN Document Server

    Mateo, Ana Baselga

    2015-01-01

    The calibration and traceability of high resolution frequency modulated continuous wave (FMCW) ladar sources is a requirement for their use in length and volume metrology. We report the calibration of a FMCW ladar length measurement system by use of spectroscopy of molecular frequency references HCN (C-band) or CO (L-band) to calibrate the chirp rate of the FMCW source. Propagating the stated uncertainties from the molecular calibrations provided by NIST and measurement errors provides an estimated uncertainty of a few ppm for the FMCW system. As a test of this calibration, a displacement measurement interferometer with a laser wavelength close to that of our FMCW system was built to make comparisons of the relative precision and accuracy. The comparisons performed show ppm agreement which is within the combined estimated uncertainties of the FMCW system and interferometer.

  5. Multispectral sensor fusion for ground-based target orientation estimation: FLIR, ladar, HRR

    Science.gov (United States)

    Kostakis, Joseph; Cooper, Matthew L.; Green, Thomas J., Jr.; Miller, Michael I.; O'Sullivan, Joseph A.; Shapiro, Jeffrey H.; Snyder, Donald L.

    1999-08-01

    In our earlier work, we focused on pose estimation of ground- based targets as viewed via forward-looking passive infrared (FLIR) systems and laser radar (LADAR) imaging sensors. In this paper, we will study individual and joint sensor performance to provide a more complete understanding of our sensor suite. We will also study the addition of a high range- resolution radar (HRR). Data from these three sensors are simulated using CAD models for the targets of interest in conjunction with XPATCH range radar simulation software, Silicon Graphics workstations and the PRISM infrared simulation package. Using a Lie Group representation of the orientation space and a Bayesian estimation framework, we quantitatively examine both pose-dependent variations in performance, and the relative performance of the aforementioned sensors via mean squared error analysis. Using the Hilbert-Schmidt norm as an error metric, the minimum mean squared error (MMSE) estimator is reviewed and mean squared error (MSE) performance analysis is presented. Results of simulations are presented and discussed. In our simulations, FLIR and HRR sensitivities were characterized by their respective signal-to-noise ratios (SNRs) and the LADAR by its carrier-to-noise ratio (CNR). These figures-of-merit can, in turn, be related to the sensor, atmosphere, and target parameters for scenarios of interest.

  6. Pose recognition of articulated target based on ladar range image with elastic shape analysis

    Science.gov (United States)

    Liu, Zheng-Jun; Li, Qi; Wang, Qi

    2014-10-01

    Elastic shape analysis is introduced for pose recognition of articulated target which is based on small samples of ladar range images. Shape deformations caused by poses changes represented as closed elastic curves given by the square-root velocity function geodesics are used to quantify shape differences and the Karcher mean is used to build a model library. Three kinds of moments - Hu moment invariants, affine moment invariants, and Zernike moment invariants based on support vector machines (SVMs) - are applied to evaluate this approach. The experiment results show that no matter what the azimuth angles of the testing samples are, this approach is capable of achieving a high recognition rate using only 3 model samples with different carrier to noise ratios (CNR); the performance of this approach is much better than that of three kinds of moments based on SVM, especially under high noise conditions.

  7. Spectral ladar: towards active 3D multispectral imaging

    Science.gov (United States)

    Powers, Michael A.; Davis, Christopher C.

    2010-04-01

    In this paper we present our Spectral LADAR concept, an augmented implementation of traditional LADAR. This sensor uses a polychromatic source to obtain range-resolved 3D spectral images which are used to identify objects based on combined spatial and spectral features, resolving positions in three dimensions and up to hundreds of meters in distance. We report on a proof-of-concept Spectral LADAR demonstrator that generates spectral point clouds from static scenes. The demonstrator transmits nanosecond supercontinuum pulses generated in a photonic crystal fiber. Currently we use a rapidly tuned receiver with a high-speed InGaAs APD for 25 spectral bands with the future expectation of implementing a linear APD array spectrograph. Each spectral band is independently range resolved with multiple return pulse recognition. This is a critical feature, enabling simultaneous spectral and spatial unmixing of partially obscured objects when not achievable using image fusion of monochromatic LADAR and passive spectral imagers. This enables higher identification confidence in highly cluttered environments such as forested or urban areas (e.g. vehicles behind camouflage or foliage). These environments present challenges for situational awareness and robotic perception which can benefit from the unique attributes of Spectral LADAR. Results from this demonstrator unit are presented for scenes typical of military operations and characterize the operation of the device. The results are discussed here in the context of autonomous vehicle navigation and target recognition.

  8. MBE based HgCdTe APDs and 3D LADAR sensors

    Science.gov (United States)

    Jack, Michael; Asbrock, Jim; Bailey, Steven; Baley, Diane; Chapman, George; Crawford, Gina; Drafahl, Betsy; Herrin, Eileen; Kvaas, Robert; McKeag, William; Randall, Valerie; De Lyon, Terry; Hunter, Andy; Jensen, John; Roberts, Tom; Trotta, Patrick; Cook, T. Dean

    2007-04-01

    Raytheon is developing HgCdTe APD arrays and sensor chip assemblies (SCAs) for scanning and staring LADAR systems. The nonlinear characteristics of APDs operating in moderate gain mode place severe requirements on layer thickness and doping uniformity as well as defect density. MBE based HgCdTe APD arrays, engineered for high performance, meet the stringent requirements of low defects, excellent uniformity and reproducibility. In situ controls for alloy composition and substrate temperature have been implemented at HRL, LLC and Raytheon Vision Systems and enable consistent run to run results. The novel epitaxial designed using separate absorption-multiplication (SAM) architectures enables the realization of the unique advantages of HgCdTe including: tunable wavelength, low-noise, high-fill factor, low-crosstalk, and ambient operation. Focal planes built by integrating MBE detectors arrays processed in a 2 x 128 format have been integrated with 2 x 128 scanning ROIC designed. The ROIC reports both range and intensity and can detect multiple laser returns with each pixel autonomously reporting the return. FPAs show exceptionally good bias uniformity Naval Air Warfare Center Weapons Division at China Lake. Excellent spatial and range resolution has been achieved with 3D imagery demonstrated both at short range and long range. Ongoing development under an Air Force Sponsored MANTECH program of high performance HgCdTe MBE APDs grown on large silicon wafers promise significant FPA cost reduction both by increasing the number of arrays on a given wafer and enabling automated processing.

  9. EO Scanned Micro-LADAR Project

    National Aeronautics and Space Administration — In this SBIR program we will develop, design and build new scanning based micro-ladar sensors with unprecedented small size, weight, and power (SWaP), thereby...

  10. EO Scanned Micro-LADAR Project

    National Aeronautics and Space Administration — In this phase II SBIR we will design, build, test, and deliver new scanning based micro-ladar sensors with unprecedented small size, weight, and power (SWaP),...

  11. Advanced measurements optical range (AMOR) ladar test facility

    Science.gov (United States)

    Keffer, Charles E.; Papetti, Thomas J.; Johnson, Eddie

    2007-04-01

    The Advanced Measurements Optical Range (AMOR) began operations in 1978 with a mission to measure ladar target signatures of ballistic missiles and to advance the understanding of object features useful for discrimination of reentry vehicles from decoy objects. Ground breaking ladar technology developments and pioneering ladar target signature studies were completed in the early years of AMOR operations. More recently, AMOR functions primarily as a user test facility measuring ladar signatures of a diverse set of objects such as reentry vehicles and decoys, missile bodies, and satellite materials as well as serving as a ladar sensor test-bed to recreate realistic missile defense engagement scenarios to exercise and test missile seeker technologies. This paper gives a status report on current AMOR capabilities including the optical system, target handling system, laser systems, and data measurement types. Plans for future facility enhancements to provide improved service to ladar data users in the modeling and simulation field and to ladar system developers with requirements for advanced test requirements are also reported.

  12. Miniature Ground Mapping LADAR Project

    National Aeronautics and Space Administration — System & Processes Engineering Corporation (SPEC) proposes a miniature solid state surface imaging LADAR, for imaging the landing areas providing precision...

  13. Ultra-compact, High Resolution, LADAR system for 3D Imaging Project

    National Aeronautics and Space Administration — SiWave proposes to develop an innovative, ultra-compact, high resolution, long range LADAR system to produce a 3D map of the exterior of any object in space such as...

  14. Optical phased-array ladar.

    Science.gov (United States)

    Montoya, Juan; Sanchez-Rubio, Antonio; Hatch, Robert; Payson, Harold

    2014-11-01

    We demonstrate a ladar with 0.5 m class range resolution obtained by integrating a continuous-wave optical phased-array transmitter with a Geiger-mode avalanche photodiode receiver array. In contrast with conventional ladar systems, an array of continuous-wave sources is used to effectively pulse illuminate a target by electro-optically steering far-field fringes. From the reference frame of a point in the far field, a steered fringe appears as a pulse. Range information is thus obtained by measuring the arrival time of a pulse return from a target to a receiver pixel. This ladar system offers a number of benefits, including broad spectral coverage, high efficiency, small size, power scalability, and versatility. PMID:25402923

  15. Development principles of frequency-modulated CW-ladar for remote detection of atmospheric trace constituents

    Science.gov (United States)

    Agishev, Ravil R.; Sagdiev, Rafael K.; Gross, Barry; Moshary, Fred; Gilerson, Alexander; Ahmed, Samir; Comeron, Adolfo

    2004-09-01

    In this paper we present a general methodology for a frequency-modulated ladar/lidar (CW-FM-ladar/lidar) concept based on principles of both CW-FM-range-finding and modulation spectroscopy, together with modern techniques of optical signal transmission using tunable laser diodes, signal detection and heterodyne processing. We develop a mathematical description of trace gas detection using CW-LD ladar developing the relationship between the heterodyne echo-signal amplitudes and frequencies and trace gas concentration for each range. In particular, precise range and gas retrieval resolution limits based on the transmitting signal modulation and absorption line parameters are obtained.

  16. Self-mixing detector candidates for an FM/cw ladar architecture

    Science.gov (United States)

    Ruff, William C.; Bruno, John D.; Kennerly, Stephen W.; Ritter, Ken; Shen, Paul H.; Stann, Barry L.; Stead, Michael R.; Sztankay, Zoltan G.; Tobin, Mary S.

    2000-09-01

    The U.S. Army Research Laboratory (ARL) is currently investigating unique self-mixing detectors for ladar systems. These detectors have the ability to internally detect and down-convert light signals that are amplitude modulated at ultra-high frequencies (UHF). ARL is also investigating a ladar architecture based on FM/cw radar principles, whereby the range information is contained in the low-frequency mixing product derived by mixing a reference UHF chirp with a detected, time-delayed UHF chirp. When inserted into the ARL FM/cw ladar architecture, the self-mixing detector eliminates the need for wide band transimpedance amplifiers in the ladar receiver because the UHF mixing is done internal to the detector, thereby reducing both the cost and complexity of the system and enhancing its range capability. This fits well with ARL's goal of developing low-cost, high-speed line array ladars for submunition applications and extremely low-cost, single pixel ladars for ranging applications. Several candidate detectors have been investigated for this application, with metal-semiconductor-metal (MSM) detectors showing the most promise. This paper discusses the requirements for a self-mixing detector, characterization measurements from several candidate detectors and experimental results from their insertion in a laboratory FM/cw ladar.

  17. Synthetic aperture ladar concept for infrastructure monitoring

    Science.gov (United States)

    Turbide, Simon; Marchese, Linda; Terroux, Marc; Bergeron, Alain

    2014-10-01

    Long range surveillance of infrastructure is a critical need in numerous security applications, both civilian and military. Synthetic aperture radar (SAR) continues to provide high resolution radar images in all weather conditions from remote distances. As well, Interferometric SAR (InSAR) and Differential Interferometric SAR (D-InSAR) have become powerful tools adding high resolution elevation and change detection measurements. State of the art SAR systems based on dual-use satellites are capable of providing ground resolutions of one meter; while their airborne counterparts obtain resolutions of 10 cm. D-InSAR products based on these systems could produce cm-scale vertical resolution image products. Deformation monitoring of railways, roads, buildings, cellular antennas, power structures (i.e., power lines, wind turbines, dams, or nuclear plants) would benefit from improved resolution, both in the ground plane and vertical direction. The ultimate limitation to the achievable resolution of any imaging system is its wavelength. State-of-the art SAR systems are approaching this limit. The natural extension to improve resolution is to thus decrease the wavelength, i.e. design a synthetic aperture system in a different wavelength regime. One such system offering the potential for vastly improved resolution is Synthetic Aperture Ladar (SAL). This system operates at infrared wavelengths, ten thousand times smaller than radar wavelengths. This paper presents a laboratory demonstration of a scaled-down infrastructure deformation monitoring with an Interferometric Synthetic Aperture Ladar (IFSAL) system operating at 1.5 ?m. Results show sub-millimeter precision on the deformation applied to the target.

  18. Characterization of InGaAs self-mixing detectors for chirp amplitude-modulated ladar (CAML)

    Science.gov (United States)

    Aliberti, Keith; Ruff, William C.; Shen, Hongen; Newman, Peter G.; Giza, Mark M.; Sarney, Wendy; Stead, Michael R.; Dammann, John; Mehandru, Rishabh; Ren, Fan

    2004-09-01

    The U.S. Army Research Laboratory (ARL) has developed a number of near-infrared, prototype laser detection and ranging (LADAR) Systems based on the chirp, amplitude-modulated LADAR (CAML) architecture. The use of self-mixing detectors in the receiver, that have the ability to internally detect and down-convert modulated optical signals, have significantly simplified the LADAR design. Recently, ARL has designed and fabricated single-pixel, self-mixing, InGaAs-based, metal-semiconductor-metal detectors to extend the LADAR operating wavelength to 1.55 mm and is currently in the process of designing linear arrays of such detectors. This paper presents fundamental detector characterization measurements of the new 1.55 mm detectors in the CAML architecture and some insights on the design of 1.55 ?m linear arrays.

  19. Characterization of a 32-element linear self-mixing detector array for an FM/cw ladar

    Science.gov (United States)

    Ruff, William C.; Aliberti, Keith; Giza, Mark M.; Shen, Paul H.; Stann, Barry L.; Stead, Michael R.

    2002-07-01

    The U.S. Army Research Laboratory (ARL) is investigating a ladar architecture based on FM/cw radar principles, whereby the range information is contained in the low-frequency mixing product derived by mixing a reference ultra-high frequency (UHF) chirp with a detected, time-delayed UHF chirp. ARL is also investigating the use of unique self-mixing detectors that have the ability to internally detect and down-convert light signals that are amplitude modulated at UHF. When inserted into the ARL FM/cw ladar architecture, the self-mixing detector eliminates the need for wide band transimpedance amplifiers in the ladar receiver thereby reducing both the cost and complexity of the system. ARL has fabricated a 32 element linear array of self-mixing detectors and incorporated it into a breadboard ladar using the ARL FM/cw architecture. This paper discusses the basic theory of detector operation, a description of the breadboard ladar and its components, and presents some fundamental measurements and imagery taken from the ladar using these unique detectors.

  20. Doublet Pulse Coherent Laser Radar for Orbital Debris Tracking of Resident Space Objects

    Science.gov (United States)

    Prasad, N.; Rudd, V.,; DiMarcantonio, A.; Sandford, S.

    2014-09-01

    In this paper, the development of a long range ladar system known as ExoSPEAR at NASA Langley Research Center for tracking rapidly moving resident space objects is discussed. Based on 100 W, nanosecond class, near-IR laser, this ladar system with coherent detection technique is currently being investigated for short dwell time measurements of resident space objects (RSOs) in LEO and beyond for space surveillance applications. This unique ladar architecture is configured using a continuously agile doublet-pulse waveform scheme coupled to a closed-loop tracking and control loop approach to simultaneously achieve mm class range precision and mm/s velocity precision and hence obtain unprecedented track accuracies. Salient features of the design architecture followed by performance simulations illustrating the dependence of range and velocity precision in LEO orbits on ladar power aperture product will be presented. Estimated limits on detectable optical cross sections of RSOs in LEO orbits will be analyzed. The suitability of this ladar for precision orbit determination will be discussed.

  1. Demonstration of advanced solid state ladar (DASSL)

    Science.gov (United States)

    Broome, Kent W.; Carstens, Anne M.; Hudson, J. Roger; Yates, Kenneth L.

    1997-08-01

    The Armament Directorate of Wright Laboratory is tasked with pursuing technologies that lead towards autonomous guidance for conventional munitions. Seeker technologies pursued include SAR, imaging infrared, millimeter wave, and laser radar seekers. Laser Radar, or LADAR, systems using uncooled diode pumped solid state lasers operating around 1 micrometers are active sensors providing high resolution range and intensity imagery. LADAR is not susceptible to variations common to thermal IR systems, allowing greater simplicity of autonomous target acquisition algorithms. Therefore, LADAR sensors combined with advanced algorithms provide robust seeker technology capable of autonomous precision guidance. The small smart bomb (SSB) is a next generation weapon concept requiring this precision guidance. The 250 pound SSB penetrator provides the lethality of 2000 pound penetrators by delivering 50 pounds of high explosive with surgical precision. Space limitations, tightly controlled impact conditions, and high weapon velocities suggest laser radar as a candidate seeker. This paper discusses phase I of the DASSL program in which SSB weapon requirements are flowed down to seeker requirements through a structured system requirement analysis, and discusses how these seeker requirements affect seeker design.

  2. Performance of an FM/cw prototype ladar using a 32-element linear self-mixing detector array

    Science.gov (United States)

    Ruff, William; Aliberti, Keith; Dammann, John; Giza, Mark; Shen, Paul; Stann, Barry

    2003-08-01

    The U.S. Army Research Laboratory (ARL) is investigating a ladar architecture based on FM/cw radar principles, whereby the range information is contained in the low-frequency mixing product derived by mixing a reference ultra-high frequency (UHF) chirp with an optically detected, time-delayed UHF chirp scattered from a target. ARL is also investigating the use of metal-semiconductor-metal (MSM) detectors as unique self-mixing detectors, which have the ability to internally detect and down-convert the modulated optical signals. ARL has recently incorporated a 1x32 element linear MSM self-mixing detector array into a prototype FM/cw ladar system and performed a series of characterization and outdoor image collection experiments using this prototype. This paper discusses the basic performance of the prototype system and presents some fundamental measurements as well as ladar imagery taken on the ARL Adelphi campus.

  3. A Comparative Study between Frequency-Modulated Continous Wave LADAR and Linear LiDAR

    Science.gov (United States)

    Massaro, R. D.; Anderson, J. E.; Nelson, J. D.; Edwards, J. D.

    2014-11-01

    Topographic Light Detection and Ranging (LiDAR) technology has advanced greatly in the past decade. Pulse repetition rates of terrestrial and airborne systems havemultiplied thus vastly increasing data acquisition rates. Geiger-mode and FLASH LiDAR have also become far more mature technologies. However, a new and relatively unknown technology is maturing rapidly: Frequency-Modulated Continuous Wave Laser Detection and Ranging (FMCW-LADAR). Possessing attributes more akin to modern radar systems, FMCWLADAR has the ability to more finely resolve objects separated by very small ranges. For tactical military applications (as described here), this can be a real advantage over single frequency, direct-detect systems. In fact, FMCW-LADAR can range resolve objects at 10-7 to 10-6 meter scales. FMCW-LADAR can also detect objects at greater range with less power. In this study, a FMCWLADAR instrument and traditional LiDAR instrument are compared. The co-located terrestrial scanning instruments were set up to perform simultaneous 3-D measurements of the given scene. Several targets were placed in the scene to expose the difference in the range resolution capabilities of the two instruments. The scans were performed at or nearly the same horizontal and vertical angular resolutions. It is demonstrated that the FMCW-LADAR surpasses the perfomance of the linear mode LiDAR scanner in terms of range resolution. Some results showing the maximum range acquisition are discussed but this was not studied in detail as the scanners' laser powers differed by a small amount. Applications and implications of this technology are also discussed.

  4. Multi-Dimensional, Non-Contact Metrology using Trilateration and High Resolution FMCW Ladar

    CERN Document Server

    Mateo, Ana Baselga

    2015-01-01

    Here we propose, describe, and provide experimental proof-of-concept demonstrations of a multi-dimensional, non-contact length metrology system design based on high resolution (millimeter to sub-100 micron) frequency modulated continuous wave (FMCW) ladar and trilateration based on length measurements from multiple, optical fiber-connected transmitters. With an accurate FMCW ladar source, the trilateration based design provides 3D resolution inherently independent of stand-off range and allows self-calibration to provide flexible setup of a field system. A proof-of-concept experimental demonstration was performed using a highly-stabilized, 2 THz bandwidth chirped laser source, two emitters, and one scanning emitter/receiver providing 1D surface profiles (2D metrology) of diffuse targets. The measured coordinate precision of < 200 microns was determined to be limited by laser speckle issues caused by diffuse scattering of the targets.

  5. Segmentation, classification, and pose estimation of maritime targets in flash-ladar imagery

    OpenAIRE

    Armbruster, Walter; Hammer, Marcus

    2012-01-01

    The paper presents new techniques for automatic segmentation, classification, and generic pose estimation of ships and boats in laser radar imagery. Segmentation, which primarily involves elimination of water reflections, is based on modeling surface waves and comparing the expected water reflection signature to the ladar intensity image. Shape classification matches a parametric shape representation of a generic ship hull with parameters extracted from the range image. The extracted paramete...

  6. Real-time 3D flash ladar imaging through GPU data processing

    Science.gov (United States)

    Wong, Chung M.; Bracikowski, Christopher; Baldauf, Brian K.; Havstad, Steven A.

    2011-01-01

    We present real-time 3D image processing of flash ladar data using our recently developed GPU parallel processing kernels. Our laboratory and airborne experiences with flash ladar focal planes have shown that per laser flash, typically only a small fraction of the pixels on the focal plane array actually produce a meaningful range signal. Therefore, to optimize overall data processing speed, the large quantity of uninformative data are filtered out and removed from the data stream prior to the mathematically intensive point cloud transformation processing. This front-end pre-processing, which largely consists of control flow instructions, is specific to the particular type of flash ladar focal plane array being used and is performed by the computer's CPU. The valid signals along with their corresponding inertial and navigation metadata are then transferred to a GPU device to perform range-correction, geo-location, and ortho-rectification on each 3D data point so that data from multiple frames can be properly tiled together either to create a wide-area map or to reconstruct an object from multiple look angles. GPU parallel processing kernels were developed using OpenCL. Postprocessing to perform fine registration between data frames via complex iterative steps also benefits greatly from this type of high-performance computing. The performance improvements obtained using GPU processing to create corrected 3D images and for frame-to-frame fine-registration are presented.

  7. 3D flash ladar at Raytheon

    Science.gov (United States)

    Halmos, Maurice J.; Jack, Michael D.; Asbrock, James F.; Anderson, C.; Bailey, Steven L.; Chapman, George; Gordon, E.; Herning, P. E.; Kalisher, Murray H.; Klaras, Louis F.; Kosai, Kim; Liquori, V.; Pines, Mike; Randall, Valerie; Reeder, Robin; Rosbeck, Joseph P.; Sen, Sanghamitra; Trotta, Patrick A.; Wetzel, P.; Hunter, Andrew T.; Jensen, John E.; DeLyon, T. J.; Trussell, Charlie W.; Hutchinson, James A.; Balcerak, Raymond S.

    2001-09-01

    Raytheon has recently been funded by DARPA to develop an FPA for single shot eyesafe ladar operation. The goal of the program is to develop new high speed imaging rays to rapidly acquire high resolution, 3D images of tactical targets at ranges as long as 7 to 10 kilometers. This would provide precision strike, target identification from rapidly moving platforms, such as air-to-ground seekers, which would enhance counter-counter measure performance and the ability to lock-on after launch. Also a goal is to demonstrate the acquisition of hidden, camouflaged and partially obscured targets. Raytheon's approach consists of using HgCdTe APD arrays which offer unique advantages for high performance eyesafe LADAR sensors. These include: eyesafe operation at room temperature, low excess noise, high gain to overcome thermal and preamp noise, Ghz bandwidth and high packing density. The detector array will be coupled with a Readout Integrated Circuit, that will capture all the information required for accurate range determination. The two components encompass a hybrid imaging array consisting of two IC circuit chips vertically integrated via an array of indium metal 'bumps'. The chip containing the PAD detector array and the silicon signal processing readout chip are independently optimized to provide the highest possible performance for each function.

  8. A low-power CMOS trans-impedance amplifier for FM/cw ladar imaging system

    Science.gov (United States)

    Hu, Kai; Zhao, Yi-qiang; Sheng, Yun; Zhao, Hong-liang; Yu, Hai-xia

    2013-09-01

    A scannerless ladar imaging system based on a unique frequency modulation/continuous wave (FM/cw) technique is able to entirely capture the target environment, using a focal plane array to construct a 3D picture of the target. This paper presents a low power trans-impedance amplifier (TIA) designed and implemented by 0.18 ?m CMOS technology, which is used in the FM/cw imaging ladar with a 64×64 metal-semiconductor-metal(MSM) self-mixing detector array. The input stage of the operational amplifier (op amp) in TIA is realized with folded cascade structure to achieve large open loop gain and low offset. The simulation and test results of TIA with MSM detectors indicate that the single-end trans-impedance gain is beyond 100 k?, and the -3 dB bandwidth of Op Amp is beyond 60 MHz. The input common mode voltage ranges from 0.2 V to 1.5 V, and the power dissipation is reduced to 1.8 mW with a supply voltage of 3.3 V. The performance test results show that the TIA is a candidate for preamplifier of the read-out integrated circuit (ROIC) in the FM/cw scannerless ladar imaging system.

  9. Development of a 3D Flash LADAR Video Camera for Entry, Decent and Landing Project

    National Aeronautics and Space Administration — Advanced Scientific Concepts, Inc. (ASC) has developed a 128 x 128 frame, 3D Flash LADAR video camera capable of a 30 Hz frame rate. Because Flash LADAR captures an...

  10. Development of a 3D Flash LADAR Video Camera for Entry, Decent, and Landing Project

    National Aeronautics and Space Administration — Advanced Scientific Concepts, Inc. (ASC) has developed a 128 x 128 frame, 3D Flash LADAR video camera which produces 3-D point clouds at 30 Hz. Flash LADAR captures...

  11. The effect of environment factors of ladar army on neurobehavioral function of military task population

    International Nuclear Information System (INIS)

    Objective: To evaluate the effect of the electromagnetic irradiation of ladar army on neurobehavioral function of military task population. Methods: 40 workers exposed to electromagnetic irradiation and 20 controls were investigated with questionnaire survey, profile of mood state and Some other neurobehavioral function tests. Results: Of all the rational symptoms, visual fatigue is ware obvious in the irradiation group and fatigue of POMS form of irradiation group have significant increased. The sum of the pursuit aiming test and the second self intercrossing test have obvious decreased. Conclusion: The mood state, hand operation ability and work efficiency in occupational people are affected by electromagnetic irradiation. (authors)

  12. Tower test results for an imaging LADAR seeker

    Science.gov (United States)

    Andressen, Cliff; Anthony, David; DaMommio, Tony; Hulsey, Don; Lawton, Clint; Neisz, James; Perona, Tay; Steinmehl, Doug; Grobmyer, Joe; Lum, Tommy

    2005-05-01

    Raytheon has developed a new tactical form-factored, imaging LADAR (LAser Detection And Ranging) seeker. In a joint activity with AMRDEC, the seeker was used in a tower test data collection at the Russell Measurement Facility at Redstone Arsenal, Alabama. The seeker collected 3D imagery of fixed structures and vehicles embedded in various clutter backgrounds for use in analysis of computer vision and automatic target recognition techniques. This paper presents a high-level overview of the seeker, a description of the test activities, representative LADAR range and intensity imagery collected during the test, and 3D rendered scenes constructed from the imagery.

  13. Retratamento de LASIK com fotoablação personalizada versus fotoablação convencional utilizando o LADAR: Alcon LASIK retreatment with customized versus conventional photo-ablation using LADAR: Alcon

    Directory of Open Access Journals (Sweden)

    Lucas Monferrari Monteiro Vianna

    2011-06-01

    Full Text Available OBJETIVO:Avaliar os resultados do retratamento convencional (LADAR, Alcon e do retratamento personalizado(LADARWave, Alcon em olhos submetidos a LASIK primário convencional. MÉTODOS: Estudo retrospectivo de revisão de prontuários consecutivos, de 38 olhos em 38 pacientes, submetidos a retratamento de LASIK para correção de miopia e astigmatismo. Os olhos operados foram divididos em dois grupos iguais. No primeiro grupo foi realizado o retratamento personalizado e, no outro, o retratamento convencional. As seguintes variáveis foram comparadas: acuidade visual de alto contraste e refração manifesta. A qualidade visual foi estimada e comparada através de inquérito subjetivo proposto aos pacientes. RESULTADOS: Não houve diferença estatística entre os grupos comparando-se as variáveis estudadas. O equivalente esférico pós-retratamento foi de 0,36 no grupo convencional e de 0,47 no personalizado (p=0,079. A acuidade visual de Snellen foi de 0,91 e 0,87, respectivamente, com p=0,07. O total de aberrações pré-operatório foi maior do que o pós-operatório no grupo personalizado (pOBJECTIVE: To evaluate the results of conventional (Ladar, Alcon and customized (LADARWave, Alcon retreatment ineyes undergoing conventional primary LASIK. METHODS: Retrospective revision of consecutive clinical report forms of 38 eyes of 38 patients who underwent LASIK retreatment for myopia and astigmatism. The operated eyes were divided into two equal groups. In the first was performed customized retreatment and, in the other, conventional retreatment. The following variables were compared: high contrast visual acuity and manifest refraction. The visual quality was estimated and compared using subjective survey offered to patients. RESULTS: There was no statistical difference between the groups when comparing the variables studied. The spherical equivalent after retreatment was 0.36 in the conventional group and 0.47 in the custom (p = 0.079. Snelen visual acuity was 0.91 and 0.87, respectively (p = 0.07. The preoperative total aberrations was higher than the postoperative period in custom group (p <0.001. In the conventional group there was no difference for any aberration evaluated. Complaints of glare (p = 0.117, photophobia (p = 0.987 and vision fluctuation (p = 0.545 were statistically similar between the two groups. CONCLUSION: Comparing the custom and conventional surgery for primary LASIK retreatment with LADAR, Alcon, there wasno statistical difference in the quantity and quality of vision. Nevertheless, there was a higher percentage of patients with complaints in relation to the visual quality in the group undergoing conventional surgery. Custom surgery seems to have greater capacity to reduce the total aberrations than conventional.

  14. A validation procedure for a LADAR system radiometric simulation model

    Science.gov (United States)

    Leishman, Brad; Budge, Scott; Pack, Robert

    2007-04-01

    The USU LadarSIM software package is a ladar system engineering tool that has recently been enhanced to include the modeling of the radiometry of Ladar beam footprints. This paper will discuss our validation of the radiometric model and present a practical approach to future validation work. In order to validate complicated and interrelated factors affecting radiometry, a systematic approach had to be developed. Data for known parameters were first gathered then unknown parameters of the system were determined from simulation test scenarios. This was done in a way to isolate as many unknown variables as possible, then build on the previously obtained results. First, the appropriate voltage threshold levels of the discrimination electronics were set by analyzing the number of false alarms seen in actual data sets. With this threshold set, the system noise was then adjusted to achieve the appropriate number of dropouts. Once a suitable noise level was found, the range errors of the simulated and actual data sets were compared and studied. Predicted errors in range measurements were analyzed using two methods: first by examining the range error of a surface with known reflectivity and second by examining the range errors for specific detectors with known responsivities. This provided insight into the discrimination method and receiver electronics used in the actual system.

  15. Synthetic aperture ladar imaging demonstrations and information at very low return levels.

    Science.gov (United States)

    Barber, Zeb W; Dahl, Jason R

    2014-08-20

    We present synthetic aperture ladar (SAL) imaging demonstrations where the return-signal level from the target is near the single-photon level per resolved pixel. Scenes consisting of both specular-point targets and diffuse-reflection, fully speckled targets are studied. Artificial retro-reflector-based phase references and/or phase-gradient-autofocus (PGA) algorithms were utilized for compensation of phase errors during the aperture motion. It was found that SAL images could reliably be formed with both methods even when the final max pixel intensity was at the few photon level, which means the SNR before azimuth compression is below unity. Mutual information-based comparison of SAL images show that average mutual information is reduced when the PGA is utilized for image-based phase compensation. The photon information efficiency of SAL and coherent imaging is discussed. PMID:25321130

  16. Perceptual Load Modulates Object-Based Attention

    Science.gov (United States)

    Ho, Ming-Chou; Atchley, Paul

    2009-01-01

    Two experimental series are reported using both reaction time (RT) and a data-limited perceptual report to examine the effects of perceptual load on object-based attention. Perceptual load was manipulated across 3 levels by increasing the complexity of perceptual judgments. Data from the RT-based experiments showed object-based effects when the…

  17. View-based 3-D object retrieval

    CERN Document Server

    Gao, Yue

    2014-01-01

    Content-based 3-D object retrieval has attracted extensive attention recently and has applications in a variety of fields, such as, computer-aided design, tele-medicine,mobile multimedia, virtual reality, and entertainment. The development of efficient and effective content-based 3-D object retrieval techniques has enabled the use of fast 3-D reconstruction and model design. Recent technical progress, such as the development of camera technologies, has made it possible to capture the views of 3-D objects. As a result, view-based 3-D object retrieval has become an essential but challenging res

  18. Geiger-mode APD camera system for single-photon 3D LADAR imaging

    Science.gov (United States)

    Entwistle, Mark; Itzler, Mark A.; Chen, Jim; Owens, Mark; Patel, Ketan; Jiang, Xudong; Slomkowski, Krystyna; Rangwala, Sabbir

    2012-06-01

    The unparalleled sensitivity of 3D LADAR imaging sensors based on single photon detection provides substantial benefits for imaging at long stand-off distances and minimizing laser pulse energy requirements. To obtain 3D LADAR images with single photon sensitivity, we have demonstrated focal plane arrays (FPAs) based on InGaAsP Geiger-mode avalanche photodiodes (GmAPDs) optimized for use at either 1.06 ?m or 1.55 ?m. These state-of-the-art FPAs exhibit excellent pixel-level performance and the capability for 100% pixel yield on a 32 x 32 format. To realize the full potential of these FPAs, we have recently developed an integrated camera system providing turnkey operation based on FPGA control. This system implementation enables the extremely high frame-rate capability of the GmAPD FPA, and frame rates in excess of 250 kHz (for 0.4 ?s range gates) can be accommodated using an industry-standard CameraLink interface in full configuration. Real-time data streaming for continuous acquisition of 2 ?s range gate point cloud data with 13-bit time-stamp resolution at 186 kHz frame rates has been established using multiple solid-state storage drives. Range gate durations spanning 4 ns to 10 ?s provide broad operational flexibility. The camera also provides real-time signal processing in the form of multi-frame gray-scale contrast images and single-frame time-stamp histograms, and automated bias control has been implemented to maintain a constant photon detection efficiency in the presence of ambient temperature changes. A comprehensive graphical user interface has been developed to provide complete camera control using a simple serial command set, and this command set supports highly flexible end-user customization.

  19. Processing 3D flash LADAR point-clouds in real-time for flight applications

    Science.gov (United States)

    Craig, R.; Gravseth, I.; Earhart, R. P.; Bladt, J.; Barnhill, S.; Ruppert, L.; Centamore, C.

    2007-04-01

    Ball Aerospace & Technologies Corp. has demonstrated real-time processing of 3D imaging LADAR point-cloud data to produce the industry's first time-of-flight (TOF) 3D video capability. This capability is uniquely suited to the rigorous demands of space and airborne flight applications and holds great promise in the area of autonomous navigation. It will provide long-range, three dimensional video information to autonomous flight software or pilots for immediate use in rendezvous and docking, proximity operations, landing, surface vision systems, and automatic target recognition and tracking. This is enabled by our new generation of FPGA based "pixel-tube" processors, coprocessors and their associated algorithms which have led to a number of advancements in high-speed wavefront processing along with additional advances in dynamic camera control, and space laser designs based on Ball's CALIPSO LIDAR. This evolution in LADAR is made possible by moving the mechanical complexity required for a scanning system into the electronics, where production, integration, testing and life-cycle costs can be significantly reduced. This technique requires a state of the art TOF read-out integrated circuit (ROIC) attached to a sensor array to collect high resolution temporal data, which is then processed through FPGAs. The number of calculations required to process the data is greatly reduced thanks to the fact that all points are captured at the same time and thus correlated. This correlation allows extremely efficient FPGA processing. This capability has been demonstrated in prototype form at both Marshal Space Flight Center and Langley Research Center on targets that represent docking and landing scenarios. This report outlines many aspects of this work as well as aspects of our recent testing at Marshall's Flight Robotics Laboratory.

  20. Coherent mode-locked 1.06-micron ladar transmitter

    Science.gov (United States)

    Papetti, Thomas J.; Pyles, C. H.; McMillan, Ronnie C.

    1992-06-01

    A coherent pulse-burst 1.06 (mu) ladar transmitter is described. The output consists of a 1.6 J, 800 microsecond(s) burst of 550 ps pulses occurring at a 50 MHz repetition rate. The burst repetition rate is 10 Hz. The optical frequency stability before coherent processing at the receiver is +/- 100 kHz. The transmitter consists of a CW-pumped mode-locked Nd:YAG oscillator followed by a pulsed double-pass amplifier, and is used as part of a calibrated range-Doppler imaging target signature measurement system

  1. Object manipulation facilitates kind-based object individuation of shape-similar objects

    DEFF Research Database (Denmark)

    Kingo, Osman Skjold; KrØjgaard, Peter

    2011-01-01

    Five experiments investigated the importance of shape and object manipulation when 12-month-olds were given the task of individuating objects representing exemplars of kinds in an event-mapping design. In Experiments 1 and 2, results of the study from Xu, Carey, and Quint (2004, Experiment 4) were partially replicated, showing that infants were able to individuate two natural-looking exemplars from different categories, but not two exemplars from the same category. In Experiment 3, infants failed to individuate two shape-similar exemplars (from Pauen, 2002a) from different categories. However, Experiment 4 revealed that allowing infants to manipulate objects shortly before the individuation task enabled them to individuate shape-similar objects from different categories. In Experiment 5, allowing object manipulation did not induce infants to individuate natural-looking objects from the same category. These findings suggest that object manipulation facilitates kind-based individuation of shape-similar objects by 12-month-olds. Keywords: Object individuation; Object shape; Object manipulation; Kind representations; Infancy

  2. Retratamento de LASIK com fotoablação personalizada versus fotoablação convencional utilizando o LADAR: Alcon / LASIK retreatment with customized versus conventional photo-ablation using LADAR: Alcon

    Scientific Electronic Library Online (English)

    Lucas Monferrari Monteiro, Vianna; Heloisa Moraes do, Nascimento; Mauro, Campos.

    2011-06-01

    Full Text Available OBJETIVO:Avaliar os resultados do retratamento convencional (LADAR, Alcon) e do retratamento personalizado(LADARWave, Alcon) em olhos submetidos a LASIK primário convencional. MÉTODOS: Estudo retrospectivo de revisão de prontuários consecutivos, de 38 olhos em 38 pacientes, submetidos a retratamento [...] de LASIK para correção de miopia e astigmatismo. Os olhos operados foram divididos em dois grupos iguais. No primeiro grupo foi realizado o retratamento personalizado e, no outro, o retratamento convencional. As seguintes variáveis foram comparadas: acuidade visual de alto contraste e refração manifesta. A qualidade visual foi estimada e comparada através de inquérito subjetivo proposto aos pacientes. RESULTADOS: Não houve diferença estatística entre os grupos comparando-se as variáveis estudadas. O equivalente esférico pós-retratamento foi de 0,36 no grupo convencional e de 0,47 no personalizado (p=0,079). A acuidade visual de Snellen foi de 0,91 e 0,87, respectivamente, com p=0,07. O total de aberrações pré-operatório foi maior do que o pós-operatório no grupo personalizado (p Abstract in english OBJECTIVE: To evaluate the results of conventional (Ladar, Alcon) and customized (LADARWave, Alcon) retreatment ineyes undergoing conventional primary LASIK. METHODS: Retrospective revision of consecutive clinical report forms of 38 eyes of 38 patients who underwent LASIK retreatment for myopia and [...] astigmatism. The operated eyes were divided into two equal groups. In the first was performed customized retreatment and, in the other, conventional retreatment. The following variables were compared: high contrast visual acuity and manifest refraction. The visual quality was estimated and compared using subjective survey offered to patients. RESULTS: There was no statistical difference between the groups when comparing the variables studied. The spherical equivalent after retreatment was 0.36 in the conventional group and 0.47 in the custom (p = 0.079). Snelen visual acuity was 0.91 and 0.87, respectively (p = 0.07). The preoperative total aberrations was higher than the postoperative period in custom group (p

  3. Advances in LADAR Components and Subsystems at Raytheon

    Science.gov (United States)

    Jack, Michael; Chapman, George; Edwards, John; McKeag, William; Veeder, Tricia; Wehner, Justin; Roberts, Tom; Robinson, Tom; Neisz, James; Andressen, Cliff; Rinker, Robert; Hall, Donald N. B.; Jacobson, Shane M.; Amzajerdian, Farzin; Cook, T. Dean

    2012-01-01

    Raytheon is developing NIR sensor chip assemblies (SCAs) for scanning and staring 3D LADAR systems. High sensitivity is obtained by integrating high performance detectors with gain, i.e., APDs with very low noise Readout Integrated Circuits (ROICs). Unique aspects of these designs include: independent acquisition (non-gated) of pulse returns, multiple pulse returns with both time and intensity reported to enable full 3D reconstruction of the image. Recent breakthrough in device design has resulted in HgCdTe APDs operating at 300K with essentially no excess noise to gains in excess of 100, low NEP <1nW and GHz bandwidths and have demonstrated linear mode photon counting. SCAs utilizing these high performance APDs have been integrated and demonstrated excellent spatial and range resolution enabling detailed 3D imagery both at short range and long ranges. In the following we will review progress in real-time 3D LADAR imaging receiver products in three areas: (1) scanning 256 x 4 configuration for the Multi-Mode Sensor Seeker (MMSS) program and (2) staring 256 x 256 configuration for the Autonomous Landing and Hazard Avoidance Technology (ALHAT) lunar landing mission and (3) Photon-Counting SCAs which have demonstrated a dramatic reduction in dark count rate due to improved design, operation and processing.

  4. Rapid and scalable 3D object recognition using LIDAR data

    Science.gov (United States)

    Matei, Bogdan C.; Tan, Yi; Sawhney, Harpreet S.; Kumar, Rakesh

    2006-05-01

    This paper describes a model-based 3D object recognition system, which makes use of 3D data acquired by LIDAR sensors. The system is based on a coarse-to-fine scheme for object indexing and verification to achieve high efficiency and accuracy. The system employs rotationally invariant semi-local spin image features for object representation and formulates the recognition process as a feature searching through a database, followed by a matching process guided by putative candidates between the query features and the model features. To achieve recognition efficiency with sublinear dependency on the size of the model database, an approximate nearest-neighbor method, the locality-sensitivity-hashing (LSH), is used for feature search. Geometrically constrained scene-model correspondences are used to generate alignment hypotheses that are refined during a matching and verification process for achieving high recognition accuracy. A large model database of commercial and military vehicles is used for experiments. Results on real data acquired with commercial LADAR sensor systems, mounted on either high-lift or airborne platforms are presented. Our results indicate that 3D object recognition on LADAR data is matured to the point that it is ready for real large-scale applications.

  5. Quantum enhancement of a coherent ladar receiver using phase-sensitive amplification

    OpenAIRE

    Shapiro, Jeffrey H.; Nair, Ranjith; Yen, Brent J.; Wong, Franco N. C.; Wasilousky, Peter A.; Smith, Kevin H.; Glasser, Ryan; Burdge, Geoffrey L.; Burberry, Lee; Deibner, Bill; Silver, Michael; Peach, Robert C.; Visone, Christopher; Kumar, Prem; Lim, Oo-kaw

    2011-01-01

    We demonstrate a balanced-homodyne LADAR receiver employing a phase-sensitive amplifier (PSA) to raise the effective photon detection efficiency (PDE) to nearly 100%. Since typical LADAR receivers suffer from losses in the receive optical train that routinely limit overall PDE to less than 50% thus degrading SNR, PSA can provide significant improvement through amplification with noise figure near 0 dB. Receiver inefficiencies arise from sub-unity quantum efficiency, array fill factors, signal...

  6. Ladar image recognition using synthetically derived discrete phase-amplitude filters in an optical correlator

    Science.gov (United States)

    Calloway, David; Goldstein, Dennis H.

    2002-03-01

    Correlation filters using computer-generated laser radar imagery have been constructed. This paper describes how the filters were constructed and reports correlating result with the synthetic imagery used in the training set, with real ladar imagery of equivalent targets, and with real ladar imagery of false targets. A comprehensive set of images was collected on the Eglin Test Range using a direct-detect scanning ladar mounted on a 100-meter tower. Various targets were placed on a large turntable and ladar range and intensity data were collected at various aspect and depression angles. The Irma scene generation software package was then used to generate synthetic ladar imagery for these targets at a similar set of range, aspect, and depression angles. Several different techniques were used to generate the filters and to process the imagery used in this research. This paper describes one of the most successful techniques. The paper provides details on the iterative approach used to generate composite filters, describes how they were applied, and compares the results produced from synthetic and real target imagery. This experiment was considered a success since the synthetically derived filters were capable of recognizing images of real targets while rejecting false targets.

  7. Research progress on a focal plane array ladar system using a laser diode transmitter and FM/cw radar principles

    Science.gov (United States)

    Stann, Barry L.; Abou-Auf, Ahmed; Aliberti, Keith; Giza, Mark M.; Ovrebo, Greg; Ruff, William C.; Simon, Deborah R.; Stead, Michael R.

    2002-07-01

    The Army Research Laboratory is developing scannerless ladar systems for smart munition and reconnaissance applications. Here we report on progress attained over the past year related to the construction of a 32x32 pixel ladar. The 32x32 pixel architecture achieves ranging based on a frequency modulation/continuous wave (FM/cw) technique implemented by directly amplitude modulating a near-IR diode laser transmitter with a radio frequency (rf) subcarrier that is linearly frequency modulated. The diode's output is collected and projected to form an illumination field in the downrange image area. The returned signal is focused onto an array of metal-semiconductor-metal (MSM) detectors where it is detected and mixed with a delayed replica of the laser modulation signal that modulates the responsivity of each detector. The output of each detector is an intermediate frequency (IF) signal (a product of the mixing process) whose frequency is proportional to the target range. This IF signal is continuously sampled over each period of the rf modulation. Following this, a N channel signal processor based-on field-programmable gate arrays calculates the discrete Fourier transform over the IF waveform in each pixel to establish the ranges to all the scatterers and their respective amplitudes. Over the past year, we have built one and two-dimensional self-mixing MSM detector arrays at .8 and 1.55 micrometers , designed and built circuit boards for reading data out of a 32x32 pixel array, and designed an N channel FPGA signal processor for high-speed formation of range gates. In this paper we report on the development and performance of these components and the results of system tests conducted in the laboratory.

  8. Research progess on scannerless ladar systems using a laser diode transmitter and FM/cw radar principles

    Science.gov (United States)

    Stann, Barry L.; Abou-Auf, Ahmed; Frankel, Scott; Giza, Mark M.; Potter, William; Ruff, William C.; Shen, Paul H.; Simon, Deborah R.; Stead, Michael R.; Sztankay, Zoltan G.; Lester, Luke F.

    2001-09-01

    The Army Research Laboratory is researching scannerless ladar systems for smart munition and reconnaissance applications. Here we report on progress attained over the past year related to the systems architectures, component development, and test results of the scannerless ladars. The imaging system architectures achieve ranging based on a frequency modulation/continuous wave technique implemented by directly amplitude modulation a near-IR diode laser transmitter with a radio frequency subcarrier that is linearly frequency modulated. The diode's output is collected and projected to from an illumination field in the downrange image area. The returned signal is focused onto an array of metal-semiconductor-metal (MSM) detectors where it is detected and mixed with a delayed replica of the laser modulation signal that modulates the responsivity of each detector. The output of each detector is an intermediate frequency signal whose frequency is proportional to the target range. This IF signal is continuously sampled over each period of the rf modulation. Following this, an N channel signal processor based-on field-programmable gate arrays calculates the discrete Fourier transform over the IF waveform in each pixel to establish the ranges to all the scatterers and their respective amplitudes. Over the past year, we have continued development of laser illuminators at .8 and 1.55 micrometers , built 1D self-mixing MSM detector arrays at .8 and 1.55 micrometers and built an N channel FPGA signal processor for high-speed formation of range gates. In this paper we report on the development and performance of these components and the results of system test conducted in the laboratory.

  9. Monitoring objects orbiting earth using satellite-based telescopes

    Energy Technology Data Exchange (ETDEWEB)

    Olivier, Scot S.; Pertica, Alexander J.; Riot, Vincent J.; De Vries, Willem H.; Bauman, Brian J.; Nikolaev, Sergei; Henderson, John R.; Phillion, Donald W.

    2015-06-30

    An ephemeris refinement system includes satellites with imaging devices in earth orbit to make observations of space-based objects ("target objects") and a ground-based controller that controls the scheduling of the satellites to make the observations of the target objects and refines orbital models of the target objects. The ground-based controller determines when the target objects of interest will be near enough to a satellite for that satellite to collect an image of the target object based on an initial orbital model for the target objects. The ground-based controller directs the schedules to be uploaded to the satellites, and the satellites make observations as scheduled and download the observations to the ground-based controller. The ground-based controller then refines the initial orbital models of the target objects based on the locations of the target objects that are derived from the observations.

  10. University collections and object-based pedagogies

    Directory of Open Access Journals (Sweden)

    Andrew Simpson

    2012-10-01

    Full Text Available Engagement with objects, either directly or through digital media, has long been recognized as a viable, constructivist pedagogy, capable of mediating significant meaning and context. The increasing uptake of digital technologies in university learning and teaching programs provides a timely opportunity for integrating museum and collection data and metadata in these programs. This project looked at the use of university museum and collection objects in teaching programs through a controlled experiment. A group of students were exposed directly to collection objects while another group was exposed to their digital surrogate. Students were then tested at later stages concerning their recall of didactic information. Results clearly show that students exposed to the original object had far better didactic recall over a longer time period than students exposed to their digital surrogates. This has implications for the development and rapid expansion of online education delivery in the tertiary education sector and elsewhere and the role university collections can play.

  11. Saliency-based object recognition in video

    OpenAIRE

    González-Díaz, Iván; Boujut, Hugo; Buso, Vincent; Benois-Pineau, Jenny; Domenger, Jean-Philippe

    2013-01-01

    In this paper we study the problem of object recognition in egocentric video recorded with cameras worn by persons. This task has gained much attention during the last years, since it has turned to be a main building block for action recognition systems in applications involving wearable cameras, such as tele-medicine or lifelogging. Under these scenarios, an action can be effectively de?ned as a sequence of manipulated or observed objects, so that recognition becomes a relevant stage of the ...

  12. Action modulates object-based selection.

    OpenAIRE

    Linnell, Kj; Humphreys, Gw; Mcintyre, Db; Laitinen, S.; Wing, Am

    2005-01-01

    Cueing attention to one part of an object can facilitate discrimination in another part (Experiment 1 [Duncan, j. (1984). Selective attention and the organization of visual information. Journal of Experimental Psychology: General, 113, 501-517]; [Egly, R., Driver, J., and Rafal, R. D. (1994). Shifting visual attention between objects and locations: evidence from normal and parietal lesion divisions. Journal of Experimental Psychology: Human Perception and Performance, 123, 161-177]). We show ...

  13. Coherent backscatter: measurement of the retroreflective BRDF peak exhibited by several surfaces relevant to ladar applications

    Science.gov (United States)

    Papetti, Thomas J.; Walker, William E.; Keffer, Charles E.; Johnson, Billy E.

    2007-09-01

    The sharp retroreflective peak that is commonly exhibited in the bidirectional reflectivity distribution function of diffuse surfaces was investigated for several materials relevant to ladar applications. The accurate prediction of target cross-sections requires target surface BRDF measurements in the vicinity of this peak. Measurements were made using the beamsplitter-based scatterometer at the U.S. Army's Advanced Measurements Optical Range (AMOR) at Redstone Arsenal, Alabama. Co-polarized and cross-polarized BRDF values at 532 nm and 1064 nm were obtained as the bistatic angle was varied for several degrees about, and including, the monostatic point with a resolution of better than 2 mrad. Measurements covered a wide range of incidence angles. Materials measured included polyurethane coated nylons (PCNs), Spectralon, a silica phenolic, and various paints. For the co-polarized case, a retroreflective peak was found to be nearly ubiquitous for high albedo materials, with relative heights as great as 1.7 times the region surrounding the peak and half-widths between 0.11° and 1.3°. The shape of the observed peaks very closely matched coherent backscattering theory, though the phenomena observed could not be positively attributed to coherent backscattering or shadow hiding alone. Several data features were noted that may be of relevance to modelers of these phenomena, including the fact that the widths of the peaks were approximately the same for 532 nm as for 1064 nm and an observation that at large incidence angles, the width of the peak usually broadened in the in-plane bistatic direction.

  14. Object Recognition Based on Dual Tree Complex Wavelet Transform

    Directory of Open Access Journals (Sweden)

    S. Elakkiya

    2014-05-01

    Full Text Available Automated recognition of objects from images plays an important role in many computer vision systems such as robot navigation, object manipulation and content based image retrieval. In this study, an approach for object recognition based on Dual Tree Complex Wavelet Transform (DTCWT is proposed. The proposed approach attempts to extract the detailed information of objects from the multi scale representation by DTCWT. The proposed system is tested on Columbia Object Image Library (COIL-100. All the objects are considered for the classification based on nearest neighbor classifier. The results show that the maximum recognition accuracy achieved by the proposed approach is 97.03%.

  15. Image-Based Multiresolution Implicit Object Modeling

    OpenAIRE

    Sarti Augusto; Tubaro Stefano

    2002-01-01

    We discuss two image-based 3D modeling methods based on a multiresolution evolution of a volumetric function?s level set. In the former method, the role of the level set implosion is to fuse ("sew" and "stitch") together several partial reconstructions (depth maps) into a closed model. In the later, the level set?s implosion is steered directly by the texture mismatch between views. Both solutions share the characteristic of operating in an adaptive multiresolution fashion, in or...

  16. Content-Based Object Movie Retrieval and Relevance Feedbacks

    OpenAIRE

    Greg C. Lee; Yi-Ping Hung; Li-Wei Chan; Cheng-Chieh Chiang

    2007-01-01

    Object movie refers to a set of images captured from different perspectives around a 3D object. Object movie provides a good representation of a physical object because it can provide 3D interactive viewing effect, but does not require 3D model reconstruction. In this paper, we propose an efficient approach for content-based object movie retrieval. In order to retrieve the desired object movie from the database, we first map an object movie into the sampling of a manifold in the feature spac...

  17. Image-Based Multiresolution Implicit Object Modeling

    Directory of Open Access Journals (Sweden)

    Augusto Sarti

    2002-10-01

    Full Text Available We discuss two image-based 3D modeling methods based on a multiresolution evolution of a volumetric function′s level set. In the former method, the role of the level set implosion is to fuse (“sew” and “stitch” together several partial reconstructions (depth maps into a closed model. In the later, the level set′s implosion is steered directly by the texture mismatch between views. Both solutions share the characteristic of operating in an adaptive multiresolution fashion, in order to boost up computational efficiency and robustness.

  18. Image-Based Multiresolution Implicit Object Modeling

    OpenAIRE

    Augusto Sarti; Stefano Tubaro

    2002-01-01

    We discuss two image-based 3D modeling methods based on a multiresolution evolution of a volumetric function′s level set. In the former method, the role of the level set implosion is to fuse (“sew” and “stitch”) together several partial reconstructions (depth maps) into a closed model. In the later, the level set′s implosion is steered directly by the texture mismatch between views. Both solutions share the characteristic of operating in an adaptive multiresoluti...

  19. Tracking target objects orbiting earth using satellite-based telescopes

    Science.gov (United States)

    De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J

    2014-10-14

    A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.

  20. Compressive sensing based video object compression schemes for surveillance systems

    Science.gov (United States)

    Narayanan, Sathiya; Makur, Anamitra

    2015-03-01

    In some surveillance videos, successive frames exhibit correlation in the sense that only a small portion changes (object motion). If the foreground moving objects are segmented from the background they can be coded independently requiring far fewer bits compared to frame-based coding. Huang et al proposed a Compressive Sensing (CS) based Video Object Error Coding (CS-VOEC) where the objects are segmented and coded via motion estimation and compensation. Since motion estimation might be computationally intensive, encoder can be kept simple by performing motion estimation the decoder rather than at the encoder. We propose a novel CS based Video Object Compression (CS-VOC) technique having a simple encoder in which the sensing mechanism is applied directly on the segmented moving objects using a CS matrix. At the decoder, the object motion is first estimated so that a CS reconstruction algorithm can efficiently recover the sparse motion-compensated video object error. In addition to simple encoding, simulation results show our coding scheme performs on par with the state-of-the-art CS based video object error coding scheme. If the object segmentation requires more computations, we propose to deploy a distributed CS framework called Distributed Compressive Video Sensing based Video Object Compression (DCVS-VOC) wherein the object segmentation is done only for key frames.

  1. Model for Knowledge Bases of Computational Objects

    OpenAIRE

    Nhon Van Do

    2010-01-01

    In the artificial intelligence field, knowledge representation and reasoning are important areas for intelligent systems, especially knowledge base systems and expert systems. Knowledge representation Methods has an important role in designing the systems. There have been many models for knowledge such as semantic networks, conceptual graphs, and neural networks. These models are useful tools to design intelligent systems. However, they are not suitable to represent knowledge in the domains o...

  2. Agents as objects with knowledge base state

    CERN Document Server

    Skarmeas, Nikolaos

    1999-01-01

    Advances in computer technology in general and computer networks in particular have significantly affected the requirements of modern applications, where the need to operate in decentralised environments is of primary importance. The conceptual models of the applications are also becoming complex and semantically rich.A promising technology towards the design and development of systems of such domains is agent based systems. Agents, having a knowledge component, act and interact with other agents and information sources in order to achieve some goals. Platforms intended for supporting the deve

  3. Object Description Based on Spatial Relations between Level-Sets

    OpenAIRE

    Garnier, Mickae?l; Hurtut, Thomas; Wendling, Laurent

    2012-01-01

    Object recognition methods usually rely on either structural or statistical description. These methods aim at describing different types of information such as the outer contour, the inner structure or texture effects. Comparing two objects then comes down to averaging different data representations which may be a tricky issue. In this paper, we introduce an object descriptor based on the spatial relations that structures object content. This descriptor integrates in a single homogeneous repr...

  4. Perceptual Object Extraction Based on Saliency and Clustering

    Directory of Open Access Journals (Sweden)

    Qiaorong Zhang

    2010-08-01

    Full Text Available Object-based visual attention has received an increasing interest in recent years. Perceptual object is the basic attention unit of object-based visual attention. The definition and extraction of perceptual objects is one of the key technologies in object-based visual attention computation model. A novel perceptual object definition and extraction method is proposed in this paper. Based on Gestalt theory and visual feature integration theory, perceptual object is defined using homogeneity region, salient region and edges. An improved saliency map generating algorithm is employed first. Based on the saliency map, salient edges are extracted. Then graph-based clustering algorithm is introduced to get homogeneity regions in the image. Finally an integration strategy is adopted to combine salient edges and homogeneity regions to extract perceptual objects. The proposed perceptual object extraction method has been tested on lots of natural images. Experiment results and analysis are presented in this paper also. Experiment results show that the proposed method is reasonable and valid.

  5. Complex perspectives on learning objectives : Stakeholders' beliefs about core objectives based on focus group interviews

    DEFF Research Database (Denmark)

    MØrcke, Anne Mette; Wichmann-Hansen, Gitte

    2006-01-01

    OBJECTIVE To understand core curriculum design and involvement of stakeholders.METHODS Twelve homogeneous focus group interviews with a total of 88 students, house officers, seniordoctors and nurses concerning an undergraduate emergency medicine curriculum. Following content coding of transcripts, we analysed by condensation, categorisation and qualitative content analyses.RESULTS The focus group participants gave a range of reasons for defining objectives or outcomes. They found their involvement in the process essential.Their argumentation and beliefs differed significantly, revealing 2 opposite perspectives: objectives as context-free theory-based rules versus objectives as personal practice-based guidelines. The students favoured theory-based objectives, which should be defined by experts conclusively as minimum levels and checklists. The senior doctors preferred practice-based objectives, which should be decided in a collaborative, local, continuous process, and should be expressed as ideals and expectations. The house officers held both perspectives. Adding to complexity, participants also interpreted competence inconsistently and mixed concepts such as knowledge, observation, supervision, experience and expertise.DISCUSSION Participating novices' perspectives on objectives differed completely from expertise level participants. These differences in perspectives should not be underestimated, as they can lead easily to misunderstandings among stakeholders, or between stakeholders, educational leaders and curriculum designers. We recommend that concepts are discussed with stakeholders in order to reach a common understanding and point of departure for discussing outcomes. Differences in perspectives, in our opinion, need to be recognised, respected and incorporated into the curriculum design process.

  6. A semantic description of learning objects based on an ontology

    Directory of Open Access Journals (Sweden)

    John-Freddy DUITAMA

    2005-01-01

    Full Text Available The number of learning objects available on the Internet has significantly grown these last years and the problem of indexing and searching these learning objects is becoming crucial. Standards and norms of educative metadata such as LOM and SCORM have been proposed to handle this problem but in our opinion these proposals are not a satisfactory solution. In this paper, we propose to extend these standards with a semantic description of learning objects based on an ontology. A learning object is described by prerequisites, a content and an acquisition function. This allows defining powerful search tools and improves reusing. For reusing, we propose to define new learning objects by assembling existing objects. Assembling is specified by a composition graph composed by learning objects and composition operators (sequence, parallel, and alternative. In order to improve flexibility, we have introduced intentional objects. An intentional object is defined by a composition graph where (at least one object has been replaced by an intentional query on the learning object repository. This model is used during the adaptive process of a learning object for a specific learner. We define a notion of quality on learning objects which mainly reflects their ability to reuse. This quality may be evaluated a posteriori using metrics on objects or controlled a priori using a type system. Our model has been implemented with Sesame, a RDF database which support SeRQL a powerful query language for RDF and RDFS.

  7. Object detection of speckle image base on curvelet transform

    Directory of Open Access Journals (Sweden)

    Nguyen Thanh Binh

    2007-06-01

    Full Text Available The speckle degrades quality of the image and makes interpretations, segmentation of objects harder. In this paper, we present a method for object detection of speckle image base on curvelet transform. The approximate properties and the high directional sensitivity of the curvelet transform make the new method for object detection of speckle image. We construct a method segmentation that provides a sparse expansion for typical images having smooth contours.

  8. Object detection of speckle image base on curvelet transform

    OpenAIRE

    Nguyen Thanh Binh; Nguyen Chi Thanh

    2007-01-01

    The speckle degrades quality of the image and makes interpretations, segmentation of objects harder. In this paper, we present a method for object detection of speckle image base on curvelet transform. The approximate properties and the high directional sensitivity of the curvelet transform make the new method for object detection of speckle image. We construct a method segmentation that provides a sparse expansion for typical images having smooth contours.

  9. a New Object Based Method for Automated Extraction of Urban Objects from Airborne Sensors Data

    Science.gov (United States)

    Moussa, A.; El-Sheimy, N.

    2012-07-01

    The classification of urban objects such as buildings, trees and roads from airborne sensors data is an essential step in numerous mapping and modelling applications. The automation of this step is greatly needed as the manual processing is costly and time consuming. The increasing availability of airborne sensors data such as aerial imagery and LIDAR data offers new opportunities to develop more robust approaches for automatic classification. These approaches should integrate these data sources that have different characteristics to exceed the accuracy achieved using any individual data source. The proposed approach presented in this paper fuses the aerial images data with single return LIDAR data to extract buildings and trees for an urban area. Object based analysis is adopted to segment the entire DSM data into objects based on height variation. These objects are preliminarily classified into buildings, trees, and ground. This primary classification is used to compute the height to ground for each object to help improve the accuracy of the second phase of classification. The overlapping perspective aerial images are used to build an ortho-photo to derive a vegetation index value for each object. The second phase of classification is performed based on the height to ground and the vegetation index of each object. The proposed approach has been tested using three areas in the centre of the city of Vaihingen provided by ISPRS test project on urban classification and 3D building reconstruction. These areas have historic buildings having rather complex shapes, few high-rising residential buildings that are surrounded by trees, and a purely residential area with small detached houses. The results of the proposed approach are presented based on a reference solution for evaluation purposes. The classification evaluation exhibits highly successful classification results of buildings class. The proposed approach follows the exact boundary of trees based on LIDAR data which provide above average classification results for the trees when compared to the assumed ideal circular shaped trees in the reference data.

  10. RFID and IP Based Object Identification in Ubiquitous Networking

    Directory of Open Access Journals (Sweden)

    Nisha Vaghela

    2012-10-01

    Full Text Available Ubiquitous networking is an integrated part of future networking technology that can provide capabilities for connecting all of objects (computers, human, PDAs, cell phones etc. in future network. It has to meet the challenge of seamless connection for communication between human and objects in internet infrastructure. Unique object identification is very much important to make the communication between objects possible. RFID tag can be used as unique identifier to identify a physical object. Radio Frequency Identification (RFID is a technology used for object identification of system. Internet Protocol (IPaddress is used to provide logical identity to find the location of object for communication. In this paper, IP based RFID architecture for unique identification and tracking of object by considering mobility isproposed. RFID Agent (RA is used to generate IP address based on RFID tags. In proposed solution, RFID-IP mapping is used to identify and track the location of object as RFID Tag ID can be used to generate unique identifier and IP can be used to find the location. RFID deployment is cost effective and IP is being used as current internet structure. In this way RFID-IP mapping provides better solution for object identification in ubiquitous networking environment.

  11. Content-Based Object Movie Retrieval and Relevance Feedbacks

    Directory of Open Access Journals (Sweden)

    Greg C. Lee

    2007-01-01

    Full Text Available Object movie refers to a set of images captured from different perspectives around a 3D object. Object movie provides a good representation of a physical object because it can provide 3D interactive viewing effect, but does not require 3D model reconstruction. In this paper, we propose an efficient approach for content-based object movie retrieval. In order to retrieve the desired object movie from the database, we first map an object movie into the sampling of a manifold in the feature space. Two different layers of feature descriptors, dense and condensed, are designed to sample the manifold for representing object movies. Based on these descriptors, we define the dissimilarity measure between the query and the target in the object movie database. The query we considered can be either an entire object movie or simply a subset of views. We further design a relevance feedback approach to improving retrieved results. Finally, some experimental results are presented to show the efficacy of our approach.

  12. A Method of Object-based De-duplication

    Directory of Open Access Journals (Sweden)

    Fang Yan

    2011-12-01

    Full Text Available Today, the world is increasingly awash in more and more unstructured data, not only because of the Internet, but also because data that used to be collected on paper or media such as film, DVDs and compact discs has moved online [1]. Most of this data is unstructured and in diverse formats such as e-mail, documents, graphics, images, and videos. In managing unstructured data complexity and scalability, object storage has a clear advantage. Object-based data de-duplication is the current most advanced method and is the effective solution for detecting duplicate data. It can detect common embedded data for the first backup across completely unrelated files and even when physical block layout changes. However, almost all of the current researches on data de-duplication do not consider the content of different file types, and they do not have any knowledge of the backup data format. It has been proven that such method cannot achieve optimal performance for compound files.In our proposed system, we will first extract objects from files, Object_IDs are then obtained by applying hash function to the objects. The resulted Object_IDs are used to build as indexing keys in B+ tree like index structure, thus, we avoid the need for a full object index, the searching time for the duplicate objects reduces to O(log n.We introduce a new concept of a duplicate object resolver. The object resolver mediates access to all the objects and is a central point for managing all the metadata and indexes for all the objects. All objects are addressable by their IDs which is unique in the universe. The resolver stores metadata with triple format. This improved metadata management strategy allows us to set, add and resolve object properties with high flexibility, and allows the repeated use of the same metadata among duplicate object.

  13. Test generation and animation based on object-oriented specifications.

    OpenAIRE

    Krieger, Matthias

    2011-01-01

    The goal of this thesis is the development of support for test generation and animation based on object-oriented specifications. We aim particularly to take advantage of state-of-the-art satisfiability solving techniques by using an appropriate representation of object-oriented data. While automated test generation seeks a large set of data to execute an implementation on, animation performs computations that comply with a specification based on user-provided input data. Animation is a valuab...

  14. Autocorrelation-based reconstruction of two-dimensional binary objects

    Science.gov (United States)

    Mejia-Barbosa, Yobani; Castaneda-Sepulveda, Roman

    2006-02-01

    A method for reconstructing two-dimensional binary objects from its autocorrelation function is discussed. The objects consist of a finite set of identical elements. The reconstruction algorithm is based on the concept of class of element pairs, defined as the set of element pairs with the same separation vector. This concept allows solving the redundancy introduced by the element pairs of each class. It is also shown that different objects, consisting of equal number of elements and the same classes of pairs, provide Fraunhofer diffraction patterns with identical intensity distributions. However, the method predicts all the possible objects that produce the same Fraunhofer pattern.

  15. Autocorrelation based reconstruction of two-dimensional binary objects

    International Nuclear Information System (INIS)

    A method for reconstructing two-dimensional binary objects from its autocorrelation function is discussed. The objects consist of a finite set of identical elements. The reconstruction algorithm is based on the concept of class of element pairs, defined as the set of element pairs with the same separation vector. This concept allows to solve the redundancy introduced by the element pairs of each class. It is also shown that different objects, consisting of an equal number of elements and the same classes of pairs, provide Fraunhofer diffraction patterns with identical intensity distributions. However, the method predicts all the possible objects that produce the same Fraunhofer pattern. (author)

  16. A Secure and Robust Object-Based Video Authentication System

    Directory of Open Access Journals (Sweden)

    Dajun He

    2004-10-01

    Full Text Available An object-based video authentication system, which combines watermarking, error correction coding (ECC, and digital signature techniques, is presented for protecting the authenticity between video objects and their associated backgrounds. In this system, a set of angular radial transformation (ART coefficients is selected as the feature to represent the video object and the background, respectively. ECC and cryptographic hashing are applied to those selected coefficients to generate the robust authentication watermark. This content-based, semifragile watermark is then embedded into the objects frame by frame before MPEG4 coding. In watermark embedding and extraction, groups of discrete Fourier transform (DFT coefficients are randomly selected, and their energy relationships are employed to hide and extract the watermark. The experimental results demonstrate that our system is robust to MPEG4 compression, object segmentation errors, and some common object-based video processing such as object translation, rotation, and scaling while securely preventing malicious object modifications. The proposed solution can be further incorporated into public key infrastructure (PKI.

  17. Object-based mapping of drumlins from DTMs

    Science.gov (United States)

    Eisank, C.; Dragut, L.; Blaschke, T.

    2012-04-01

    Until recently, landforms such as drumlins have only been manually delineated due to the difficulty in integrating contextual and semantic landform information in per cell classification approaches. Therefore, in most cases the results of per cell classifications presented basic landform elements or broad-scale physiographic regions that were only thematically defined. In contrast, object-based analysis provides spatially configured landform objects that are generated by terrain segmentation, the process of merging DTM cells to meaningful terrain objects at multiple scales. Such terrain objects should be favoured for landform modelling due to the following reasons: Firstly, their outlines potentially better correspond to the spatial limits of landforms as conceptualised by geoscientists; secondly, spatially aware objects enable the integration of semantic descriptions in the classification process. We present a multi-scale object-based study on automated delineation and classification of drumlins for a small test area in Bavaria, Germany. The multi-resolution segmentation algorithm is applied to create statistically meaningful objects patterns of selected DTMs, which are derived from a 5 m LiDAR DEM. For the subsequent classification of drumlins a semantics-based approach, which uses the principles of semantic modelling, is employed: initially, a geomorphological concept of the landform type drumlin is developed. The drumlin concept should ideally comprise verbal descriptions of the fundamental morphometric, morphological, hierarchical and contextual properties. Subsequently, the semantic model is built by structuring the conceptualised knowledge facts, and by associating those facts with object and class-related features, which are available in commonly used object-based software products for the development of classification rules. For the accuracy assessment we plan an integrated approach, which combines a statistical comparison to field maps and a qualitative evaluation based on expert consultation. The study on drumlins should demonstrate the applicability of the object-based approach for the extraction of specific landforms from DTMs in a multi-scale framework. The provision of meaningful spatial modelling units and the straightforward way for the integration of semantics make object-based analysis superior to field-based methods. However, an explicit representation of geomorphological knowledge - as for example in the form of a semantic model - prior to landform classification is a prerequisite for effective mapping. Such an approach allows the user to delineate and map drumlins in a way that is close to the human cognition of landforms. Once most of the drumlins are recognized by the developed classification system, those objects can further be investigated with respect to their morphometry and morphology in order to improve the understanding of glacial processes.

  18. Stereovision-Based Object Segmentation for Automotive Applications

    Directory of Open Access Journals (Sweden)

    Fu Shan

    2005-01-01

    Full Text Available Obstacle detection and classification in a complex urban area are highly demanding, but desirable for pedestrian protection, stop & go, and enhanced parking aids. The most difficult task for the system is to segment objects from varied and complicated background. In this paper, a novel position-based object segmentation method has been proposed to solve this problem. According to the method proposed, object segmentation is performed in two steps: in depth map ( - plane and in layered images ( - planes. The stereovision technique is used to reconstruct image points and generate the depth map. Objects are detected in the depth map. Afterwards, the original edge image is separated into different layers based on the distance of detected objects. Segmentation performed in these layered images can be easier and more reliable. It has been proved that the proposed method offers robust detection of potential obstacles and accurate measurement of their location and size.

  19. Possibility of object recognition using Altera's model based design approach

    International Nuclear Information System (INIS)

    Object recognition is an image processing task of finding a given object in a selected image or video sequence. Object recognition can be divided into two areas: one of these is decision-theoretic and deals with patterns described by quantitative descriptors, for example such as length, area, shape and texture. With this Graphical User Interface Circuitry (GUIC) methodology employed here being relatively new for object recognition systems, the aim of this work is to identify if the developed circuitry can detect certain shapes or strings within the target image. A much smaller reference image feeds the preset data for identification, tests are conducted for both binary and greyscale and the additional mathematical morphology to highlight the area within the target image with the object(s) are located is also presented. This then provides proof that basic recognition methods are valid and would allow the progression to developing decision-theoretical and learning based approaches using GUICs for use in multidisciplinary tasks.

  20. Identification of vehicle targets from low-cost ladar-seeker imagery

    Science.gov (United States)

    Wellfare, Michael R.; Holmes, V. Todd; Pohlman, Scott; Geci, Duane; Norris-Zachery, Karen; Patton, Ronald

    1996-06-01

    Use of ladar seekers for autonomous vehicle identification and targeting from short range, expendable munitions is increasingly of interest due to the inherently high resolution shape data and the relatively low unit cost of the sensor. In addition, low-cost digital signal processors are now available that can manage the computational workload required for autonomous operation in a wide variety of tactical scenarios. A set of detection, segmentation, and vehicle identification algorithms have been developed which have been demonstrated on real and synthetic seeker data and have been targeted for the architecture and resources available on a tactically realistic processor. Results of preliminary algorithm testing are presented.

  1. Liquid crystal clad waveguide laser scanner and waveguide amplifier for LADAR and sensing applications

    Science.gov (United States)

    Davis, Scott R.; Rommel, Scott D.; Johnson, Seth; Anderson, Michael H.; Yu, Anthony W.

    2015-02-01

    We will describe the construction and performance of a prototype high speed, non-mechanically scanned, laser system that is coupled to a custom planar waveguide optical amplifier. The system provides high speed (10 kHz) scanning of design and construction of custom planar waveguide amplifiers to which our EO scanner can be free space end-fire coupled. The amplifiers and scanners were designed for operation at 1.645 microns. This will enable long-range, eye-safe LADAR and sensing applications, such as CH4 sensors.

  2. Distinct mechanisms subserve location- and object-based visual attention.

    Science.gov (United States)

    Chou, Wei-Lun; Yeh, Su-Ling; Chen, Chien-Chung

    2014-01-01

    Visual attention can be allocated to either a location or an object, named location- or object-based attention, respectively. Despite the burgeoning evidence in support of the existence of two kinds of attention, little is known about their underlying mechanisms in terms of whether they are achieved by enhancing signal strength or excluding external noises. We adopted the noise-masking paradigm in conjunction with the double-rectangle method to probe the mechanisms of location-based attention and object-based attention. Two rectangles were shown, and one end of one rectangle was cued, followed by the target appearing at (a) the cued location; (b) the uncued end of the cued rectangle; and (c) the equal-distant end of the uncued rectangle. Observers were required to detect the target that was superimposed at different levels of noise contrast. We explored how attention affects performance by assessing the threshold versus external noise contrast (TvC) functions and fitted them with a divisive inhibition model. Results show that location-based attention - lower threshold at cued location than at uncued location - was observed at all noise levels, a signature of signal enhancement. However, object-based attention - lower threshold at the uncued end of the cued than at the uncued rectangle - was found only in high-noise conditions, a signature of noise exclusion. Findings here shed a new insight into the current theories of object-based attention. PMID:24904472

  3. A Wavelet - Based Object Watermarking System for MPEG4 Video

    Directory of Open Access Journals (Sweden)

    F.Regragui

    2010-01-01

    Full Text Available Efficient storage, transmission and use of video information are key requirements in many multimedia applications currently being addressed by MPEG-4. To fulfill these requirements, a new approach for representing video information which relies on an object-based representation, has been adopted. Therefore, object-based watermarking schemes are needed for copyright protection. This paper presents a novel object based watermarking solution for MPEG4 video authentication using the shape adaptive-discrete wavelet transform (SA-DWT. In order to make the watermark robust and transparent, the watermark is embedded in the average of wavelet blocks using the visual model based on the human visual system. Wavelet coefficients n least significant bits (LSBs are adjusted in concert with the average. Simulation results shows that the proposed watermarking scheme is perceptually invisible and robust against many attacks such as lossy compression (e.g. MPEG1 and MPEG2,MPEG-4,H264

  4. Segmentation of object-based video of gaze communication

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Stegmann, Mikkel Bille

    2005-01-01

    Aspects of video communication based on gaze interaction are considered. The overall idea is to use gaze interaction to control video, e.g. for video conferencing. Towards this goal, animation of a facial mask is demonstrated. The animation is based on images using Active Appearance Models (AAM). Good quality reproduction of (low-resolution) coded video of an animated facial mask as low as 10-20 kbit/s using MPEG-4 object based video is demonstated.

  5. Saliency-based artificial object detection for satellite images

    Science.gov (United States)

    Ke, Shidong; Ding, Xiaoying; Yang, Daiqin; Chen, Zhenzhong; Fang, Yuming

    2015-03-01

    In this paper, we introduce a computational model of top-down saliency based on multiscale orientation information for artificial object detection for satellite images. Further more, the top-down saliency is integrated with bottom-up saliency to obtain the saliency map in satellite images. We compare our method to several state-of-the-art saliency detection models and demonstrate the superior performance in artificial object detection for satellite images.

  6. Visualization of spirography-based objective measures in Parkinson's disease

    OpenAIRE

    Memedi, Mevludin; Jusufi, Ilir; Nyholm, Dag

    2014-01-01

    Objective: To investigate whether advanced visualizations of spirography-based objective measures are useful in differentiating drug-related motor dysfunctions between Off and dyskinesia in Parkinson’s disease (PD). Background: During the course of a 3 year longitudinal clinical study, in total 65 patients (43 males and 22 females with mean age of 65) with advanced PD and 10 healthy elderly (HE) subjects (5 males and 5 females with mean age of 61) were assessed. Both patients and HE subject...

  7. Novel Scheme for Object-based Embedded Image Coding

    Directory of Open Access Journals (Sweden)

    Yuer Wang

    2012-11-01

    Full Text Available Conventional EBCOT algorithm encodes an image with the same block-based coding strategy and it is difficult to acquire perceptually consistent results in practical applications. This paper presents a new scheme for object-based embedded coding aiming to enhance the flexibility and the coding efficiency. In our scheme, an original image is firstly segmented into objects, which are taken as basic coding units and are encoded independently. Then the compressed streams of all objects are further truncated and reassembled based on rate-distortion optimization principle according to given bit-rate. In our scheme, each object can be encoded independently with different strategy according to its visual interest at the encoder. At the decoder, it can be decoded and reconstructed independently and progressively. As a whole, the new scheme is more flexible and may enhance the overall subjective quality of reconstructed images. Experiments are conducted and the results show the proposed scheme can implement object-based image coding and rate control effectively.

  8. An objective prior that unifies objective Bayes and information-based inference

    CERN Document Server

    LaMont, Colin H

    2015-01-01

    There are three principle paradigms of statistical inference: (i) Bayesian, (ii) information-based and (iii) frequentist inference. We describe an objective prior (the weighting or $w$-prior) which unifies objective Bayes and information-based inference. The $w$-prior is chosen to make the marginal probability an unbiased estimator of the predictive performance of the model. This definition has several other natural interpretations. From the perspective of the information content of the prior, the $w$-prior is both uniformly and maximally uninformative. The $w$-prior can also be understood to result in a uniform density of distinguishable models in parameter space. Finally we demonstrate the the $w$-prior is equivalent to the Akaike Information Criterion (AIC) for regular models in the asymptotic limit. The $w$-prior appears to be generically applicable to statistical inference and is free of {\\it ad hoc} regularization. The mechanism for suppressing complexity is analogous to AIC: model complexity reduces mo...

  9. Performance bounds of the phase gradient autofocus algorithm for synthetic aperture ladar

    Science.gov (United States)

    Gatt, Phillip; Jacob, Don; Bradford, Bert; Marron, Joe; Krause, Brian

    2009-05-01

    An important issue in synthetic aperture ladar is phase noise mitigation, since phase noise corrupts image quality. There are many phase noise contributors including, residual platform motion, local oscillator phase/frequency instability, atmospheric turbulence, and additive receiver noise. The Phase Gradient Autofocus (PGA) algorithm is a common phase noise correction algorithm utilized in synthetic aperture radar. The Cramer-Rao Lower Bound for the phase-difference estimate variance of PGA can be found in the radar literature. This lower bound describes the precision of the phasedifference estimate between any two pulses as a function of the carrier-to-noise ratio (CNR). However, this lower bound does not account for speckle saturation limitations, present in both synthetic aperture ladar and radar. This paper extends the PGA performance theory to include a high CNR saturation term which accounts for speckle decorrelation. This term is shown to be proportional to the ratio of the image spot size to the laser pulse repetition frequency (PRF). This paper also describes impact of PGA estimate variance on image cross-range resolution. We show, given a fixed PRF and fixed PGA phase-difference estimate variance, that resolution initially improves with increasing dwell times but eventually saturates to a level proportional to the product of the PGA estimate variance and the laser PRF.

  10. High power CO2 coherent ladar haven't quit the stage of military affairs

    Science.gov (United States)

    Zhang, Heyong

    2015-05-01

    The invention of the laser in 1960 created the possibility of using a source of coherent light as a transmitter for a laser radar (ladar). Coherent ladar shares many of the basic features of more common microwave radars. However, it is the extremely short operating wavelength of lasers that introduces new military applications, especially in the area of missile identification, space target tracking, remote rang finding, camouflage discrimination and toxic agent detection. Therefore, the most popular application field such as laser imaging and ranging were focused on CO2 laser in the last few decades. But during the development of solid state and fiber laser, some people said that the CO2 laser will be disappeared and will be replaced by the solid and fiber laser in the field of military and industry. The coherent CO2 laser radar will have the same destiny in the field of military affairs. However, to my opinion, the high power CO2 laser will be the most important laser source for laser radar and countermeasure in the future.

  11. Inverse treatment planning using volume-based objective functions

    International Nuclear Information System (INIS)

    The results of optimization of inverse treatment plans depend on a choice of the objective function. Even when the optimal solution for a given cost function can be obtained, a better solution may exist for a given clinical scenario and it could be obtained with a revised objective function. In the approach presented in this work mixed integer programming was used to introduce a new volume-based objective function, which allowed for minimization of the number of under- or overdosed voxels in selected structures. By selecting and prioritizing components of this function the user could drive the computations towards the desired solution. This optimization approach was tested using cases of patients treated for prostate and oropharyngeal cancer. Initial solutions were obtained based on minimization/maximization of the dose to critical structures and targets. Subsequently, the volume-based objective functions were used to locate solutions, which satisfied better clinical objectives particular to each of the cases. For prostate cases, these additional solutions offered further improvements in sparing of the rectum or the bladder. For oropharyngeal cases, families of solutions were obtained satisfying an intensity modulated radiation therapy protocol for this disease site, while offering significant improvement in the sparing of selected critical structures, e.g., parotid glands. An additional advantage of the present approach was in providing a convenient mechanism to testn providing a convenient mechanism to test the feasibility of the dose-volume histogram constraints

  12. Inverse treatment planning using volume-based objective functions

    Science.gov (United States)

    Bednarz, Greg; Michalski, Darek; Anne, Pramila R.; Valicenti, Richard K.

    2004-06-01

    The results of optimization of inverse treatment plans depend on a choice of the objective function. Even when the optimal solution for a given cost function can be obtained, a better solution may exist for a given clinical scenario and it could be obtained with a revised objective function. In the approach presented in this work mixed integer programming was used to introduce a new volume-based objective function, which allowed for minimization of the number of under- or overdosed voxels in selected structures. By selecting and prioritizing components of this function the user could drive the computations towards the desired solution. This optimization approach was tested using cases of patients treated for prostate and oropharyngeal cancer. Initial solutions were obtained based on minimization/maximization of the dose to critical structures and targets. Subsequently, the volume-based objective functions were used to locate solutions, which satisfied better clinical objectives particular to each of the cases. For prostate cases, these additional solutions offered further improvements in sparing of the rectum or the bladder. For oropharyngeal cases, families of solutions were obtained satisfying an intensity modulated radiation therapy protocol for this disease site, while offering significant improvement in the sparing of selected critical structures, e.g., parotid glands. An additional advantage of the present approach was in providing a convenient mechanism to test the feasibility of the dose-volume histogram constraints.

  13. Object-Based Epistemology at a Creationist Museum

    Science.gov (United States)

    Wendel, Paul J.

    2011-01-01

    In a regional young-earth creationist museum, objects are presented as if they speak for themselves, purportedly embodying proof that the earth is less than 10,000 years old, that humans have lived on earth throughout its history, and that dinosaurs and humans lived simultaneously. In public lectures, tours, and displays, museum associates emphasize direct observation over inference or theory. These emphases resonate closely with the "object-based epistemology" of the late nineteenth century described in Steven Conn's Museums and American Intellectual Life, 1876- 1926. In Conn's description, museum objects, artfully arranged and displayed, were intended to speak for themselves, and observation and categorization were valued over experiment and theory. The regional young-earth creationist museum is observed to partly succeed and partly fail in implementing an object-based epistemology. Although object-based epistemology represents a nineteenth-century approach to knowledge and museum display, it is compatible with an inductive approach to biblical interpretation and it confers various rhetorical advantages to creationist arguments. It is concluded that a focus on the theory-laden nature of data would likely strengthen nature-of-science education efforts to increase public acceptance of evolution.

  14. Multi-objective Optimization Problem Based on Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Li Heng

    2013-01-01

    Full Text Available Target weighted multi-objective optimization genetic algorithm for solving the problem is to place all aggregated into a target objective function with parameters. In the multi-objective optimization evaluation index system, determine the weights of attributes have a pivotal position. So how to scientifically and reasonably determine the attribute weights, the results related to the multi-objective optimization reliability and validity. The first focuses on the weighted sum of the genetic algorithm, uniform design created by combining the initial population and its standardization of the objective function to create a new fitness function, we propose a dynamic allocation weighting scheme, based on the design of a new weight distribution strategy multi-objective genetic algorithm for solving multi-objective optimization problem. The algorithm can find the sparse regions of non-dominated frontier, to search for sparse areas, making the search to a more uniform distribution of non-dominated solutions, introduces a uniform crossover operator and single point crossover two kinds of hybrid composite operator, to make up for a simulated binary search capability is weak crossover defects and gives proof of convergence of the algorithm by simulation to verify the effectiveness of the algorithm.

  15. Fuzzy-Rule-Based Object Identification Methodology for NAVI System

    Directory of Open Access Journals (Sweden)

    Rosalyn R. Porle

    2005-08-01

    Full Text Available We present an object identification methodology applied in a navigation assistance for visually impaired (NAVI system. The NAVI has a single board processing system (SBPS, a digital video camera mounted headgear, and a pair of stereo earphones. The captured image from the camera is processed by the SBPS to generate a specially structured stereo sound suitable for vision impaired people in understanding the presence of objects/obstacles in front of them. The image processing stage is designed to identify the objects in the captured image. Edge detection and edge-linking procedures are applied in the processing of image. A concept of object preference is included in the image processing scheme and this concept is realized using a fuzzy-rule base. The blind users are trained with the stereo sound produced by NAVI for achieving a collision-free autonomous navigation.

  16. A Fuzzy Multi-Objective Class Based Storage Location Assignment

    Directory of Open Access Journals (Sweden)

    B. Maleki Vishkaei

    2011-10-01

    Full Text Available The required storage space and the material handing cost in a warehouse hinge on the storage implementation decision. Effects of storage area reduction on order picking and storage space cost are incorporated. Moreover, merchandises which are in the same shape and can be stored beside each other easily or goods that don't cause any danger like causing a fire if be in touch with each other, can be stored in one class together. In this paper first a multi-objective class based storage model is presented in which two objectives are considered; one is the sum of storage space cost and handing cost and the other is the quantitative objective "efficiency of storing products in one class". The demand rates and the second objective are evaluated with linguistic values. Fuzzy dynamic approach will be used to solve the proposed model considering an illustrative example to clarify it.

  17. Object detection with discriminatively trained part-based models.

    Science.gov (United States)

    Felzenszwalb, Pedro F; Girshick, Ross B; McAllester, David; Ramanan, Deva

    2010-09-01

    We describe an object detection system based on mixtures of multiscale deformable part models. Our system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object detection challenges. While deformable part models have become quite popular, their value had not been demonstrated on difficult benchmarks such as the PASCAL data sets. Our system relies on new methods for discriminative training with partially labeled data. We combine a margin-sensitive approach for data-mining hard negative examples with a formalism we call latent SVM. A latent SVM is a reformulation of MI--SVM in terms of latent variables. A latent SVM is semiconvex, and the training problem becomes convex once latent information is specified for the positive examples. This leads to an iterative training algorithm that alternates between fixing latent values for positive examples and optimizing the latent SVM objective function. PMID:20634557

  18. Distributed Database for Reusable Learning Object-Based System

    Directory of Open Access Journals (Sweden)

    S.H.A. Hamid

    2008-01-01

    Full Text Available In this study, discusses enhancing the e-learning system by employing a distributed database that apply reusable learning object as one of the technologies that is applied to e-learning development. An e-learning system named e-notes is able to assist students and facilitators to interact with each other. Learning objects are used to conceptualize the learning process and offer accessibility, interoperability, adaptability, durability, reusability and granularity for the e-learning environment. This study also shows the test result of a comparison for learning objects` performance applied to a centralized database and a distributed database and the performance in reusability of learning objects. The e-notes architecture, based on a client-side application, is designed with the intention to help the student in a computer tutorial system which offers reusability attributes.

  19. Vector ordinal optimization based multi-objective transmission planning

    International Nuclear Information System (INIS)

    The deregulation of the power industry has resulted in a restructured industry. The integrated power industry has been separated into generation companies, transmission company and distribution companies. Each individual market participant has its own goal of maximizing its profit in power system planning and power system operation. In this paper, the vector ordinal optimization (VOO) theory was applied to solve the multi-objective transmission expansion planning (TEP) problems. The weight-summation of multiple objectives was considered as a single objective. In order to reflect the interests of different market participants and the social benefit, the authors used the Transmission Economic Assessment Methodology (TEAM) to formulate the multi-objective TEP. The VOO solution algorithm was presented and tested based on the TEAM model. Numerical examples were presented to test the proposed VOO based solution algorithm. The 4 indices of the transmission economic assessment methodology were used as the 4 objectives for transmission planning. VOO uses crude models to estimate the indices of the TEAM base multi-objective optimization problem to determine a select subset of schemes to simulate and find solutions which have been termed as good enough. The calculation burden was reduced significantly by using this method. Test results on the modified IEEE 14-bus system show that the VOO is efficient and practical for solving multi-objective TEP problems. The test results show ttive TEP problems. The test results show that the proposed VOO approach can find good enough solutions in a short time with less computational burden. 11 refs., 5 tabs., 3 figs., 1 appendix.

  20. Archive Design Based on Planets Inspired Logical Object Model

    DEFF Research Database (Denmark)

    Zierau, Eld; Johansen, Anders

    2008-01-01

    We describe a proposal for a logical data model based on preliminary work the Planets project In OAIS terms the main areas discussed are related to the introduction of a logical data model for representing the past, present and future versions of the digital object associated with the Archival Storage Package for the publications deposited by our client repositories.

  1. Vision-based autonomous grasping of unknown piled objects

    International Nuclear Information System (INIS)

    Computer vision techniques have been used to develop a vision-based grasping capability for autonomously picking and placing unknown piled objects. This work is currently being applied to the problem of hazardous waste sorting in support of the Department of Energy's Mixed Waste Operations Program

  2. Metadata management for CDP in object-based file system

    Science.gov (United States)

    Yao, Jie; Cao, Qiang; Huang, Jianzhong

    2009-08-01

    Object-based storage system integrates advantage of both NAS and SAN, can be applied in large-capacity, low-cost and large-scale storage systems which are built from commodity devices. Continuous data protection (CDP) is a methodology that continuously captures or tracks data modifications and stores changes independent of the primary data, enabling recovery points from any point in the past. An efficient file system optimized for CDP is needed to provide CDP feature in object-based storage system. In this thesis, a new metadata management method is present. All necessary meta data information are recorded when changes happened to file system. We have a journal-like data placement algorithm to store these metadata. Secondly, this metadata management method provides both CDP feature and Object-based feature. Two type write operations are analyzed to reduce storage space consumption. Object-based data allocation algorithm can take the advantage of distributed file system to concurrently process CDP operations over storage nodes. Thirdly, history revisions and recovery operations are discussed. Finally, the experiment test result is present and analyzed.

  3. Algebraic Analysis of Object-Based Key Assignment Schemes

    Directory of Open Access Journals (Sweden)

    Khair Eddin Sabri

    2014-08-01

    Full Text Available The confidentiality of information is an important aspect of security. One way to achieve the confidentiality is through restricting access to information to the authorized users only. Access control can be enforced by using encryption. In this case, all the information is encrypted and keys are assigned to users such that each key reveals the authorized part of the information. Key assignment can be classified as key-based or object-based schemes based on the focus of the scheme. Sabri and Khedri [1] present algebraic structures to specify algebraically cryptosystems by capturing the common properties of ciphers, secrets and keys. Also, these structures are used for the analysis of security properties in object-based key assignment schemes. However, these structures are abstract, and no linkage has been proposed to the existing cryptosystems. In this paper, we extend their work by giving concrete models for their algebraic structures. We give concrete models to Vigenere, transposition ciphers, DES, and RSA cryptosystems. Also, we investigate the effects of extra algebraic properties that some cryptosystems may have on the security analysis of object-based schemes.

  4. A model of proto-object based saliency.

    Science.gov (United States)

    Russell, Alexander F; Mihala?, Stefan; von der Heydt, Rudiger; Niebur, Ernst; Etienne-Cummings, Ralph

    2014-01-01

    Organisms use the process of selective attention to optimally allocate their computational resources to the instantaneously most relevant subsets of a visual scene, ensuring that they can parse the scene in real time. Many models of bottom-up attentional selection assume that elementary image features, like intensity, color and orientation, attract attention. Gestalt psychologists, however, argue that humans perceive whole objects before they analyze individual features. This is supported by recent psychophysical studies that show that objects predict eye-fixations better than features. In this report we present a neurally inspired algorithm of object based, bottom-up attention. The model rivals the performance of state of the art non-biologically plausible feature based algorithms (and outperforms biologically plausible feature based algorithms) in its ability to predict perceptual saliency (eye fixations and subjective interest points) in natural scenes. The model achieves this by computing saliency as a function of proto-objects that establish the perceptual organization of the scene. All computational mechanisms of the algorithm have direct neural correlates, and our results provide evidence for the interface theory of attention. PMID:24184601

  5. Agent-based Algorithm for Spatial Distribution of Objects

    KAUST Repository

    Collier, Nathan

    2012-06-02

    In this paper we present an agent-based algorithm for the spatial distribution of objects. The algorithm is a generalization of the bubble mesh algorithm, initially created for the point insertion stage of the meshing process of the finite element method. The bubble mesh algorithm treats objects in space as bubbles, which repel and attract each other. The dynamics of each bubble are approximated by solving a series of ordinary differential equations. We present numerical results for a meshing application as well as a graph visualization application.

  6. A Constrained Object Model for Configuration Based Workflow Composition

    CERN Document Server

    Albert, P; Kleiner, M; Albert, Patrick; Henocque, Laurent; Kleiner, Mathias

    2005-01-01

    Automatic or assisted workflow composition is a field of intense research for applications to the world wide web or to business process modeling. Workflow composition is traditionally addressed in various ways, generally via theorem proving techniques. Recent research observed that building a composite workflow bears strong relationships with finite model search, and that some workflow languages can be defined as constrained object metamodels . This lead to consider the viability of applying configuration techniques to this problem, which was proven feasible. Constrained based configuration expects a constrained object model as input. The purpose of this document is to formally specify the constrained object model involved in ongoing experiments and research using the Z specification language.

  7. Nanoscale synthesis and characterization of graphene-based objects

    Directory of Open Access Journals (Sweden)

    Daisuke Fujita

    2011-01-01

    Full Text Available Graphene-based nano-objects such as nanotrenches, nanowires, nanobelts and nanoscale superstructures have been grown by surface segregation and precipitation on carbon-doped mono- and polycrystalline nickel substrates in ultrahigh vacuum. The dominant morphologies of the nano-objects were nanowire and nanosheet. Nucleation of graphene sheets occurred at surface defects such as step edges and resulted in the directional growth of nanowires. Surface analysis by scanning tunneling microscopy (STM has clarified the structure and functionality of the novel nano-objects at atomic resolution. Nanobelts were detected consisting of bilayer graphene sheets with a nanoscale width and a length of several microns. Moiré patterns and one-dimensional reconstruction were observed on multilayer graphite terraces. As a useful functionality, application to repairable high-resolution STM probes is demonstrated.

  8. Features Extraction for Object Detection Based on Interest Point

    Directory of Open Access Journals (Sweden)

    Amin Mohamed Ahsan

    2013-05-01

    Full Text Available In computer vision, object detection is an essential process for further processes such as object tracking, analyzing and so on. In the same context, extraction features play important role to detect the object correctly. In this paper we present a method to extract local features based on interest point which is used to detect key-points within an image, then, compute histogram of gradient (HOG for the region surround that point. Proposed method used speed-up robust feature (SURF method as interest point detector and exclude the descriptor. The new descriptor is computed by using HOG method. The proposed method got advantages of both mentioned methods. To evaluate the proposed method, we used well-known dataset which is Caltech101. The initial result is encouraging in spite of using a small data for training.

  9. A VSS Algorithm Based on Multiple Features for Object Tracking

    Directory of Open Access Journals (Sweden)

    Bin Xu

    2013-12-01

    Full Text Available A variable search space (VSS approach according to the color feature combined with point feature for object tracking is presented. Mean shift is a well-established and fundamental algorithm that works on the basis of color probability distributions, and is robust to given color targets. As it solely depends upon back projected probabilities, it may miss the targets because of illumination and noise. To overcome the flaw, we proposes VSS algorithm based on the color and robust feature of the detected object. The proposed algorithm can solve the problem that the color of the detected object is similar to the background, and achieve better real-time tracking due to change the search window’s size. Experimental work demonstrates that the presented method is robust and computationally effective.

  10. Improved Brain Tumor Detection Using Object Based Segmentation

    Directory of Open Access Journals (Sweden)

    Harneet Kaur

    2014-07-01

    Full Text Available This paper has focused on the brain tumor detection techniques. The brain tumor detection is a very important vision application in the medical field. This work has firstly presented a review on various well known techniques for automatic segmentation of heterogeneous image data that takes a step toward bridging the gap between bottom-up affinity-based segmentation methods and top-down generative model based approaches. The main objective of the work is to explore various techniques to detect brain tumor in an efficient way. It has been found that the most of existing methods has ignored the poor quality images like images with noise or poor brightness. Also the most of the existing work on tumor detection has neglected the use of object based segmentation. So to overcome the limitations of earlier work a new technique has been proposed in this research work. The technique has shown quite effective results than neural based tumor detection technique. The design and implementation of the proposed algorithm is done in MATLAB using image processing toolbox. The comparison has shown that the proposed technique has achieved up to 94 % accuracy which was 78 % in neural based technique. Also for high corrupted noisy images the proposed technique has shown quite effective results than the neural based tumor detection.

  11. Likelihood-based CT reconstruction of objects containing known components

    Energy Technology Data Exchange (ETDEWEB)

    Stayman, J. Webster [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Biomedical Engineering; Otake, Yoshito; Uneri, Ali; Prince, Jerry L.; Siewerdsen, Jeffrey H.

    2011-07-01

    There are many situations in medical imaging where there are known components within the imaging volume. Such is the case in diagnostic X-ray CT imaging of patients with implants, in intraoperative CT imaging where there may be surgical tools in the field, or in situations where the patient support (table or frame) or other devices are outside the (truncated) reconstruction FOV. In such scenarios it is often of great interest to image the relation between the known component and the surrounding anatomy, or to provide high-quality images at the boundary of these objects, or simply to minimize artifacts arising from such components. We propose a framework for simultaneously estimating the position and orientation of a known component and the surrounding volume. Toward this end, we adopt a likelihood-based objective function with an image volume jointly parameterized by a known object, or objects, with unknown registration parameters and an unknown background attenuation volume. The objective is solved iteratively using an alternating minimization approach between the two parameter types. Because this model integrates a substantial amount of prior knowledge about the overall volume, we expect a number of advantages including the reduction of metal artifacts, potential for more sparse data acquisition (decreased time and dose), and/or improved image quality. We illustrate this approach using simulated spine CT data that contains pedicle screws placed in a vertebra, and demonstrate improved performance over traditional filtered-backprojection and penalized-likelihood reconstruction techniques. (orig.)

  12. Knowledge-based simulation using object-oriented programming

    Science.gov (United States)

    Sidoran, Karen M.

    1993-01-01

    Simulations have become a powerful mechanism for understanding and modeling complex phenomena. Their results have had substantial impact on a broad range of decisions in the military, government, and industry. Because of this, new techniques are continually being explored and developed to make them even more useful, understandable, extendable, and efficient. One such area of research is the application of the knowledge-based methods of artificial intelligence (AI) to the computer simulation field. The goal of knowledge-based simulation is to facilitate building simulations of greatly increased power and comprehensibility by making use of deeper knowledge about the behavior of the simulated world. One technique for representing and manipulating knowledge that has been enhanced by the AI community is object-oriented programming. Using this technique, the entities of a discrete-event simulation can be viewed as objects in an object-oriented formulation. Knowledge can be factual (i.e., attributes of an entity) or behavioral (i.e., how the entity is to behave in certain circumstances). Rome Laboratory's Advanced Simulation Environment (RASE) was developed as a research vehicle to provide an enhanced simulation development environment for building more intelligent, interactive, flexible, and realistic simulations. This capability will support current and future battle management research and provide a test of the object-oriented paradigm for use in large scale military applications.

  13. A CDP method in an object-based file system

    Science.gov (United States)

    Yao, Jie; Cao, Qiang; Li, Huaiyang

    2008-12-01

    Recent advances in large-capacity, low-cost storage devices have led to active research in design of large-scale storage system built from commodity devices. These storage systems are composed of thousands of storage device and require an efficient file system to provide high system bandwidth and petabyte-scale data storage. Object-based file system integrates advantage of both NAS and SAN, can be applied in above environment. Continuous data protection (CDP) is a methodology that continuously captures or tracks data modifications and stores changes independent of the primary data, enabling recovery points from any point in the past. All changes to files and file metadata are stored and managed. A CDP method in Object-based file system is presented in this thesis to improve the system reliability. Firstly, we can get detail at byte level of every write request because data protection operates at the file system level. It can consume less storage space. Secondly, every object storage server can compute the recovery strip data object independently to decrease the recovery time. Thirdly a journal-like metadata management way is introduced to provide metadata optimization for CDP.

  14. A Learning Object Approach To Evidence based learning

    Directory of Open Access Journals (Sweden)

    Zabin Visram

    2005-06-01

    Full Text Available This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has meant increasingly, there is a desperate need to adopt wireless schemes, whereby bespoke courses can be developed to help practitioners keep up with expanding knowledge base. Evidently, without current best evidence, practice risks becoming rapidly out of date, to the detriment of the patient. There is a need to provide a tactical, operational and effective environment, which allows professional to update their education, and complete specialised training, just-in-time, in their own time and location. Following this demand in the marketplace the information engineering group, in combination with several medical and dental schools, set out to develop and design a conceptual framework which form the basis of pioneering research, which at last, enables practitioner's to adopt a philosophy of life long learning. The body and structure of this framework is subsumed under the term Object oriented approach to Evidence Based learning, Just-in-time, via Internet sustained by Reusable Learning Objects (The OEBJIRLO Progression. The technical pillars which permit this concept of life long learning are pivoted by the foundations of object oriented technology, Learning objects, Just-in-time education, Data Mining, intelligent Agent technology, Flash interconnectivity and remote wireless technology, which allow practitioners to update their professional skills, complete specialised training which leads to accredited qualifications. This paper sets out to develop and implement a range of teaching and learning strategies that would accommodate the flexibility required by such a scheme. At the same time the specific requirements of individual programmes are satisfied. The body of elements provide an integrated path taking students through the range of operational, tactical and strategic issues involved in Web Based Learning, sustained by learning object abstract framework and Agent technology, within a distant learning context.

  15. Region competition based active contour for medical object extraction.

    Science.gov (United States)

    Shang, Yanfeng; Yang, Xin; Zhu, Lei; Deklerck, Rudi; Nyssen, Edgard

    2008-03-01

    In this paper, a probabilistic and level set model for three-dimensional medical object extraction is proposed, which is called region competition based active contour. The algorithms are derived by minimizing a region based probabilistic energy function and implemented in a level set framework. An additional speed-controlling term makes the active contour quickly convergent to the actual contour on strong edges, whereas a probabilistic model makes the active contour performing well for weak edges. Prior knowledge about the initial contour and the probabilistic distribution contributes to more efficient extraction. The developed model has been applied to a variety of medical images, from CTA and MRA of the coronary to rotationally scanned and real-time three-dimensional echocardiography images of the mitral valve. As the results show, the algorithm is fast, convergent, adapted to a broad range of medical objects and produces satisfactory results. PMID:18083344

  16. Cloud Aggregation and Bursting for Object Based Sharable Environment

    OpenAIRE

    Mr. Pradeep Kumar Tripathi; Prof. Surendra Mishra; Pankaj Kawadkar

    2011-01-01

    Cloud computing promises innate scalability and high availability at low cost. So far cloud storage deployments were subject to big companies but an increasing amount of available open-source systems allow also smaller private cloud installations. In this paper we discuss cloud aggregation and cloud bursting with their empirical review. Based on the review we map class and object in the sharable small clouds for making clouds more efficient. We also consider some of the security concern for t...

  17. Tactile objects based on an amplitude disturbed diffraction pattern method

    OpenAIRE

    Liu, Yuan; Nikolovski, Jean-Pierre; MECHBAL, Nazih; Hafez, Moustapha; Vergé, Michel

    2009-01-01

    Tactile sensing is becoming widely used in human-computer interfaces. Recent advances in acoustic approaches demonstrated the possibilities to transform ordinary solid objects into interactive interfaces. This letter proposes a static finger contact localization process using an amplitude disturbed diffraction pattern method. The localization method is based on the following physical phenomenon: a finger contact modifies the energy distribution of acoustic wave in a solid; these variations de...

  18. Proxy caching based on object location considering semantic usage

    OpenAIRE

    Rochat, Philippe; Thompson, Stuart

    1999-01-01

    With the Internet success leading to heavy demands on network, proxies have beco me an unavoidable necessity. In this paper we present a new technique to improve caching services for an Internet user group. We propose an alternative to classical LRU, LFU or similar algorithms. Our appro ach is based on object usage, cross-references and geographic location. With our system we will not only improve on storing performance taking into account pref erences and usage of specific user groups, but w...

  19. Geographic Object-Based Image Analysis – Towards a new paradigm

    OpenAIRE

    Blaschke, Thomas; Hay, Geoffrey J.; Kelly, Maggi; Lang, Stefan; Hofmann, Peter; Addink, Elisabeth; Queiroz Feitosa, Raul; Meer, Freek; Werff, Harald; Coillie, Frieke; Tiede, Dirk

    2014-01-01

    The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience)...

  20. Geographic Object-Based Image Analysis - Towards a new paradigm.

    Science.gov (United States)

    Blaschke, Thomas; Hay, Geoffrey J; Kelly, Maggi; Lang, Stefan; Hofmann, Peter; Addink, Elisabeth; Queiroz Feitosa, Raul; van der Meer, Freek; van der Werff, Harald; van Coillie, Frieke; Tiede, Dirk

    2014-01-01

    The amount of scientific literature on (Geographic) Object-based Image Analysis - GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the 'per-pixel paradigm' and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm. PMID:24623958

  1. Graph - Based High Resolution Satellite Image Segmentation for Object Recognition

    Science.gov (United States)

    Ravali, K.; Kumar, M. V. Ravi; Venugopala Rao, K.

    2014-11-01

    Object based image processing and analysis is challenging research in very high resolution satellite utilisation. Commonly ei ther pixel based classification or visual interpretation is used to recognize and delineate land cover categories. The pixel based classification techniques use rich spectral content of satellite images and fail to utilise spatial relations. To overcome th is drawback, traditional time consuming visual interpretation methods are being used operational ly for preparation of thematic maps. This paper addresses computational vision principles to object level image segmentation. In this study, computer vision algorithms are developed to define the boundary between two object regions and segmentation by representing image as graph. Image is represented as a graph G (V, E), where nodes belong to pixels and, edges (E) connect nodes belonging to neighbouring pixels. The transformed Mahalanobis distance has been used to define a weight function for partition of graph into components such that each component represents the region of land category. This implies that edges between two vertices in the same component have relatively low weights and edges between vertices in different components should have higher weights. The derived segments are categorised to different land cover using supervised classification. The paper presents the experimental results on real world multi-spectral remote sensing images of different landscapes such as Urban, agriculture and mixed land cover. Graph construction done in C program and list the run time for both graph construction and segmentation calculation on dual core Intel i7 system with 16 GB RAM, running 64bit window 7.

  2. Object-oriented programming of PLC based on IEC 1131

    OpenAIRE

    Weule, Hartmut; Spath, Dieter; Schelberg, Hans-joachim

    1994-01-01

    The software development for programmable logical controllers is usually based on low-level languages such as the instruction list or the ladder diagram. At the same time, the programmer looks at a machine or an assembly system in a bit-oriented way: he translates the operational sequences into logical and/or time based combinations of binary signals described by the means of boolean algebra. A machine, however, does not only consist of binary signals but of technical components, i.e. objects...

  3. Maritime target identification in flash-ladar imagery

    Science.gov (United States)

    Armbruster, Walter; Hammer, Marcus

    2012-05-01

    The paper presents new techniques and processing results for automatic segmentation, shape classification, generic pose estimation, and model-based identification of naval vessels in laser radar imagery. The special characteristics of focal plane array laser radar systems such as multiple reflections and intensity-dependent range measurements are incorporated into the algorithms. The proposed 3D model matching technique is probabilistic, based on the range error distribution, correspondence errors, the detection probability of potentially visible model points and false alarm errors. The match algorithm is robust against incomplete and inaccurate models, each model having been generated semi-automatically from a single range image. A classification accuracy of about 96% was attained, using a maritime database with over 8000 flash laser radar images of 146 ships at various ranges and orientations together with a model library of 46 vessels. Applications include military maritime reconnaissance, coastal surveillance, harbor security and anti-piracy operations.

  4. Maximum a-posteriori LADAR Image estimation in the presence of scintillation and speckle noise

    Science.gov (United States)

    Dayton, David C.; Nolasco, Rudolph; Sena, John-Paul; Myers, Michael; Fertig, Gregory; Oliver, Jeremy

    2012-10-01

    Laser aided detection and ranging (LADAR) imaging systems are usually corrupted by several pathologic noises. Speckle noise is due to the coherent nature of the laser illuminator. Scintillation noise is introduced by atmospheric turbulence over the outgoing illumination path and manifests itself as a multiplicative noise in the imagery. These noises can be mitigated by a simple recursive averaging algorithm when looking at fixed targets in staring mode. However if the target under observation is moving with respect to the imaging platform, the averaging will cause the target image to smear. In such a case, a maximum a-posteriori (MAP) approach can be used to estimate localized statistics of the scene under observation as well as the scintillation. The parameter estimates can then be incorporated into a spatially and temporally adaptive averaging approach which mitigates the noise while at the same time preserving motion in the scene.

  5. Inferred-boundary-based approach to object recognition

    Science.gov (United States)

    Ralescu, Anca L.; Shanahan, James G.

    1995-03-01

    We are concerned with object recognition in the framework of a navigation support system (NSS). Unlike a vision based navigation system where the navigating agent must solve obstacle avoidance problems, path planning, etc., different problems must be solved in the NSS: for instance it must inform the user that it has reached a desired location once objects associated with that location have been recognized. In this general context we present a framework to compute perceptual organization. It incorporates a number of concepts from human visual analysis especially the Gestalt laws of organization. Fuzzy techniques are used for the definition and evaluation of the grouping/non-grouping properties as well as for the construction of structures from grouped input tokens. This method takes as input the initially fitted line segments (tokens) and then recursively groups these tokens into higher level structures (tokens) such as lines, u-structures, quadrilaterals, etc. The output high level structures can then be used to compare with object models and thus lead to object recognition. In this paper inference (grouping) of line segments, line symmetry, junctions, closed regions and strands is presented. The approach is supported by experimental results on 2D images of an office scene environment.

  6. Multiview-Based Cooperative Tracking of Multiple Human Objects

    Directory of Open Access Journals (Sweden)

    Kuo-Chin Lien

    2008-03-01

    Full Text Available Human tracking is a popular research topic in computer vision. However, occlusion problem often complicates the tracking process. This paper presents the so-called multiview-based cooperative tracking of multiple human objects based on the homographic relation between different views. This cooperative tracking applies two hidden Markov processes (tracking and occlusion processes for each target in each view. The tracking process locates the moving target in each view, whereas the occlusion process represents the possible visibility of the specific target in that designated view. Based on the occlusion process, the cooperative tracking process may reallocate tracking resources for different trackers in different views. Experimental results show the efficiency of the proposed method.

  7. Multiview-Based Cooperative Tracking of Multiple Human Objects

    Directory of Open Access Journals (Sweden)

    Lien Kuo-Chin

    2008-01-01

    Full Text Available Abstract Human tracking is a popular research topic in computer vision. However, occlusion problem often complicates the tracking process. This paper presents the so-called multiview-based cooperative tracking of multiple human objects based on the homographic relation between different views. This cooperative tracking applies two hidden Markov processes (tracking and occlusion processes for each target in each view. The tracking process locates the moving target in each view, whereas the occlusion process represents the possible visibility of the specific target in that designated view. Based on the occlusion process, the cooperative tracking process may reallocate tracking resources for different trackers in different views. Experimental results show the efficiency of the proposed method.

  8. Analysis of manufacturing based on object oriented discrete event simulation

    Directory of Open Access Journals (Sweden)

    Eirik Borgen

    1990-01-01

    Full Text Available This paper describes SIMMEK, a computer-based tool for performing analysis of manufacturing systems, developed at the Production Engineering Laboratory, NTH-SINTEF. Its main use will be in analysis of job shop type of manufacturing. But certain facilities make it suitable for FMS as well as a production line manufacturing. This type of simulation is very useful in analysis of any types of changes that occur in a manufacturing system. These changes may be investments in new machines or equipment, a change in layout, a change in product mix, use of late shifts, etc. The effects these changes have on for instance the throughput, the amount of VIP, the costs or the net profit, can be analysed. And this can be done before the changes are made, and without disturbing the real system. Simulation takes into consideration, unlike other tools for analysis of manufacturing systems, uncertainty in arrival rates, process and operation times, and machine availability. It also shows the interaction effects a job which is late in one machine, has on the remaining machines in its route through the layout. It is these effects that cause every production plan not to be fulfilled completely. SIMMEK is based on discrete event simulation, and the modeling environment is object oriented. The object oriented models are transformed by an object linker into data structures executable by the simulation kernel. The processes of the entity objects, i.e. the products, are broken down to events and put into an event list. The user friendly graphical modeling environment makes it possible for end users to build models in a quick and reliable way, using terms from manufacturing. Various tests and a check of model logic are helpful functions when testing validity of the models. Integration with software packages, with business graphics and statistical functions, is convenient in the result presentation phase.

  9. Cloud Aggregation and Bursting for Object Based Sharable Environment

    Directory of Open Access Journals (Sweden)

    Mr. Pradeep Kumar Tripathi

    2011-09-01

    Full Text Available Cloud computing promises innate scalability and high availability at low cost. So far cloud storage deployments were subject to big companies but an increasing amount of available open-source systems allow also smaller private cloud installations. In this paper we discuss cloud aggregation and cloud bursting with their empirical review. Based on the review we map class and object in the sharable small clouds for making clouds more efficient. We also consider some of the security concern for the cloud computing for authorized data sharing between clouds.

  10. A Fuzzy Multi-Objective Class Based Storage Location Assignment

    OpenAIRE

    B. Maleki Vishkaei; M. EbrahimNezhad Moghadam Rashti

    2011-01-01

    The required storage space and the material handing cost in a warehouse hinge on the storage implementation decision. Effects of storage area reduction on order picking and storage space cost are incorporated. Moreover, merchandises which are in the same shape and can be stored beside each other easily or goods that don't cause any danger like causing a fire if be in touch with each other, can be stored in one class together. In this paper first a multi-objective class based storage model is ...

  11. Multi-Objective Multicast Routing based on Ant Colony Optimization

    OpenAIRE

    Pinto, Diego; Bara?n, Benjami?n; Fabregat Gesa, Ramon

    2005-01-01

    This work presents a new multiobjective algorithm based on ant colonies, which is used in the construction of the multicast tree for data transmission in a computer network. The proposed algorithm simultaneously optimizes cost of the multicast tree, average delay and maximum end-to-end delay. In this way, a set of optimal solutions, know as Pareto set, is calculated in only one run of the algorithm, without a priori restrictions. The proposed algorithm was inspired in a Multi-objective Ant Co...

  12. An object-based methodology for knowledge representation

    Energy Technology Data Exchange (ETDEWEB)

    Kelsey, R.L. [Los Alamos National Lab., NM (United States)|New Mexico State Univ., Las Cruces, NM (United States); Hartley, R.T. [New Mexico State Univ., Las Cruces, NM (United States); Webster, R.B. [Los Alamos National Lab., NM (United States)

    1997-11-01

    An object based methodology for knowledge representation is presented. The constructs and notation to the methodology are described and illustrated with examples. The ``blocks world,`` a classic artificial intelligence problem, is used to illustrate some of the features of the methodology including perspectives and events. Representing knowledge with perspectives can enrich the detail of the knowledge and facilitate potential lines of reasoning. Events allow example uses of the knowledge to be represented along with the contained knowledge. Other features include the extensibility and maintainability of knowledge represented in the methodology.

  13. An Object-oriented Design and Push Web Server based Framework for Physical Object Interactions and Services

    Directory of Open Access Journals (Sweden)

    Runhe Huang

    2008-11-01

    Full Text Available One of the substantial issues in ubiquitous computing is the automatic processing of information from real world objects and enabling their interactions in the background. This scenario requires a framework on which such information processing and object interaction can be supported. This article presents our research progress in developing a framework based on the object-oriented design approach and the use of a push web server. With the concept of object abstraction, an object can hide its internal structure from the outside world, which can make the object secure. Moreover, object interaction can be conducted via message exchanges, which makes the interface simple and standardized and the heterogeneous objects can be easily handled as well. Instead of using the traditional pull web server, a push web server, i.e., Comet, which runs on top of HTTP protocol is used to exchange messages. To this, object interactions can be operated smoothly and seamlessly in real time with shorter delay.

  14. A self-similarity based unification of BL Lacertae objects.

    Science.gov (United States)

    Georganopoulos, M.; Marscher, A. P.

    1997-12-01

    BL Lacertae (BL Lac) objects have been traditionally classified as radio selected BL Lacs (RBLs) or X-ray selected BL Lacs (XBLs) according to the discovery method. The recent discovery of a BL Lac population with observational properties intermediate between those of RBLs and XBLs, strongly suggest that this bimodal classification is misleading, and essentially reflects the two different discovery methods. We propose a unification scheme for BL Lac objects based on the following scenario: the kinetic luminosity of the jet Lambda_ {kin} scales with the size of the jet r, following the relation Lambda_ {kin} ~ r(2) . Additionally, the intensive physical variables that describe the relativistic jet in the BL Lac objects have a small intrinsic range of values. The combination of these two assumptions suggests a unification scheme, where the observed properties of a BL Lac depend mainly on the kinetic luminosity of the jet and the angle between the line of sight and the jet axis. We apply this scheme using the accelerating inner jet model, comparing the predictions of this unification with observational data from complete BL Lac samples. Finally, we briefly address the question of extending this unified scheme to include the family of flat spectrum radio quasars.

  15. Visual-adaptation-mechanism based underwater object extraction

    Science.gov (United States)

    Chen, Zhe; Wang, Huibin; Xu, Lizhong; Shen, Jie

    2014-03-01

    Due to the major obstacles originating from the strong light absorption and scattering in a dynamic underwater environment, underwater optical information acquisition and processing suffer from effects such as limited range, non-uniform lighting, low contrast, and diminished colors, causing it to become the bottleneck for marine scientific research and projects. After studying and generalizing the underwater biological visual mechanism, we explore its advantages in light adaption which helps animals to precisely sense the underwater scene and recognize their prey or enemies. Then, aiming to transform the significant advantage of the visual adaptation mechanism into underwater computer vision tasks, a novel knowledge-based information weighting fusion model is established for underwater object extraction. With this bionic model, the dynamical adaptability is given to the underwater object extraction task, making them more robust to the variability of the optical properties in different environments. The capability of the proposed method to adapt to the underwater optical environments is shown, and its outperformance for the object extraction is demonstrated by comparison experiments.

  16. OBJECT BASED SEGMENTATION TECHNIQUES FOR CLASSIFICATION OF SATELLITE IMAGE

    Directory of Open Access Journals (Sweden)

    B.Ankayarkanni

    2014-07-01

    Full Text Available Automatic feature extraction of features such as building, roads, vegetation etc., which also includes collapsed, height-changed and removed buildings, require the use of high resolution images. This research is helpful to develop a technique that can detect changes in urban buildings after natural disasters such as earthquakes, typhoons or tsunamis. This is also helpful in providing an accurate information about the changes for urban planning and updating Geo-spatial information system (GIS.It is necessary that the remote sensing imagery has to be converted into some meaning information, which in turn requires some segmentation methods followed by classification. Earlier pixel based approaches was followed which requires more computation on these high resolution images .This paper proposes few object based method (K-means , KFCM , Moving KFCMfor classification that segments the image followed by classification.

  17. Tactile objects based on an amplitude disturbed diffraction pattern method

    Science.gov (United States)

    Liu, Yuan; Nikolovski, Jean-Pierre; Mechbal, Nazih; Hafez, Moustapha; Vergé, Michel

    2009-12-01

    Tactile sensing is becoming widely used in human-computer interfaces. Recent advances in acoustic approaches demonstrated the possibilities to transform ordinary solid objects into interactive interfaces. This letter proposes a static finger contact localization process using an amplitude disturbed diffraction pattern method. The localization method is based on the following physical phenomenon: a finger contact modifies the energy distribution of acoustic wave in a solid; these variations depend on the wave frequency and the contact position. The presented method first consists of exciting the object with an acoustic signal with plural frequency components. In a second step, a measured acoustic signal is compared with prerecorded values to deduce the contact position. This position is then used for human-machine interaction (e.g., finger tracking on computer screen). The selection of excitation signals is discussed and a frequency choice criterion based on contrast value is proposed. Tests on a sandwich plate (liquid crystal display screen) prove the simplicity and easiness to apply the process in various solids.

  18. Area-based and location-based validation of classified image objects

    Science.gov (United States)

    Whiteside, Timothy G.; Maier, Stefan W.; Boggs, Guy S.

    2014-05-01

    Geographic object-based image analysis (GEOBIA) produces results that have both thematic and geometric properties. Classified objects not only belong to particular classes but also have spatial properties such as location and shape. Therefore, any accuracy assessment where quantification of area is required must (but often does not) take into account both thematic and geometric properties of the classified objects. By using location-based and area-based measures to compare classified objects to corresponding reference objects, accuracy information for both thematic and geometric assessment is available. Our methods provide location-based and area-based measures with application to both a single-class feature detection and a multi-class object-based land cover analysis. In each case the classification was compared to a GIS layer of associated reference data using randomly selected sample areas. Error is able to be pin-pointed spatially on per-object, per class and per-sample area bases although there is no indication whether the errors exist in the classification product or the reference data. This work showcases the utility of the methods for assessing the accuracy of GEOBIA derived classifications provided the reference data is accurate and of comparable scale.

  19. Object Persistence: A Framework Based On Design Patterns

    OpenAIRE

    Kienzle, Jörg; Romanovsky, Alexander

    2000-01-01

    The poster presents a framework for providing object persistence in object-oriented programming languages without modifying the run-time system or the language itself. The framework does not rely on any kind of special programming language features. It only uses basic object-oriented programming techniques, and is therefore implementable in any object-oriented programming language.

  20. Mobile object retrieval in server-based image databases

    Science.gov (United States)

    Manger, D.; Pagel, F.; Widak, H.

    2013-05-01

    The increasing number of mobile phones equipped with powerful cameras leads to huge collections of user-generated images. To utilize the information of the images on site, image retrieval systems are becoming more and more popular to search for similar objects in an own image database. As the computational performance and the memory capacity of mobile devices are constantly increasing, this search can often be performed on the device itself. This is feasible, for example, if the images are represented with global image features or if the search is done using EXIF or textual metadata. However, for larger image databases, if multiple users are meant to contribute to a growing image database or if powerful content-based image retrieval methods with local features are required, a server-based image retrieval backend is needed. In this work, we present a content-based image retrieval system with a client server architecture working with local features. On the server side, the scalability to large image databases is addressed with the popular bag-of-word model with state-of-the-art extensions. The client end of the system focuses on a lightweight user interface presenting the most similar images of the database highlighting the visual information which is common with the query image. Additionally, new images can be added to the database making it a powerful and interactive tool for mobile contentbased image retrieval.

  1. Object-Based Building Extraction from High Resolution Satellite Imagery

    Science.gov (United States)

    Attarzadeh, R.; Momeni, M.

    2012-07-01

    Automatic building extraction from high resolution satellite imagery is considered as an important field of research in remote sensing and machine vision. Many algorithms for extraction of buildings from satellite images have been presented so far. These algorithms mainly have considered radiometric, geometric, edge detection and shadow criteria approaches to perform the building extraction. In this paper, we propose a novel object based approach for automatic and robust detection and extraction of building in high spatial resolution images. To achieve this goal, we use stable and variable features together. Stable features are derived from inherent characteristics of building phenomenon and variable features are extracted using SEparability and THresholds analysis tool. The proposed method has been applied on a QuickBird imagery of an urban area in Isfahan city and visual validation demonstrates that the proposed method provides promising results.

  2. RFID and IP Based Object Identification in Ubiquitous Networking

    OpenAIRE

    Nisha Vaghela; Parikshit Mahalle

    2012-01-01

    Ubiquitous networking is an integrated part of future networking technology that can provide capabilities for connecting all of objects (computers, human, PDAs, cell phones etc.) in future network. It has to meet the challenge of seamless connection for communication between human and objects in internet infrastructure. Unique object identification is very much important to make the communication between objects possible. RFID tag can be used as unique identifier to identify a physical object...

  3. Noise Based Detection and Segmentation of Nebulous Objects

    CERN Document Server

    Akhlaghi, Mohammad

    2015-01-01

    A noise based non parametric technique to detect nebulous objects, for example irregular or clumpy galaxies, and their structure in noise is introduced. Noise based and non parametric imply that it imposes negligible constraints on the properties of the targets and that it employs no regression analysis or fittings. The sub-sky detection threshold is defined, and initial detections are found, independent of the sky value. False detections are then estimated and removed using the ambient noise as a reference. This results in a purity level of 0.86 for the final detections as compared to 0.27 for SExtractor when a completeness of 1 is desired for a sample extremely faint and diffuse identical mock galaxy profiles. The dispersion in their measured magnitudes is less by one magnitude, allowing much more accurate photometry. Defining the accuracy of detection as the difference of the measured sky with the known background of mock images, an order of magnitude less biased sky measurement is achieved. A non parametr...

  4. Apparatus and method for generating Audio output signals using Object Based Metadata

    OpenAIRE

    Schreiner, S.; Fiesel, W.; Neusinger, M.; Hellmuth, O.; Sperschneider, R.

    2010-01-01

    An apparatus for generating at least one audio output signal representing a superposition of at least two different audio objects comprises a processor for processing an audio input signal to provide an object representation of the audio input signal, where this object representation can be generated by a parametrically guided approximation of original objects using an object downmix signal. An object manipulator individually manipulates objects using audio object based metadata referring to ...

  5. Advances in linear and area HgCdTe APD arrays for eyesafe LADAR sensors

    Science.gov (United States)

    Jack, Michael D.; Asbrock, James F.; Anderson, C.; Bailey, Steven L.; Chapman, George; Gordon, E.; Herning, P. E.; Kalisher, Murray H.; Kosai, Kim; Liquori, V.; Randall, Valerie; Rosbeck, Joseph P.; Sen, Sanghamitra; Wetzel, P.; Halmos, Maurice J.; Trotta, Patrick A.; Hunter, Andrew T.; Jensen, John E.; de Lyon, Terence J.; Johnson, W.; Walker, B.; Trussel, Ward; Hutchinson, Andy; Balcerak, Raymond S.

    2001-11-01

    HgCdTe APDs and APD arrays offer unique advantages for high-performance eyesafe LADAR sensors. These include: operation at room temperature, low-excess noise, high gain, high-quantum efficiency at eyesafe wavelengths, GHz bandwidth, and high-packing density. The utility of these benefits for systems are being demonstrated for both linear and area array sensors. Raytheon has fabricated 32 element linear APD arrays utilizing liquid phase epitaxy (LPE), and packaged and integrating these arrays with low-noise amplifiers. Typical better APDs configured as 50-micron square pixels and fabricated utilizing RIE, have demonstrated high fill factors, low crosstalk, excellent uniformity, low dark currents, and noise equivalent power (NEP) from 1-2 nW. Two units have been delivered to NVESD, assembled with range extraction electronics, and integrated into the CELRAP laser radar system. Tests on these sensors in July and October 2000 have demonstrated excellent functionality, detection of 1-cm wires, and range imaging. Work is presently underway under DARPA's 3-D imaging Sensor Program to extend this excellent performance to area arrays. High-density arrays have been fabricated using LPE and molecular beam epitaxy (MBE). HgCdTe APD arrays have been made in 5 X 5, 10 X 10 and larger formats. Initial data shows excellent typical better APD performance with unmultiplied dark current < 10 nA; and NEP < 2.0 nW at a gain of 10.

  6. Micro-Doppler effect analysis and feature extraction in inverse synthetic aperture imaging LADAR imaging

    Science.gov (United States)

    He, Jin; Zhang, Qun; Luo, Ying; Liang, Xianjiao; Yang, Xiaoyou

    2011-01-01

    The micro-Doppler (m-D) effect describes the subtle micromotion features of a radar target and provides a new approach for feature extraction and auto radar target recognition. However, the microwave radar cannot provide enough resolution to detect the m-D effect of small targets and long distance targets. In order to obtain high range resolution for the extraction of subtle m-D signatures, inverse synthetic aperture imaging LADAR (ISAIL) is used here. Because the ISAIL uses a frequency modulation continuous wave signal, the m-D effect of ISAIL is different from the microwave radar. In this paper, the m-D effect of ISAIL is analyzed. The features of the m-D signatures in ISAIL are extracted by an improved Hough transform method associated with erosion and dilation operations in binary mathematical morphology. The simulations are given to validate the theoretical analyses and the proposed m-D extraction method. The experiment results show that the ISAIL can offer sufficient information of micromotions when the feature of motions is tiny.

  7. Wandering: A Web-Based Platform for the Creation of Location-Based Interactive Learning Objects

    Science.gov (United States)

    Barak, Miri; Ziv, Shani

    2013-01-01

    Wandering is an innovative web-based platform that was designed to facilitate outdoor, authentic, and interactive learning via the creation of location-based interactive learning objects (LILOs). Wandering was integrated as part of a novel environmental education program among middle school students. This paper describes the Wandering platform's…

  8. Scheduler for monitoring objects orbiting earth using satellite-based telescopes

    Energy Technology Data Exchange (ETDEWEB)

    Olivier, Scot S; Pertica, Alexander J; Riot, Vincent J; De Vries, Willem H; Bauman, Brian J; Nikolaev, Sergei; Henderson, John R; Phillion, Donald W

    2015-04-28

    An ephemeris refinement system includes satellites with imaging devices in earth orbit to make observations of space-based objects ("target objects") and a ground-based controller that controls the scheduling of the satellites to make the observations of the target objects and refines orbital models of the target objects. The ground-based controller determines when the target objects of interest will be near enough to a satellite for that satellite to collect an image of the target object based on an initial orbital model for the target objects. The ground-based controller directs the schedules to be uploaded to the satellites, and the satellites make observations as scheduled and download the observations to the ground-based controller. The ground-based controller then refines the initial orbital models of the target objects based on the locations of the target objects that are derived from the observations.

  9. Object Recognition Algorithm Utilizing Graph Cuts Based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Zhaofeng Li

    2014-02-01

    Full Text Available This paper concentrates on designing an object recognition algorithm utilizing image segmentation. The main innovations of this paper lie in that we convert the image segmentation problem into graph cut problem, and then the graph cut results can be obtained by calculating the probability of intensity for a given pixel which is belonged to the object and the background intensity. After the graph cut process, the pixels in a same component are similar, and the pixels in different components are dissimilar. To detect the objects in the test image, the visual similarity between the segments of the testing images and the object types deduced from the training images is estimated. Finally, a series of experiments are conducted to make performance evaluation. Experimental results illustrate that compared with existing methods, the proposed scheme can effectively detect the salient objects. Particularly, we testify that, in our scheme, the precision of object recognition is proportional to image segmentation accuracy

  10. Object-based modelling for representing and processing speech corpora

    OpenAIRE

    Altosaar, Toomas

    2001-01-01

    This thesis deals with modelling data existing in large speech corpora using an object-oriented paradigm which captures important linguistic structures. Information from corpora is transformed into objects and are assigned properties regarding their behaviour. These objects, called speech units, are placed onto a multi-dimensional framework and have their relationships to other units explicitly defined through the use of links. Frameworks that model temporal utterances or atemporal informatio...

  11. Partial Evaluation for Class-Based Object-Oriented Languages

    DEFF Research Database (Denmark)

    Schultz, Ulrik Pagh

    2001-01-01

    Object-oriented programming facilitates the development of generic software, but at a significant cost in terms of performance. We apply partial evaluation to object-oriented programs, to automatically map generic software into specific implementations. In this paper we give a concise, formal description of a simple partial evaluator for a minimal object-oriented language, and give directions for extending this partial evaluator to handle realistic programs.

  12. Optical MEMS-based arrays

    Science.gov (United States)

    Ruffin, Paul B.

    2003-07-01

    Industrial Micro Electro Mechanical Systems (MEMS) developers are rapidly bringing to demonstration inertial radio frequency, and optical MEMS devices and components. The Army has a requirement for compact, highly reliable, and inexpensive laser beam steering components for missile seekers and unmanned aerial vehicles remote sensing components to provide a fast scanning capability for pointing, acquisition, tracking, and data communication. The coupling of this requirement with recent developments in the micro-optics area, has led scientists and engineers at the Army Aviation and Missile Command (AMCOM) to consider optical MEMS-based phased arrays, which have potential applications in the commercial industry as well as in the military, as a replacement for gimbals. Laser beam steering in commercial applications such as free space communicataion, scanning display, bar-code reading, and gimbaled seekers; require relatively large monolithic micro-mirrors to accomplish the required optical resolution. The Army will benefit from phased arrays composed of relatively small micro-mirrors that can be actuated through large deflection angles with substantially reduced volume times. The AMCOM Aviation and Missile Research, Development, and Engineering Center (AMRDEC) has initiated a research project to develop MEMS-based phased arrays for use in a small volume, inexpensive Laser Detection and Ranging (LADAR) seeker that is particularly attractive because of its ability to provide large field-of-regard and autonomous target acquisition for reconnaissance mission applications. The primary objective of the collaborative project with the Defence Advanced Research Projects Agency (DARPA) is to develop a rugged, MEMS-based phased arrays for incorporation into the 2-D scanner of a LADAR seeker. Design challenges and approach to achieving performance requirements will be discussed.

  13. A Framework for Geographic Object-Based Image Analysis (GEOBIA) based on geographic ontology

    Science.gov (United States)

    Gu, H. Y.; Li, H. T.; Yan, L.; Lu, X. J.

    2015-06-01

    GEOBIA (Geographic Object-Based Image Analysis) is not only a hot topic of current remote sensing and geographical research. It is believed to be a paradigm in remote sensing and GIScience. The lack of a systematic approach designed to conceptualize and formalize the class definitions makes GEOBIA a highly subjective and difficult method to reproduce. This paper aims to put forward a framework for GEOBIA based on geographic ontology theory, which could implement "Geographic entities - Image objects - Geographic objects" true reappearance. It consists of three steps, first, geographical entities are described by geographic ontology, second, semantic network model is built based on OWL(ontology web language), at last, geographical objects are classified with decision rule or other classifiers. A case study of farmland ontology was conducted for describing the framework. The strength of this framework is that it provides interpretation strategies and global framework for GEOBIA with the property of objective, overall, universal, universality, etc., which avoids inconsistencies caused by different experts' experience and provides an objective model for mage analysis.

  14. Orbit determination of space objects based on sparse optical data

    CERN Document Server

    Milani, A; Farnocchia, D; Rossi, A; Schildknecht, T; Jehn, R

    2010-01-01

    While building up a catalog of Earth orbiting objects, if the available optical observations are sparse, not deliberate follow ups of specific objects, no orbit determination is possible without previous correlation of observations obtained at different times. This correlation step is the most computationally intensive, and becomes more and more difficult as the number of objects to be discovered increases. In this paper we tested two different algorithms (and the related prototype software) recently developed to solve the correlation problem for objects in geostationary orbit (GEO), including the accurate orbit determination by full least squares solutions with all six orbital elements. Because of the presence in the GEO region of a significant subpopulation of high area to mass objects, strongly affected by non-gravitational perturbations, it was actually necessary to solve also for dynamical parameters describing these effects, that is to fit between 6 and 8 free parameters for each orbit. The validation w...

  15. A biological hierarchical model based underwater moving object detection.

    Science.gov (United States)

    Shen, Jie; Fan, Tanghuai; Tang, Min; Zhang, Qian; Sun, Zhen; Huang, Fengchen

    2014-01-01

    Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater applications. Aiming to solve the problems originated from the inhomogeneous lumination and the unstable background, the mechanism of the visual information sensing and processing pattern from the eye of frogs are imitated to produce a hierarchical background model for detecting underwater objects. Firstly, the image is segmented into several subblocks. The intensity information is extracted for establishing background model which could roughly identify the object and the background regions. The texture feature of each pixel in the rough object region is further analyzed to generate the object contour precisely. Experimental results demonstrate that the proposed method gives a better performance. Compared to the traditional Gaussian background model, the completeness of the object detection is 97.92% with only 0.94% of the background region that is included in the detection results. PMID:25140194

  16. Dynamic Cell Formation based on Multi-objective Optimization Model

    OpenAIRE

    Guozhu Jia; Wen Kong

    2013-01-01

    In this paper, a multi-objective model is proposed to address the dynamic cellular manufacturing (DCM) formation problem. This model considers four conflicting objectives: relocation cost, machine utilization, material handling cost and maintenance cost. The model also considers the situation that some machines could be shared by more than one cell at the same period. A genetic algorithm is applied to get the solution of this mathematical model. Three numerical examples are simulate...

  17. A Biological Hierarchical Model Based Underwater Moving Object Detection

    OpenAIRE

    Jie Shen; Tanghuai Fan; Min Tang; Qian Zhang; Zhen Sun; Fengchen Huang

    2014-01-01

    Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater appl...

  18. Rendering Realistic Augmented Objects Using a Image Based Lighting Approach

    OpenAIRE

    Karlsson, Johan; Selega?rd, Mikael

    2005-01-01

    Augmented Reality (AR), the combination of real and virtual worlds, is a growing area in computer graphics. Until now, most of the focus has been on placing synthetic objects in the right position with regards to the real world, and to explor the possibilities of human interaction within the two worlds. This thesis presents the fact that virtual objects must not only be placed correctly but also lit truthfully in order to achieve a good degree of immersion. Conventional rendering techniques s...

  19. Distributed Database for Reusable Learning Object-Based System

    OpenAIRE

    Hamid, S. H. A.; Nasir, M. H. N. M.; Hassan, N. H.

    2008-01-01

    In this study, discusses enhancing the e-learning system by employing a distributed database that apply reusable learning object as one of the technologies that is applied to e-learning development. An e-learning system named e-notes is able to assist students and facilitators to interact with each other. Learning objects are used to conceptualize the learning process and offer accessibility, interoperability, adaptability, durability, reusability and granularity for the e-learning envi...

  20. Drifting Recovery Base Concept for GEO Derelict Object Capture

    Science.gov (United States)

    Bacon, John B.

    2009-01-01

    Over 250 objects hover within 6 m/sec of perfect geostationary orbit. Over half of these objects lie within 0.1 m/sec of the GEO velocity. Such items have 62% of the total velocity required to achieve Earth gravitational escape. A conceptual architecture is proposed to clean this orbit area of derelict objects while providing a demonstration mission for many facets of future asteroid mining operations. These near-GEO objects average nearly 2000kg each, consisting of (typically functioning) power systems, batteries, and large quantities of components and raw aerospace-grade refined materials. Such a demonstration collection system could capture, collect and remove all GEO derelict objects in an international effort to create a depot of components and of aerospace-grade raw materials--with a total mass greater than that of the International Space Station--as a space scrap depot ready for transfer to lunar or Mars orbit, using only two heavy-lift launches and 2-3 years of on-orbit operations.

  1. Implementation of multiview stereoscopic images based on adaptive object segmentation

    Science.gov (United States)

    Lee, Jong-Ho; Bae, Kyung-Hoon; Kim, Eun-Soo

    2002-07-01

    In general, the stereo input images obtained by the parallel-axis camera system lacks in the common field of view and the disparity information of the object due to its configuration limitation. In this paper, a new scheme is proposed, in which this stereopsis can be improved by adaptively controlling the disparity of the input stereo images. In the proposed method, each object in the stereo input image is segmented by considering the relative distance information of them and then, each segmented object is horizontally shifted according to these values, in which especially the differential shifting scheme is applied to maximize the stereopsis of the stereo input images. From some experimental results, it is shown that the proposed method improves the disparity of the original stereo image about 1.6 dB in PSNR. In addition, 6-view stereoscopic image synthesized by the proposed method is presented.

  2. MOPSO-based multi-objective TSO planning considering uncertainties

    DEFF Research Database (Denmark)

    Wang, Qi; Zhang, Chunyu

    2014-01-01

    The concerns of sustainability and climate change have posed a significant growth of renewable energy associated with smart grid technologies. Various uncertainties are the major problems need to be handled by transmission system operator (TSO) planning. This paper mainly focuses on three uncertain factors, i.e. load growth, generation capacity and line faults, and aims to enhance the transmission system via the multi-objective TSO planning (MOTP) approach. The proposed MOTP approach optimizes three objectives simultaneously, namely the probabilistic available transfer capability (PATC), investment cost and power outage cost. A two-phase MOPSO algorithm is employed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity ofPareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved MOPSO have been verified by the 77-bus system.

  3. LOCAL BINARY PATTERN BASED EDGE- TEXTURE FEATURES FOR OBJECT RECOGNITION

    Directory of Open Access Journals (Sweden)

    Abhijeet S. Tayde*

    2015-03-01

    Full Text Available In object recognition, there are two sets of edge-texture features and discriminative Robust Local Binary Pattern (DRLBP and Ternary Pattern (DRLTP. By knowing the limitations of Local Binary Pattern (LBP, Local Ternary Pattern (LTP and Robust LBP (RLBP. DRLBP and DRLTP are proposed with new features to solve the problem of discrimination between a bright object against a dark background and vice-versa inherent in LBP and LTP. DRLBP also solves the problem of RLBP whereby LBP codes and complements in the specific block are mapped to the same code. Furthermore, the proposed features maintain contrast information for representation of object contours discard by LBP, LTP, and RLBP. These features are tested on seven data sets like INRIA Human, Caltech Pedestrian, UIUC Car, Caltech 101, Caltech256 and Brodatz, with KTH-TIPS2. Results shows that the proposed features outperform the compared approaches on most data sets.

  4. Object-based localization of buried objects using high-resolution array processing techniques

    Science.gov (United States)

    Sahin, Adnan; Miller, Eric L.

    1996-05-01

    In this paper we explore the use of high-resolution array processing techniques for the detection and localization of buried objects with known shapes. A ground penetrating radar measurement geometry is considered where the scattered electric field due to an incident plane wave is observed over a linear receiver array positioned above the targets. We have modified the high-resolution algorithm MUSIC to explicitly account for the near-field physics and solved the target localization problem in two ways. The first method uses the MUSIC algorithm in a matched field processing scheme and determines both the bearing and the range of the targets. Under the second approach, the sensor array is divided into non-overlapping subarrays. The targets are assumed to lie in the far-field of each subarray ensuring a plane wave incidence over each partition. The DOAs are then found with the conventional plane wave MUSIC and the locations of the targets are determined by triangulation of the DOAs. Using simulated data we demonstrate that these techniques are quite useful for the detection and localization of metallic and dielectric mines as well as buried metallic drums. The favorable detection results are shown to hold over a wide range of soil conditions and signal to noise ratios.

  5. Dynamic Cell Formation based on Multi-objective Optimization Model

    Directory of Open Access Journals (Sweden)

    Guozhu Jia

    2013-08-01

    Full Text Available In this paper, a multi-objective model is proposed to address the dynamic cellular manufacturing (DCM formation problem. This model considers four conflicting objectives: relocation cost, machine utilization, material handling cost and maintenance cost. The model also considers the situation that some machines could be shared by more than one cell at the same period. A genetic algorithm is applied to get the solution of this mathematical model. Three numerical examples are simulated to evaluate the validity of this model.  

  6. Object-Based Epistemology at a Creationist Museum

    Science.gov (United States)

    Wendel, Paul J.

    2011-01-01

    In a regional young-earth creationist museum, objects are presented as if they speak for themselves, purportedly embodying proof that the earth is less than 10,000 years old, that humans have lived on earth throughout its history, and that dinosaurs and humans lived simultaneously. In public lectures, tours, and displays, museum associates…

  7. Objective, Way and Method of Faculty Management Based on Ergonomics

    Science.gov (United States)

    WANG, Hong-bin; Liu, Yu-hua

    2008-01-01

    The core problem that influences educational quality of talents in colleges and universities is the faculty management. Without advanced faculty, it is difficult to cultivate excellent talents. With regard to some problems in present faculty construction of colleges and universities, this paper puts forward the new objectives, ways and methods of…

  8. Ontology-Based Annotation of Learning Object Content

    Science.gov (United States)

    Gasevic, Dragan; Jovanovic, Jelena; Devedzic, Vladan

    2007-01-01

    The paper proposes a framework for building ontology-aware learning object (LO) content. Previously ontologies were exclusively employed for enriching LOs' metadata. Although such an approach is useful, as it improves retrieval of relevant LOs from LO repositories, it does not enable one to reuse components of a LO, nor to incorporate an explicit…

  9. IMAGE BASED EXTRACTION OF FLUORESCENT COMPONENT IN COMPOSITE OBJECT.

    Directory of Open Access Journals (Sweden)

    V.S.Sangeetha

    2015-04-01

    Full Text Available In the field of computer vision, recognizing objects by their fluorescence and is always excluded even by various experts owing to its complexity. But in reality fluorescence is a very common phenomenon observed in many objects, from gems, corals and even in our clothes. Despite ordinary reflectance color appearance of a fluorescent object is unaffected by illumination. We have explained that the color appearance of objects with reflective and fluorescent components can be represented as a linear combination of the two components. This paper includes extraction of fluorescent and reflective components from the composite image and estimating its total area, extracted components area and percentage of area/image area. Additionally we have demonstrated this project with the study of identifying defective area extraction and particle extraction. LabVIEW software helps in the identification of defective area, separation of fluorescence, reflectance and particle extraction. The programming software helps in evaluating the area and number of pixels. This study helps in extracting fluorescence for outdoor images also which is a complex task in various previous studies on fluorescence. The effectiveness of the proposed paper is demonstrated under various illumination of light and separates the fluorescence from the reflectance in an image.

  10. Integration of object-oriented knowledge representation with the CLIPS rule based system

    Science.gov (United States)

    Logie, David S.; Kamil, Hasan

    1990-01-01

    The paper describes a portion of the work aimed at developing an integrated, knowledge based environment for the development of engineering-oriented applications. An Object Representation Language (ORL) was implemented in C++ which is used to build and modify an object-oriented knowledge base. The ORL was designed in such a way so as to be easily integrated with other representation schemes that could effectively reason with the object base. Specifically, the integration of the ORL with the rule based system C Language Production Systems (CLIPS), developed at the NASA Johnson Space Center, will be discussed. The object-oriented knowledge representation provides a natural means of representing problem data as a collection of related objects. Objects are comprised of descriptive properties and interrelationships. The object-oriented model promotes efficient handling of the problem data by allowing knowledge to be encapsulated in objects. Data is inherited through an object network via the relationship links. Together, the two schemes complement each other in that the object-oriented approach efficiently handles problem data while the rule based knowledge is used to simulate the reasoning process. Alone, the object based knowledge is little more than an object-oriented data storage scheme; however, the CLIPS inference engine adds the mechanism to directly and automatically reason with that knowledge. In this hybrid scheme, the expert system dynamically queries for data and can modify the object base with complete access to all the functionality of the ORL from rules.

  11. Dominant object detection for autonomous vision-based surveillance:

    OpenAIRE

    Celik, H.

    2010-01-01

    The deployment of visual surveillance and monitoring systems has reached massive proportions. Consequently, a need to automate the processes involved in retrieving useful information from surveillance videos, such as detecting and counting objects, and interpreting their individual and joint behavior, has emerged. The existing methods targeting such automation and working towards "smart" surveillance solutions largely rely on pattern recognition solutions trained offline in a supervised fashi...

  12. Mobile object retrieval in server-based image databases

    OpenAIRE

    Manger, Daniel; Pagel, Frank; Widak, Heiko

    2013-01-01

    The increasing number of mobile phones equipped with powerful cameras leads to huge collections of user-generated images. To utilize the information of the images on site, image retrieval systems are becoming more and more popular to search for similar objects in an own image database. As the computational performance and the memory capacity of mobile devices are constantly increasing, this search can often be performed on the device itself. This is feasible, for example, if the images are re...

  13. Classification of change detection algorithms for object-based applications

    OpenAIRE

    Cavallaro, Andrea; Ebrahimi, Touradj

    2003-01-01

    Change detection is a temporal segmentation tool aiming at identifying changes in image sets or image sequences at two different times. Many change detection algorithms have been proposed over the past decade for the generation of video objects in a wide range of applications, ranging from interactive multimedia to remote surveillance. Most of these algorithms are tailored to the specific application at hand. Therefore there is a need of a general model for change detection which could suppor...

  14. Application of Object-Based Industrial Controls for Cryogenics

    CERN Document Server

    Casas-Cubillos, J; Gomes, P; Pezzetti, M; Sicard, Claude Henri; Varas, F J

    2002-01-01

    The first application of the CERN Unified Industrial Control system (UNICOS) has been developed for the 1.8 K refrigerator at point 1.8 in mid-2001. This paper presents the engineering methods used for application development, in order to reach the objectives of maintainability and reusability, in the context of a development done by an external consortium of engineering firms. It will also review the lessons learned during this first development and the improvements planned for the next applications.

  15. Programming Model Based on Concurrent Objects for the AIBO Robot

    OpenAIRE

    Mart??n Rico, Francisco; Ca??as, Jos?? Mar??a; Gonz??lez-Careaga, Rafaela; Matell??n Olivera, Vicente

    2012-01-01

    This paper presents the object-oriented programing envir- onment for the AIBO robot, focusing in its concurrency model. Con- currency problems arise when programming a robot due to the various sensors and actuators that the programmers must manage. As this man- agement has some aspects of real time and communication, involves some coplexity. In order to deal with this complexity Sony has developed a framework for programming the AIBO Robot. The description of this API cal...

  16. Modeling multimedia objects for content-based retrieval

    OpenAIRE

    Amato, Giuseppe; Mainetto, Gianni; Savino, Pasquale; Rabitti, Fausto

    1996-01-01

    This paper reports the work-in-progress on the definition of an object-oriented data model tailored for multimedia applications within the HERMES project. The wide diffusion of multimedia applications that use CD quality audio, video, high quality images, etc. and the initial availability of multimedia databases lead to the need of finding suitable solutions for the retrieval and the manipulation of multimedia data. In this paper we present a multimedia data model that addresses the aspects r...

  17. Semantic-based Anomalous Pattern Discovery in Moving Object Trajectories

    OpenAIRE

    Camossi, Elena; Villa, Paola; Mazzola, Luca

    2013-01-01

    In this work, we investigate a novel semantic approach for pattern discovery in trajectories that, relying on ontologies, enhances object movement information with event semantics. The approach can be applied to the detection of movement patterns and behaviors whenever the semantics of events occurring along the trajectory is, explicitly or implicitly, available. In particular, we tested it against an exacting case scenario in maritime surveillance, i.e., the discovery of su...

  18. Real-time Object Detection Based on ARM9

    Directory of Open Access Journals (Sweden)

    M.Vijay babu

    2013-09-01

    Full Text Available Object detection applications are associated with real-time performance constraints that originate from the embedded system that they are often deployed in. Our Embedded system using ARM 32 bit Microcontroller has the feature of image/video processing by using various features and classification algorithms have been proposed for object detection. It overcomes the performance in terms of sensors and hardware cost is also very high. So, our design Embedded system that detects partially visible pedestrians with low false alarm rate and high speed wherever they enter the camera view. This system takes captured image by means of web camera connected to ARM microcontroller through USB and the image is processed by using image processing technique. Image processing is a signal processing for which the input is an image, whether it is a photograph or a video frame; the output of image processing may be either an image or a set of characteristics or parameters related to the image. The captured image undergoes spatio temporal reference samples in terms of both back ground and fore ground estimation, evaluation and spatial Gaussian kernel to provide high quality image of object detection that detected image is continuously displayed on display unit and the data is stored in pen drive connected to it.

  19. Integration of an object knowledge base into a medical workstation.

    OpenAIRE

    Timmers, T.; Mulligen, E.M. van; van den Heuvel, F.

    1991-01-01

    A simple, yet powerful, knowledge base and its development environment is described that can act as a "knowledge server", integrated into a medical workstation. In many areas, such an integration of a knowledge base with other modules and systems is required, but difficult or impossible to achieve with existing commercial development shells. Three applications of the knowledge base are described: a controlled vocabulary for the classification of Congenital Heart Diseases, an extended data mod...

  20. An Automated Video Object Extraction System Based on Spatiotemporal Independent Component Analysis and Multiscale Segmentation

    Directory of Open Access Journals (Sweden)

    Zhang Xiao-Ping

    2006-01-01

    Full Text Available Video content analysis is essential for efficient and intelligent utilizations of vast multimedia databases over the Internet. In video sequences, object-based extraction techniques are important for content-based video processing in many applications. In this paper, a novel technique is developed to extract objects from video sequences based on spatiotemporal independent component analysis (stICA and multiscale analysis. The stICA is used to extract the preliminary source images containing moving objects in video sequences. The source image data obtained after stICA analysis are further processed using wavelet-based multiscale image segmentation and region detection techniques to improve the accuracy of the extracted object. An automated video object extraction system is developed based on these new techniques. Preliminary results demonstrate great potential for the new stICA and multiscale-segmentation-based object extraction system in content-based video processing applications.

  1. Object Structure from Manipulation via Particle Filter and Robot-based Active Learning

    OpenAIRE

    Li, Kun; Meng, Max Q. -h

    2014-01-01

    To learn object models for robotic manipulation, unsupervised methods cannot provide accurate object structural information and supervised methods require a large amount of manually labeled training samples, thus interactive object segmentation is developed to automate object modeling. In this article, we formulate a novel dynamic process for interactive object segmentation, and develop a solution based on particle filter and active learning so that a robot can manipulate an...

  2. Buried object location based on frequency-domain UWB measurements

    International Nuclear Information System (INIS)

    In this paper, a wideband ground penetrating radar (GPR) system and a proposed frequency-domain data analysis technique are presented for the detection of shallow buried objects such as anti-personnel landmines. The GPR system uses one transmitting antenna and an array of six monopole receiving antenna elements and operates from 1 GHz to 20 GHz. This system is able to acquire, save and analyse data in the frequency domain. A common source or wide-angle reflection and refraction technique has been used for acquiring and processing the data. This technique is effective for the rejection of ground surface clutter. By applying the C-scan scheme, metallic and plastic mine-like targets buried in dry soil will be located

  3. Android Based Robot Implementation For Pick and Retain of Objects

    Directory of Open Access Journals (Sweden)

    Ranjith Kumar Goud

    2014-10-01

    Full Text Available Now-a-days it is complicated about terrorists and their bomb attacks. Even though we found a bomb it is much more complicated to remove the bomb safely. Many lives are depending on the bomb diffusion. Our project helps in diffusion of bombs with safe distance from the bomb. Bomb diffusion is controlled with the help of wireless communication using android phones. By our project we can diffuse the bomb from safe distance and it can save more lives. We can send the few commands to the robot situated at the bomb. We can control two motors situated at the wheels for direction control and other two motors at robot hand. With these four motors we can control all the directions of the robot and at the same time we can pick any object at any direction.

  4. Object-based change detection for landslide monitoring based on SPOT imagery

    Science.gov (United States)

    Hölbling, Daniel; Friedl, Barbara; Eisank, Clemens

    2014-05-01

    The steadily increasing availability of Earth observation (EO) data from a wide range of sensors facilitates the long-time monitoring of mass movements and retrospective analysis. Pixel-based approaches are most commonly used for detecting changes based on optical remote sensing data. However, single pixels are not suitable for depicting natural phenomena such as landslides in their full complexity and their transformation over time. By applying semi-automated object-based change detection limitations inherent to pixel-based methods can be overcome to a certain extent. For instance, the problem of variant spectral reflectance for the same pixel location in images from different points in time can be minimized. Therefore, atmospheric and radiometric correction of input data sets - although highly recommended - seems to be not that important for developing a straightforward change detection approach based on object-based image analysis (OBIA). The object-based change detection approach was developed for a subset of the Baichi catchment, which is located in the Shihmen Reservoir watershed in northern Taiwan. The study area is characterized by mountainous terrain with steep slopes and is regularly affected by severe landslides and debris flows. Several optical satellite images, i.e. SPOT images from different years and seasons with a spatial resolution ranging from 2.5 to 6.25 m, have been used for monitoring the past evolution of landslides and landslide affected areas. A digital elevation model (DEM) with 5 m spatial resolution was integrated in the analysis for supporting the differentiation of landslides and debris flows. The landslide changes were identified by comparing feature values of segmentation-derived image objects between two subsequent images in eCognition (Trimble) software. To increase the robustness and transferability of the approach we identified changes by using the relative difference in values of band-specific relational features, spectral indices and texture instead of by applying absolute spectral thresholds. Especially the Normalized Differenced Vegetation Index (NDVI) turned out to be useful as indicator for change. In this course, recent landslides can be differentiated from already existing mass movements. Furthermore, old landslides, which are already overgrown by vegetation, can be identified as well as reactivated ones. The presented approach can be applied for the regular update of existing landslide inventory maps or for the identification of areas that are potentially susceptible to landslides by analyzing the frequency of landslide events in the past. This might be of interest for decision makers and local stakeholders, as this kind of information can serve as useful input for disaster prevention and risk analysis.

  5. Object-based learning in higher education: The pedagogical power of museums

    OpenAIRE

    Helen J. Chatterjee

    2010-01-01

    Following a special conference focused on object-based learning in higher education at University College London (UCL), this paper provides the overview for a series of subsequent papers which explore the value of object-based learning, including the pedagogical framework for museum learning in the university classroom and practice led examples from a range of disciplines. Object-based learning in higher education draws on many of the learning strategies already known to inform students, incl...

  6. Relational and Object-Oriented Methodology in Data Bases Systems

    Directory of Open Access Journals (Sweden)

    Marian Pompiliu CRISTESCU

    2006-01-01

    Full Text Available Database programming languages integrate concepts of databases and programming languages to provide both implementation tools for data-intensive applications and high-level user interfaces to databases. Frequently, database programs contain a large amount of application knowledge which is hidden in the procedural code and thus difficult to maintain with changing data and user views. This paper presents a first attempt to improve the situation by supporting the integrated definition and management of data and rules based on a setoriented and predicative approach. The use of database technology for integrated fact and rule base management is shown to have some important advantages in terms of fact and rule integrity, question-answering, and explanation of results.

  7. Hierarchical Object-Based Visual Attention for Machine Vision

    OpenAIRE

    Sun, Yaoru

    2003-01-01

    Human vision uses mechanisms of covert attention to selectively process interesting information and overt eye movements to extend this selectivity ability. Thus, visual tasks can be effectively dealt with by limited processing resources. Modelling visual attention for machine vision systems is not only critical but also challenging. In the machine vision literature there have been many conventional attention models developed but they are all space-based only and cannot perform ...

  8. Rule Based Selection of 2D Urban Area Map Objects

    OpenAIRE

    Jagdish Lal Raheja; Mr. Umesh Kumar

    2010-01-01

    The purpose of cartographic generalization is to represent a particular situation adapted to the needs of its users, with adequate legibility of the representation and perceptional congruity with the real situation. In this paper, a simple approach is presented for the selection process of building ground plans that are represented as 2D line, square and polygon segments. It is based on simple selection process from the field of computer graphics. It is important to preserve the overall chara...

  9. A Review of Computer Vision based Algorithms for accurate and efficient Object Detection

    OpenAIRE

    Aneissha Chebolu; Manvi Malik

    2013-01-01

    In this paper two vision-based algorithms are adopted to locate and identify the objects and obstacles from the environment. In recent days, robot vision and navigation are emerging as essential services especially in hazardous environments. In this work, two vision based techniques such as color based thresholding and template matching – both correlation based similarity measure and FFT (Fast Fourier Transform) based have been adopted and used for object identification and classification u...

  10. A Review of Computer Vision based Algorithms for accurate and efficient Object Detection

    Directory of Open Access Journals (Sweden)

    Aneissha Chebolu

    2013-05-01

    Full Text Available In this paper two vision-based algorithms are adopted to locate and identify the objects and obstacles from the environment. In recent days, robot vision and navigation are emerging as essential services especially in hazardous environments. In this work, two vision based techniques such as color based thresholding and template matching – both correlation based similarity measure and FFT (Fast Fourier Transform based have been adopted and used for object identification and classification using the image captured in CCD camera attached to the robotic arm. Then, the robotic arm manipulator is integrated with the computer for futher manipulation of the objects based on the application.

  11. Intra-Inter Triplet Object Interaction Mechanism in Triplet-Based Hierarchical Interconnection Network

    Directory of Open Access Journals (Sweden)

    Shahnawaz Talpur

    2013-07-01

    Full Text Available Object oriented languages usually avoid direct message passing, due to its complicated implementation, though that is the promising way to communicate in concurrently inherited objects. With the advancement in the high performance computing system, interaction between parallel application objects onto physical cores becomes one of the significant issues, which is not fully explored yet. In object oriented programming attribute data is included in objects and their state can be changed using the methods. Objects enable massage passing to other objects interacting with each other. Comprehensive problems can be molded by object-oriented methodology, and solves difficult program running object-oriented programs.Cores communicate with each other through communicator and groups in MPI, but in our reference architecture TBHIN (Triplet Based Hierarchical Interconnection Network, the cores are already faction in Triplets. We propose IITOIM Model to improve the performance with efficient intra-inter triplet cores communication mechanism between the objects in TBHIN

  12. Design of Object-based Information System Prototype

    Directory of Open Access Journals (Sweden)

    Suhyeon Yoo

    2014-06-01

    Full Text Available Researchers who use science and technology information were found to ask an information service in which they can excerpt the contents they needed, rather than using the information at article level. In this study, we micronized the contents of scholarly articles into text, image, and table and then constructed a micro-content DB to design a new information system prototype based on this micro-content. After designing the prototype, we performed usability test for this prototype so as to confirm the usefulness of the system prototype. We expect that the outcome of this study will fulfill the segmented and diversified information need of researchers.

  13. An object-oriented feature-based design system face-based detection of feature interactions

    International Nuclear Information System (INIS)

    This paper presents an object-oriented, feature-based design system which supports the integration of design and manufacture by ensuring that part descriptions fully account for any feature interactions. Manufacturing information is extracted from the feature descriptions in the form of volumes and Tool Access Directions, TADs. When features interact, both volumes and TADs are updated. This methodology has been demonstrated by developing a prototype system in which ACIS attributes are used to record feature information within the data structure of the solid model. The system implemented in the C++ programming language and embedded in a menu-driven X-windows user interface to the ACIS 3D Toolkit. (author)

  14. Geometric measurement of moving object based on visual detecting-learning mechanism

    Science.gov (United States)

    Wang, Hong; Deng, Jia

    2015-02-01

    This paper proposes a novel geometric statistical measurement of long sequence moving objects, which can accurately measure the geometry of the moving objects in non-contact measurement environment. The proposed algorithm adopts detecting-learning method for tracking moving objects in a long-term, gets the moving sequence data, extracts the geometric contour and computes the geometric and motion parameters of the objects. Then we analyze the long sequence to train the parameters. Experimental data showed that the adoption of geometric measurement of moving objects based on detecting-learning mechanism performs favorably. The method can provide high-accuracy geometric and motion parameters of the objects.

  15. A Scale Adaptive Method Based On Quaternion Correlation in Object Tracking

    Directory of Open Access Journals (Sweden)

    Jie Hu

    2014-09-01

    Full Text Available In this paper, we proposed a scale adaptive Kalman filter algorithm based on quaternion correlation of color image. First, Kalman filter is used to estimate the object motion direction. The correlation of object and the searching window image is calculated to get the accurate position of the object. The scale adaptive method is efficient to the situation of object size changing. In order to reduce the influence of illumination, we proposed to use HSV color space instead of RGB color space. Experiments results showed that the algorithm can detect the object correctly even the size and the color of the object changed.

  16. Rule Based Selection of 2D Urban Area Map Objects

    Directory of Open Access Journals (Sweden)

    Jagdish Lal Raheja

    2010-09-01

    Full Text Available The purpose of cartographic generalization is to represent a particular situation adapted to the needs of its users, with adequate legibility of the representation and perceptional congruity with the real situation. In this paper, a simple approach is presented for the selection process of building ground plans that are represented as 2D line, square and polygon segments. It is based on simple selection process from the field of computer graphics. It is important to preserve the overall characteristics of the buildings; the lines are simplified with regard to geometric relations. These characteristics allow for an easy recognition of buildings even on small displays of mobile devices. Such equipment has become a tool for our everyday life in the form of mobile phones, personal digital assistants and GPS assisted navigation systems. Although the computing performance and network bandwidth will increase further, such devices will always be limited by the rather small display area available for communicating the spatial information. This means that an appropriate transformation and visualization of building data as presented in this paper is essential.

  17. Spectroscopic Assessment of WISE-based Young Stellar Object Selection

    CERN Document Server

    Koenig, Xavier; Padgett, Deborah; DeFelippis, Daniel

    2015-01-01

    We have conducted a sensitive search down to the hydrogen burning limit for unextincted stars over $\\sim$200 square degrees around Lambda Orionis and 20 square degrees around Sigma Orionis using the methodology of Koenig & Leisawitz (2014). From WISE and 2MASS data we identify 544 and 418 candidate YSOs in the vicinity of Lambda and Sigma respectively. Based on our followup spectroscopy for some candidates and the existing literature for others, we found that $\\sim$80% of the K14-selected candidates are probable or likely members of the Orion star forming region. The yield from the photometric selection criteria shows that WISE sources with $K_S -w3 > 1.5$ mag and $K_S $ between 10--12 mag are most likely to show spectroscopic signs of youth, while WISE sources with $K_S -w3 > 4$ mag and $K_S > 12$ were often AGNs when followed up spectroscopically. The population of candidate YSOs traces known areas of active star formation, with a few new `hot spots' of activity near Lynds 1588 and 1589 and a more dispe...

  18. Study on Objective Integrated Control of New Energy Power Projects Based on Reliability Theory

    OpenAIRE

    Yunna Wu; Zezhong Li; Lirong Liu

    2013-01-01

    Based on the research status of objective control theory of new energy power projects, analysed the system components of power projects, proposed the subsystem reliability control theory directed at four objectives, gave reliability control standards and calculation methods of four objectives, obtained the objective integrated method of subsystem reliability, used disjoint minimal path sets method to deal with the minimal path sets in the project construction process, proposed system reliabil...

  19. An Object Tracking Algorithm Based on the "Current" Statistical Model and the Multi-Feature Fusion

    OpenAIRE

    Jinhua Wang; Jie Cao; Di Wu; Yabing Yu

    2012-01-01

    Aimed at accurary and real-time object tracking under complex background,an object tracking algorithm based on multi feature fusion is proposed. Feature points tracking is used to reduce the match time and improve the real-time of tracking; To overcome the inaccuracy of a single feature tracking, the object model is presented by the color and texture features. For the traditional "current" statistical model in maneuvering object tracking defects, an improved algorithm which combined with adap...

  20. Cascade Boosting-Based Object Detection from High-Level Description to Hardware Implementation

    OpenAIRE

    Khattab K; Dubois J; Miteran J

    2009-01-01

    Object detection forms the first step of a larger setup for a wide variety of computer vision applications. The focus of this paper is the implementation of a real-time embedded object detection system while relying on high-level description language such as SystemC. Boosting-based object detection algorithms are considered as the fastest accurate object detection algorithms today. However, the implementation of a real time solution for such algorithms is still a challenge. A new parallel im...

  1. Acoustic Sensor-Based Multiple Object Tracking with Visual Information Association

    OpenAIRE

    Jinseok Lee; Sangjin Hong; Nammee Moon; Seong-Jun Oh

    2010-01-01

    Abstract Object tracking by an acoustic sensor based on particle filtering is extended for the tracking of multiple objects. In order to overcome the inherent limitation of the acoustic sensor for the simultaneous multiple object tracking, support from the visual sensor is considered. Cooperation from the visual sensor, however, is better to be minimized, as the visual sensor's operation requires much higher computational resources than the acoustic sensor-based estimation, especially when th...

  2. Geographic object-based delineation of neighborhoods of Accra, Ghana using QuickBird satellite imagery

    OpenAIRE

    Stow, Douglas A.; Lippitt, Christopher D.; Weeks, John R.

    2010-01-01

    The objective was to test GEographic Object-based Image Analysis (GEOBIA) techniques for delineating neighborhoods of Accra, Ghana using QuickBird multispectral imagery. Two approaches to aggregating census enumeration areas (EAs) based on image-derived measures of vegetation objects were tested: (1) merging adjacent EAs according to vegetation measures and (2) image segmentation. Both approaches exploit readily available functions within commercial GEOBIA software. Image-derived neighborhood...

  3. Object Classification based Context Management for Identity Management in Internet of Things

    DEFF Research Database (Denmark)

    Mahalle, Parikshit N.; Prasad, Neeli R.

    2013-01-01

    As computing technology is becoming more tightly coupled into dynamic and mobile world of the Internet of Things (IoT), security mechanism is more stringent, flexible and less intrusive. Scalability issue in IoT makes identity management (IdM) of ubiquitous objects more challenging, and there is a need of context-aware access control solution for IdM. Confronting uncertainty of different types of objects in IoT is not easy. This paper presents the logical framework for object classification in context aware IoT, as richer contextual information creates an impact on the access control. This paper proposes decision theory based object classification to provide contextual information and context management. Simulation results show that the proposed object classification is useful to improve network lifetime. Results also give motivation of object classification in terms of energy consumption. This paper also presents proof of concept and time analysis of the proposed decision theory based object classification.

  4. Video Image Object Tracking Algorithm based on Improved Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Liping Wang

    2014-05-01

    Full Text Available Since the existing object tracking algorithms are very difficult to adapt the object appearance changes caused by illumination changes, large pose variations, and partial or full occlusions, an object tracking algorithm based on two-dimensional principal component analysis (2DPCA and sparse-representation is proposed in this paper. The tracking algorithm adopts 2DPCA and sparse-representation to establish object appearance model. In order to reduce dimension of object template, incremental subspace updating algorithm is introduced to online update the object template, reduce the requirement of memory space and enhance the precision of object appearance description. Experimental results show the proposed algorithm is robust for image illumination variance and object partial occlusion.

  5. Space-based visual attention models and object selection: constraints, problems, and possible solutions.

    Science.gov (United States)

    Schneider, W X

    1993-01-01

    One of the functions of visual attention is the selection of object information. This seems to be in line with an influential group of attentional models that assume that attentional selection is space based. These models assume that the selection of an object in vision is realized by selection of the location of that object. Whether this relatively simple idea of space-based attention and the corresponding, more elaborated space-based models are sufficient to handle selected constraints and problems of object selection is the main issue of this article. The first step toward an answer is to describe the common computational structure of space-based attentional models. Two model classes will be distinguished: capacity-limited models (e.g., Treisman, 1988; LaBerge & Brown, 1989) and models that do not assume a capacity limitation (e.g., Van der Heijden, 1992). Next, three kinds of task and data on object selection are introduced that are especially challenging for space-based models. The first type of data refers to experiments that require selection between overlapping objects. The second type of data concerns the influence of early perceptual grouping--a strong object-defining factor--on late response competition, and the third type consists of a selection task in which a high-level (semantic) attribute defines an object and controls selection. In all three cases, problems of space-based models are analyzed and possible solutions are sketched. Finally, a brief evaluative summary is given. PMID:8310103

  6. Object-based Conditional Random Fields for Road Extraction from Remote Sensing Image

    Science.gov (United States)

    Huang, Zhijian; Xu, Fanjiang; Lu, Lei; Nie, Hongshan

    2014-03-01

    To make full use of spatially contextual information and topological information in the procedure of Object-based Image Analysis (OBIA), an object-based conditional random field is proposed and used for road extraction. Objects are produced with an initial segmentation, then their neighbours are constructed. Each object is represented by three kinds of features, including the colour, the gradient of histogram and the texture. Formulating the road extraction as a binary classification problem, a Conditional Random Fields model learns and is used for inference. The experimental results demonstrate that the proposed method is effective.

  7. UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

    Directory of Open Access Journals (Sweden)

    J. Fernandez Galarreta

    2014-09-01

    Full Text Available Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs. 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level.

  8. UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

    Science.gov (United States)

    Fernandez Galarreta, J.; Kerle, N.; Gerke, M.

    2014-09-01

    Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs). 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA) of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level.

  9. Object-based classification of residential land use within Accra, Ghana based on QuickBird satellite data.

    Science.gov (United States)

    Stow, D; Lopez, A; Lippitt, C; Hinton, S; Weeks, J

    2007-01-01

    A segmentation and hierarchical classification approach applied to QuickBird multispectral satellite data was implemented, with the goal of delineating residential land use polygons and identifying low and high socio-economic status of neighbourhoods within Accra, Ghana. Two types of object-based classification strategies were tested, one based on spatial frequency characteristics of multispectral data, and the other based on proportions of Vegetation-Impervious-Soil sub-objects. Both approaches yielded residential land-use maps with similar overall percentage accuracy (75%) and kappa index of agreement (0.62) values, based on test objects from visual interpretation of QuickBird panchromatic imagery. PMID:19424445

  10. Object-based attention underlies the rehearsal of feature binding in visual working memory.

    Science.gov (United States)

    Shen, Mowei; Huang, Xiang; Gao, Zaifeng

    2015-04-01

    Feature binding is a core concept in many research fields, including the study of working memory (WM). Over the past decade, it has been debated whether keeping the feature binding in visual WM consumes more visual attention than the constituent single features. Previous studies have only explored the contribution of domain-general attention or space-based attention in the binding process; no study so far has explored the role of object-based attention in retaining binding in visual WM. We hypothesized that object-based attention underlay the mechanism of rehearsing feature binding in visual WM. Therefore, during the maintenance phase of a visual WM task, we inserted a secondary mental rotation (Experiments 1-3), transparent motion (Experiment 4), or an object-based feature report task (Experiment 5) to consume the object-based attention available for binding. In line with the prediction of the object-based attention hypothesis, Experiments 1-5 revealed a more significant impairment for binding than for constituent single features. However, this selective binding impairment was not observed when inserting a space-based visual search task (Experiment 6). We conclude that object-based attention underlies the rehearsal of binding representation in visual WM. PMID:25602968

  11. Moving Object Localization Using Sound-Based Positioning System with Doppler Shift Compensation

    Directory of Open Access Journals (Sweden)

    Slamet Widodo

    2013-04-01

    Full Text Available Sound-based positioning systems are a potential alternative low-cost navigation system. Recently, we developed such an audible sound-based positioning system, based on a spread spectrum approach. It was shown to accurately localize a stationary object. Here, we extend this localization to a moving object by compensating for the Doppler shift associated with the object movement. Numerical simulations and experiments indicate that by compensating for the Doppler shift, the system can accurately determine the position of an object moving along a non-linear path. When the object moved in a circular path with an angular velocity of 0 to 1.3 rad/s, it could be localized to within 25 mm of the actual position. Experiments also showed the proposed system has a high noise tolerance of up to ?25 dB signal-to-noise ratio (SNR without compromising accuracy.

  12. Web Services Based Learning Objects Generator for Device-Independent M-Learning

    OpenAIRE

    Akram Moh. Alkouz

    2006-01-01

    Learning objects, which are the base component of m-learning system, are usually target to modifications in contexts and formats. The device- dependent applications of hand-held devices have proven to be ineffective for creating m-learning courseware. Learning Objects Metadata (LOM) is the most popular standard specification for learning objects but lacks the ability to facilitate platforms descriptions. This paper outlines various aspects of design and implementation of Web Services Oriente...

  13. Technique of identifying speedy hyperspectral images object based on spectrum repository

    International Nuclear Information System (INIS)

    Aimed at the imported airborne hyperspectral data collection system (CASI/SASI), the authors first introduced the knowledge based spectral repository for multi ground objects, the study on the technique approaches to identifying object at speed with hyperspectral images, and then expound the principle of object identification, the flow of data processing and the programming procedure with open code, finally make a brief analysis for the results and its application. (authors)

  14. From 3D Point Clouds To Semantic Objects An Ontology-Based Detection Approach

    OpenAIRE

    Ben Hmida, Helmi; Cruz, Christophe; Boochs, Frank; Nicolle, Christophe

    2011-01-01

    This paper presents a knowledge-based detection of objects approach using the OWL ontology language, the Semantic Web Rule Language, and 3D processing built-ins aiming at combining geometrical analysis of 3D point clouds and specialist's knowledge. This combination allows the detection and the annotation of objects contained in point clouds. The context of the study is the detection of railway objects such as signals, technical cupboards, electric poles, etc. Thus, the resul...

  15. Principal Objects Detection Using Graph-Based Segmentation and Normalized Histogram

    Directory of Open Access Journals (Sweden)

    Pham The Bao

    2012-01-01

    Full Text Available In this paper, we introduce a new method to distinguish the principal objects in image datasets using graph-based segmentation and normalized histogram (PODSH. Unlike the usual object detection systems which require the input objects, we propose a new approach to recognize objects one might focus on when taking images. Motivated by the habit of taking picture, we suppose that the position of a main object is located near the image centre and this object always holds a large area. The normalized histogram is added to increase the effect of our system. In the experiment, we used images which consist of objects to test the precision of PODSH. Our system is implemented by Matlab.

  16. Object-based classification of residential land use within Accra, Ghana based on QuickBird satellite data

    OpenAIRE

    Stow, D.; Lopez, A.; Lippitt, C.; Hinton, S.; Weeks, J.

    2007-01-01

    A segmentation and hierarchical classification approach applied to QuickBird multispectral satellite data was implemented, with the goal of delineating residential land use polygons and identifying low and high socio-economic status of neighbourhoods within Accra, Ghana. Two types of object-based classification strategies were tested, one based on spatial frequency characteristics of multispectral data, and the other based on proportions of Vegetation–Impervious–Soil sub-objects. Both app...

  17. Attention-Guided Organized Perception and Learning of Object Categories Based on Probabilistic Latent Variable Models

    Directory of Open Access Journals (Sweden)

    Masayasu Atsumi

    2013-05-01

    Full Text Available This paper proposes a probabilistic model of object category learning in conjunction with attention-guided organized perception. This model consists of a model of attention-guided organized perception of object segments on Markov random fields and a model of learning object categories based on a probabilistic latent component analysis. In attention guided organized perception, concurrent figure-ground segmentation is performed on dynamically-formed Markov random fields around salient preattentive points and co-occurring segments are grouped in the neighborhood of selective attended segments. In object category learning, a set of classes of each object category is obtained based on the probabilistic latent component analysis with the variable number of classes from bags of features of segments extracted from images which contain the categorical objects in context and an object category is represented by a composite of object classes. Through experiments using two image data sets, it is shown that the model learns a probabilistic structure of intra-categorical composition and inter-categorical difference of object categories and achieves high performance in object category recognition.

  18. The Object-Based Simon Effect: Grasping Affordance or Relative Location of the Graspable Part?

    Science.gov (United States)

    Cho, Dongbin; Proctor, Robert W.

    2010-01-01

    Reaction time is often shorter when the irrelevant graspable handle of an object corresponds with the location of a keypress response to the relevant attribute than when it does not. This object-based Simon effect has been attributed to an affordance for grasping the handle with the hand to the same side. Because a grasping affordance should…

  19. Object-based learning in higher education: The pedagogical power of museums

    Directory of Open Access Journals (Sweden)

    Helen J. Chatterjee

    2010-01-01

    Full Text Available Following a special conference focused on object-based learning in higher education at University College London (UCL, this paper provides the overview for a series of subsequent papers which explore the value of object-based learning, including the pedagogical framework for museum learning in the university classroom and practice led examples from a range of disciplines. Object-based learning in higher education draws on many of the learning strategies already known to inform students, including active learning and experiential learning; this collection of papers draws together examples of object-based learning pioneered at UCL and seeks to encourage enhanced use of university collections in new, pedagogically powerful, modes.

  20. Developing Goals and Objectives for a Process-Based Technology Education Curriculum.

    Science.gov (United States)

    Wicklein, Robert C.

    1993-01-01

    An 11-member DACUM team identified necessary instructional elements and student outcomes for process-based secondary technology education. A panel of 43 exemplary teachers then validated goals and objectives, resulting in a curriculum framework. (SK)

  1. An Ada-based preprocessor language for concurrent object oriented programming

    International Nuclear Information System (INIS)

    In this paper, implementation issues of concurrent-objected programming using Ada 95 are addressed. Ada is not a pure object-oriented language; in order to make it so, a uniform template for structuring object classes is proposed. The template constitutes a basis for an Ada-based preprocessor language that handles concurrent object-oriented programming. The preprocessor accepts Ada-like object-oriented programs (object classes, subclasses and main program) as input and produces Ada 95 concurrent object-oriented program units as output. The preprocessor language has the advantage of adding a new component to the class specification called the protocol, which specifies the order for requesting methods f an object. The preprocessor also touches on the extensibility of object classes issue. It supports defining class hierarchies by inheritance and aggregation. In addition, the preprocessor language supports the re-use of Ada packages, which are not necessarily written according to the object-oriented approach. The paper also investigates the definition of circular dependent object classes and proposes a solution for introducing a collection of classes. (author)

  2. Biologically-Based Interactive Neural Network Models for Visual Attention and Object Recognition

    OpenAIRE

    Saifullah, Mohammad

    2012-01-01

    The main focus of this thesis is to develop biologically-based computational models for object recognition. A series of models for attention and object recognition were developed in the order of increasing functionality and complexity. These models are based on information processing in the primate brain, and specially inspired from the theory of visual information processing along the two parallel processing pathways of the primate visual cortex. To capture the true essence of incremental, c...

  3. Object classification methods for application in FPGA based vehicle video detector

    Directory of Open Access Journals (Sweden)

    Wies?aw PAMU?A

    2009-01-01

    Full Text Available The paper presents a discussion of properties of object classification methods utilized in processing video streams from a camera. Methods based on feature extraction, model fitting and invariant determination are evaluated. Petri nets are used for modelling the processing flow. Data objects and transitions are defined which are suitable for efficient implementation in FPGA circuits. Processing characteristics and problems of the implementations are shown. An invariant based method is assessed as most suitable for application in a vehicle video detector.

  4. Learning to recognize objects on the fly: a neurally based dynamic field approach.

    Science.gov (United States)

    Faubel, Christian; Schöner, Gregor

    2008-05-01

    Autonomous robots interacting with human users need to build and continuously update scene representations. This entails the problem of rapidly learning to recognize new objects under user guidance. Based on analogies with human visual working memory, we propose a dynamical field architecture, in which localized peaks of activation represent objects over a small number of simple feature dimensions. Learning consists of laying down memory traces of such peaks. We implement the dynamical field model on a service robot and demonstrate how it learns 30 objects from a very small number of views (about 5 per object are sufficient). We also illustrate how properties of feature binding emerge from this framework. PMID:18501555

  5. Independence Analysis of Firing and Rule-based Net Transformations in Reconfigurable Object Nets

    OpenAIRE

    Biermann, Enrico; Modica, Tony

    2008-01-01

    The main idea behind Reconfigurable Object Nets (RONs) is to support the visual specification of controlled rule-based net transformations of place/transition nets (P/T nets). RONs are high-level nets with two types of tokens: object nets (place/transition nets) and net transformation rules (a dedicated type of graph transformation rules). Firing of high-level transitions may involve firing of object net transitions, transporting object net tokens through the high-level net, and applying net ...

  6. Object density-based image segmentation and its applications in biomedical image analysis.

    Science.gov (United States)

    Yu, Jinhua; Tan, Jinglu

    2009-12-01

    In many applications of medical image analysis, the density of an object is the most important feature for isolating an area of interest (image segmentation). In this research, an object density-based image segmentation methodology is developed, which incorporates intensity-based, edge-based and texture-based segmentation techniques. The proposed method consists of three main stages: preprocessing, object segmentation and final segmentation. Image enhancement, noise reduction and layer-of-interest extraction are several subtasks of preprocessing. Object segmentation utilizes a marker-controlled watershed technique to identify each object of interest (OI) from the background. A marker estimation method is proposed to minimize over-segmentation resulting from the watershed algorithm. Object segmentation provides an accurate density estimation of OI which is used to guide the subsequent segmentation steps. The final stage converts the distribution of OI into textural energy by using fractal dimension analysis. An energy-driven active contour procedure is designed to delineate the area with desired object density. Experimental results show that the proposed method is 98% accurate in segmenting synthetic images. Segmentation of microscopic images and ultrasound images shows the potential utility of the proposed method in different applications of medical image processing. PMID:19473717

  7. The research of moving object detection based on background difference compensation

    Science.gov (United States)

    Song, Yan-bin; Ying, Jie; Lu, Lin-li

    2013-08-01

    Moving object detection was implemented in dynamic background based on background difference compensation. Background differential can effectively segment the moving object in static background. But in moving video, the camera motion causes corresponding movement of the target and background, which makes the prospect moving object hard to separate from the background. In order to detect moving object, we can compensate the movement of the background and transfer the dynamic background to static. Moving object detection in static background image was implemented using a new weights updating method that the weights were updated during a certain period. This method based on classical Gaussian mixture model improved the efficiency of image segmentation greatly. Moving object detection in dynamic background was realized using background differential compensation. The global motion of the background was established according to the affined parameters model. The model parameters were estimated by feature points matching based on the search strategy. Invalid matching points were eliminated using the method of distance consistency. Backward mapping was used to get the motion parameters of the background. After compensation of the background with the global motion parameters, frame difference between the current frame and the background can detect moving objects effectively. Experiments were done on computer with the programming tools of VS2010 and MATLAB. Experimental results showed that the algorithm based on differential compensation was effective.

  8. Unique Measure for Geometrical Shape Object Detection-based on Area Matching

    Directory of Open Access Journals (Sweden)

    Debasis Chaudhuri

    2012-01-01

    Full Text Available Object classifier often operates by making decisions based on the values of several shape properties measured from an image of the object. The paper introduces a unique definition of measure for 2-D geometrical object shape detection. Using this definition different object shapes can be identified on the basis of their degree of fitness parameter. Basically, we have fitted a 2-D polygon/curve on the object as a best fitted polygon/curve and computed the parameter degree of fitness which is the ratio of the matching area and non-matching area due to the fitted polygon/curve and the object both. The results show the effectiveness of the proposed measure.Defence Science Journal, 2012, 62(1, pp.58-66, DOI:http://dx.doi.org/10.14429/dsj.62.942

  9. Object Class Detection and Classification using Multi Scale Gradient and Corner Point based Shape Descriptors

    OpenAIRE

    Fernando, Basura; Karaoglu, Sezer; Saha, Sajib Kumar

    2015-01-01

    This paper presents a novel multi scale gradient and a corner point based shape descriptors. The novel multi scale gradient based shape descriptor is combined with generic Fourier descriptors to extract contour and region based shape information. Shape information based object class detection and classification technique with a random forest classifier has been optimized. Proposed integrated descriptor in this paper is robust to rotation, scale, translation, affine deformati...

  10. A Framework based on concurrent Object-oriented programming for Building Behavior-based Control Systems for Mobile Robots

    Scientific Electronic Library Online (English)

    José Eduardo Mendonça, Xavier; Hansjörg Andreas, Schneebeli.

    1998-04-01

    Full Text Available An approach based on concurrent object oriented programming (COOP) to build a control system for a mobile robot is presented. A behavior-based control system is decomposed in intercommunicating concurrent objects named Agents. These agents belong to five categories: Primitive Sensor, Virtual Sensor, [...] Behavior, Primitive Actuator and Virtual Actuator. Based on this approach, a C++ tool is developed, where the categories above are implemented as C++ classes, in which built-in communication mechanisms are included. Each class has a standard interface and functionality. It is possible, then, to develop a complex control system by deriving new classes from the base classes and by instantiating objects. These objects are interconnected in a dynamic manner and thus building a control system with different behavior levels, which is able to react to environment changes.

  11. Automatic Multi-Level Thresholding Segmentation Based on Multi-Objective Optimization

    Directory of Open Access Journals (Sweden)

    L. DJEROU,

    2012-01-01

    Full Text Available In this paper, we present a new multi-level image thresholding technique, called Automatic Threshold based on Multi-objective Optimization "ATMO" that combines the flexibility of multi-objective fitness functions with the power of a Binary Particle Swarm Optimization algorithm "BPSO", for searching the "optimum" number of the thresholds and simultaneously the optimal thresholds of three criteria: the between-class variances criterion, the minimum error criterion and the entropy criterion. Some examples of test images are presented to compare our segmentation method, based on the multi-objective optimization approach with Otsu’s, Kapur’s and Kittler’s methods. Our experimental results show that the thresholding method based on multi-objective optimization is more efficient than the classical Otsu’s, Kapur’s and Kittler’s methods.

  12. Modeling and Analysis for Obstacle Avoidance of a Behavior-Based Robot with Objected Oriented Methods

    Directory of Open Access Journals (Sweden)

    Qian Zhang

    2009-04-01

    Full Text Available Object Modeling Technique is widely applied in the field of software engineering; and in this paper we applied this technique to model a mobile robot including its behaviors and interactions with environment. The paper first describes key background knowledge about object oriented analysis in software engineering, behavior based robotics and their similarities. Then, based on these similarities, the paper uses object oriented methods of software engineering, such as unified modeling language (UML, to analyze and model the architecture; and to design behaviors for a behavior-based robot, which is expected to wander with autonomous obstacle avoidance in unknown environment. Object oriented methods permit a translation from conceptual behavior models to computer programming representations, and separate concrete control algorithms from robot modeling. With this approach, the paper implements a fuzzy algorithm for obstacle avoidance behavior of the constructed behavior models in a physical robot, and made experiments in the given indoor environment.

  13. A Python-Based Open Source System for Geographic Object-Based Image Analysis (GEOBIA) Utilizing Raster Attribute Tables

    OpenAIRE

    Daniel Clewley; Peter Bunting; James Shepherd; Sam Gillingham; Neil Flood; John Dymond; Richard Lucas; John Armston; Mahta Moghaddam

    2014-01-01

    A modular system for performing Geographic Object-Based Image Analysis (GEOBIA), using entirely open source (General Public License compatible) software, is presented based around representing objects as raster clumps and storing attributes as a raster attribute table (RAT). The system utilizes a number of libraries, developed by the authors: The Remote Sensing and GIS Library (RSGISLib), the Raster I/O Simplification (RIOS) Python Library, the KEA image format and TuiView image viewer. All l...

  14. Mining moving object trajectories in location-based services for spatio-temporal database update

    Science.gov (United States)

    Guo, Danhuai; Cui, Weihong

    2008-10-01

    Advances in wireless transmission and mobile technology applied to LBS (Location-based Services) flood us with amounts of moving objects data. Vast amounts of gathered data from position sensors of mobile phones, PDAs, or vehicles hide interesting and valuable knowledge and describe the behavior of moving objects. The correlation between temporal moving patterns of moving objects and geo-feature spatio-temporal attribute was ignored, and the value of spatio-temporal trajectory data was not fully exploited too. Urban expanding or frequent town plan change bring about a large amount of outdated or imprecise data in spatial database of LBS, and they cannot be updated timely and efficiently by manual processing. In this paper we introduce a data mining approach to movement pattern extraction of moving objects, build a model to describe the relationship between movement patterns of LBS mobile objects and their environment, and put up with a spatio-temporal database update strategy in LBS database based on trajectories spatiotemporal mining. Experimental evaluation reveals excellent performance of the proposed model and strategy. Our original contribution include formulation of model of interaction between trajectory and its environment, design of spatio-temporal database update strategy based on moving objects data mining, and the experimental application of spatio-temporal database update by mining moving objects trajectories.

  15. A generic discriminative part-based model for geospatial object detection in optical remote sensing images

    Science.gov (United States)

    Zhang, Wanceng; Sun, Xian; Wang, Hongqi; Fu, Kun

    2015-01-01

    Detecting geospatial objects with complex structure has been explored for years and it is still a challenging task in high resolution optical remote sensing images (RSI) interpretation. In this paper, we mainly focus on the problem of rotation variance in detecting geospatial objects and propose a generic discriminative part-based model (GDPBM) to build a practical object detection framework. In our model, a geospatial object with arbitrary orientation is divided into several parts and represented via three terms: the appearance features, the spatial deformation features and the rotation deformation features. The appearance features characterize the local patch appearance of the object and parts, and we propose a new kind of rotation invariant feature to represent the appearance using the local intensity gradients. The spatial deformation features capture the geometric deformation of parts by representing the relative displacements among parts. The rotation deformation features define the pose variances of the parts relative to the objects based on their dominant orientations. In generating the two deformation features, we introduce the statistic methods to encode the features in the category level. Concatenating the three terms of the features, a classifier based on the support vector machine is learned to detect geospatial objects. In the experiments, two datasets in optical RSI are used to evaluate the performance of our model and the results demonstrate its robustness and effectiveness.

  16. LABRADOR: a learning autonomous behavior-based robot for adaptive detection and object retrieval

    Science.gov (United States)

    Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

    2013-01-01

    As part of the TARDEC-funded CANINE (Cooperative Autonomous Navigation in a Networked Environment) Program, iRobot developed LABRADOR (Learning Autonomous Behavior-based Robot for Adaptive Detection and Object Retrieval). LABRADOR was based on the rugged, man-portable, iRobot PackBot unmanned ground vehicle (UGV) equipped with an explosives ordnance disposal (EOD) manipulator arm and a custom gripper. For LABRADOR, we developed a vision-based object learning and recognition system that combined a TLD (track-learn-detect) filter based on object shape features with a color-histogram-based object detector. Our vision system was able to learn in real-time to recognize objects presented to the robot. We also implemented a waypoint navigation system based on fused GPS, IMU (inertial measurement unit), and odometry data. We used this navigation capability to implement autonomous behaviors capable of searching a specified area using a variety of robust coverage strategies - including outward spiral, random bounce, random waypoint, and perimeter following behaviors. While the full system was not integrated in time to compete in the CANINE competition event, we developed useful perception, navigation, and behavior capabilities that may be applied to future autonomous robot systems.

  17. 3D object following based on visual information for Unmanned Aerial Vehicles

    OpenAIRE

    Mondragon Bernal, Ivan Fernando; Campoy Cervera, Pascual; Olivares Me?ndez, Miguel A?ngel; Marti?nez Luna, Carol Viviana

    2011-01-01

    This article presents a novel system and a control strategy for visual following of a 3D moving object by an Unmanned Aerial Vehicle UAV. The presented strategy is based only on the visual information given by an adaptive tracking method based on the color information, which jointly with the dynamics of a camera fixed to a rotary wind UAV are used to develop an Image-based visual servoing IBVS system. This system is focused on continuously following a 3D moving target object, maintaining it w...

  18. Investigation of a combined portable IR system for laser scanning land-based object

    International Nuclear Information System (INIS)

    Some problems of informative capacities of laser radar are considered. An analysis of specific properties realizing IR identification systems has been developed for land-based objects laser scanning. Some technical characteristics of the systems are mentioned, such as systems response speed, 3D imaging non-scanning by using 3D FPA detectors. The combined portable facilities as a whole present a joint structure Laser IR Scanner and IR irradiation detector for identifying land-based object. The estimation of channel capacity and delays in the synchronization system between base station and mobile station are given

  19. A genetic algorithm based multi-objective shape optimization scheme for cementless femoral implant.

    Science.gov (United States)

    Chanda, Souptick; Gupta, Sanjay; Kumar Pratihar, Dilip

    2015-03-01

    The shape and geometry of femoral implant influence implant-induced periprosthetic bone resorption and implant-bone interface stresses, which are potential causes of aseptic loosening in cementless total hip arthroplasty (THA). Development of a shape optimization scheme is necessary to achieve a trade-off between these two conflicting objectives. The objective of this study was to develop a novel multi-objective custom-based shape optimization scheme for cementless femoral implant by integrating finite element (FE) analysis and a multi-objective genetic algorithm (GA). The FE model of a proximal femur was based on a subject-specific CT-scan dataset. Eighteen parameters describing the nature of four key sections of the implant were identified as design variables. Two objective functions, one based on implant-bone interface failure criterion, and the other based on resorbed proximal bone mass fraction (BMF), were formulated. The results predicted by the two objective functions were found to be contradictory; a reduction in the proximal bone resorption was accompanied by a greater chance of interface failure. The resorbed proximal BMF was found to be between 23% and 27% for the trade-off geometries as compared to ?39% for a generic implant. Moreover, the overall chances of interface failure have been minimized for the optimal designs, compared to the generic implant. The adaptive bone remodeling was also found to be minimal for the optimally designed implants and, further with remodeling, the chances of interface debonding increased only marginally. PMID:25392855

  20. An object oriented framework of EPICS for MicroTCA based control system

    International Nuclear Information System (INIS)

    EPICS (Experimental Physics and Industrial Control System) is a distributed control system platform which has been widely used for large scientific devices control like particle accelerators and fusion plant. EPICS has introduced object oriented (C++) interfaces to most of the core services. But the major part of EPICS, the run-time database, only provides C interfaces, which is hard to involve the EPICS record concerned data and routines in the object oriented architecture of the software. This paper presents an object oriented framework which contains some abstract classes to encapsulate the EPICS record concerned data and routines in C++ classes so that full OOA (Objected Oriented Analysis) and OOD (Object Oriented Design) methodologies can be used for EPICS IOC design. We also present a dynamic device management scheme for the hot swap capability of the MicroTCA based control system. (authors)

  1. MULTI OBJECTIVE OPTIMIZATION OF VEHICLE ACTIVE SUSPENSION SYSTEM USING DEBBO BASED PID CONTROLLER

    OpenAIRE

    Kalaivani Rajagopal; Lakshmi Ponnusamy

    2014-01-01

    This paper proposes the Multi Objective Optimization (MOO) of Vehicle Active Suspension System (VASS) with a hybrid Differential Evolution (DE) based Biogeography-Based Optimization (BBO) (DEBBO) for the parameter tuning of Proportional Integral Derivative (PID) controller. Initially a conventional PID controller, secondly a BBO, an rising nature enthused global optimization procedure based on the study of the ecological distribution of biological organisms and a hybridized DEBBO algorithm wh...

  2. An object-oriented, knowledge-based system for cardiovascular rehabilitation--phase II.

    OpenAIRE

    Ryder, R. M.; Inamdar, B.

    1995-01-01

    The Heart Monitor is an object-oriented, knowledge-based system designed to support the clinical activities of cardiovascular (CV) rehabilitation. The original concept was developed as part of graduate research completed in 1992. This paper describes the second generation system which is being implemented in collaboration with a local heart rehabilitation program. The PC UNIX-based system supports an extensive patient database organized by clinical areas. In addition, a knowledge base is empl...

  3. Product Informations modelling within the supply chain based on communicating object's approach

    OpenAIRE

    Cea Ramirez, Aldo; Bajic, Eddy

    2007-01-01

    This article aims to analyze and contribute to the implementation of the communicating object concept in the supply chain. This approach considers a product as a service provider or a service requester. The proposed methodology is based on the ambient services architecture concept in order to manage product's services in an automatic and ubiquitous way. The UPnP technology (Universal Plug and Play) was chosen to manage the services of the communicating objects. In this approach, the direct co...

  4. Monitoring Post Disturbance Forest Regeneration with Hierarchical Object-Based Image Analysis

    OpenAIRE

    Monika Moskal, L.; Jakubauskas, Mark E.

    2013-01-01

    The main goal of this exploratory project was to quantify seedling density in post fire regeneration sites, with the following objectives: to evaluate the application of second order image texture (SOIT) in image segmentation, and to apply the object-based image analysis (OBIA) approach to develop a hierarchical classification. With the utilization of image texture we successfully developed a methodology to classify hyperspatial (high-spatial) imagery to fine detail level of tree crowns, shad...

  5. A weight space-based approach to fuzzy multiple-objective linear programming

    OpenAIRE

    Borges, Ana Rosa; Antunes, Carlos Henggeler

    2003-01-01

    In this paper, the effects of uncertainty on multiple-objective linear programming models are studied using the concepts of fuzzy set theory. The proposed interactive decision support system is based on the interactive exploration of the weight space. The comparative analysis of indifference regions on the various weight spaces (which vary according to intervals of values of the satisfaction degree of objective functions and constraints) enables to study the stability and evolution of the bas...

  6. Object modelling data base of geographical information system of transmissions pipelines

    OpenAIRE

    Levic?nik, Toni

    2008-01-01

    : The master science thesis work is focused on object modelling data base of geographical information system of transmissions pipelines. The main reason for object modelling geographical information system is integrated in this in business information system of the company and Integrity management system of transmission infrastructure. The first of the system design was digitizing the data. A lot of work was done by checking the data. The main phase was creating an application for making anal...

  7. Vision Based Object Recognition and Localisation by a Wireless Connected Distributed Robotic Systems

    OpenAIRE

    Ahmed, M. Shuja

    2012-01-01

    Object recognition and localisation are important processes in computer vision and robotics. Advances in computer vision have resulted in many object recognition techniques, but most of them are computationally very intensive and require robots with powerful processing systems. For small robots, these techniques are not applicable because of the constraints of execution time. In this study, an optimised implementation of SURF based recognition technique is presented. Suitable image pre-proces...

  8. APPLICATION OF DE BASED WAFGP IN MULTI OBJECTIVE OPTIMAL POWER FLOW USING TCSC

    OpenAIRE

    Vanitha, R.; Baskaran, J.; Sudhakaran, M.

    2014-01-01

    This paper proposes the application of Differential Evolution (DE) algorithm based Weighted Additive Fuzzy Goal Programming (WAFGP) in solving a Multi objective Optimal Power Flow (MOPF) problem. The multiple objectives considered are maximizing the loadability, minimizing the total real power loss and minimizing the overall system cost which comprises of installation cost of FACTS devices and generation fuel cost. The optimal solution for this MOPF problem is obtained by opti...

  9. Size metrology of a pure phase object based on the laser probe beam reshaping

    Science.gov (United States)

    Fromager, Michael; Brunel, Marc; Aït-Ameur, Kamel

    2014-03-01

    We propose a simple method for determining the size of a transparent object based on the reshaping of a laser probe beam which is initially Gaussian in shape. For a given ratio between the sizes of the incident beam and of the phase object, the diffracted laser probe beam is transformed in the far-field region into a hollow beam. The detection of the intensity dip in the beam centre is made with a simple photodiode. The potential of the proposed technique for quantifying the nanoscale change of the phase object could be very useful to study the dynamics of a living cell membrane for instance.

  10. A Methodology to Evaluate Object oriented Software Systems Using Change Requirement Traceability Based on Impact Analysis

    Directory of Open Access Journals (Sweden)

    Sunil T. D

    2014-06-01

    Full Text Available It is a well known fact that software maintenance plays a major role and finds importance in software development life cycle. As object - oriented programming has become the standard, it is very important to understand the problems of maintaining object -oriented software systems. This paper aims at evaluating object - oriented software system through change requirement traceability – based impact analysis methodology for non functional requirements using functional requirements . The major issues have been related to change impact algorithms and inheritance of functionality.

  11. The effect of input data transformations on object-based image analysis.

    Science.gov (United States)

    Lippitt, Christopher D; Coulter, Lloyd L; Freeman, Mary; Lamantia-Bishop, Jeffrey; Pang, Wyson; Stow, Douglas A

    2012-01-01

    The effect of using spectral transform images as input data on segmentation quality and its potential effect on products generated by object-based image analysis are explored in the context of land cover classification in Accra, Ghana. Five image data transformations are compared to untransformed spectral bands in terms of their effect on segmentation quality and final product accuracy. The relationship between segmentation quality and product accuracy is also briefly explored. Results suggest that input data transformations can aid in the delineation of landscape objects by image segmentation, but the effect is idiosyncratic to the transformation and object of interest. PMID:21673829

  12. Eigenvalue and graph-based object extraction from mobile laser scanning point clouds

    Science.gov (United States)

    Bremer, M.; Wichmann, V.; Rutzinger, M.

    2013-10-01

    The mapping of road environments is an important task, providing important input data for a broad range of scientific disciplines. Pole-like objects, their visibility and their influence onto local light and traffic noise conditions are of particular interest for traffic safety, public health and ecological issues. Detailed knowledge can support the improvement of traffic management, noise reducing infrastructure or the planning of photovoltaic panels. Mobile Mapping Systems coupled with computer aided mapping work-flows allow an effective data acquisition and provision. We present a classification work flow focussing on pole-like objects. It uses rotation and scale invariant point and object features for classification, avoiding planar segmentation and height slicing steps. Single objects are separated by connected component and Dijkstra-path analysis. Trees and artificial objects are separated using a graph based approach considering the branching levels of the given geometries. For the focussed semantic groups, classification accuracies higher than 0.9 are achieved. This includes both the quality of object aggregation and separation, where the combination of Dijkstrapath aggregation and graph-based classification shows good results. For planar objects the classification accuracies are lowered, recommending the usage of planar segmentation for classification and subdivision issues as presented by other authors. The presented work-flow provides sufficient input data for further 3D reconstructions and tree modelling.

  13. Region-Based Object Recognition by Color Segmentation Using a Simplified PCNN.

    Science.gov (United States)

    Chen, Yuli; Ma, Yide; Kim, Dong Hwan; Park, Sung-Kee

    2014-12-01

    In this paper, we propose a region-based object recognition (RBOR) method to identify objects from complex real-world scenes. First, the proposed method performs color image segmentation by a simplified pulse-coupled neural network (SPCNN) for the object model image and test image, and then conducts a region-based matching between them. Hence, we name it as RBOR with SPCNN (SPCNN-RBOR). Hereinto, the values of SPCNN parameters are automatically set by our previously proposed method in terms of each object model. In order to reduce various light intensity effects and take advantage of SPCNN high resolution on low intensities for achieving optimized color segmentation, a transformation integrating normalized Red Green Blue (RGB) with opponent color spaces is introduced. A novel image segmentation strategy is suggested to group the pixels firing synchronously throughout all the transformed channels of an image. Based on the segmentation results, a series of adaptive thresholds, which is adjustable according to the specific object model is employed to remove outlier region blobs, form potential clusters, and refine the clusters in test images. The proposed SPCNN-RBOR method overcomes the drawback of feature-based methods that inevitably includes background information into local invariant feature descriptors when keypoints locate near object boundaries. A large number of experiments have proved that the proposed SPCNN-RBOR method is robust for diverse complex variations, even under partial occlusion and highly cluttered environments. In addition, the SPCNN-RBOR method works well in not only identifying textured objects, but also in less-textured ones, which significantly outperforms the current feature-based methods. PMID:25494514

  14. Hyperspectral Data for Mangrove Species Mapping: A Comparison of Pixel-Based and Object-Based Approach

    Directory of Open Access Journals (Sweden)

    Muhammad Kamal

    2011-10-01

    Full Text Available Visual image interpretation and digital image classification have been used to map and monitor mangrove extent and composition for decades. The presence of a high-spatial resolution hyperspectral sensor can potentially improve our ability to differentiate mangrove species. However, little research has explored the use of pixel-based and object-based approaches on high-spatial hyperspectral datasets for this purpose. This study assessed the ability of CASI-2 data for mangrove species mapping using pixel-based and object-based approaches at the mouth of the Brisbane River area, southeast Queensland, Australia. Three mapping techniques used in this study: spectral angle mapper (SAM and linear spectral unmixing (LSU for the pixel-based approaches, and multi-scale segmentation for the object-based image analysis (OBIA. The endmembers for the pixel-based approach were collected based on existing vegetation community map. Nine targeted classes were mapped in the study area from each approach, including three mangrove species: Avicennia marina, Rhizophora stylosa, and Ceriops australis. The mapping results showed that SAM produced accurate class polygons with only few unclassified pixels (overall accuracy 69%, Kappa 0.57, the LSU resulted in a patchy polygon pattern with many unclassified pixels (overall accuracy 56%, Kappa 0.41, and the object-based mapping produced the most accurate results (overall accuracy 76%, Kappa 0.67. Our results demonstrated that the object-based approach, which combined a rule-based and nearest-neighbor classification method, was the best classifier to map mangrove species and its adjacent environments.

  15. Research On The Classification Of High Resolution Image Based On Object-oriented And Class Rule

    Science.gov (United States)

    Li, C. K.; Fang, W.; Dong, X. J.

    2015-06-01

    With the development of remote sensing technology, the spatial resolution, spectral resolution and time resolution of remote sensing data is greatly improved. How to efficiently process and interpret the massive high resolution remote sensing image data for ground objects, which with spatial geometry and texture information, has become the focus and difficulty in the field of remote sensing research. An object oriented and rule of the classification method of remote sensing data has presents in this paper. Through the discovery and mining the rich knowledge of spectrum and spatial characteristics of high-resolution remote sensing image, establish a multi-level network image object segmentation and classification structure of remote sensing image to achieve accurate and fast ground targets classification and accuracy assessment. Based on worldview-2 image data in the Zangnan area as a study object, using the object-oriented image classification method and rules to verify the experiment which is combination of the mean variance method, the maximum area method and the accuracy comparison to analysis, selected three kinds of optimal segmentation scale and established a multi-level image object network hierarchy for image classification experiments. The results show that the objectoriented rules classification method to classify the high resolution images, enabling the high resolution image classification results similar to the visual interpretation of the results and has higher classification accuracy. The overall accuracy and Kappa coefficient of the object-oriented rules classification method were 97.38%, 0.9673; compared with object-oriented SVM method, respectively higher than 6.23%, 0.078; compared with object-oriented KNN method, respectively more than 7.96%, 0.0996. The extraction precision and user accuracy of the building compared with object-oriented SVM method, respectively higher than 18.39%, 3.98%, respectively better than the object-oriented KNN method 21.27%, 14.97%.

  16. A Situation Analysis Decision Support System Based on Dynamic Object Oriented Bayesian Networks

    Directory of Open Access Journals (Sweden)

    Mohsen Naderpour

    2014-08-01

    Full Text Available This paper proposes a situation analysis decision support system (SADSS for safety of safety-critical systems where the operators are stressed by the task of understanding what is going on in the situation. The proposed SADSS is developed based on a new model-driven engineering approach for hazardous situations modeling based on dynamic object oriented Bayesian networks to reduce the complexity of the decision-making process by aiding operators’ cognitive activities. The SADSS includes four major elements: a situation data collection based on observable variables such as sensors, a situation knowledge-base which consists of dynamic object oriented Bayesian networks to model hazardous situations, a situation analysis which shows the current state of hazardous situations based on risk concept and possible near future state, and a human-computer interface. Finally two evaluation methods for partial and full validation of SADSS are presented.   Manuscript received September 5, 2013; revised September 25, 2013; accepted October 5, 2013.

  17. Efficient view based 3-D object retrieval using Hidden Markov Model

    Science.gov (United States)

    Jain, Yogendra Kumar; Singh, Roshan Kumar

    2013-12-01

    Recent research effort has been dedicated to view based 3-D object retrieval, because of highly discriminative property of 3-D object and has multi view representation. The state-of-art method is highly depending on their own camera array setting for capturing views of 3-D object and use complex Zernike descriptor, HAC for representative view selection which limit their practical application and make it inefficient for retrieval. Therefore, an efficient and effective algorithm is required for 3-D Object Retrieval. In order to move toward a general framework for efficient 3-D object retrieval which is independent of camera array setting and avoidance of representative view selection, we propose an Efficient View Based 3-D Object Retrieval (EVBOR) method using Hidden Markov Model (HMM). In this framework, each object is represented by independent set of view, which means views are captured from any direction without any camera array restriction. In this, views are clustered (including query view) to generate the view cluster, which is then used to build the query model with HMM. In our proposed method, HMM is used in twofold: in the training (i.e. HMM estimate) and in the retrieval (i.e. HMM decode). The query model is trained by using these view clusters. The EVBOR query model is worked on the basis of query model combining with HMM. The proposed approach remove statically camera array setting for view capturing and can be apply for any 3-D object database to retrieve 3-D object efficiently and effectively. Experimental results demonstrate that the proposed scheme has shown better performance than existing methods. [Figure not available: see fulltext.

  18. Semi-Automatic Objects Recognition in Urban Areas Based on Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Federico Prandi

    2010-05-01

    Full Text Available Three dimensional object extraction and recognition (OER from geographic data has been definitely one of more important topic in photogrammetry for quite a long time. Today, the capability of rapid generating high-density DSM increases the supply of geographic information but the discrete nature of the measuring makes more difficult to recognize correctly and to extract 3D objects from these surface. The proposed methodology wants to semi-automate some geographic objects clustering operations, in order to perform the recognition process. The clustering is a subjective process; the same set of data items often needs to be partitioned differently based on the application. Fuzzy logic gives the possibility to use in a mathematical process the uncertain information typical of human reasoning. The concept at the base of our proposal is to use the information contained in Image Matching or LiDAR DSM, and typically understood by the human operator, in a fuzzy recognition process able to combine the different input in order to perform the classification. So the object recognition approach proposed in our workflow integrates 3D structural descriptive components of objects, extracted from DSM, into a fuzzy reasoning process in order to exploit more fully all available information, which can contribute to the extraction and recognition process and, to handling the object’s vagueness. The recognition algorithm has been tested with to different data set and different objectives. An important issue is to apply the typical human process which allows to recognize objects in a range image in a fuzzy reasoning process. The investigations presented here have given a first demonstration of the capability of this approach.

  19. Double Polarization SAR Image Classification based on Object-Oriented Technology

    Directory of Open Access Journals (Sweden)

    Yongsheng Li

    2010-05-01

    Full Text Available This paper proposed to use double polarization synthetic aperture radar (SAR image to classify surface feature, based on DEM. It takes fully use of the polarization information and external information. This pa-per utilizes ENVISAT ASAR APP double-polarization data of Poyang lake area in Jiangxi Province. Com-pared with traditional pixel-based classification, this paper fully uses object features (color, shape, hierarchy and accessorial DEM information. The classification accuracy improves from the original 73.7% to 91.84%. The result shows that object-oriented classification technology is suitable for double polarization SAR’s high precision classification.

  20. Prism adaptation does not alter object-based attention in healthy participants

    Science.gov (United States)

    Bultitude, Janet H.

    2013-01-01

    Hemispatial neglect (‘neglect’) is a disabling condition that can follow damage to the right side of the brain, in which patients show difficulty in responding to or orienting towards objects and events that occur on the left side of space. Symptoms of neglect can manifest in both space- and object-based frames of reference. Although patients can show a combination of these two forms of neglect, they are considered separable and have distinct neurological bases. In recent years considerable evidence has emerged to demonstrate that spatial symptoms of neglect can be reduced by an intervention called prism adaptation. Patients point towards objects viewed through prismatic lenses that shift the visual image to the right. Approximately five minutes of repeated pointing results in a leftward recalibration of pointing and improved performance on standard clinical tests for neglect. The understanding of prism adaptation has also been advanced through studies of healthy participants, in whom adaptation to leftward prismatic shifts results in temporary neglect-like performance. Here we examined the effect of prism adaptation on the performance of healthy participants who completed a computerised test of space- and object-based attention. Participants underwent adaptation to leftward- or rightward-shifting prisms, or performed neutral pointing according to a between-groups design. Significant pointing after-effects were found for both prism groups, indicating successful adaptation. In addition, the results of the computerised test revealed larger reaction-time costs associated with shifts of attention between two objects compared to shifts of attention within the same object, replicating previous work. However there were no differences in the performance of the three groups, indicating that prism adaptation did not influence space- or object-based attention for this task. When combined with existing literature, the results are consistent with the proposal that prism adaptation may only perturb cognitive functions for which normal baseline performance is already biased. PMID:24715960

  1. Region-Based Image Retrieval Using an Object Ontology and Relevance Feedback

    Directory of Open Access Journals (Sweden)

    Vasileios Mezaris

    2004-06-01

    Full Text Available An image retrieval methodology suited for search in large collections of heterogeneous images is presented. The proposed approach employs a fully unsupervised segmentation algorithm to divide images into regions and endow the indexing and retrieval system with content-based functionalities. Low-level descriptors for the color, position, size, and shape of each region are subsequently extracted. These arithmetic descriptors are automatically associated with appropriate qualitative intermediate-level descriptors, which form a simple vocabulary termed object ontology. The object ontology is used to allow the qualitative definition of the high-level concepts the user queries for (semantic objects, each represented by a keyword and their relations in a human-centered fashion. When querying for a specific semantic object (or objects, the intermediate-level descriptor values associated with both the semantic object and all image regions in the collection are initially compared, resulting in the rejection of most image regions as irrelevant. Following that, a relevance feedback mechanism, based on support vector machines and using the low-level descriptors, is invoked to rank the remaining potentially relevant image regions and produce the final query results. Experimental results and comparisons demonstrate, in practice, the effectiveness of our approach.

  2. When action turns into words. Activation of motor-based knowledge during categorization of manipulable objects

    DEFF Research Database (Denmark)

    Gerlach, Christian; Law, Ian

    2002-01-01

    Functional imaging studies have demonstrated that processing of man-made objects activate the left ventral premotor cortex, which is known to be concerned with motor function. This has led to the suggestion that the comprehension of man-made objects may rely on motor-based knowledge of object utilization (action knowledge). Here we show that the left ventral premotor cortex is activated during categorization of "both" fruit/vegetables and articles of clothing, relative to animals and nonmanipulable man-made objects. This observation suggests that action knowledge may not be important for the processing of man-made objects per se, but rather for the processing of manipulable objects in general, whether natural or man-made. These findings both support psycholinguistic theories suggesting that certain lexical categories may evolve from, and the act of categorization rely upon, motor-based knowledge of action equivalency, and have important implications for theories of category specificity. Thus, the finding thatthe processing of vegetables/fruit and articles of clothing give rise to similar activation is difficult to account for should knowledge representations in the brain be truly categorically organized. Instead, the data are compatible with the suggestion that categories differ in the weight they put on different types of knowledge.

  3. Track-Before-Detect Algorithm for Faint Moving Objects based on Random Sampling and Consensus

    Science.gov (United States)

    Dao, P.; Rast, R.; Schlaegel, W.; Schmidt, V.; Dentamaro, A.

    2014-09-01

    There are many algorithms developed for tracking and detecting faint moving objects in congested backgrounds. One obvious application is detection of targets in images where each pixel corresponds to the received power in a particular location. In our application, a visible imager operated in stare mode observes geostationary objects as fixed, stars as moving and non-geostationary objects as drifting in the field of view. We would like to achieve high sensitivity detection of the drifters. The ability to improve SNR with track-before-detect (TBD) processing, where target information is collected and collated before the detection decision is made, allows respectable performance against dim moving objects. Generally, a TBD algorithm consists of a pre-processing stage that highlights potential targets and a temporal filtering stage. However, the algorithms that have been successfully demonstrated, e.g. Viterbi-based and Bayesian-based, demand formidable processing power and memory. We propose an algorithm that exploits the quasi constant velocity of objects, the predictability of the stellar clutter and the intrinsically low false alarm rate of detecting signature candidates in 3-D, based on an iterative method called "RANdom SAmple Consensus” and one that can run real-time on a typical PC. The technique is tailored for searching objects with small telescopes in stare mode. Our RANSAC-MT (Moving Target) algorithm estimates parameters of a mathematical model (e.g., linear motion) from a set of observed data which contains a significant number of outliers while identifying inliers. In the pre-processing phase, candidate blobs were selected based on morphology and an intensity threshold that would normally generate unacceptable level of false alarms. The RANSAC sampling rejects candidates that conform to the predictable motion of the stars. Data collected with a 17 inch telescope by AFRL/RH and a COTS lens/EM-CCD sensor by the AFRL/RD Satellite Assessment Center is used to assess the performance of the algorithm. In the second application, a visible imager operated in sidereal mode observes geostationary objects as moving, stars as fixed except for field rotation, and non-geostationary objects as drifting. RANSAC-MT is used to detect the drifter. In this set of data, the drifting space object was detected at a distance of 13800 km. The AFRL/RH set of data, collected in the stare mode, contained the signature of two geostationary satellites. The signature of a moving object was simulated and added to the sequence of frames to determine the sensitivity in magnitude. The performance compares well with the more intensive TBD algorithms reported in the literature.

  4. Efficient Fast Object-Tracking Scheme Based on Motion-vector-located Pattern Match

    Directory of Open Access Journals (Sweden)

    Liubai Li

    2012-05-01

    Full Text Available In the process of object tracking, the major problem is how to mark the tracking box of the object. Moreover, multi-objects tracking is also difficult. This paper proposed and efficient fast object-tracking scheme based on motion-vector-located pattern match, which adopts motion vector of Mpeg2 to mark the moving targets in static video in order to mark and locate the targets automatically and quickly. Then, extract multi-dimensional characteristics from the initial targets taken by motion vector and make the model. Then accurately identifies the particles of larger weight and combines with inertia factor of velocity through matching the original data and the observations of particle filter. The matching of the characteristics of the new particle and the original one is more accurate and faster because of adopting the method of pattern classifying. The experiments show that the algorithm had good tracking performance and strong robustness.

  5. A prototype distributed object-oriented architecture for image-based automatic laser alignment

    International Nuclear Information System (INIS)

    Designing a computer control system for the National Ignition Facility (NIF) is a complex undertaking because of the system's large size and its distributed nature. The controls team is addressing that complexity by adopting the object-oriented programming paradigm, designing reusable software frameworks, and using the Common Object Request Broker Architecture (CORBA) for distribution. A prototype system for image-based automatic laser alignment has been developed to evaluate and gain experience with CORBA and OOP in a small distributed system. The prototype is also important in evaluating alignment concepts, image processing techniques, speed and accuracy of automatic alignment objectives for the NIF, and control hardware for aligment devices. The prototype system has met its inital objectives and provides a basis for continued development

  6. A New Merging Algorithm Based on Semantic Relationships of Learning Objects

    Directory of Open Access Journals (Sweden)

    Elio Rivas-Sanchez

    2013-12-01

    Full Text Available Learning Objects are key elements within e-Learning environment because describe the created educational material for students, besides, it permits the reusing and sharing in di_erent Learning Management Systems. Usually, when teachers need to create and structure educational experiences, they attend to repositories for retrieving resources ?tted to their interest, for reducing the e_ort and the computational time. In this paper, a proposal is presented for merging Learning Objects from heterogeneous repositories; the model is based on semantic relationships between Learning Objects retrieved from a meta-search engine, as an alternative for locating ?tted educational resources for teacher’s interest. The model exposed in the proposal has been implemented as initial prototype, which retrieves Learning Objects from open repositories. An initial study results con?rm the usefulness of the model.

  7. Evaluation of SVM classification of metallic objects based on a magnetic-dipole representation

    Science.gov (United States)

    Fernández, Juan Pablo; Barrowes, Benjamin; O'Neill, Kevin; Paulsen, Keith; Shamatava, Irma; Shubitidze, Fridon; Sun, Keli

    2006-05-01

    In the electromagnetic-induction (EMI) detection and discrimination of unexploded ordnance (UXO) it is important for inversion purposes to have an efficient forward model of the detector-target interaction. Here we revisit an attractively simple model for EMI response of a metallic object, namely a hypothetical anisotropic, infinitesimal magnetic dipole characterized by its magnetic polarizability tensor, and investigate the extent to which one can train a Support Vector Machine (SVM) to produce reliable gross characterization of objects based on the inferred tensor elements as discriminators. We obtain the frequency-dependent polarizability tensor elements for various object characteristics by using analytical solutions to the EMI equations. Then, using synthetic data and focusing on gross shape and especially size, we evaluate the classification success of different SVM formulations for different kinds of objects.

  8. Cascade Boosting-Based Object Detection from High-Level Description to Hardware Implementation

    Directory of Open Access Journals (Sweden)

    Khattab K

    2009-01-01

    Full Text Available Object detection forms the first step of a larger setup for a wide variety of computer vision applications. The focus of this paper is the implementation of a real-time embedded object detection system while relying on high-level description language such as SystemC. Boosting-based object detection algorithms are considered as the fastest accurate object detection algorithms today. However, the implementation of a real time solution for such algorithms is still a challenge. A new parallel implementation, which exploits the parallelism and the pipelining in these algorithms, is proposed. We show that using a SystemC description model paired with a mainstream automatic synthesis tool can lead to an efficient embedded implementation. We also display some of the tradeoffs and considerations, for this implementation to be effective. This implementation proves capable of achieving 42 fps for images as well as bringing regularity in time consuming.

  9. Cascade Boosting-Based Object Detection from High-Level Description to Hardware Implementation

    Directory of Open Access Journals (Sweden)

    K. Khattab

    2009-01-01

    Full Text Available Object detection forms the first step of a larger setup for a wide variety of computer vision applications. The focus of this paper is the implementation of a real-time embedded object detection system while relying on high-level description language such as SystemC. Boosting-based object detection algorithms are considered as the fastest accurate object detection algorithms today. However, the implementation of a real time solution for such algorithms is still a challenge. A new parallel implementation, which exploits the parallelism and the pipelining in these algorithms, is proposed. We show that using a SystemC description model paired with a mainstream automatic synthesis tool can lead to an efficient embedded implementation. We also display some of the tradeoffs and considerations, for this implementation to be effective. This implementation proves capable of achieving 42 fps for 320×240 images as well as bringing regularity in time consuming.

  10. Quantifying Spatial Heterogeneity in Urban Landscapes: Integrating Visual Interpretation and Object-Based Classification

    Directory of Open Access Journals (Sweden)

    Weiqi Zhou

    2014-04-01

    Full Text Available Describing and quantifying the spatial heterogeneity of land cover in urban systems is crucial for developing an ecological understanding of cities. This paper presents a new approach to quantifying the fine-scale heterogeneity in urban landscapes that capitalizes on the strengths of two commonly used approaches—visual interpretation and object-based image analysis. This new approach integrates the ability of humans to detect pattern with an object-based image analysis that accurately and efficiently quantifies the components that give rise to that pattern. Patches that contain a mix of built and natural land cover features were first delineated through visual interpretation. These patches served as pre-defined boundaries for finer-scale segmentation and classification of within-patch land cover features which were classified using object-based image analysis. Patches were then classified based on the within-patch proportion cover of features. We applied this approach to the Gwynns Falls watershed in Baltimore, Maryland, USA. The object-based classification approach proved to be effective for classifying within-patch land cover features. The overall accuracy of the classification maps of 1999 and 2004 were 92.3% and 93.7%, respectively. This exercise demonstrates that by integrating visual interpretation with object-based classification, the fine-scale spatial heterogeneity in urban landscapes and land cover change can be described and quantified in a more efficient and ecologically meaningful way than either purely automated or visual methods alone. This new approach provides a tool that allows us to quantify the structure of the urban landscape including both built and non-built components that will better accommodate ecological research linking system structure to ecological processes.

  11. Object Hierarchy-based Supervised Characterisation ofSynthetic Aperture Radar Sensor Images

    Directory of Open Access Journals (Sweden)

    Ish Rishabh

    2008-01-01

    Full Text Available A method of supervised characterisation of synthetic aperture radar (SAR satellite imageshas been discussed in which simple object shape features of satellite images have been usedto classify and describe the terrain types. This scheme is based on a multilevel approach inwhich objects of interest are first segmented out from the image and subsequently characterisedbased on their shape features. Once all objects have been characterised, the entire image canbe characterised. Emphasis has been laid on the hierarchical information extraction from theimage which enables greater flexibility in characterising the image and is not restricted to mereclassification. The paper also describes a method for giving relative importance among features,i.e., to give more weights to those features that are better than others in distinguishing betweencompeting classes. A method of comparing two SAR sensor images based on terrain elementspresent in the images has also been described here.

  12. Probabilistic safety assessment model in consideration of human factors based on object-oriented bayesian networks

    International Nuclear Information System (INIS)

    Effect of Human factors on system safety is increasingly serious, which is often ignored in traditional probabilistic safety assessment methods however. A new probabilistic safety assessment model based on object-oriented Bayesian networks is proposed in this paper. Human factors are integrated into the existed event sequence diagrams. Then the classes of the object-oriented Bayesian networks are constructed which are converted to latent Bayesian networks for inference. Finally, the inference results are integrated into event sequence diagrams for probabilistic safety assessment. The new method is applied to the accident of loss of coolant in a nuclear power plant. the results show that the model is not only applicable to real-time situation assessment, but also applicable to situation assessment based certain amount of information. The modeling complexity is kept down and the new method is appropriate to large complex systems due to the thoughts of object-oriented. (authors)

  13. Geographic object-based delineation of neighborhoods of Accra, Ghana using QuickBird satellite imagery.

    Science.gov (United States)

    Stow, Douglas A; Lippitt, Christopher D; Weeks, John R

    2010-08-01

    The objective was to test GEographic Object-based Image Analysis (GEOBIA) techniques for delineating neighborhoods of Accra, Ghana using QuickBird multispectral imagery. Two approaches to aggregating census enumeration areas (EAs) based on image-derived measures of vegetation objects were tested: (1) merging adjacent EAs according to vegetation measures and (2) image segmentation. Both approaches exploit readily available functions within commercial GEOBIA software. Image-derived neighborhood maps were compared to a reference map derived by spatial clustering of slum index values (from census data), to provide a relative assessment of potential map utility. A size-constrained iterative segmentation approach to aggregation was more successful than standard image segmentation or feature merge techniques. The segmentation approaches account for size and shape characteristics, enabling more realistic neighborhood boundaries to be delineated. The percentage of vegetation patches within each EA yielded more realistic delineation of potential neighborhoods than mean vegetation patch size per EA. PMID:20689664

  14. Automatic object detection in point clouds based on knowledge guided algorithms

    Science.gov (United States)

    Truong, Hung; Karmacharya, Ashish; Mordwinzew, Waldemar; Boochs, Frank; Chudyk, Celeste; Habed, Adlane; Voisin, Yvon

    2013-04-01

    The modeling of real-world scenarios through capturing 3D digital data has been proven applicable in a variety of industrial applications, ranging from security, to robotics and to fields in the medical sciences. These different scenarios, along with variable conditions, present a challenge in discovering flexible appropriate solutions. In this paper, we present a novel approach based on a human cognition model to guide processing. Our method turns traditional data-driven processing into a new strategy based on a semantic knowledge system. Robust and adaptive methods for object extraction and identification are modeled in a knowledge domain, which has been created by purely numerical strategies. The goal of the present work is to select and guide algorithms following adaptive and intelligent manners for detecting objects in point clouds. Results show that our approach succeeded in identifying the objects of interest while using various data types.

  15. Building and Programming a Smart Robotic System for Distinguishing Objects Based on their Shape and Colour

    Science.gov (United States)

    Sharari, T. M.

    2015-03-01

    This paper presents a robotic system designed for holding and placing objects based on their colour and shape. The presented robot is given a complete set of instructions of positions and orientation angles for each manipulation motion. The main feature in this paper is that the developed robot used a combination of vision and motion systems for holding and placing the work-objects, mounted on the flat work-plane, based on their shapes and colors. This combination improves the flexibility of manipulation which may help eliminate the use of some expensive manipulation tasks in a variety of industrial applications. The robotic system presented in this paper is designed as an educational robot that possesses the ability for holding-and-placing operations with limited load. To process the various instructions for holding and placing the work objects, a main control unit - Manipulation Control Unit (MCU) is used as well as a slave unit that performed the actual instructions from the MCU.

  16. Development of the competency-based objective resident education using virtual patients system

    OpenAIRE

    Christopher Becket Mahnke; Holly Olson; Alan Stein; Taylor Sawyer

    2011-01-01

    The Accreditation Council for Graduate Medical Education (ACGME) requires U.S. physician training programs to teach and evaluate their trainees in six core competencies. Developing innovative methods to meet the ACGME requirements is an ongoing area of research in medical education. Here we describe the development of the Competency-based Objective Resident Education using Virtual Patients (CORE-VP) system, a web-based virtual patient simulator to teach and measure the ACGME core competencies...

  17. An Object-Based Hierarchical Method for Change Detection Using Unmanned Aerial Vehicle Images

    OpenAIRE

    Rongjun Qin

    2014-01-01

    There have been increasing demands for automatically monitoring urban areas in very high detail, and the Unmanned Aerial Vehicle (UAV) with auto-navigation (AUNA) system offers such capability. This study proposes an object-based hierarchical method to detect changes from UAV images taken at different times. It consists of several steps. In the first step, an octocopter with AUNA capability is used to acquire images at different dates. These images are registered automatically, based on SIFT ...

  18. Multi-equipment condition based maintenance optimization by multi- objective genetic algorithm

    OpenAIRE

    S?, Valc?uha; U?radni?c?ek, J.; Goti, A.; Navarro, I.

    2011-01-01

    Purpose: This paper deals with the optimization of the condition based maintenance (CBM) applied on manufacturing multi-equipment system under cost and benefit criteria.Design/methodology/approach: The system is modeled using Discrete Event Simulation (DES) and optimized by means of the application of a Multi-Objective Evolutionary Algorithm (MOEA).Findings: Solution for the joint optimization of the condition based maintenance model applied on several equipment has been obtained.Research li...

  19. A graph-based model of object recognition self-learning

    OpenAIRE

    Gorbenko, A.

    2013-01-01

    In this paper, we study the object recognition self-learning for robots.In particular, we consider the self-learning during solution of typicaltasks. We propose a graph-based model for self-learning. This model isbased on the problem of monochromatic path for given set of weights.We prove that the problem is NP-complete. We consider an approachto solve the problem. This approach is based on an explicit reductionfrom the problem to the satisfiability problem.

  20. Objects extraction and recognition for camera-based interaction : heuristic and statistical approaches

    OpenAIRE

    Wang, Hao

    2007-01-01

    In this thesis, heuristic and probabilistic methods are applied to a number of problems for camera-based interactions. The goal is to provide solutions for a vision based system that is able to extract and analyze interested objects in camera images and to use that information for various interactions for mobile usage. New methods and new attempts of combination of existing methods are developed for different applications, including text extraction from complex scene images, bar code reading ...

  1. Interactive Reference Point-Based Guided Local Search for the Bi-objective Inventory Routing Problem

    OpenAIRE

    Huber, Sandra; Geiger, Martin Josef; Sevaux, Marc

    2014-01-01

    Eliciting preferences of a decision maker is a key factor to successfully combine search and decision making in an interactive method. Therefore, the progressively integration and simulation of the decision maker is a main concern in an application. We contribute in this direction by proposing an interactive method based on a reference point-based guided local search to the bi-objective Inventory Routing Problem. A local search metaheuristic, working on the delivery interval...

  2. Multi-objective scheduling in an agent based Holonic manufacturing system

    OpenAIRE

    Jana, T. K.; Bairagi, B.; Paul, S.; Sk. Sahnawaj; Sarkar, B.; Saha, J.

    2014-01-01

    The present paper is aimed at multi-objective scheduling in an agent based holonic manufacturing system to satisfy the goal of several communities namely the product, the resource, and the organization simultaneously. In this attempt, first a multi criteria based priority rule is developed following Simple Additive Weight (SAW) method under Multi Criteria Decision Making (MCDM) environment to rank the products. Accordingly, the products are allowed to select a particular resource for executio...

  3. Fuzzy Concurrent Object Oriented Expert System for Fault Diagnosis in 8085 Microprocessor Based System Board

    OpenAIRE

    Kodavade, D. V.; Apte, Dr S. D.

    2014-01-01

    With the acceptance of artificial intelligence paradigm, a number of successful artificial intelligence systems were created. Fault diagnosis in microprocessor based boards needs lot of empirical knowledge and expertise and is a true artificial intelligence problem. Research on fault diagnosis in microprocessor based system boards using new fuzzy-object oriented approach is presented in this paper. There are many uncertain situations observed during fault diagnosis. These uncertain situations...

  4. A component-based, distributed object services architecture for a clinical workstation.

    OpenAIRE

    Chueh, H. C.; Raila, W. F.; Pappas, J. J.; Ford, M.; Zatsman, P.; Tu, J.; Barnett, G. O.

    1996-01-01

    Attention to an architectural framework in the development of clinical applications can promote reusability of both legacy systems as well as newly designed software. We describe one approach to an architecture for a clinical workstation application which is based on a critical middle tier of distributed object-oriented services. This tier of network-based services provides flexibility in the creation of both the user interface and the database tiers. We developed a clinical workstation for a...

  5. Environmental Object Based Method for Electrical Engineering Subjects to Enhance Learning and Teaching

    OpenAIRE

    Ka Wai E. Cheng; Weimin Wang

    2013-01-01

    Environmental protection is now an important area of study as well as the global concern. Many teaching and learning may involve the environment as part of their study. In engineering, there are many topics related to them, but most of the syllabus may too theoretical and it is necessary to develop an object based method to assist students’ learning. A demonstration of the environmental protection and energy saving concept to Outcome-based education through a web-site development has been s...

  6. SATEN An Object-Oriented Web-Based Revision and Extraction Engine

    CERN Document Server

    Williams, M A; Williams, Mary-Anne; Sims, Aidan

    2000-01-01

    SATEN is an object-oriented web-based extraction and belief revision engine. It runs on any computer via a Java 1.1 enabled browser such as Netscape 4. SATEN performs belief revision based on the AGM approach. The extraction and belief revision reasoning engines operate on a user specified ranking of information. One of the features of SATEN is that it can be used to integrate mutually inconsistent commensuate rankings into a consistent ranking.

  7. SATEN: An Object-Oriented Web-Based Revision and Extraction Engine

    OpenAIRE

    Williams, Mary-anne; Sims, Aidan

    2000-01-01

    SATEN is an object-oriented web-based extraction and belief revision engine. It runs on any computer via a Java 1.1 enabled browser such as Netscape 4. SATEN performs belief revision based on the AGM approach. The extraction and belief revision reasoning engines operate on a user specified ranking of information. One of the features of SATEN is that it can be used to integrate mutually inconsistent commensuate rankings into a consistent ranking.

  8. A Case of Web-Based Inquiry Learning Model Using Learning Objects

    Science.gov (United States)

    Al Musawi, A.; Asan, A.; Abdelraheem, A.; Osman, M.

    2012-01-01

    This research seeks to (1) implement a model for an inquiry based learning environment using learning objects (LOs), and (2) apply the model to examine its impact on students' learning. This research showed that a well-designed learning environment can enhance students learning experiences. The proposed model was applied to an undergraduate course…

  9. Pruning-Based Pareto Front Generation for Mixed-Discrete Bi-Objective Optimization

    OpenAIRE

    Hong, Seungbum; Ahn, Jaemyung; Choi, Han-lim

    2013-01-01

    This note proposes an effective pruning-based Pareto front generation method in mixed-discrete bi-objective optimization. The mixed-discrete problem is decomposed into multiple continuous subproblems; two-phase pruning steps identify and prune out non-contributory subproblems to the Pareto front construction. The efficacy of the proposed method is demonstrated on two benchmark examples.

  10. Fuzzy modeling based on generalized neural networks and fuzzy clustering objective functions

    Science.gov (United States)

    Sun, Chuen-Tsai; Jang, Jyh-Shing

    1991-01-01

    An approach to the formulation of fuzzy if-then rules based on clustering objective functions is proposed. The membership functions are then calibrated with the generalized neural networks technique to achieve a desired input-output mapping. The learning procedure is basically a gradient-descent algorithm. A Kalman filter algorithm is used to improve the overall performance.

  11. An Unsupervised Approach to Activity Recognition and Segmentation based on Object-Use Fingerprints

    DEFF Research Database (Denmark)

    Gu, Tao; Chen, Shaxun

    2010-01-01

    Human activity recognition is an important task which has many potential applications. In recent years, researchers from pervasive computing are interested in deploying on-body sensors to collect observations and applying machine learning techniques to model and recognize activities. Supervised machine learning techniques typically require an appropriate training process in which training data need to be labeled manually. In this paper, we propose an unsupervised approach based on object-use ?ngerprints to recognize activities without human labeling. We show how to build our activity models based on object-use ?ngerprints, which are sets of contrast patterns describing signi?cant differences of object use between any two activity classes. We then propose a ?ngerprint-based algorithm to recognize activities. We also propose two heuristic algorithms based on object relevance to segment a trace and detect the boundary of any two adjacent activities. We develop a wearable RFID system and conduct a real-world trace collection done by seven volunteers in a smart home over a period of 2 weeks. We conduct comprehensive experimental evaluations and comparison study. The results show that our recognition algorithm achieves a precision of 91.4% and a recall 92.8%, and the segmentation algorithm achieves an accuracy of 93.1% on the dataset we collected.

  12. Learning with Web-Based Interactive Objects: An Investigation into Student Perceptions of Effectiveness

    Science.gov (United States)

    Salajan, Florin D.; Perschbacher, Susanne; Cash, Mindy; Talwar, Reena; El-Badrawy, Wafa; Mount, Greg J.

    2009-01-01

    In its efforts to continue the modernization of its curriculum, the Faculty of Dentistry at the University of Toronto has developed a series of web-based interactive learning applications. This article presents the production cycle of these new interactive learning objects and the preliminary study conducted to measure the students' perception of…

  13. Object-oriented change detection based on weighted polarimetric scattering differences on POLSAR images

    Science.gov (United States)

    Shi, X.; Lu, L.; Yang, S.; Huang, G.; Zhao, Z.

    2015-06-01

    For wide application of change detection with SAR imagery, current processing technologies and methods are mostly based on pixels. It is difficult for pixel-based technologies to utilize spatial characteristics of images and topological relations of objects. Object-oriented technology takes objects as processing unit, which takes advantage of the shape and texture information of image. It can greatly improve the efficiency and reliability of change detection. Recently, with the development of polarimetric synthetic aperture radar (PolSAR), more backscattering features on different polarization state can be available for usage of object-oriented change detection study. In this paper, the object-oriented strategy will be employed. Considering the fact that the different target or target's state behaves different backscattering characteristics dependent on polarization state, an object-oriented change detection method that based on weighted polarimetric scattering difference of PolSAR images is proposed. The method operates on the objects generated by generalized statistical region merging (GSRM) segmentation processing. The merit of GSRM method is that image segmentation is executed on polarimetric coherence matrix, which takes full advantages of polarimetric backscattering features. And then, the measurement of polarimetric scattering difference is constructed by combining the correlation of covariance matrix and the difference of scattering power. Through analysing the effects of the covariance matrix correlation and the scattering echo power difference on the polarimetric scattering difference, the weighted method is used to balance the influences caused by the two parts, so that more reasonable weights can be chosen to decrease the false alarm rate. The effectiveness of the algorithm that proposed in this letter is tested by detection of the growth of crops with two different temporal radarsat-2 fully PolSAR data. First, objects are produced by GSRM algorithm based on the coherent matrix in the pre-processing. Then, the corresponding patches are extracted in two temporal images to measure the differences of objects. To detect changes of patches, a difference map is created by means of weighted polarization scattering difference. Finally, the result of change detection can be obtained by threshold determining. The experiments show that this approach is feasible and effective, and a reasonable choice of weights can improve the detection accuracy significantly.

  14. A Generalized Definition Language for Implementing the Object Based Fuzzy Class Model

    Directory of Open Access Journals (Sweden)

    Debasis Dwibedy, Dr. Laxman Sahoo, Sujoy Dutta

    2013-04-01

    Full Text Available The emerging application domains in Engineering, Scientific Technology, Multimedia, GIS, Knowledge management, Expert system design etc require advanced data models to represent and manipulate the data values, because the information resides in these domains are often vague or imprecise in nature & difficult to represent while implementing the application software. In order to fulfill the requirements of such application demands, researchers have put the innovative concept of object based fuzzy database system by extending the object oriented system and adding fuzzy techniques to handle complex object and imprecise data together. Some extensions of the OODMS have been proposed in the literature, but what is still lacking a unifying & systematic formalization of these dedicated concepts. This paper is the consequence research of our previous work, in which we proposed an effective & formal Fuzzy class model to represent all type of fuzzy attributes & objects those can be confined to fuzzy class. Here, we introduce a generalized definition language for the fuzzy class which can efficiently define the proposed fuzzy class model along with all possible fuzzy data type to describe the structure of the database & thus serve as data definition language for the object based fuzzy database system.

  15. Web Services Based Learning Objects Generator for Device-Independent M-Learning

    Directory of Open Access Journals (Sweden)

    Akram Moh. Alkouz

    2006-06-01

    Full Text Available Learning objects, which are the base component of m-learning system, are usually target to modifications in contexts and formats. The device- dependent applications of hand-held devices have proven to be ineffective for creating m-learning courseware. Learning Objects Metadata (LOM is the most popular standard specification for learning objects but lacks the ability to facilitate platforms descriptions. This paper outlines various aspects of design and implementation of Web Services Oriented Rendering Architecture (WSORA which combines LOM Editor with any available published web services. This arrangement is devised in order to make a device-independent m-learning gateway between different mobile devices, such as cell phones, PDA’s, palmtops, and laptops and the vast learning objects available on the World Wide Web. The key technologies behind WSORA are extending the IEEE LOM base scheme structure, LOM Editor, device-independent LO generator, and web services. The major advantage of WSORA is thus achieved to give mobile devices of different types clean and quick access to learning objects customarily designed for desktop browsers.

  16. Object-based land-cover classification for metropolitan Phoenix, Arizona, using aerial photography

    Science.gov (United States)

    Li, Xiaoxiao; Myint, Soe W.; Zhang, Yujia; Galletti, Chritopher; Zhang, Xiaoxiang; Turner, Billie L.

    2014-12-01

    Detailed land-cover mapping is essential for a range of research issues addressed by the sustainability and land system sciences and planning. This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program. It employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data. The classification rule was established on a hierarchical image object network, and the properties of parcels in the vector layer were used to establish land cover types. Image segmentations were initially utilized to separate the aerial photos into parcel sized objects, and were further used for detailed land type identification within the parcels. Characteristics of image objects from contextual and geometrical aspects were used in the decision rule set to reduce the spectral limitation of the four-band aerial photography. Classification results include 12 land-cover classes and subclasses that may be assessed from the sub-parcel to the landscape scales, facilitating examination of scale dynamics. The proposed object-based classification method provides robust results, uses minimal and readily available ancillary data, and reduces computational time.

  17. Intelligent Video Object Classification Scheme using Offline Feature Extraction and Machine Learning based Approach

    Directory of Open Access Journals (Sweden)

    Chandra Mani Sharma

    2012-01-01

    Full Text Available Classification of objects in video stream is important because of its application in many emerging areas such as visual surveillance, content based video retrieval and indexing etc. The task is far more challenging because the video data is of heavy and highly variable nature. The processing of video data is required to be in real-time. This paper presents a multiclass object classification technique using machine learning approach. Haar-like features are used for training the classifier. The feature calculation is performed using Integral Image representation and we train the classifier offline using a Stage-wise Additive Modeling using a Multiclass Exponential loss function (SAMME. The validity of the method has been verified from the implementation of a real-time human-car detector. Experimental results show that the proposed method can accurately classify objects, in video, into their respective classes. The proposed object classifier works well in outdoor environment in presence of moderate lighting conditions and variable scene background. The proposed technique is compared, with other object classification techniques, based on various performance parameters.

  18. Object tracking based on incremental Bi-2DPCA learning with sparse structure.

    Science.gov (United States)

    Bai, Bendu; Li, Ying; Fan, Jiulun; Price, Chris; Shen, Qiang

    2015-04-01

    In this paper, we propose a novel object tracking method that can work well in challenging scenarios such as appearance changes, motion blurs, and especially partial occlusions and noise. Our method applies bilateral two-dimensional principal component analysis (Bi-2DPCA) for efficient object modeling and real-time computation requirement. An incremental Bi-2DPCA learning algorithm is proposed for characterizing the appearance changes of newly tracked objects. Also, to account for noise and occlusions, a sparse structure is introduced into our Bi-2DPCA object representation model. With this sparse structure, the appearance of an object can be represented by a linear combination of basis images and an additional noise image. The noise image, which indicates the location of noise and occlusions, can be used to effectively eliminate the influence caused by noise and occlusions and lead to a robust tracker. Instead of the reconstruction error commonly used in eigen-based tracking methods, a more accurate method is adopted for the computation of observation likelihood. The method is based on the energy distribution of coefficient matrix projected by Bi-2DPCA. Experimental results on challenging image sequences demonstrate the effectiveness of the proposed tracking method. PMID:25967206

  19. An image-based multi-directional reflectance measurement setup for flexible objects

    Science.gov (United States)

    Sole, Aditya S.; Farup, Ivar; Tominaga, Shoji

    2015-03-01

    This paper presents an image-based method to measure reflectance of a homogeneous flexible object material (usually used in packaging). A point light source and a commercially available RGB camera is used to illuminate and measure the radiance reflected from the object surface in multiple reflection directions. By curving the flexible object onto a cylinder of known radius we are able to record radiance at multiple reflection angles in a faster way. In order to estimate the reflectance and to characterise the material, a spectralon reference tile is used. The spectralon tile is assumed to be homogenous and has near lambertain surface properties. Using Lambert's cosine law, irradiance at a given point on the object surface is calculated. This information is then used to calculate a BRDF using Phong reflection model to describe the sample surface reflection properties. The measurement setup is described and discussed in this paper along with its use to estimate a BRDF for a given material/substrate. Results obtained indicate that the proposed image-based technique works well to measure light reflected at different planar angles and record information to estimate the BRDF of the sample materials that can be modelled using Phong reflection model. The object material properties, sample curvature and camera resolution decides the number of incident and reflection angles at which the bi-directional reflectance, or the material BRDF, can be estimated using this method.

  20. Multi-class geospatial object detection and geographic image classification based on collection of part detectors

    Science.gov (United States)

    Cheng, Gong; Han, Junwei; Zhou, Peicheng; Guo, Lei

    2014-12-01

    The rapid development of remote sensing technology has facilitated us the acquisition of remote sensing images with higher and higher spatial resolution, but how to automatically understand the image contents is still a big challenge. In this paper, we develop a practical and rotation-invariant framework for multi-class geospatial object detection and geographic image classification based on collection of part detectors (COPD). The COPD is composed of a set of representative and discriminative part detectors, where each part detector is a linear support vector machine (SVM) classifier used for the detection of objects or recurring spatial patterns within a certain range of orientation. Specifically, when performing multi-class geospatial object detection, we learn a set of seed-based part detectors where each part detector corresponds to a particular viewpoint of an object class, so the collection of them provides a solution for rotation-invariant detection of multi-class objects. When performing geographic image classification, we utilize a large number of pre-trained part detectors to discovery distinctive visual parts from images and use them as attributes to represent the images. Comprehensive evaluations on two remote sensing image databases and comparisons with some state-of-the-art approaches demonstrate the effectiveness and superiority of the developed framework.

  1. A bio-inspired method and system for visual object-based attention and segmentation

    Science.gov (United States)

    Huber, David J.; Khosla, Deepak

    2010-04-01

    This paper describes a method and system of human-like attention and object segmentation in visual scenes that (1) attends to regions in a scene in their rank of saliency in the image, (2) extracts the boundary of an attended proto-object based on feature contours, and (3) can be biased to boost the attention paid to specific features in a scene, such as those of a desired target object in static and video imagery. The purpose of the system is to identify regions of a scene of potential importance and extract the region data for processing by an object recognition and classification algorithm. The attention process can be performed in a default, bottom-up manner or a directed, top-down manner which will assign a preference to certain features over others. One can apply this system to any static scene, whether that is a still photograph or imagery captured from video. We employ algorithms that are motivated by findings in neuroscience, psychology, and cognitive science to construct a system that is novel in its modular and stepwise approach to the problems of attention and region extraction, its application of a flooding algorithm to break apart an image into smaller proto-objects based on feature density, and its ability to join smaller regions of similar features into larger proto-objects. This approach allows many complicated operations to be carried out by the system in a very short time, approaching real-time. A researcher can use this system as a robust front-end to a larger system that includes object recognition and scene understanding modules; it is engineered to function over a broad range of situations and can be applied to any scene with minimal tuning from the user.

  2. Three-dimensional visualization environment for multisensor data analysis, interpretation, and model-based object recognition

    Science.gov (United States)

    Goss, Michael E.; Beveridge, J. Ross; Stevens, Mark; Fuegi, Aaron D.

    1995-04-01

    Model-based object recognition must solve three-dimensional geometric problems involving the registration of multiple sensors and the spatial relationship of a three-dimensional model to the sensors. Observation and verification of the registration and recognition processes requires display of these geometric relationships. We have developed a prototype software system which allows a user to interact with the sensor data and model matching system in a three- dimensional environment. This visualization environment combines range imagery, color imagery, thermal (infrared) imagery, and CAD models of objects to be recognized. We are currently using imagery of vehicles travelling off-road (a challenging environment for the object recognizer). Range imagery is used to create a partial three-dimensional representation of a scene. Optical imagery is mapped onto this partial 3D representation. Visualization allows monitoring of the recognizer as it solves for the type and position of the object. The object is rendered from its associated CAD model. In addition to its usefulness in development of the object recognizer, we foresee eventual use of this technology in a fielded system for operator verification of automatic target recognition results.

  3. A foreground object features-based stereoscopic image visual comfort assessment model

    Science.gov (United States)

    Jin, Xin; Jiang, G.; Ying, H.; Yu, M.; Ding, S.; Peng, Z.; Shao, F.

    2014-11-01

    Since stereoscopic images provide observers with both realistic and discomfort viewing experience, it is necessary to investigate the determinants of visual discomfort. By considering that foreground object draws most attention when human observing stereoscopic images. This paper proposes a new foreground object based visual comfort assessment (VCA) metric. In the first place, a suitable segmentation method is applied to disparity map and then the foreground object is ascertained as the one having the biggest average disparity. In the second place, three visual features being average disparity, average width and spatial complexity of foreground object are computed from the perspective of visual attention. Nevertheless, object's width and complexity do not consistently influence the perception of visual comfort in comparison with disparity. In accordance with this psychological phenomenon, we divide the whole images into four categories on the basis of different disparity and width, and exert four different models to more precisely predict its visual comfort in the third place. Experimental results show that the proposed VCA metric outperformance other existing metrics and can achieve a high consistency between objective and subjective visual comfort scores. The Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are over 0.84 and 0.82, respectively.

  4. Thermodynamic modeling and multi-objective evolutionary-based optimization of a new multigeneration energy system

    International Nuclear Information System (INIS)

    Highlights: • Comprehensive thermodynamic modeling of a multi-generation system is reported. • New multi-generation systems are proposed for more environmentally benign applications. • Multi-objective optimization technique is applied based on a code developed in the Matlab software. • A sensitivity analysis to determine the effect of design parameters on objective functions is conducted. - Abstract: A comprehensive thermodynamic modeling and multi-objective optimization is reported of a multigeneration energy system, based on a micro gas turbine, a dual pressure heat recovery steam generator, an absorption chiller, an ejector refrigeration cycle, a domestic water heater and a proton exchange membrane electrolyzer, that produces multiple commodities: power, heating, cooling, hot water and hydrogen. Energy and exergy analyses and an environmental impact assessment are included. A multi-objective optimization method based on a fast and elitist non-dominated sorting genetic algorithm (NSGA-II) is applied to determine the best design parameters for the system. The two objective functions utilized in the optimization study are the total cost rate of the system, which is the cost associated with fuel, component purchasing and environmental impact, and the system exergy efficiency. The total cost rate of the system is minimized while the cycle exergy efficiency is maximized using an evolutionary algorithm. To provide insight, the Pareto frontier is shown for a multi-objective optimization. In addition, a closed form equation for the relationship between exergy efficiency and total cost rate is derived. A sensitivity analysis is performed to assess the effects of several design parameters on the system total exergy destruction rate, CO2 emission and exergy efficiency

  5. Implementation of intelligent nuclear material diagnosis module based on the component object model

    International Nuclear Information System (INIS)

    In this paper, the implementation techniques of intelligent nuclear material surveillance system based on the COM (Component Object Model) and SOM (Self Organized Mapping) was described. The surveillance system that is to be developed is consist of CCD cameras, neutron monitors, and PC for data acquisition. To develop the system, the properties of the COM based software development technology was investigated, and the characteristics of related platform APIs was summarized. This report could be used for the developers who want to develop the intelligent surveillance system for various experimental environments based on the DVR and sensors using Borland C++ Builder

  6. A Robust Approach to Segment Desired Object Based on Salient Colors

    Directory of Open Access Journals (Sweden)

    Jérôme Da Rugna

    2008-01-01

    Full Text Available This paper presents a clustering-based color segmentation method where the desired object is focused on. As classical methods suffer from a lack of robustness, salient colors appearing in the object are used to intuitively tune the algorithm. These salient colors are extracted according to a psychovisual scheme and a peak-finding step. Results on various test sequences, covering a representative set of outdoor real videos, show the improvement when compared to a simple implementation of the same K-means oriented segmentation algorithm with ad hoc parameter setting strategy and with the well-known mean-shift algorithm.

  7. Techniques for Efficient Tracking of Road-Network-Based Moving Objects

    DEFF Research Database (Denmark)

    Civilis, Alminas; Jensen, Christian SØndergaard

    2005-01-01

    With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects. This scenario is characterized by large volumes of updates, for which reason location update technologies become important. A setting is assumed in which a central database stores a representation of each moving object's current position. This position is to be maintained so that it deviates from the user's real position by at most a given threshold. To do so, each moving object stores locally the central representation of its position. Then an object updates the database whenever the deviation between its actual position (as obtained from a GPS device) and the database position exceeds the threshold. The main issue considered is how to represent the location of a moving object in a database so that tracking can be donewith as few updates as possible. The paper proposes to use the road network within which the objects are assumed to move for predicting their future positions. The paper presents algorithms that modify an initial road-network representation, so that it works better as a basis for predicting an object's position; it proposes to use known movement patterns of the object, in the form of routes; and it proposes to use acceleration profiles together with the routes. Using real GPS-data and a corresponding real road network, the paper offers empirical evaluations and comparisons that include three existing approaches and all the proposed approaches.

  8. Techniques for efficient road-network-based tracking of moving objects

    DEFF Research Database (Denmark)

    Civilis, A.; Jensen, Christian SØndergaard

    2005-01-01

    With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects. This scenario is characterized by large volumes of updates, for which reason location update technologies become important. A setting is assumed in which a central database stores a representation of each moving object's current position. This position is to be maintained so that it deviates from the user's real position by at most a given threshold. To do so, each moving object stores locally the central representation of its position. Then an object updates the database whenever the deviation between its actual position (as obtained from a GPS device) and the database position exceeds the threshold. The main issue considered is how to represent the location of a moving object in a database so that tracking can be done with as few updates as possible. The paper proposes to use the road network within which the objects are assumed to move for predicting their future positions. The paper presents algorithms that modify an initial road-network representation, so that it works better as a basis for predicting an object's position; it proposes to use known movement patterns of the object, in the form of routes; and it proposes to use acceleration profiles together with the routes. Using real GPS-data and a corresponding real road network, the paper offers empirical evaluations and comparisons that include three existing approaches and all the proposed approaches. Udgivelsesdato: May

  9. Image motion-blur-based object's speed measurement using an interlaced scan image

    International Nuclear Information System (INIS)

    In motion-blur-based speed measurement, a key step is the calculation of the horizontal blur extent. To perform this calculation robustly and accurately when both a defocus blur and a motion blur occur, and for a moving object with irregular shape edges, we propose a novel scheme using the image matting and transparency map. This scheme can isolate the defocus blur from the motion blur effectively, and can also calculate the horizontal blur extent accurately, regardless of the object's shape. Moreover, our novel scheme can also perform speed measurement for an object with uniformly accelerated/retarded motion (i.e. a rigid body linear motion with a constant acceleration) by using one interlaced scan CCD image. Simulation and real experiments prove that our scheme not only outperforms the current scan-line algorithm for blur extent computation, but can also perform speed measurement accurately for uniformly accelerated/retarded motion

  10. Kernel Based Approach toward Automatic object Detection and Tracking in Surveillance Systems

    Directory of Open Access Journals (Sweden)

    Amir Aliabadian

    2012-03-01

    Full Text Available A modified object-tracking algorithm that uses the flexible Metric Distance Transform kernel and multiple features for the Mean shift procedure is proposed and tested. The Faithful target separation based on RGB joint pdf of the target region and that of a neighborhood surrounding the object is obtained. The non-linear log-likelihood function maps the multimodal object/background distribution as positive values for colors associated with foreground, while negative values are marked for background. This replaces the more usual Epanechnikov kernel (E-kernel, improving target representation and localization without increasing the processing time, minimizing the similarity measure using the Bhattacharya coefficient. The algorithm is tested on several image sequences and shown to achieve robust and reliable frame-rate tracking.

  11. Static Object Detection Based on a Dual Background Model and a Finite-State Machine

    Directory of Open Access Journals (Sweden)

    Heras Evangelio Rubén

    2011-01-01

    Full Text Available Detecting static objects in video sequences has a high relevance in many surveillance applications, such as the detection of abandoned objects in public areas. In this paper, we present a system for the detection of static objects in crowded scenes. Based on the detection of two background models learning at different rates, pixels are classified with the help of a finite-state machine. The background is modelled by two mixtures of Gaussians with identical parameters except for the learning rate. The state machine provides the meaning for the interpretation of the results obtained from background subtraction; it can be implemented as a look-up table with negligible computational cost and it can be easily extended. Due to the definition of the states in the state machine, the system can be used either full automatically or interactively, making it extremely suitable for real-life surveillance applications. The system was successfully validated with several public datasets.

  12. Real-Time Projection-Based Augmented Reality System for Dynamic Objects in the Performing Arts

    Directory of Open Access Journals (Sweden)

    Jaewoon Lee

    2015-02-01

    Full Text Available This paper describes the case study of applying projection-based augmented reality, especially for dynamic objects in live performing shows, such as plays, dancing, or musicals. Our study aims to project imagery correctly inside the silhouettes of flexible objects, in other words, live actors or the surface of actor’s costumes; the silhouette transforms its own shape frequently. To realize this work, we implemented a special projection system based on the real-time masking technique, that is to say real-time projection-based augmented reality system for dynamic objects in performing arts. We installed the sets on a stage for live performance, and rehearsed particular scenes of a musical. In live performance, using projection-based augmented reality technology enhances technical and theatrical aspects which were not possible with existing video projection techniques. The projected images on the surfaces of actor’s costume could not only express the particular scene of a performance more effectively, but also lead the audience to an extraordinary visual experience.

  13. Multi-objective Differential Evolution Algorithm based on Adaptive Mutation and Partition Selection

    Directory of Open Access Journals (Sweden)

    Sen Zhao

    2013-10-01

    Full Text Available A multi-objective differential evolution algorithm based on adaptive mutation strategies and partition selected search is proposed based on classical differential evolution(DE to further improve the convergence and diversity of multi-objective optimization problems. This algorithm improves mutation operation in DE, makes search oriented and ensures the convergence of algorithm by adaptively selecting mutation strategies based on the non-inferiority of the individuals of the population in evolution. In addition, a partition-based elitist preserving mechanism is applied to select the best individuals for the next generation, thus improving the selection operation in DE and maintaining the diversity of Pareto optimal set. The experiment on 5 ZDT test functions and 3 DTLZ test functions and comparison with and analysis of other classical algorithms such as NSGA-II and SPEA2 show that this algorithm converges the populations towards non-inferior frontier rapidly on the premise of maintaining the diversity of the populations. From the measure and graphs, it can be seen that this algorithm is feasible and effective in solving the multi-objective optimization problems.

  14. Image Coding Scheme Based on Object Extraction and Hybrid Transformation Technique

    Directory of Open Access Journals (Sweden)

    Usama S. Mohammed

    2010-05-01

    Full Text Available This paper describes an efficient object-based hybrid image coding (OB-HIC scheme. The proposed scheme is based on using the discrete wavelet transform (DWT in conjunction with the discrete cosine transform (DCT to provide coding performance superior to the popular image coders. The proposed method uses combination of the object-based DCT coding and the high performance of the set partitioning in hierarchical tree (SPIHT coding. The subband image data in the wavelet domain is modified based on the DCT and the object classification of the coefficient in the low-frequency image subband (LL. The modification process provides a new subband image data containing almost the same information of the original one but having smaller values of the wavelet coefficients. Simulation results of the proposed method demonstrate that, with small addition in the computational complexity of the coding process, the peak signal-to-noise ratio (PSNR performance of the proposed algorithm is much higher than that of the SPIHT test coder and some of famous image coding techniques.

  15. A New Object-Based System for Fractal Video Sequences Compression

    Directory of Open Access Journals (Sweden)

    Kamel Belloulata

    2007-06-01

    Full Text Available A novel object-based fractal monocular and stereo video compression scheme with quadtree-based motion and disparity compensation is proposed in this paper. Fractal coding is adopted and each object is encoded independently by a prior image segmentation alpha plane, which is defined exactly as in MPEG-4. The first n frames of right video sequence are encoded by using the Circular Prediction Mapping (CPM and the remaining frames are encoded by using the Non Contractive Interframe Mapping (NCIM. The CPM and NCIM methods accomplish the motion estimation/ compensation of right video sequence. According to the different coding or user requirements, the spatial correlations between the left and right frames can be explored by partial or full affine transformation quadtree-based disparity estimation/ compensation, or simply by applying CPM/NCIM on left video sequence. The testing results with the nature monocular and stereo video sequences provide promising performances at low bit rate coding. We believe it will be a powerful and efficient technique for the object-based monocular and stereo video sequences coding.

  16. Operational Automatic Remote Sensing Image Understanding Systems: Beyond Geographic Object-Based and Object-Oriented Image Analysis (GEOBIA/GEOOIA). Part 1: Introduction

    OpenAIRE

    Andrea Baraldi; Luigi Boschetti

    2012-01-01

    According to existing literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA) systems and three-stage iterative geographic object-oriented image analysis (GEOOIA) systems, where GEOOIA/GEOBIA, remain affected by a lack of productivity, general consensus and research. To outperform the degree of automation, accuracy, efficiency, robustness, scalability and timeliness of existing GEOBIA/GEOOIA systems in complianc...

  17. Studies on pansharpening and object-based classification of Worldview-2 multispectral image

    Science.gov (United States)

    Wycza?ek, I.; Wycza?ek, E.

    2013-12-01

    The new information contained in four additional spectral bands of high - resolution images from the satellite sensor WorldView - 2 should provide a visible improvement in the quality of analysis of large - scale phenomena occurring at the ground. Selected part of the image of Poznan was analyzed in order to verify these possibilities in relation to the urban environment. It includes riverside green area and a number of adjacent buildings. Attention has been focused on two components of object - oriented analysis - sharpening the image and its classification. In terms of pansharpening the aim was to obtain a clear picture of terrain objects in details, what should lead to the correct division of the image into homogenous segments and the subsequent fine classification. It was intended to ensure the possibility of separating small field objects within the set of classes. The task was carried out using various computer programs that enable the development and analysis of raster data (IDRISI Andes, ESRI ArcGIS 9.3, eCognition Developer 8) and some own computational modules. The main scientific objective of this study was to determine how much information from new spectral image layers after their pansharpening affects the quality of object - based classification of land cover in green and building areas of the city. As a basis for improving the quality of the classification was above mentioned ability of using additional data from new spectral bands of WorldView - 2 image. To assess the quality of the classification we used test that examines only the uncertain areas of t he picture, that is these which lie on differently classified types of land cover. The outcome of assessment confirmed the thesis of the positive albeit small impact of additional spectral channels on the result of object - based classification. But also pansharpening itself only slightly improves the quality of classified image

  18. Coregistration refinement of hyperspectral images and DSM: An object-based approach using spectral information

    Science.gov (United States)

    Avbelj, Janja; Iwaszczuk, Dorota; Müller, Rupert; Reinartz, Peter; Stilla, Uwe

    2015-02-01

    For image fusion in remote sensing applications the georeferencing accuracy using position, attitude, and camera calibration measurements can be insufficient. Thus, image processing techniques should be employed for precise coregistration of images. In this article a method for multimodal object-based image coregistration refinement between hyperspectral images (HSI) and digital surface models (DSM) is presented. The method is divided in three parts: object outline detection in HSI and DSM, matching, and determination of transformation parameters. The novelty of our proposed coregistration refinement method is the use of material properties and height information of urban objects from HSI and DSM, respectively. We refer to urban objects as objects which are typical in urban environments and focus on buildings by describing them with 2D outlines. Furthermore, the geometric accuracy of these detected building outlines is taken into account in the matching step and for the determination of transformation parameters. Hence, a stochastic model is introduced to compute optimal transformation parameters. The feasibility of the method is shown by testing it on two aerial HSI of different spatial and spectral resolution, and two DSM of different spatial resolution. The evaluation is carried out by comparing the accuracies of the transformations parameters to the reference parameters, determined by considering object outlines at much higher resolution, and also by computing the correctness and the quality rate of the extracted outlines before and after coregistration refinement. Results indicate that using outlines of objects instead of only line segments is advantageous for coregistration of HSI and DSM. The extraction of building outlines in comparison to the line cue extraction provides a larger amount of assigned lines between the images and is more robust to outliers, i.e. false matches.

  19. Aerial surveillance based on hierarchical object classification for ground target detection

    Science.gov (United States)

    Vázquez-Cervantes, Alberto; García-Huerta, Juan-Manuel; Hernández-Díaz, Teresa; Soto-Cajiga, J. A.; Jiménez-Hernández, Hugo

    2015-03-01

    Unmanned aerial vehicles have turned important in surveillance application due to the flexibility and ability to inspect and displace in different regions of interest. The instrumentation and autonomy of these vehicles have been increased; i.e. the camera sensor is now integrated. Mounted cameras allow flexibility to monitor several regions of interest, displacing and changing the camera view. A well common task performed by this kind of vehicles correspond to object localization and tracking. This work presents a hierarchical novel algorithm to detect and locate objects. The algorithm is based on a detection-by-example approach; this is, the target evidence is provided at the beginning of the vehicle's route. Afterwards, the vehicle inspects the scenario, detecting all similar objects through UTM-GPS coordinate references. Detection process consists on a sampling information process of the target object. Sampling process encode in a hierarchical tree with different sampling's densities. Coding space correspond to a huge binary space dimension. Properties such as independence and associative operators are defined in this space to construct a relation between the target object and a set of selected features. Different densities of sampling are used to discriminate from general to particular features that correspond to the target. The hierarchy is used as a way to adapt the complexity of the algorithm due to optimized battery duty cycle of the aerial device. Finally, this approach is tested in several outdoors scenarios, proving that the hierarchical algorithm works efficiently under several conditions.

  20. Age-based hiring discrimination as a function of equity norms and self-perceived objectivity.

    Science.gov (United States)

    Lindner, Nicole M; Graser, Alexander; Nosek, Brian A

    2014-01-01

    Participants completed a questionnaire priming them to perceive themselves as either objective or biased, either before or after evaluating a young or old job applicant for a position linked to youthful stereotypes. Participants agreed that they were objective and tended to disagree that they were biased. Extending past research, both the objective and bias priming conditions led to an increase in age discrimination compared to the control condition. We also investigated whether equity norms reduced age discrimination, by manipulating the presence or absence of an equity statement reminding decision-makers of the legal prohibitions against discrimination "on the basis of age, disability, national or ethnic origin, race, religion, or sex." The presence of equity norms increased enthusiasm for both young and old applicants when participants were not already primed to think of themselves as objective, but did not reduce age-based hiring discrimination. Equity norms had no effect when individuals thought of themselves as objective - they preferred the younger more than the older job applicant. However, the presence of equity norms did affect individuals' perceptions of which factors were important to their hiring decisions, increasing the perceived importance of applicants' expertise and decreasing the perceived importance of the applicants' age. The results suggest that interventions that rely exclusively on decision-makers' intentions to behave equitably may be ineffective. PMID:24465429

  1. Bionics-Based Approach for Object Tracking to Implementin Robot Applications

    Directory of Open Access Journals (Sweden)

    Hussam K. Abdul-Ameer

    2010-01-01

    Full Text Available In this paper, an approach for object tracking that is inspired from human oculomotor system is proposed and verified experimentally. The developed approach divided into two phases, fast tracking or saccadic phase and smooth pursuit phase. In the first phase, the field of the view is segmented into four regions that are analogue to retinal periphery in the oculomotor system. When the object of interest is entering these regions, the developed vision system responds by changing the values of the pan and tilt angles to allow the object lies in the fovea area and then the second phase will activate. A fuzzy logic method is implemented in the saccadic phase as an intelligent decision maker to select the values of the pan and tilt angle based on suggested logical rules. In smooth pursuit phase, the object is kept in the center area of the field of the view by smooth adjusting the values of the pan and tilt angles where this stage is analogue to putting the observing object in the fovea centralis of the oculomotor system. The proposed approach was implemented by using (Camera-Pan / Tilt configuration and showed good results to improve the vision capability of the humanoid robots.

  2. IMPLEMENTATION OF OBJECT TRACKING SYSTEM USING REGION FILTERING ALGORITHM BASED ON SIMULINK BLOCKSETS

    Directory of Open Access Journals (Sweden)

    DR.P.SUBASHINI

    2011-08-01

    Full Text Available Video tracking is the process of locating a moving object in time that is visualized by camera and are widely used in surveillance, animation and robotics Tracking describes the process of recording movement and translating that movement onto a digital model. The set of constraints that produce the most accurate tracking is the one that describes better the action performed. The key difficulty in video tracking is to associate target locations in consecutive video frames, especially when the objects are moving fast relative to the frame rate. Here, a video tracking system is been employed in which motion model describes how the image of the target might change for different possible motions of the object to track. The role of the tracking algorithm adopted for this system is to analyze the video frames to estimate the motion parameters. These parameters characterize the location of the target. In this research, three features are been extracted from each moving objects such as centroid, area, average luminance. Finally the similarity function is applied to tracking and the attempt proves that the chosen method has good performance under dynamic circumstances for real time tracking. Simulink is integrated with MATLAB to build a model for object tracking and data transfer is easily handled between the programs. The Simulink based customizable framework is designed for rapid simulation, implementation, and verification of video and image processing algorithms and systems.

  3. Simplified production of multimedia based radiological learning objects using the flash format

    International Nuclear Information System (INIS)

    Purpose: evaluation of the applicability of the flash format for the production of radiological learning objects used in an e-learning environment. Material and methods: five exemplary learning objects with different didactic purposes referring to radiological diagnostics are presented. They have been intended for the use within the multimedia, internet-based e-learning environment LaMedica. Interactive learning objects were composed using the Flash 5.0 software (Macromedia, San Francisco, USA) on the basis of digital CT and MR images, digitized conventional radiographs and different graphical elements prepared as TIFF files or in a vector graphics format. Results: after a short phase of initial skill adaptation training, a radiologist author was soon able to create independently all learning objects. The import of different types of images and graphical elements was carried out without complications. Despite manifold design options, handling of the program is easy due to clear arrangement and structure, thus enabling the creation of simple as well as complex learning objects that provided a high degree of attractiveness and interaction. Data volume and bandwidth demand for online use was significantly reduced by the flash format compression without a substantial loss of visual quality. (orig.)

  4. The neural bases of crossmodal object recognition in non-human primates and rodents: a review.

    Science.gov (United States)

    Cloke, Jacob M; Jacklin, Derek L; Winters, Boyer D

    2015-05-15

    The ability to integrate information from different sensory modalities to form unique multisensory object representations is a highly adaptive cognitive function. Surprisingly, non-human animal studies of the neural substrates of this form of multisensory integration have been somewhat sparse until very recently, and this may be due in part to a relative paucity of viable testing methods. Here we review the historical development and use of various "crossmodal" cognition tasks for non-human primates and rodents, focusing on tests of "crossmodal object recognition", the ability to recognize an object across sensory modalities. Such procedures have great potential to elucidate the cognitive and neural bases of object representation as it pertains to perception and memory. Indeed, these studies have revealed roles in crossmodal cognition for various brain regions (e.g., prefrontal and temporal cortices) and neurochemical systems (e.g., acetylcholine). A recent increase in behavioral and physiological studies of crossmodal cognition in rodents augurs well for the future of this research area, which should provide essential information about the basic mechanisms of object representation in the brain, in addition to fostering a better understanding of the causes of, and potential treatments for, cognitive deficits in human diseases characterized by atypical multisensory integration. PMID:25286314

  5. Recovering Use Case Diagrams from Object Oriented Code: an MDA-based Approach

    Directory of Open Access Journals (Sweden)

    Claudia T. Pereira

    2012-07-01

    Full Text Available Modernization of legacy systems requires the existence of technicalframeworks for information integration and tool interoperability that allow managing new platform technologies, design techniques and processes. MDA (Model Driven Architecture, adopted by the OMG (Object Management Group, is aligned with this requirement. Reverse engineering techniques play a crucial role in system modernization. In light of these issues, this article describes a framework to reverse engineering MDA models from object oriented code. This framework distinguishes three different abstraction levelslinked to models, metamodels and formal specifications. At model level,transformations are based on static and dynamic analysis. At metamodel level, transformations are specified as OCL (Object Constraint Languagecontracts between MOF (Meta Object Facility metamodels which control the consistency of these transformations. The level of formal specification includes algebraic specifications of MOF metamodels and metamodel-based transformations. This article shows how to reverse engineering use case diagrams from Java code in the MDA context focusing on transformations at model and metamodel levels. We validate our approach by using Eclipse Modeling Framework, Ecore metamodels and ATL (Atlas Transformation Language.

  6. Robust Object-Based Watermarking Using SURF Feature Matching and DFT Domain

    Directory of Open Access Journals (Sweden)

    M. Cedillo-Hernandez

    2013-12-01

    Full Text Available In this paper we propose a robust object-based watermarking method, in which the watermark is embedded into the middle frequencies band of the Discrete Fourier Transform (DFT magnitude of the selected object region, altogether with the Speeded Up Robust Feature (SURF algorithm to allow the correct watermark detection, even if the watermarked image has been distorted. To recognize the selected object region after geometric distortions, during the embedding process the SURF features are estimated and stored in advance to be used during the detection process. In the detection stage, the SURF features of the distorted image are estimated and match them with the stored ones. From the matching result, SURF features are used to compute the Affine-transformation parameters and the object region is recovered. The quality of the watermarked image is measured using the Peak Signal to Noise Ratio (PSNR, Structural Similarity Index (SSIM and the Visual Information Fidelity (VIF. The experimental results show the proposed method provides robustness against several geometric distortions, signal processing operations and combined distortions. The receiver operating characteristics (ROC curves also show the desirable detection performance of the proposed method. The comparison with a previously reported methods based on different techniques is also provided.

  7. Internet of Things based on smart objects technology, middleware and applications

    CERN Document Server

    Trunfio, Paolo

    2014-01-01

    The Internet of Things (IoT) usually refers to a world-wide network of interconnected heterogeneous objects (sensors, actuators, smart devices, smart objects, RFID, embedded computers, etc) uniquely addressable, based on standard communication protocols. Beyond such a definition, it is emerging a new definition of IoT seen as a loosely coupled, decentralized system of cooperating smart objects (SOs). A SO is an autonomous, physical digital object augmented with sensing/actuating, processing, storing, and networking capabilities. SOs are able to sense/actuate, store, and interpret information created within themselves and around the neighbouring external world where they are situated, act on their own, cooperate with each other, and exchange information with other kinds of electronic devices and human users. However, such SO-oriented IoT raises many in-the-small and in-the-large issues involving SO programming, IoT system architecture/middleware and methods/methodologies for the development of SO-based applica...

  8. PE-CMOS based C-scan ultrasound for foreign object detection in soft tissue.

    Science.gov (United States)

    Liu, Chu-Chuan; Lo, Shih-Chung Ben; Freedman, Matthew T; Lasser, Marvin E; Kula, John; Sarcone, Anita; Wang, Yue

    2010-01-01

    In this paper, we introduce a C-scan ultrasound prototype and three imaging modalities for the detection of foreign objects inserted in porcine soft tissue. The object materials include bamboo, plastics, glass and aluminum alloys. The images of foreign objects were acquired using the C-scan ultrasound, a portable B-scan ultrasound, film-based radiography, and computerized radiography. The C-scan ultrasound consists of a plane wave transducer, a compound acoustic lens system, and a newly developed ultrasound sensor array based on the complementary metal-oxide semiconductor coated with piezoelectric material (PE-CMOS). The contrast-to-noise ratio (CNR) of the images were analyzed to quantitatively evaluate the detectability using different imaging modalities. The experimental results indicate that the C-scan prototype has better CNR values in 4 out of 7 objects than other modalities. Specifically, the C-scan prototype provides more detail information of the soft tissues without the speckle artifacts that are commonly seen with conventional B-scan ultrasound, and has the same orientation as the standard radiographs but without ionizing radiation. PMID:20036873

  9. Vineyard parcel identification from Worldview-2 images using object-based classification model

    Science.gov (United States)

    Sertel, Elif; Yay, Irmak

    2014-01-01

    Accurate identification of spatial distribution and characteristics of vineyard parcels is an important task for the effective management of vineyard areas, precision viticulture, and farmer registries. This study aimed to develop rule sets to be used in object-based classification of Worldview-2 satellite images to accurately delineate the boundaries of vineyards having different plantation styles. Multilevel segmentation was applied to Worldview-2 images to create different sizes of image objects representing different land cover categories with respect to scale parameter. Texture analysis and several new spectral indices were applied to objects at different segmentation levels to accurately classify land cover classes of forest, cultivated areas, harvested areas, impervious, bareland, and vineyards. A specific attention was given to vineyard class to identify vine areas at the parcel level considering their different plantation styles. The results illustrated that the combined usage of a newly developed decision tree and image segmentation during the object-based classification process could provide highly accurate results for the identification of vineyard parcels. Linearly planted vineyards could be classified with 100% producer's accuracy due to their regular textural characteristics, whereas regular gridwise and irregular gridwise (distributed) vineyard parcels could be classified with 94.87% producer's accuracy in this research.

  10. Determination of the Traveling Speed of a Moving Object of a Video Using Background Extraction and Region Based Segmentation

    OpenAIRE

    Md. Shafiul Azam; Md. Rashedul Islam; Md. Omar Faruqe

    2011-01-01

    This paper is concerned with the determination of the traveling speed of a moving object of a video clip based on subsequent object detection techniques. After preprocessing of the original image sequence, which is sampled from the video camera, the target moving object is detected with the improved algorithm in which the moving object region can be extracted completely through several processing of background extraction and region based segmentation such as region-connection, region- merging...

  11. A Layer-Based Object-Oriented Parallel Framework for Beam Dynamics Studies

    International Nuclear Information System (INIS)

    A three-dimensional time-dependent parallel particle-in-cell framework has been developed to model complex accelerator systems. This framework has been designed based on object-oriented methodology using a layered structure. The layer-based object-oriented software design helps to encapsulate both the details of the physical application and its parallel implementation and gives the program good maintainability and extensibility. The new framework is currently being applied to the study of the LEDA beam halo experiment at the Los Alamos National Laboratory. Using the new framework running on a parallel supercomputer we can simulate, with high resolution, multiple bunches propagating and merging through the LEDA system, including the effects of interbunch and intrabunch 3D space-charge forces. Such high resolution multi-bunch simulation is beyond the capability of current serial beam dynamics codes.

  12. How a face may affect object-based attention: evidence from adults and 8-month-old infants.

    Science.gov (United States)

    Valenza, Eloisa; Franchin, Laura; Bulf, Hermann

    2014-01-01

    Object-based attention operates on perceptual objects, opening the possibility that the costs and benefits humans have to pay to move attention between-objects might be affected by the nature of the stimuli. The current study reported two experiments with adults and 8-month-old infants investigating whether object-based-attention is affected by the type of stimulus (faces vs. non-faces stimuli). Using the well-known cueing task developed by Egly et al. (1994) to study the object-based component of attention, in Experiment 1 adult participants were presented with two upright, inverted or scrambled faces and an eye-tracker measured their saccadic latencies to find a target that could appear on the same object that was just cued or on the other object that was uncued. Data showed that an object-based effect (a smaller cost to shift attention within- compared to between-objects) occurred only with scrambled face, but not with upright or inverted faces. In Experiment 2 the same task was performed with 8-month-old infants, using upright and inverted faces. Data revealed that an object-based effect emerges only for inverted faces but not for upright faces. Overall, these findings suggest that object-based attention is modulated by the type of stimulus and by the experience acquired by the viewer with different objects. PMID:24723860

  13. Extracting Objects and Events from MPEG Videos for Highlight-based Indexing and Retrieval

    OpenAIRE

    Jinchang Ren; Jianmin Jiang; Juan Chen; Ipson, Stan S.

    2010-01-01

    Automatic recognition of highlights from videos is a fundamental and challenging problem for content-based indexing and retrieval applications. In this paper, we propose techniques to solve this problem using knowledge supported extraction of semantics, and compressed-domain processing is employed for efficiency. Firstly, knowledgebased rules are utilized for shot detection on extracted DCimages, and statistical skin detection is applied for human object detection. Secondly, through filtering...

  14. The effect of input data transformations on object-based image analysis

    OpenAIRE

    Lippitt, Christopher D.; Coulter, Lloyd L.; Freeman, Mary; Lamantia-bishop, Jeffrey; Pang, Wyson; Stow, Douglas A.

    2012-01-01

    The effect of using spectral transform images as input data on segmentation quality and its potential effect on products generated by object-based image analysis are explored in the context of land cover classification in Accra, Ghana. Five image data transformations are compared to untransformed spectral bands in terms of their effect on segmentation quality and final product accuracy. The relationship between segmentation quality and product accuracy is also briefly explored. Results sugges...

  15. A comparison of perceptually-based metrics for objective evaluation of geometry processing

    OpenAIRE

    Lavoue, Guillaume; Corsini, Massimiliano

    2010-01-01

    Recent advances in 3D graphics technologies have led to an increasing use of processing techniques on 3D meshes, such as filtering, compression, watermarking, simplification, deformation and so forth. Since these processes may modify the visual appearance of the 3D objects, several metrics have been introduced to properly drive or evaluate them, from classic geometric ones such as Hausdorff distance, to more complex perceptually-based measures. This paper presents a survey on existing percept...

  16. Geometric Layout Based Graphical Model for Multi-Part Object Tracking

    OpenAIRE

    Badrinarayanan, Vijay; Le Clerc, Francois; Oisel, Lionel; Perez, Patrick

    2008-01-01

    This work puts forth a probabilistic graphical framework to track unoccluded objects undergoing large out of image plane rotations and/or presenting large scale variations in video sequences. The proposed scheme incorporates measurements from an ensemble of local patch trackers and inter-patch geometric layout to arrive at a sample based approximation of the state posterior. Following this, the geometric layout is updated online using the Iterative Conditional Estimation technique. These step...

  17. Environmental perceptions and objective walking trail audits inform a community-based participatory research walking intervention

    OpenAIRE

    Zoellner Jamie; Hill Jennie L; Zynda Karen; Sample Alicia D; Yadrick Kathleen

    2012-01-01

    Abstract Background Given the documented physical activity disparities that exist among low-income minority communities and the increased focused on socio-ecological approaches to address physical inactivity, efforts aimed at understanding the built environment to support physical activity are needed. This community-based participatory research (CBPR) project investigates walking trails perceptions in a high minority southern community and objectively examines walking trails. The primary aim ...

  18. Bootstrapping a Compiler for an Equation-Based Object-Oriented Language

    OpenAIRE

    Sjölund, Martin; Fritzson, Peter; Pop, Adrian

    2014-01-01

    What does it mean to bootstrap a compiler, and why do it? This paper reports on the first bootstrapping of a full-scale EOO (Equation-based Object-Oriented) modeling language such as Modelica. Bootstrapping means that the compiler of a language can compile itself. However, the usual application area for the Modelica is modeling and simulation of complex physical systems. Fortunately it turns out that with some minor extensions, the Modelica language is well suited for the modeling of language...

  19. Manipulating Deformable Linear Objects: Characteristic Features for Vision-Based Detection of Contact State Transitions

    OpenAIRE

    Acker, Jürgen; Henrich, Dominik

    2003-01-01

    This paper deals with the handling of deformable linear objects (DLOs), such as hoses, wires, or leaf springs. It investigates usable features for the vision-based detection of a changing contact situation between a DLO and a rigid polyhedral obstacle and a classification of such contact state transitions. The result is a complete classification of contact state transitions and of the most significant features for each class. This knowledge enables reliable detection of changes in the DLO con...

  20. Microlensing-Based Estimate of the Mass Fraction in Compact Objects in Lens

    OpenAIRE

    Mediavilla, E.; Munoz, J. A.; Falco, E.; Motta, V.; Guerras, E.; Canovas, H.; Jean, C.; Oscoz, A.; Mosquera, A. M.

    2009-01-01

    We estimate the fraction of mass that is composed of compact objects in gravitational lens galaxies. This study is based on microlensing measurements (obtained from the literature) of a sample of 29 quasar image pairs seen through 20 lens galaxies. We determine the baseline for no microlensing magnification between two images from the ratios of emission line fluxes. Relative to this baseline, the ratio between the continua of the two images gives the difference in microlensi...

  1. Object-Based Classification of Urban Areas Using VHR Imagery and Height Points Ancillary Data

    Directory of Open Access Journals (Sweden)

    Vivek Dey

    2012-08-01

    Full Text Available Land cover classification of very high resolution (VHR imagery over urban areas is an extremely challenging task. Impervious land covers such as buildings, roads, and parking lots are spectrally too similar to be separated using only the spectral information of VHR imagery. Additional information, therefore, is required for separating such land covers by the classifier. One source of additional information is the vector data, which are available in archives for many urban areas. Further, the object-based approach provides a more effective way to incorporate vector data into the classification process as the misregistration between different layers is less problematic in object-based compared to pixel-based image analysis. In this research, a hierarchical rule-based object-based classification framework was developed based on a small subset of QuickBird (QB imagery coupled with a layer of height points called Spot Height (SH to classify a complex urban environment. In the rule-set, different spectral, morphological, contextual, class-related, and thematic layer features were employed. To assess the general applicability of the rule-set, the same classification framework and a similar one using slightly different thresholds applied to larger subsets of QB and IKONOS (IK, respectively. Results show an overall accuracy of 92% and 86% and a Kappa coefficient of 0.88 and 0.80 for the QB and IK Test image, respectively. The average producers’ accuracies for impervious land cover types were also 82% and 74.5% for QB and IK.

  2. Pixel-based and object-oriented change detection analysis using high-resolution imagery

    International Nuclear Information System (INIS)

    The high spatial resolution of state-of-the-art commercial satellite imagery provides a good basis for recognising and monitoring even small-scale structural changes within nuclear facilities and for planning of routine and/or challenge inspections of nuclear sites. Despite the advantages of the improved spatial resolution some problems exist that may make the interpretation of the changes more difficult: Firstly, the results of the change analysis can be very complex and unclear at a glance. Secondly, shadow formation and off-nadir images due to different sensor and solar conditions at the acquisition times can cause false signals or overlap real changes. In view to the fast-growing amount of data from different sensor types there are then some requirements of an effective change detection procedure for safeguards purposes: i. The techniques involved should possess a certain amount of robustness in terms of small misregistration errors, different atmospheric conditions at the acquiring dates, off-nadir angles. ii. Given large multisensor data sets it would be necessary that the procedure operates as automatically as possible. Iii. The procedure has to imply techniques to initially pinpoint out those parts of a scene in which significant changes have taken place. iv. All image areas indicating changes then should be subject to a detailed classification and interpretation procedure. We have already investigated some pixel-based change detection for the routine nuclear change detection for the routine nuclear verification, based on recently published visualisation and change detection algorithms: canonical correlation analysis (MAD transformation) to enhance the change information in the difference images and bayesian techniques for the automatic determination of significant thresholds. Some steps have been taken by combining pixel- and object-oriented approaches, i.e. MAD transformation of the image data and object- oriented post-classification of the changes and object extraction for the image data or MAD transformation of the objects and post-classification of the change objects. Another approach implies a solely object-oriented change detection technique: Object extraction, semantic classification and post- classification comparison by means of a change matrix. The object-oriented change analysis procedures are carried out with a relatively new technology for image analysis, eCognition (http://www.definiens-imaging.com)

  3. An object-based approach to weather analysis and its applications

    Science.gov (United States)

    Troemel, Silke; Diederich, Malte; Horvath, Akos; Simmer, Clemens; Kumjian, Matthew

    2013-04-01

    The research group 'Object-based Analysis and SEamless prediction' (OASE) within the Hans Ertel Centre for Weather Research programme (HErZ) pursues an object-based approach to weather analysis. The object-based tracking approach adopts the Lagrange perspective by identifying and following the development of convective events over the course of their lifetime. Prerequisites of the object-based analysis are a high-resolved observational data base and a tracking algorithm. A near real-time radar and satellite remote sensing-driven 3D observation-microphysics composite covering Germany, currently under development, contains gridded observations and estimated microphysical quantities. A 3D scale-space tracking identifies convective rain events in the dual-composite and monitors the development over the course of their lifetime. The OASE-group exploits the object-based approach in several fields of application: (1) For a better understanding and analysis of precipitation processes responsible for extreme weather events, (2) in nowcasting, (3) as a novel approach for validation of meso-? atmospheric models, and (4) in data assimilation. Results from the different fields of application will be presented. The basic idea of the object-based approach is to identify a small set of radar- and satellite derived descriptors which characterize the temporal development of precipitation systems which constitute the objects. So-called proxies of the precipitation process are e.g. the temporal change of the brightband, vertically extensive columns of enhanced differential reflectivity ZDR or the cloud top temperature and heights identified in the 4D field of ground-based radar reflectivities and satellite retrievals generated by a cell during its life time. They quantify (micro-) physical differences among rain events and relate to the precipitation yield. Analyses on the informative content of ZDR columns as precursor for storm evolution for example will be presented to demonstrate the use of such system-oriented predictors for nowcasting. Columns of differential reflectivity ZDR measured by polarimetric weather radars are prominent signatures associated with thunderstorm updrafts. Since greater vertical velocities can loft larger drops and water-coated ice particles to higher altitudes above the environmental freezing level, the integrated ZDR column above the freezing level increases with increasing updraft intensity. Validation of atmospheric models concerning precipitation representation or prediction is usually confined to comparisons of precipitation fields or their temporal and spatial statistics. A comparison of the rain rates alone, however, does not immediately explain discrepancies between models and observations, because similar rain rates might be produced by different processes. Within the event-based approach for validation of models both observed and modeled rain events are analyzed by means of proxies of the precipitation process. Both sets of descriptors represent the basis for model validation since different leading descriptors - in a statistical sense- hint at process formulations potentially responsible for model failures.

  4. Glandular object based tumor morphometry in H&E biopsy samples for prostate cancer prognosis

    Science.gov (United States)

    Fogarasi, Stephen I.; Khan, Faisal M.; Pang, Ho-Yuen H.; Mesa-Tejada, Ricardo; Donovan, Michael J.; Fernandez, Gerardo

    2011-03-01

    Morphological and architectural characteristics of primary prostate tissue compartments, such as epithelial nuclei (EN) and cytoplasm, provide critical information for cancer diagnosis, prognosis and therapeutic response prediction. The subjective and variable Gleason grade assessed by expert pathologists in Hematoxylin and Eosin (H&E) stained specimens has been the standard for prostate cancer diagnosis and prognosis. We propose a novel morphometric, glandular object-oriented image analysis approach for the robust quantification of H&E prostate biopsy images. We demonstrate the utility of features extracted through the proposed method in predicting disease progression post treatment in a multi-institution cohort of 1027 patients. The biopsy based features were univariately predictive for clinical response post therapy; with concordance indexes (CI) = 0.6. In multivariate analysis, a glandular object feature quantifying tumor epithelial cells not directly associated with an intact tumor gland was selected in a model incorporating preoperative clinical data, protein biomarker and morphological imaging features. The model achieved a CI of 0.73 in validation, which was significantly higher than a CI of 0.69 for the standard multivariate model based solely on clinical features currently used in clinical practice. This work presents one of the first demonstrations of glandular object based morphological features in the H&E stained biopsy specimen to predict disease progression post primary treatment. Additionally, it is the largest scale study of the efficacy and robustness of the proposed features in prostate cancer prognosis.

  5. A preference-based multi-objective model for the optimization of best management practices

    Science.gov (United States)

    Chen, Lei; Qiu, Jiali; Wei, Guoyuan; Shen, Zhenyao

    2015-01-01

    The optimization of best management practices (BMPs) at the watershed scale is notably complex because of the social nature of decision process, which incorporates information that reflects the preferences of decision makers. In this study, a preference-based multi-objective model was designed by modifying the commonly-used Non-dominated Sorting Genetic Algorithm (NSGA-II). The reference points, achievement scalarizing functions and an indicator-based optimization principle were integrated for searching a set of preferred Pareto-optimality solutions. Pareto preference ordering was also used for reducing objective numbers in the final decision-making process. This proposed model was then tested in a typical watershed in the Three Gorges Region, China. The results indicated that more desirable solutions were generated, which reduced the burden of decision effort of watershed managers. Compare to traditional Genetic Algorithm (GA), those preferred solutions were concentrated in a narrow region close to the projection point instead of the entire Pareto-front. Based on Pareto preference ordering, the solutions with the best objective function values were often the more desirable solutions (i.e., the minimum cost solution and the minimum pollutant load solution). In the authors' view, this new model provides a useful tool for optimizing BMPs at watershed scale and is therefore of great benefit to watershed managers.

  6. Object-Based Image Classification of Summer Crops with Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    José M. Peña

    2014-05-01

    Full Text Available The strategic management of agricultural lands involves crop field monitoring each year. Crop discrimination via remote sensing is a complex task, especially if different crops have a similar spectral response and cropping pattern. In such cases, crop identification could be improved by combining object-based image analysis and advanced machine learning methods. In this investigation, we evaluated the C4.5 decision tree, logistic regression (LR, support vector machine (SVM and multilayer perceptron (MLP neural network methods, both as single classifiers and combined in a hierarchical classification, for the mapping of nine major summer crops (both woody and herbaceous from ASTER satellite images captured in two different dates. Each method was built with different combinations of spectral and textural features obtained after the segmentation of the remote images in an object-based framework. As single classifiers, MLP and SVM obtained maximum overall accuracy of 88%, slightly higher than LR (86% and notably higher than C4.5 (79%. The SVM+SVM classifier (best method improved these results to 89%. In most cases, the hierarchical classifiers considerably increased the accuracy of the most poorly classified class (minimum sensitivity. The SVM+SVM method offered a significant improvement in classification accuracy for all of the studied crops compared to the conventional decision tree classifier, ranging between 4% for safflower and 29% for corn, which suggests the application of object-based image analysis and advanced machine learning methods in complex crop classification tasks.

  7. Fuzzy Concurrent Object Oriented Expert System for Fault Diagnosis in 8085 Microprocessor Based System Board

    Directory of Open Access Journals (Sweden)

    Mr.D. V. Kodavade

    2014-09-01

    Full Text Available With the acceptance of artificial intelligence paradigm, a number of successful artificial intelligence systems were created. Fault diagnosis in microprocessor based boards needs lot of empirical knowledge and expertise and is a true artificial intelligence problem. Research on fault diagnosis in microprocessor based system boards using new fuzzy-object oriented approach is presented in this paper. There are many uncertain situations observed during fault diagnosis. These uncertain situations were handled using fuzzy mathematics properties. Fuzzy inference mechanism is demonstrated using one case study. Some typical faults in 8085 microprocessor board and diagnostic procedures used is presented in this paper.

  8. A Novel Objective Image Quality Metric for Image Fusion Based on Renyi Entropy

    Directory of Open Access Journals (Sweden)

    Youzhi Zheng

    2008-01-01

    Full Text Available In this study, a novel objective image quality metric is proposed. The proposed metric can be used for image fusion evaluation without a reference image. The proposed metric is an extension of Mutual Information (MI metric based on Renyi entropy which is a single parameter generalization of Shannon entropy. Renyi MI measures the total amount of information that fused image contains about source images. Also, the overlapping information problem is considered by using Generalized Normalized MI to avoid its influence. Experimental results show that the presented metric well correlated with human subjective evaluations and it is much better than conventional MI metrics based on Shannon entropy and Tsallis entropy.

  9. Object-based delineation of homogeneous landscape units at regional scale based on MODIS time series

    Science.gov (United States)

    Bisquert, Mar; Bégué, Agnès; Deshayes, Michel

    2015-05-01

    Landscapes can be described by seasonal and spatial patterns linked to vegetation type and phenology, environmental conditions, and human activities. The objective of this work is to propose and test an approach for delineating homogeneous landscape units at a regional scale by using only Earth observation data. We used MODIS (Moderate Imaging Spectroradiometer) images from 2007 to 2011, acquired over the whole continental French territory at 250 m spatial resolution. The data set includes time series of the Enhanced Vegetation Index (EVI) and time series of five Haralick texture indices. A principal components analysis (PCA) allowed us to choose the most representative indices (spectral and textural) and dates to be used in the region-growing segmentation. Different combinations of input data, as well as different segmentation parameters, were tested and compared using unsupervised evaluation methods. These methods were used to analyze the radiometric homogeneity of the regions and the radiometric disparity between regions when changing the homogeneity criterion of the segmentation. The best segmentation results obtained included three EVI images, together with three images of the texture 2nd moment, corresponding to the average of the months of April, July and December from 2007 to 2011. The optimum homogeneity criterion for the region-growing segmentation using this combination of variables was 15. We believe this method is applicable at other scales and other data sets for vegetation and biodiversity studies, and for habitat mapping.

  10. Multimodal saliency-based attention for object-based scene analysis

    OpenAIRE

    Schauerte, B.; Ku?hn, Benjamin; Kroschel, Kristian; Stiefelhagen, Rainer

    2011-01-01

    Multimodal attention is a key requirement for humanoid robots in order to navigate in complex environments and act as social, cognitive human partners. To this end, robots have to incorporate attention mechanisms that focus the processing on the potentially most relevant stimuli while controlling the sensor orientation to improve the perception of these stimuli. In this paper, we present our implementation of audio-visual saliency-based attention that we integrated in a system for knowledge-d...

  11. Object-based cropland degradation identification: a case study in Uzbekistan

    Science.gov (United States)

    Dubovyk, Olena; Menz, Gunter; Conrad, Christopher; Khamzina, Asia

    2012-10-01

    Sustainability of irrigated agriculture-based economies, such as in Central Asia, is threatened by cropland degradation. The field-based identification of the degraded agricultural areas can aid in developing appropriate land rehabilitation and monitoring programs. This paper combined the object-based change detection and spectral mixture analysis to develop an approach for identifying parcels of irrigated degraded cropland in Northern Uzbekistan, Central Asia. A linear spectral unmixing, followed by the object-based change vector analysis, was applied to the multiple Landsat TM images, acquired in 1987 and 2009. Considering a spectral dimensionality of Landsat TM, a multiple 4-endmember model (green vegetation, water, dark soil, and bright soil) was set up for the analysis. The spectral unmixing results were valid, as indicated by the overall root mean square errors of <2.5% reflectance for all images. The results of change detection revealed that about 33% (84,540 ha) of cropland in the study area were affected by the degradation processes to varying degrees. Spatial distribution of degraded fields was mainly associated with the abandoned fields and lands with inherently low fertile soils. The proposed approach could be elaborated for a field-based monitoring of cropland degradation in similar landscapes of Central Asia and elsewhere.

  12. Multi-objective optimum design of fast tool servo based on improved differential evolution algorithm

    International Nuclear Information System (INIS)

    The flexure-based mechanism is a promising realization of fast tool servo (FTS), and the optimum determination of flexure hinge parameters is one of the most important elements in the FTS design. This paper presents a multi-objective optimization approach to optimizing the dimension and position parameters of the flexure-based mechanism, which is based on the improved differential evolution algorithm embedding chaos and nonlinear simulated anneal algorithm. The results of optimum design show that the proposed algorithm has excellent performance and a well-balanced compromise is made between two conflicting objectives, the stroke and natural frequency of the FTS mechanism. The validation tests based on finite element analysis (FEA) show good agreement with the results obtained by using the proposed theoretical algorithm of this paper. Finally, a series of experimental tests are conducted to validate the design process and assess the performance of the FTS mechanism. The designed FTS reaches up to a stroke of 10.25 ?m with at least 2 kHz bandwidth. Both of the FEA and experimental results demonstrate that the parameters of the flexure-based mechanism determined by the proposed approaches can achieve the specified performance and the proposed approach is suitable for the optimum design of FTS mechanism and of excellent performances

  13. MULTI OBJECTIVE OPTIMIZATION OF VEHICLE ACTIVE SUSPENSION SYSTEM USING DEBBO BASED PID CONTROLLER

    Directory of Open Access Journals (Sweden)

    Kalaivani Rajagopal

    2014-03-01

    Full Text Available This paper proposes the Multi Objective Optimization (MOO of Vehicle Active Suspension System (VASS with a hybrid Differential Evolution (DE based Biogeography-Based Optimization (BBO (DEBBO for the parameter tuning of Proportional Integral Derivative (PID controller. Initially a conventional PID controller, secondly a BBO, an rising nature enthused global optimization procedure based on the study of the ecological distribution of biological organisms and a hybridized DEBBO algorithm which inherits the behaviours of BBO and DE have been used to find the tuning parameters of the PID controller to improve the performance of VASS by considering a MOO function as the performance index. Simulations of passive system, active system having PID controller with and without optimizations have been performed by considering dual and triple bump kind of road disturbances in MATLAB/Simulink environment. The simulation results show the effectiveness of DEBBO based PID (DEBBOPID in achieving the goal.

  14. Highly accurate moving object detection in variable bit rate video-based traffic monitoring systems.

    Science.gov (United States)

    Huang, Shih-Chia; Chen, Bo-Hao

    2013-12-01

    Automated motion detection, which segments moving objects from video streams, is the key technology of intelligent transportation systems for traffic management. Traffic surveillance systems use video communication over real-world networks with limited bandwidth, which frequently suffers because of either network congestion or unstable bandwidth. Evidence supporting these problems abounds in publications about wireless video communication. Thus, to effectively perform the arduous task of motion detection over a network with unstable bandwidth, a process by which bit-rate is allocated to match the available network bandwidth is necessitated. This process is accomplished by the rate control scheme. This paper presents a new motion detection approach that is based on the cerebellar-model-articulation-controller (CMAC) through artificial neural networks to completely and accurately detect moving objects in both high and low bit-rate video streams. The proposed approach is consisted of a probabilistic background generation (PBG) module and a moving object detection (MOD) module. To ensure that the properties of variable bit-rate video streams are accommodated, the proposed PBG module effectively produces a probabilistic background model through an unsupervised learning process over variable bit-rate video streams. Next, the MOD module, which is based on the CMAC network, completely and accurately detects moving objects in both low and high bit-rate video streams by implementing two procedures: 1) a block selection procedure and 2) an object detection procedure. The detection results show that our proposed approach is capable of performing with higher efficacy when compared with the results produced by other state-of-the-art approaches in variable bit-rate video streams over real-world limited bandwidth networks. Both qualitative and quantitative evaluations support this claim; for instance, the proposed approach achieves Similarity and F1 accuracy rates that are 76.40% and 84.37% higher than those of existing approaches, respectively. PMID:24805212

  15. 6DoF object pose measurement by a monocular manifold-based pattern recognition technique

    International Nuclear Information System (INIS)

    In this paper, a novel solution to the compound problem of object recognition and 3D pose estimation is presented. An accurate measurement of the geometrical configuration of a recognized target, relative to a known coordinate system, is of fundamental importance and constitutes a prerequisite for several applications such as robot grasping or obstacle avoidance. The proposed method lays its foundations on the following assumptions: (a) the same object captured under varying viewpoints and perspectives represents data that could be projected onto a well-established and highly distinguishable subspace; (b) totally different objects observed under the same viewpoints and perspectives share identical 3D pose that can be sufficiently modeled to produce a generalized model. Toward this end, we propose an advanced architecture that allows both recognizing patterns and providing efficient solution for 6DoF pose estimation. We employ a manifold modeling architecture that is grounded on a part-based representation of an object, which in turn, is accomplished via an unsupervised clustering of the extracted visual cues. The main contributions of the proposed framework are: (a) the proposed part-based architecture requires minimum supervision, compared to other contemporary solutions, whilst extracting new features encapsulating both appearance and geometrical attributes of the objects; (b) contrary to related projects that extract high-dimensional data, thus, increasing the complexity of the system, the proposed manifold modeling approach makes use of low dimensionality input vectors; (c) the formulation of a novel input–output space mapping that outperforms the existing dimensionality reduction schemes. Experimental results justify our theoretical claims and demonstrate the superiority of our method comparing to other related contemporary projects. (paper)

  16. Object-based class modelling for multi-scale riparian forest habitat mapping

    Science.gov (United States)

    Strasser, Thomas; Lang, Stefan

    2015-05-01

    Object-based class modelling allows for mapping complex, hierarchical habitat systems. The riparian zone, including forests, represents such a complex ecosystem. Forests within riparian zones are biologically high productive and characterized by a rich biodiversity; thus considered of high community interest with an imperative to be protected and regularly monitored. Satellite earth observation (EO) provides tools for capturing the current state of forest habitats such as forest composition including intermixture of non-native tree species. Here we present a semi-automated object based image analysis (OBIA) approach for the mapping of riparian forests by applying class modelling of habitats based on the European Nature Information System (EUNIS) habitat classifications and the European Habitats Directive (HabDir) Annex 1. A very high resolution (VHR) WorldView-2 satellite image provided the required spatial and spectral details for a multi-scale image segmentation and rule-base composition to generate a six-level hierarchical representation of riparian forest habitats. Thereby habitats were hierarchically represented within an image object hierarchy as forest stands, stands of homogenous tree species and single trees represented by sunlit tree crowns. 522 EUNIS level 3 (EUNIS-3) habitat patches with a mean patch size (MPS) of 12,349.64 m2 were modelled from 938 forest stand patches (MPS = 6868.20 m2) and 43,742 tree stand patches (MPS = 140.79 m2). The delineation quality of the modelled EUNIS-3 habitats (focal level) was quantitatively assessed to an expert-based visual interpretation showing a mean deviation of 11.71%.

  17. Line-Based Object Recognition using Hausdorff Distance: From Range Images to Molecular Secondary Structure

    International Nuclear Information System (INIS)

    Object recognition algorithms are fundamental tools in automatic matching of geometric shapes within a background scene. Many approaches have been proposed in the past to solve the object recognition problem. Two of the key aspects that distinguish them in terms of their practical usability are: (i) the type of input model description and (ii) the comparison criteria used. In this paper we introduce a novel scheme for 3D object recognition based on line segment representation of the input shapes and comparison using the Hausdor distance. This choice of model representation provides the flexibility to apply the scheme in different application areas. We define several variants of the Hausdor distance to compare the models within the framework of well defined metric spaces. We present a matching algorithm that efficiently finds a pattern in a 3D scene. The algorithm approximates a minimization procedure of the Hausdor distance. The output error due to the approximation is guaranteed to be within a known constant bound. Practical results are presented for two classes of objects: (i) polyhedral shapes extracted from segmented range images and (ii) secondary structures of large molecules. In both cases the use of our approximate algorithm allows to match correctly the pattern in the background while achieving the efficiency necessary for practical use of the scheme. In particular the performance is improved substantially with minor degradation of the quality of the matchingdegradation of the quality of the matching

  18. Thermoeconomic multi-objective optimization of a novel biomass-based integrated energy system

    International Nuclear Information System (INIS)

    Both thermoeconomic modeling and multi-objective optimization studies are undertaken for a novel integrated multigeneration system, containing a biomass combustor, an organic Rankine cycle to produce electricity, a double-effect absorption chiller for cooling, a heat exchanger, a proton exchange membrane electrolyzer to produce hydrogen, a domestic water heater to produce hot water and a reverse osmosis desalination unit to produce fresh water. Energy and exergy analyses and an environmental impact assessment are included. A multi-objective optimization method based on a fast and elitist NSGA-II (non-dominated sorting genetic algorithm) is developed and employed to determine the best design parameters for the system. The two objective functions utilized in the optimization study are the total cost rate of the system, which is the cost associated with fuel, component purchasing and environmental impact, and the system exergy efficiency. The total cost rate of the system is minimized while the cycle exergy efficiency is maximized using an evolutionary algorithm. To provide insight, the Pareto frontier is shown for a multi-objective optimization. In addition, a closed form equation for the relationship between exergy efficiency and total cost rate is derived. A sensitivity analysis is performed to assess the effects of several design parameters on the system total exergy destruction rate, CO2 emission and exergy efficiency

  19. Objective Functions for Information-Content-Based Optimal Monitoring Network Design

    Science.gov (United States)

    Weijs, S. V.; Huwald, H.; Parlange, M. B.

    2013-12-01

    Information theory has the potential to provide a common language for the quantification of uncertainty and its reduction by choosing optimally informative monitoring network layout. Numerous different objectives based on information measures have been proposed in recent literature, often focusing simultaneously on maximum information and minimum dependence between the chosen locations for data collection. We discuss these objective functions and conclude that a single objective optimization of joint entropy suffices to maximize the collection of information. Minimum dependence is a secondary objective that automatically follows from the first, but has no intrinsic justification. Furthermore it is demonstrated how the curse of dimensionality complicates the determination of information content for time series. In many cases found in the monitoring network literature, discrete multivariate joint distributions are estimated from relatively little data, leading to the occurrence of spurious dependencies in data, which change interpretations of previously published results. Aforementioned numerical challenges stem from inherent difficulties and subjectivity in determining information content. From information-theoretical logic it is clear that the information content of data depends on the state of knowledge prior to obtaining them. Less assumptions in formulating this state of knowledge leads to higher data requirements in formulating it. We further clarify the role of prior information in information content by drawing an analogy with data compression.

  20. Development of a flexure-based, force-sensing microgripper for micro-object manipulation

    International Nuclear Information System (INIS)

    This paper presents the design and development of a flexure-based microgripper, accompanied with a real-time, vision-based force sensing system to handle objects of various sizes ranging from 100 µm to 1 mm. A simulation-based design methodology is adopted to develop an initial microgripper design, which is then optimized using theoretical modeling. The final prototype developed generated a large stroke length of over 500 µm with high-deflection magnification (ratio of the end deflection (output) to the input deflection) of 3.52. A spring system has been incorporated into the microgripper for easy measurement and control of the gripping forces. The web-camera-based visual system enables real-time force measurement with a resolution of 2.37 mN and can be operated in both manual and automatic modes to control the applied forces. The system has successfully demonstrated gripping of a variety of micro-objects including a 100 µm human hair and a 1 mm steel rod with forces as small as 43 mN and 159 mN, respectively

  1. Remote Sensing in Mapping Mangrove Ecosystems — An Object-Based Approach

    Directory of Open Access Journals (Sweden)

    Quoc Tuan Vo

    2013-01-01

    Full Text Available Over the past few decades, clearing for shrimp farming has caused severe losses of mangroves in the Mekong Delta (MD of Vietnam. Although the increasing importance of shrimp aquaculture in Vietnam has brought significant financial benefits to the local communities, the rapid and largely uncontrolled increase in aquacultural area has contributed to a considerable loss of mangrove forests and to environmental degradation. Although different approaches have been used for mangrove classification, no approach to date has addressed the challenges of the special conditions that can be found in the aquaculture-mangrove system in the Ca Mau province of the MD. This paper presents an object-based classification approach for estimating the percentage of mangroves in mixed mangrove-aquaculture farming systems to assist the government to monitor the extent of the shrimp farming area. The method comprises multi-resolution segmentation and classification of SPOT5 data using a decision tree approach as well as local knowledge from the region of interest. The results show accuracies higher than 75% for certain classes at the object level. Furthermore, we successfully detect areas with mixed aquaculture-mangrove land cover with high accuracies. Based on these results, mangrove development, especially within shrimp farming-mangrove systems, can be monitored. However, the mangrove forest cover fraction per object is affected by image segmentation and thus does not always correspond to the real farm boundaries. It remains a serious challenge, then, to accurately map mangrove forest cover within mixed systems.

  2. Remote sensing and object-based techniques for mapping fine-scale industrial disturbances

    Science.gov (United States)

    Powers, Ryan P.; Hermosilla, Txomin; Coops, Nicholas C.; Chen, Gang

    2015-02-01

    Remote sensing provides an important data source for the detection and monitoring of disturbances; however, using this data to recognize fine-spatial resolution industrial disturbances dispersed across extensive areas presents unique challenges (e.g., accurate delineation and identification) and deserves further investigation. In this study, we present and assess a geographic object-based image analysis (GEOBIA) approach with high-spatial resolution imagery (SPOT 5) to map industrial disturbances using the oil sands region of Alberta's northeastern boreal forest as a case study. Key components of this study were (i) the development of additional spectral, texture, and geometrical descriptors for characterizing image-objects (groups of alike pixels) and their contextual properties, and (ii) the introduction of decision trees with boosting to perform the object-based land cover classification. Results indicate that the approach achieved an overall accuracy of 88%, and that all descriptor groups provided relevant information for the classification. Despite challenges remaining (e.g., distinguishing between spectrally similar classes, or placing discrete boundaries), the approach was able to effectively delineate and classify fine-spatial resolution industrial disturbances.

  3. Object-Based Analysis of Aerial Photogrammetric Point Cloud and Spectral Data for Land Cover Mapping

    Science.gov (United States)

    Debella-Gilo, M.; Bjørkelo, K.; Breidenbach, J.; Rahlf, J.

    2013-04-01

    The acquisition of 3D point data with the use of both aerial laser scanning (ALS) and matching of aerial stereo images coupled with advances in image processing algorithms in the past years provide opportunities to map land cover types with better precision than before. The present study applies Object-Based Image Analysis (OBIA) to 3D point cloud data obtained from matching of stereo aerial images together with spectral data to map land cover types of the Nord-Trøndelag county of Norway. The multi-resolution segmentation algorithm of the Definiens eCognition™ software is used to segment the scenes into homogenous objects. The objects are then classified into different land cover types using rules created based on the definitions given for each land cover type by the Norwegian Forest and Landscape Institute. The quality of the land cover map was evaluated using data collected in the field as part of the Norwegian National Forest Inventory. The results show that the classification has an overall accuracy of about 80% and a kappa index of about 0.65. OBIA is found to be a suitable method for utilizing 3D remote sensing data for land cover mapping in an effort to replace manual delineation methods.

  4. Multi-objective scheduling in an agent based Holonic manufacturing system

    Directory of Open Access Journals (Sweden)

    T. K. Jana

    2014-01-01

    Full Text Available The present paper is aimed at multi-objective scheduling in an agent based holonic manufacturing system to satisfy the goal of several communities namely the product, the resource, and the organization simultaneously. In this attempt, first a multi criteria based priority rule is developed following Simple Additive Weight (SAW method under Multi Criteria Decision Making (MCDM environment to rank the products. Accordingly, the products are allowed to select a particular resource for execution by negotiation considering minimum time as criterion. The interests of different communities are accomplished by allocating the ordered rank of products to the ordered rank of resources. Conflict, if arises between products and resources, are resolved by introducing the concept of Early Finish Time (EFT as criterion for task allocation. A scheduling algorithm is proposed for execution of the rule. In view of machine failure, a cooperation strategy is evolved that also optimizes reallocation of the incomplete task. It is concluded that the proposed scheduling algorithm together with the disturbance handling algorithm are poised to satisfy the agent’s local objective as well as organization’s global objective concurrently and are commensurable with multi agent paradigm.

  5. Simulated Prosthetic Vision: The Benefits of Computer-Based Object Recognition and Localization.

    Science.gov (United States)

    Macé, Marc J-M; Guivarch, Valérian; Denis, Grégoire; Jouffrais, Christophe

    2015-07-01

    Clinical trials with blind patients implanted with a visual neuroprosthesis showed that even the simplest tasks were difficult to perform with the limited vision restored with current implants. Simulated prosthetic vision (SPV) is a powerful tool to investigate the putative functions of the upcoming generations of visual neuroprostheses. Recent studies based on SPV showed that several generations of implants will be required before usable vision is restored. However, none of these studies relied on advanced image processing. High-level image processing could significantly reduce the amount of information required to perform visual tasks and help restore visuomotor behaviors, even with current low-resolution implants. In this study, we simulated a prosthetic vision device based on object localization in the scene. We evaluated the usability of this device for object recognition, localization, and reaching. We showed that a very low number of electrodes (e.g., nine) are sufficient to restore visually guided reaching movements with fair timing (10?s) and high accuracy. In addition, performance, both in terms of accuracy and speed, was comparable with 9 and 100 electrodes. Extraction of high level information (object recognition and localization) from video images could drastically enhance the usability of current visual neuroprosthesis. We suggest that this method-that is, localization of targets of interest in the scene-may restore various visuomotor behaviors. This method could prove functional on current low-resolution implants. The main limitation resides in the reliability of the vision algorithms, which are improving rapidly. PMID:25900238

  6. Building and Programming a Smart Robotic System for Distinguishing Objects Based on their Shape and Colour

    Directory of Open Access Journals (Sweden)

    Sharari T. M.

    2015-03-01

    Full Text Available This paper presents a robotic system designed for holding and placing objects based on their colour and shape. The presented robot is given a complete set of instructions of positions and orientation angles for each manipulation motion. The main feature in this paper is that the developed robot used a combination of vision and motion systems for holding and placing the work-objects, mounted on the flat work-plane, based on their shapes and colors. This combination improves the flexibility of manipulation which may help eliminate the use of some expensive manipulation tasks in a variety of industrial applications. The robotic system presented in this paper is designed as an educational robot that possesses the ability for holding-and-placing operations with limited load. To process the various instructions for holding and placing the work objects, a main control unit - Manipulation Control Unit (MCU is used as well as a slave unit that performed the actual instructions from the MCU.

  7. Object composition

    OpenAIRE

    Bono, Viviana; Bettini, Lorenzo

    2010-01-01

    an extension of Java with incomplete objects. This extension is based on the definition of specific annotations (thus the Java grammar is not extended). It provides a preprocessor that, given a program that uses our special annotations (for incomplete classes) and generates standard Java classes. Incomplete Objects The programmer, besides standard classes, can define incomplete classes whose instances are incomplete objects that can be composed in an object-based fashion. Hence, in our langua...

  8. Optimization and Reconfiguration of Advanced Manufacturing Mode Based on Object-Based Knowledge Mesh and Improved Immune Genetic Algorithm

    Science.gov (United States)

    Xue, Chaogai; Cao, Haiwang

    This paper deals with an approach to the optimization and reconfiguration of advanced manufacturing mode based on the object-based knowledge mesh (OKM) and improved immune genetic algorithm (IGA). To explore the optimization and reconfiguration of the new OKM by the user's function requirements, an optimization procedure of an OKM aiming at the user's maximum function-satisfaction is proposed. Firstly, based on the definitions of the fuzzy function-satisfaction degree relationships of the users' requirements for the OKM functions and the multiple fuzzy function-satisfaction degrees of the relationships, the optimization model of the OKM multiple set operation expression is constructed. And the OKM multiple set operation expression is optimized by the immune genetic algorithm, with the steps of the OKM optimization presented in detail as well. Based upon the above, the optimization and reconfiguration of an advanced manufacturing mode are illustrated by an actual OKM example. The proposed approach proves to be very effective.

  9. Multi-equipment condition based maintenance optimization by multi- objective genetic algorithm

    Directory of Open Access Journals (Sweden)

    Š. Val?uha

    2011-04-01

    Full Text Available Purpose: This paper deals with the optimization of the condition based maintenance (CBM applied on manufacturing multi-equipment system under cost and benefit criteria.Design/methodology/approach: The system is modeled using Discrete Event Simulation (DES and optimized by means of the application of a Multi-Objective Evolutionary Algorithm (MOEA.Findings: Solution for the joint optimization of the condition based maintenance model applied on several equipment has been obtained.Research limitations/implications: The developed approach has been successfully applied to the optimization of condition based maintenance activities of a hubcap production system composed by three plastic injection machines and a painting station, for management decision support.Originality/value: This paper provides a solution for the joint optimization of CBM strategies applied on several equipments

  10. Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

    Directory of Open Access Journals (Sweden)

    Ming Xue

    2014-02-01

    Full Text Available To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a multiple linear classifier group based on a K-combined voting (KCV function is proposed. As the dictionary evolves, the models are also trained to timely adapt the target appearance variation. Qualitative and quantitative evaluations on challenging image sequences compared with state-of-the-art algorithms demonstrate that the proposed tracking algorithm achieves a more favorable performance. We also illustrate its relay application in visual sensor networks.

  11. A Software Designed For STP Data Plot and Analysis Based on Object-oriented Methodology

    Science.gov (United States)

    Lina, L.; Murata, K.

    2006-12-01

    In the present study, we design a system that is named "STARS (Solar-Terrestrial data Analysis and Reference System)". The STARS provides a research environment that researchers can refer to and analyse a variety of data with single software. This software design is based on the OMT (Object Modeling Technique). The OMT is one of the object-oriented techniques, which has an advantage in maintenance improvement, reuse and long time development of a system. At the Center for Information Technology, Ehime University, after our designing of the STARS, we have already started implementing the STARS. The latest version of the STARS, the STARS5, was released in 2006. Any user can download the system from our WWW site (http:// www.infonet.cite.ehime-u.ac.jp/STARS). The present paper is mainly devoted to the design of a data analysis software system. Through our designing, we paid attention so that the design is flexible and applicable when other developers design software for the similar purpose. If our model is so particular only for our own purpose, it would be useless for other developers. Through our design of the domain object model, we carefully removed the parts, which depend on the system resources, e.g. hardware and software. We put the dependent parts into the application object model. In the present design, therefore, the domain object model and the utility object model are independent of computer resource. This helps anther developer to construct his/her own system based the present design. They simply modify their own application object models according to their system resource. This division of the design between dependent and independent part into three object models is one of the advantages in the OMT. If the design of software is completely done along with the OMT, implementation is rather simple and automatic: developers simply map their designs on our programs. If one creates "ganother STARS" with other programming language such as Java, the programmer simply follows the present system as long as the language is object-oriented language. Researchers would want to add their data into the STARS. In this case, they simply add their own data class in the domain object model. It is because any satellite data has properties such as time or date, which are inherited from the upper class. In this way, their effort is less than in other old methodologies. In the OMT, description format of the system is rather strictly standardized. When new developers take part in STARS project, they have only to understand each model to obtain the overview of the STARS. Then they follow this designs and documents to implement the system. The OMT makes a new comer easy to join into the project already running.

  12. Monitoring Post Disturbance Forest Regeneration with Hierarchical Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    L. Monika Moskal

    2013-10-01

    Full Text Available The main goal of this exploratory project was to quantify seedling density in post fire regeneration sites, with the following objectives: to evaluate the application of second order image texture (SOIT in image segmentation, and to apply the object-based image analysis (OBIA approach to develop a hierarchical classification. With the utilization of image texture we successfully developed a methodology to classify hyperspatial (high-spatial imagery to fine detail level of tree crowns, shadows and understory, while still allowing discrimination between density classes and mature forest versus burn classes. At the most detailed hierarchical Level I classification accuracies reached 78.8%, a Level II stand density classification produced accuracies of 89.1% and the same accuracy was achieved by the coarse general classification at Level III. Our interpretation of these results suggests hyperspatial imagery can be applied to post-fire forest density and regeneration mapping.

  13. Extracting Objects and Events from MPEG Videos for Highlight-based Indexing and Retrieval

    Directory of Open Access Journals (Sweden)

    Jinchang Ren

    2010-04-01

    Full Text Available Automatic recognition of highlights from videos is a fundamental and challenging problem for content-based indexing and retrieval applications. In this paper, we propose techniques to solve this problem using knowledge supported extraction of semantics, and compressed-domain processing is employed for efficiency. Firstly, knowledgebased rules are utilized for shot detection on extracted DCimages, and statistical skin detection is applied for human object detection. Secondly, through filtering outliers in motion vectors, improved detection of camera motions like zooming, panning and tilting are achieved. Video highlight high-level semantics are then automatically extracted via low-level analysis in the detection of human objects and camera motion events, and finally these highlights are taken for shot-level annotation, indexing and retrieval. Results using a large test video data set have demonstrated the accuracy and robustness of the proposed techniques.

  14. ROCIT : a visual object recognition algorithm based on a rank-order coding scheme.

    Energy Technology Data Exchange (ETDEWEB)

    Gonzales, Antonio Ignacio; Reeves, Paul C.; Jones, John J.; Farkas, Benjamin D.

    2004-06-01

    This document describes ROCIT, a neural-inspired object recognition algorithm based on a rank-order coding scheme that uses a light-weight neuron model. ROCIT coarsely simulates a subset of the human ventral visual stream from the retina through the inferior temporal cortex. It was designed to provide an extensible baseline from which to improve the fidelity of the ventral stream model and explore the engineering potential of rank order coding with respect to object recognition. This report describes the baseline algorithm, the model's neural network architecture, the theoretical basis for the approach, and reviews the history of similar implementations. Illustrative results are used to clarify algorithm details. A formal benchmark to the 1998 FERET fafc test shows above average performance, which is encouraging. The report concludes with a brief review of potential algorithmic extensions for obtaining scale and rotational invariance.

  15. Automatic textual annotation of video news based on semantic visual object extraction

    Science.gov (United States)

    Boujemaa, Nozha; Fleuret, Francois; Gouet, Valerie; Sahbi, Hichem

    2003-12-01

    In this paper, we present our work for automatic generation of textual metadata based on visual content analysis of video news. We present two methods for semantic object detection and recognition from a cross modal image-text thesaurus. These thesaurus represent a supervised association between models and semantic labels. This paper is concerned with two semantic objects: faces and Tv logos. In the first part, we present our work for efficient face detection and recogniton with automatic name generation. This method allows us also to suggest the textual annotation of shots close-up estimation. On the other hand, we were interested to automatically detect and recognize different Tv logos present on incoming different news from different Tv Channels. This work was done jointly with the French Tv Channel TF1 within the "MediaWorks" project that consists on an hybrid text-image indexing and retrieval plateform for video news.

  16. A Moving Objects Detection Algorithm Based on Three-Frame Difference and Sparse Optical Flow

    Directory of Open Access Journals (Sweden)

    Guo-Wu Yuan

    2014-01-01

    Full Text Available Moving objects detection is an important research of computer vision. Optical flow method is a main way, but it is limited to use because of its complexity. A moving objects detection algorithm based on three-frame difference and optical flow is proposed. The calculation of optical flow is simplified. Harris corners are detected and then only the corners are selected to compute optical flow information, which reduce the algorithm’s complexity. Because the detected moving target area is not complete, three-frame difference method is introduced as a supplement. The experimental results show that the algorithm can achieve real-time and has better results than anyone of these two separate algorithms.

  17. Evolutionary Algorithm based on simulated annealing for the multi-objective optimization of combinatorial problems

    Directory of Open Access Journals (Sweden)

    Elias David Nino Ruiz

    2013-05-01

    Full Text Available This paper states a novel hybrid-metaheuristic based on the Theory of Deterministic Swapping, Theory of Evolution and Simulated Annealing Metaheuristic for the multi-objective optimization of combinatorial problems. The proposed algorithm is named EMSA. It is an improvement of MODS algorithm. Unlike MODS, EMSA works using a search direction given through the assignation of weights to each function of the combinatorial problem to optimize. Also, in order to avoid local optimums, EMSA uses crossover strategy of Genetic Algorithm. Lastly, EMSA is tested using well know instances of the Bi-Objective Traveling Salesman Problem (TSP from TSPLIB. Its results were compared with MODS Metaheuristic (its precessor. The comparison was made using metrics from the specialized literature such as Spacing, Generational Distance, Inverse Generational Distance and Non-Dominated Generation Vectors. In every case, the EMSA results on the metrics were always better and in some of those cases, the superiority was 100%.

  18. A Novel Multi-objective Genetic Algorithms-Based Calculation of Hill's Coefficients

    Science.gov (United States)

    Hariharan, Krishnaswamy; Chakraborti, Nirupam; Barlat, Frédéric; Lee, Myoung-Gyu

    2014-06-01

    The anisotropic coefficients of Hill's yield criterion are determined through a novel genetic algorithms-based multi-objective optimization approach. The classical method of determining anisotropic coefficients is sensitive to the effective plastic strain. In the present procedure, that limitation is overcome using a genetically evolved meta-model of the entire stress strain curve, obtained from uniaxial tension tests conducted in the rolling direction and transverse directions, and biaxial tension. Then, an effective strain that causes the least error in terms of two theoretically derived objective functions is chosen. The anisotropic constants evolved through genetic algorithms correlate very well with the classical results. This approach is expected to be successful for more complex constitutive equations as well.

  19. A new method for feature selection based on fuzzy similarity measures using multi objective genetic algorithm

    Directory of Open Access Journals (Sweden)

    Hassan Nosrati Nahook

    2014-06-01

    Full Text Available Feature selection (FS is considered to be an important preprocessing step in machine learning and pattern recognition, and feature evaluation is the key issue for constructing a feature selection algorithm. Feature selection process can also reduce noise and this way enhance the classification accuracy. In this article, feature selection method based on fuzzy similarity measures by multi objective genetic algorithm (FSFSM - MOGA is introduced and performance of the proposed method on published data sets from UCI was evaluated. The results show the efficiency of the method is compared with the conventional version. When this method multi-objective genetic algorithms and fuzzy similarity measures used in CFS method can improve it.

  20. High-accuracy measurement for small scale specular objects based on PMD with illuminated film

    Science.gov (United States)

    Liu, Yuankun; Lehtonen, Petri; Su, Xianyu

    2012-03-01

    In this paper we describe an approach to measure small glossy objects by illuminated film based on Phase Measuring Deflectometry (PMD) system. In this setup, the standard sinusoidal fringe patterns are produced by the photographic film frame (135-film), which is illuminated from behind using LED and diffuser, instead of the well-known LCD monitor plane or digital projector. This setup can avoid the influence of electronic noise and screen refreshing, and fulfill the test of small objects in low cost. Moreover the system is easily calibrated with its vertical setup. With the experiments of measuring a plastic contactless smartcard and a metal plate, it is proven that the setup can reach sub-micrometer accuracy with respect to the data of the Wyko white light interferometer. This setup will be promising in the small scale measurement field.

  1. Multi-objective Optimization of RFID Network Based on Genetic Programming

    Directory of Open Access Journals (Sweden)

    Xie Qingsheng

    2011-01-01

    Full Text Available With the widespread application of RFID tags, the layout of RFID readers under guaranteed the rate of coverage, RFID network load balance and communication quality which becomes a major focus of current research on RFID network. Present study analyzes the characteristics of RFID network and the disadvantages of current optimization methods on readers network, by establishing the mathematical optimization model of RFID network, a kind of method that multi-objective optimization of RFID network based on Genetic Programming is proposed and the evolutional topological operators, terminal set and fitness functions are designed. Finally, it realized the module of the multi-objective optimization algorithm, the number of readers and the layout of readers automatic optimization. The experimental results show that it has higher efficiency, faster convergence rate and good accuracy. It can keep well balance between topology and parameter search. This research has important reference value in the theory and practice.

  2. Fast object reconstruction in block-based compressive low-light-level imaging

    Science.gov (United States)

    Ke, Jun; Sui, Dong; Wei, Ping

    2014-11-01

    In this paper we propose a simply yet effective and efficient method for long-term object tracking. Different from traditional visual tracking method which mainly depends on frame-to-frame correspondence, we combine high-level semantic information with low-level correspondences. Our framework is formulated in a confidence selection framework, which allows our system to recover from drift and partly deal with occlusion problem. To summarize, our algorithm can be roughly decomposed in a initialization stage and a tracking stage. In the initialization stage, an offline classifier is trained to get the object appearance information in category level. When the video stream is coming, the pre-trained offline classifier is used for detecting the potential target and initializing the tracking stage. In the tracking stage, it consists of three parts which are online tracking part, offline tracking part and confidence judgment part. Online tracking part captures the specific target appearance information while detection part localizes the object based on the pre-trained offline classifier. Since there is no data dependence between online tracking and offline detection, these two parts are running in parallel to significantly improve the processing speed. A confidence selection mechanism is proposed to optimize the object location. Besides, we also propose a simple mechanism to judge the absence of the object. If the target is lost, the pre-trained offline classifier is utilized to re-initialize the whole algorithm as long as the target is re-located. During experiment, we evaluate our method on several challenging video sequences and demonstrate competitive results.

  3. Balancing multiple objectives using a classification-based forest management system in Changbai Mountains, China.

    Science.gov (United States)

    Zhao, Fuqiang; Yang, Jian; Liu, Zhihua; Dai, Limin; He, Hong S

    2011-12-01

    Contemporary forest management often consists of multiple objectives, including restoration of human-impacted forested landscapes toward their range of natural variability (RNV) and sustainable levels of timber production. Balancing multiple management objectives is often challenging due to intrinsic conflicts between these objectives and a lack of reference conditions for evaluating the effectiveness of forest restoration efforts. We used a spatially explicit forest landscape model to assess how well a classification-based forest management (CFM) system could achieve multiple objectives in a Korean pine broadleaf mixed forest ecosystem at Changbai Mountain in Northeast China. The CFM system divided the forest landscape into three management areas (Commercial Forest, Special Ecological Welfare Forest, and General Ecological Welfare Forest), each with its own management objectives and prescriptions, but with an overall goal of increasing the ecological and economic sustainability of the entire landscape. The zoning approach adopted in the Chinese CFM system is very similar to the TRIAD approach that is being advocated for managing public forests in Canada. In this study, a natural disturbance scenario and seven harvest scenarios (one identical to the current harvest regime and six alternative scenarios) were simulated to examine how tree species composition, age structure, and timber production at the landscape level can be affected by different strategies under the CFM system. The results indicated that the current forest management regime would not only fail to reach the designated timber production level but also move the forest landscape far away from its RNV. In order to return the currently altered forest landscape to approach its RNV while providing a stable level of timber production over time, harvest intensities should be reduced to a level that is equivalent to the amount of timber removals that would occur under the natural disturbances; and the establishment of forest plantations is also required. PMID:21452058

  4. Target Object Identification and Location Based on Multi-sensor Fusion

    Directory of Open Access Journals (Sweden)

    Yong Jiang

    2013-03-01

    Full Text Available For an unknown environment, how to make a mobile robot identify a target object and locate it autonomously, this is a very challenging question. In this paper, a novel multi-sensor fusion method based on a camera and a laser range finder (LRF for mobile manipulations is proposed. Although a camera can acquire large quantities of information, it does not directly get the 3D data of the environment. Moreover, the camera image processing is complex and easily influenced from the change in ambient light. In view of the ability of the LRF to directly get the 3D coordinates of the environment and its stability against outside influence, and the superiority of the camera to acquire rich color information, the combination of the two sensors by making use of their advantages is employed to obtain more accurate measurement as well as to simplify information processing. To overlay the camera image with the measurement point cloud of the pitching LRF and to reconstruct the 3D image which includes pixel depth information, the homogeneous transformation model of the system is built. Then, based on the combination of the color features from the camera image and the shape features from the LRF measurement data, the autonomous identification and location of target object are achieved. In order to extract the shape features of the object, a two-step method is introduced, and a sliced point cloud algorithm is proposed for the preliminary classification of the measurement data of the LRF. The effectiveness of the proposed method is validated by the experimental testing and analysis carried out on the mobile manipulator platform. The experimental results show that by this method, the robot can not only identify target object autonomously, but also determine whether it can be operated, and acquire a proper grasping location.

  5. Tabu Search Based Algorithm for Multi-Objective Network Reconfiguration Problem

    Directory of Open Access Journals (Sweden)

    Jaswanti Jaswanti

    2011-06-01

    Full Text Available Abstract: The electric power distribution usually operates in a radial configuration, with tie switches between circuits to provide alternate feeds. The losses would be minimized if all switches were closed, but this is not done because it complicates the system’s protection against over currents. Whenever components fail, some of the switches must be operated to restore power to as many customers as possible. As loads vary with time, switch operations may reduce losses in the system. All of these are applications for reconfiguration.
    The reconfiguration problem is combinatorial problem, which precludes algorithms that guarantee a global optimum. Most existing reconfiguration algorithms fall into two categories. In the first, branch exchange, the system operates in a feasible radial configuration and the algorithm opens and closes candidate switches in pairs. In the second, loop cutting, the system is completely meshed and the algorithm opens candidate switches to reach a feasible radial configuration. Reconfiguration algorithms based on neural network, heuristics, genetic algorithms, and simulated annealing have also been reported, but not widely used.
    The objective of the paper presented in this work is to make a Tabu Search (TS based algorithm for multi-objective programming to solve the network reconfiguration problem in a radial distribution system. Here six objectives are considered in conjunction with network constraints. The main objective of research is allocation of optimal switches to reduce the power losses of the system. It is tested for 33 bus systems. Simulation results of the case studies demonstrate the effectiveness of the solution algorithm and proved that the TS is suitable to solve this kind of problems.
    Key words: Combinatorial optimization; Distribution system; Energy Loss minimization; Genetic Algorithm; Simulating Annealing; Tabu search

  6. Object-Based Crop Species Classification Based on the Combination of Airborne Hyperspectral Images and LiDAR Data

    Directory of Open Access Journals (Sweden)

    Xiaolong Liu

    2015-01-01

    Full Text Available Identification of crop species is an important issue in agricultural management. In recent years, many studies have explored this topic using multi-spectral and hyperspectral remote sensing data. In this study, we perform dedicated research to propose a framework for mapping crop species by combining hyperspectral and Light Detection and Ranging (LiDAR data in an object-based image analysis (OBIA paradigm. The aims of this work were the following: (i to understand the performances of different spectral dimension-reduced features from hyperspectral data and their combination with LiDAR derived height information in image segmentation; (ii to understand what classification accuracies of crop species can be achieved by combining hyperspectral and LiDAR data in an OBIA paradigm, especially in regions that have fragmented agricultural landscape and complicated crop planting structure; and (iii to understand the contributions of the crop height that is derived from LiDAR data, as well as the geometric and textural features of image objects, to the crop species’ separabilities. The study region was an irrigated agricultural area in the central Heihe river basin, which is characterized by many crop species, complicated crop planting structures, and fragmented landscape. The airborne hyperspectral data acquired by the Compact Airborne Spectrographic Imager (CASI with a 1 m spatial resolution and the Canopy Height Model (CHM data derived from the LiDAR data acquired by the airborne Leica ALS70 LiDAR system were used for this study. The image segmentation accuracies of different feature combination schemes (very high-resolution imagery (VHR, VHR/CHM, and minimum noise fractional transformed data (MNF/CHM were evaluated and analyzed. The results showed that VHR/CHM outperformed the other two combination schemes with a segmentation accuracy of 84.8%. The object-based crop species classification results of different feature integrations indicated that incorporating the crop height information into the hyperspectral extracted features provided a substantial increase in the classification accuracy. The combination of MNF and CHM produced higher classification accuracy than the combination of VHR and CHM, and the solely MNF-based classification results. The textural and geometric features in the object-based classification could significantly improve the accuracy of the crop species classification. By using the proposed object-based classification framework, a crop species classification result with an overall accuracy of 90.33% and a kappa of 0.89 was achieved in our study area.

  7. Object-based glacier mapping in the Hohe Tauern Mountains of Austria

    Science.gov (United States)

    Aubrey Robson, Benjamin; Hölbling, Daniel; Nuth, Christopher; Olaf Dahl, Svein

    2015-04-01

    Up-to-date and frequent glacier outlines are a necessity for many applications within glaciology. While multispectral band ratios are a comparatively robust method for automatically classifying clean ice on a pixel-based level, semi- or fully automated glacier inventories are complicated by spectral similarities between classes such as debris-covered glacier ice and the surrounding bedrock and moraines, or between clean ice and turbid pro-glacial water. Most glacier inventories therefore require a great deal of manual correction. Here, we present a glacier inventory of the Hohe Tauern Mountains in the Central Eastern Alps in Austria. Numerous glaciers, including the Pasterze Glacier, which is the longest glacier in the Eastern Alps, shape this mountainous region. The mapping of glaciers is based on object-based image analysis (OBIA) using both high resolution (HR) satellite imagery from Landsat 8 and a digital elevation model (DEM) derived from Airborne Laser Scanning (ALS) data. We automatically classify clean ice, debris-covered ice and glacial lakes. Image objects are created by applying the multiresolution segmentation algorithm implemented in the eCognition (Trimble) software. The resulting image objects are classified using a combination of various features, whereby a focus was put on the selection of robust features that are ideally applicable for mapping large areas, for example spectral indices such as the Normalized Differenced Vegetation Index (NDVI), Normalized Difference Snow and Ice Index (NDSI), Normalised Difference Water Index (NDWI), Land and Water Mask (LWK) and a ratio of the SWIR and NIR spectral bands. The ability of OBIA to incorporate optical and elevation data and to individually address data-specific characteristics helps differentiate debris-covered ice from surrounding features not only by using spectral properties but also based on morphological and topographic parameters, while the inclusion of rulesets relying on contextuality, size and shape and hierarchical criteria allow semantic corrections of shadow and supra-glacial lakes. In addition, the absence of the 'salt and pepper' effect often found when using pixel-based methods reduce the amount of post-processing and manual correction necessary. The results are compared to the Randolph Glacier Inventory, although given that over Austria this inventory was based on imagery from 2003 the comparability with such databases is limited. Against the background of the lack of up-to-data data and the fact that glaciers undergo steady changes, and thus, are a highly important indicator of climate change, it can be said there is a need for reliable methods for mapping and monitoring glaciers. The presented method based on remote sensing data and OBIA is one promising way to tackle these issues.

  8. Advanced algorithms for identifying targets from a three-dimensional reconstruction of sparse 3D ladar data

    Science.gov (United States)

    Berechet, Ion; Berginc, Gérard

    2011-10-01

    There is a considerable interest in the development of new optical imaging systems that are able to give threedimensional images. Potential applications range across medical imaging, surveillance and robotic vision. Identifying targets or objects concealed by foliage or camouflage is a critical requirement for operations in public safety, law enforcement and defense. The most promising techniques for these tasks are 3D laser imaging techniques. Their principles are to use movable light sources and detectors to collect information on laser scattering and to reconstruct the 3D objects of interest. 3D reconstruction algorithm is a major component in these optical systems for identification of camouflaged objects. But 3D reconstruction must take into account sparse collected data i.e. concealed objects and reconstruction algorithms must solve a complex multi-parameter inverse problem. Therefore the inverse problem of recovering the surface three-dimensional shape function from intensity data is more challenging. The objective of our paper is to present a new algorithmic approach for the generation of 3D surface data from 3D point clouds corresponding to reconstruction algorithm. This algorithmic approach is based on research of automatic minimization of an energy function associated with a sparse structure of 3D points. The role of this type of algorithmic data-driving process is to complete the incomplete 3D image at satisfactory levels for reliable identification of concealed objects.

  9. High-speed three-dimensional shape measurement for isolated objects based on fringe projection

    International Nuclear Information System (INIS)

    A method for high-speed measurement of the three-dimensional (3D) shape of spatially isolated objects is proposed. Two sinusoidal fringe patterns with phase difference ? and an encoded pattern are used to measure the 3D shape. A modified Fourier transform profilometry (FTP) method is used for phase retrieval and obtaining high-quality texture. The measurable slope of the height variation is larger than for methods based on traditional FTP and the same as that for methods based on phase measurement profilometry (PMP). The number of patterns is less than for the high-speed methods based on PMP, using which isolated objects can be measured. Consequently, this approach is less sensitive to object motion. In the proposed method, the encoded pattern consists of vertical stripes with width the same as the period of the sinusoidal fringe. Three gray levels are used to form the stripes. Six symbols are encoded with these three gray levels. Then, a pseudorandom sequence is constructed with an alphabet of these six symbols. The stripes are arranged according to the sequence to form the pattern. In the procedure of phase unwrapping, the strings (subsequences) are constructed with symbols corresponding to three neighbor periods of the deformed fringe. The position of the subsequence is worked out by string matching in the pseudorandom sequence. The ranking number of the fringe is identified and then the absolute phase of the deformed fringe is obtained. The 3D shape of the objects is reconstructed with triangulation. A system consisting of a specially designed digital light processing projector and a high-speed camera is presented. The 3D capture speed of 60 frames per second (fps), with a resolution of 640 × 480 points, and that of 120 fps, with a resolution of 320 × 240 points, were achieved. Preliminary experimental results are given. If the control logic of the digital micromirror device was modified and a camera with higher speed was employed, the measurement speed would reach thousands of fps. This makes it possible to analyze dynamic objects

  10. THE EFFECTS OF OPERATIONAL OBJECTIVES-BASED TRAINING PROGRAM ON JUNIOR II MALE HANDBALL PLAYERS

    Directory of Open Access Journals (Sweden)

    Sufaru Constantin

    2014-06-01

    Full Text Available This paper aims to prove the effectiveness of the operational objectives-based sports training program in the junior II male handball players from the Bacau School Sports Club, during the technical-tactical drills. The aim of this research was to test the subjects throughout the competition season by applying a series of technical-tactical tests. We presumed that after applying the operational objective-based athletic training program in the junior II male handball players, the progress in the technical-tactical drills will be ascending, recording superior final results, these being conditioned by an optimal programing of the training.The goal of this study was to prove that the progress of the Bacau School Sports Club junior II male handball players in the technical-tactical drills was correlated with the operational objective-based program.The research subjects consisted of an experimental group from the Bacau School Sports Club and a witness group from School 3 - the Adjud School Sports Club Both groups comprised 19 junior II male players. In order to emphasize the progress recorded in the technical-tactical training, we gathered data from three control drills and from the assessment of the players' actions during the game. The progress was conditioned by the programing of the athletic training; during the training sessions, we intervened each time through the operational objectives, for improving the training process.The more prominent progress during the first part of the competition season is due to the technical training, while the sufficiently prominent progress in the last part of the season is due to the tactical training, a fact that results from the programing of the operational objectives - the ones for the technical training are more in the first part of the season, while the ones for the tactical training are in larger number in the second part of the season.The effectiveness of the programs gained them a first place in the Junior II National Championship.

  11. Neural activity associated with self, other, and object-based counterfactual thinking.

    Science.gov (United States)

    De Brigard, Felipe; Nathan Spreng, R; Mitchell, Jason P; Schacter, Daniel L

    2015-04-01

    Previous research has shown that autobiographical episodic counterfactual thinking-i.e., mental simulations about alternative ways in which one's life experiences could have occurred-engages the brain's default network (DN). However, it remains unknown whether or not the DN is also engaged during impersonal counterfactual thoughts, specifically those involving other people or objects. The current study compares brain activity during counterfactual simulations involving the self, others and objects. In addition, counterfactual thoughts involving others were manipulated in terms of similarity and familiarity with the simulated characters. The results indicate greater involvement of DN during person-based (i.e., self and other) as opposed to object-based counterfactual simulations. However, the involvement of different regions of the DN during other-based counterfactual simulations was modulated by how close and/or similar the simulated character was perceived to be by the participant. Simulations involving unfamiliar characters preferentially recruited dorsomedial prefrontal cortex. Simulations involving unfamiliar similar characters, characters with whom participants identified personality traits, recruited lateral temporal gyrus. Finally, our results also revealed differential coupling of right hippocampus with lateral prefrontal and temporal cortex during counterfactual simulations involving familiar similar others, but with left transverse temporal gyrus and medial frontal and inferior temporal gyri during counterfactual simulations involving either oneself or unfamiliar dissimilar others. These results suggest that different brain mechanisms are involved in the simulation of personal and impersonal counterfactual thoughts, and that the extent to which regions associated with autobiographical memory are recruited during the simulation of counterfactuals involving others depends on the perceived similarity and familiarity with the simulated individuals. PMID:25579447

  12. Effective Scanned-Certification Image Retrieval Based on Local Object and Block Matching

    Directory of Open Access Journals (Sweden)

    Hao Zhang

    2014-03-01

    Full Text Available Scanned certifications are widely used in China as proof of past achievements. To avoid repetitive usage of the same certification in various awards or funding applications, we design and implement a scanned-certification image retrieval system based on local object and block matching. The seal is used as a salient feature and a modified Hough round detection method is applied for extraction. And local round seals are combined with blocks attributes of the seals to build image indexes. Experimental results will demonstrate the effectiveness of the system. Additionally, we conduct experiments on single color histogram, which further demonstrates the effectiveness of the proposed image retrieval method.

  13. Developing a framework for monitoring coastal habitats using aerial imagery and object-based image analysis

    DEFF Research Database (Denmark)

    Juel, Anders

    Denmark contains major areas of coastal habitats, including a significant part of the European area of coastal dunes and salt marshes. The natural dynamics in coastal habitats are a prerequisite for the maintenance of their structure and biodiversity, yet very little research on the implications of decreased habitat dynamics exists. A valuable source of land cover changes are historical aerial imagery of which Denmark has unique datasets.This poster presents an object-based image analysis approach for mapping and monitoring af coastal habitat stucture, which integrates the high spectral resolution and consistency of satellite imagery, with the high spatial resolution of aerial imagery.

  14. Object based change detection in urban area using KTH-SEG

    OpenAIRE

    Bergsjö, Joline

    2014-01-01

    Today more and more people are moving to the cities around the world. This puts a lot of strain on the infrastructure as the cities grow in both width and height. To be able to monitor the ongoing change remote sensing is an effective tool and ways to make it even more effective, better and easier to use are constantly sought after. One way to monitor change detection is object based change detection. The idea has been around since the seventies, but it wasn’t until the early 2000 when it was...

  15. Dynamic Verification of an Object-Rule Knowledge Base Using Colored Petri Nets

    Directory of Open Access Journals (Sweden)

    Chakib Tadj

    2006-06-01

    Full Text Available In this paper, we propose a formal description for the dynamic verification of an Object-Rule Hybrid Knowledge-based System (HKBS, capitalizing on the work carried out within the verification framework of Frame-Rule Hybrid Expert Systems. The main idea is to model an HKBS by means of a Colored Petri Network (CPN. In this way, method invocations, state class changes, rules and productions will be modeled as components of the CPN. Detection and analysis of the HKBS will be carried out by the construction and analysis of the markings graph, which results from the inference process.

  16. Segmentation-based filtering and object-based feature extraction from airborne LiDAR point cloud data

    Science.gov (United States)

    Chang, Jie

    Three dimensional (3D) information about ground and above-ground features such as buildings and trees is important for many urban and environmental applications. Recent developments in Light Detection And Ranging (LiDAR) technology provide promising alternatives to conventional techniques for acquiring such information. The focus of this dissertation research is to effectively and efficiently filter massive airborne LiDAR point cloud data and to extract main above-ground features such as buildings and trees in the urban area. A novel segmentation algorithm for point cloud data, namely the 3D k mutual nearest neighborhood (kMNN) segmentation algorithm, was developed based on the improvement to the kMNN clustering algorithm by employing distances in 3D space to define mutual nearest neighborhoods. A set of optimization strategies, including dividing dataset into multiple blocks and small size grids, and using distance thresholds in x and y, were implemented to improve the efficiency of the segmentation algorithm. A segmentation based filtering method was then employed to filter the generated segments, which first generates segment boundaries using Voronoi polygon and dissolving operations, and then labels the segments as ground and above-ground based on their size and relative heights to the surrounding segments. An object-based feature extraction approach was also devised to extract buildings and trees from the above-ground segments based on object-level statistics derived, which were subject to a rule based classification system developed by either human experts or an inductive machine-learning algorithm. Case studies were conducted with four different LiDAR datasets to evaluate the effectiveness and efficiency of the proposed approaches. The proposed segmentation algorithm proved to be not only effective in separating ground and above-ground measurements into different segments, but also efficient in processing large datasets. The segmentation based filtering and object based feature extraction approaches have also demonstrated effectiveness in labeling the segments into ground and above-ground and in extracting buildings and trees from the above-ground segments. When incorporating spectral information from remote sensing imagery with the LiDAR data, the accuracy for feature extraction was further increased.

  17. Cooperative Moving Object Segmentation using Two Cameras based on Background Subtraction and Image Registration

    Directory of Open Access Journals (Sweden)

    Zhigao Cui

    2014-03-01

    Full Text Available Moving camera, such as PTZ (pan-tilt-zoom camera, has been widely applied in visual surveillance system. However, it’s difficult to extract moving objects because of the dynamic background caused by the camera motion. In this paper, a novel framework for moving object segmentation exploiting two cameras collaboration is presented by combining background subtraction and image registration method. The proposed method uses one static camera to capture large-view images at low resolution, and one moving camera (i.e. PTZ camera to capture local-view images at high resolution. Different with methods using a single moving camera, the moving objects can be effectively segmented in the static camera image by background subtraction method. Then image registration method can be applied to extract moving region in the moving camera image. To deal with the resolution and intensity discrepancy between two synchronized images, we design a practical three-step image registration method, which has higher registration accuracy than traditional feature based method. Experimental results on outdoor scene demonstrate the effectiveness and robustness of proposed approach.

  18. Reference Point Based TR-PSO for Multi-Objective Environmental/Economic Dispatch

    Directory of Open Access Journals (Sweden)

    Mohamed A. El-Shorbagy

    2013-05-01

    Full Text Available A reference point based multi-objective optimization using a combination between trust region (TR algorithm and particle swarm optimization (PSO to solve the multi-objective environmental/economic dispatch (EED problem is presented in this paper. The EED problem is handled by Reference Point Interactive Approach. One of the main advantages of the proposed approach is integrating the merits of both TR and PSO, where TR has provided the initial set (close to the Pareto set as possible and the reference point of the decision maker followed by PSO to improve the quality of the solutions and get all the points on the Pareto frontier. The performance of the proposed algorithm is tested on standard IEEE 30-bus 6-genrator test system and is compared with conventional methods. The results demonstrate the capabilities of the proposed approach to generate true and well-distributed Pareto-optimal non-dominated solutions in one single run. The comparison with the classical methods demonstrates the superiority of the proposed approach and confirms its potential to solve the multi-objective EED problem.

  19. The gamma slideshow: object-based perceptual cycles in a model of the visual cortex.

    Directory of Open Access Journals (Sweden)

    ThomasMiconi

    2010-11-01

    Full Text Available While recent studies have shed light on the mechanisms that generate gamma (>40Hz oscillations, the functional role of these oscillations (if any is still debated. Here we suggest that the purported mechanism of gamma oscillations (feedback inhibition from local interneurons, coupled with lateral connections implementing “Gestalt” principles of object integration, naturally leads to a decomposition of the visual input into object-based “perceptual cycles”, in which neuron populations representing different objects within the scene will tend to fire at successive cycles of the local gamma oscillation. We describe a simple model of V1 in which such perceptual cycles emerge automatically from the interaction between lateral excitatory connections (linking oriented cells falling along a continuous contour and fast feedback inhibition (implementing competitive firing and gamma oscillations. Despite its extreme simplicity, the model spontaneously gives rise to perceptual cycles even when faced with natural images. The robustness of the system to parameter variation and to image complexity, together with the paucity of assumptions built in the model, support the hypothesis that perceptual cycles occur in natural vision.

  20. An interactive system for creating object models from range data based on simulated annealing

    International Nuclear Information System (INIS)

    In hazardous applications such as remediation of buried waste and dismantlement of radioactive facilities, robots are an attractive solution. Sensing to recognize and locate objects is a critical need for robotic operations in unstructured environments. An accurate 3-D model of objects in the scene is necessary for efficient high level control of robots. Drawing upon concepts from supervisory control, the authors have developed an interactive system for creating object models from range data, based on simulated annealing. Site modeling is a task that is typically performed using purely manual or autonomous techniques, each of which has inherent strengths and weaknesses. However, an interactive modeling system combines the advantages of both manual and autonomous methods, to create a system that has high operator productivity as well as high flexibility and robustness. The system is unique in that it can work with very sparse range data, tolerate occlusions, and tolerate cluttered scenes. The authors have performed an informal evaluation with four operators on 16 different scenes, and have shown that the interactive system is superior to either manual or automatic methods in terms of task time and accuracy

  1. Identification of Mine-Shaped Objects based on an Efficient Phase Stepped-Frequency Radar Approach

    DEFF Research Database (Denmark)

    SØrensen, Helge Bjarup Dissing; Jakobsen, Kaj Bjarne

    1997-01-01

    A computational efficient approach to identify very small mine-shaped plastic objects, e.g. M56 Anti-Personnel (AP) mines buried in the ground, is presented. The size of the objects equals the smallest AP-mines in use today, i.e., the most difficult mines to detect with respect to humanitarian mine clearance. Our approach consists of three stages, the phase stepped-frequency radar method, generation of a quarternary image and template crosscorrelation. The phase stepped-frequency radar method belongs to the class of stepped-frequency radar methods. In a two-dimensional mesh-grid above the ground a radar probe is moved automatically to measure in each grid point a set of reflection coefficients from which phase and amplitude information are extracted. Based on a simple processing of the phase information, quarternary image and template cross-correlation a successful detection of metal- and non-metal mine-shaped objects is possible. Measurements have been performed on loamy soil containing different mine-shapedobjects

  2. Simple Ontology of Manipulation Actions based on Hand-Object Relations

    DEFF Research Database (Denmark)

    Wörgötter, Florentin; Aksoy, E. E.

    2013-01-01

    Humans can perform a multitude of different actions with their hands (manipulations). In spite of this, so far there have been only a few attempts to represent manipulation types trying to understand the underlying principles. Here we first discuss how manipulation actions are structured in space and time. For this we use as temporal anchor points those moments where two objects (or hand and object) touch or un-touch each other during a manipulation. We show that by this one can define a relatively small tree-like manipulation ontology. We find less than 30 fundamental manipulations. The temporal anchors also provide us with information about when to pay attention to additional important information, for example when to consider trajectory shapes and relative poses between objects. As a consequence a highly condensed representation emerges by which different manipulations can be recognized and encoded. Examples of manipulations recognition and execution by a robot based on this representation are given at theend of this study.

  3. Culture belief based multi-objective hybrid differential evolutionary algorithm in short term hydrothermal scheduling

    International Nuclear Information System (INIS)

    Highlights: ? Culture belief is integrated into multi-objective differential evolution. ? Chaotic sequence is imported to improve evolutionary population diversity. ? The priority of convergence rate is proved in solving hydrothermal problem. ? The results show the quality and potential of proposed algorithm. - Abstract: A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic emission (SHOSEE) problem. This problem is formulated for compromising thermal cost and emission issue while considering its complicated non-linear constraints with non-smooth and non-convex characteristics. The proposed algorithm integrates a modified multi-objective differential evolutionary algorithm into the computation model of culture algorithm (CA) as well as some communication protocols between population space and belief space, three knowledge structures in belief space are redefined according to these problem-solving characteristics, and in the differential evolution a chaotic factor is embedded into mutation operator for avoiding the premature convergence by enlarging the search scale when the search trajectory reaches local optima. Furthermore, a new heuristic constraint-handling technique is utilized to handle those complex equality and inequality constraints of SHOSEE problem. After the application on hydrothermal scheduling system, the efficiency and stability of the propoiciency and stability of the proposed CB-MOHDE is verified by its more desirable results in comparison to other method established recently, and the simulation results also reveal that CB-MOHDE can be a promising alternative for solving SHOSEE.

  4. An object-oriented hybrid knowledge representation method based on the ASME code

    International Nuclear Information System (INIS)

    In this paper knowledge based system technology is adopted in the application process of the ASME boiler and pressure vessel core section III for bettering design quality and efficiency of nuclear component. At present no a single knowledge representation method could express all of the ASME code's rules sufficiently, integrally and exactly. An object-oriented hybrid knowledge representation method (OOHKRM) is presented in the paper. The rule expression of the ASME code is divided into three modes such as statement, list and graphic illustration by detailed analyzing the organization characteristics and rules of the code. According to the differences of knowledge features, knowledge of the ASME code is classified approximately into three main categories: illustrative knowledge, procedural knowledge, and Meta knowledge, which are represented by list, frame, production rule and Petri net respectively for expressing the knowledge integrally and exactly. A knowledge Petri net model is also defined for the same reason. Moreover, several class objects corresponding to different types of knowledge are defined especially. The method not only reserves merits of the other four used representation methods, but also processes characteristics of object-oriented technologies. Consequently, the method has good universality while it is used to represent the knowledge of ASME codes or other engineering standards. (author)

  5. A grid based multi-objective evolutionary algorithm for the optimization of power plants

    International Nuclear Information System (INIS)

    There is an increasing need for optimization of energy conversion systems, in particular concerning energy consumption and efficiency to reduce their environmental impact. Usually, optimization is based on designers' backgrounds, which are able to analyze system performances and modify appropriate operating parameters. However, if these changes aim to optimize simultaneously multiple conflicting objectives, the task becomes quite complex and the use of sophisticated tools is mandatory. This paper presents a multi-objective optimization method that permits solutions that simultaneously satisfy multiple conflicting objectives to be determined. The optimization process is carried out by using an evolutionary algorithm developed around an innovative technique that consists of partitioning the solution search space (i.e., a population of solutions) into parallel corridors. Within these corridors, 'header' solutions are trapped to be then involved in a reproduction process of new populations by using genetic operators. The proposed methodology is coupled to specific power plant models that are used to optimize two different power plants: (i) a cogeneration thermal plant and (ii) an advanced steam power station. In both cases the proposed technique has shown to be very powerful, robust and reliable. Further, this methodology can be used as an effective tool to find the set of best solutions and thus providing a realistic support to the decision-making.he decision-making.

  6. Real-time underwater object detection based on an electrically scanned high-resolution sonar

    DEFF Research Database (Denmark)

    Henriksen, Lars

    1994-01-01

    The paper describes an approach to real time detection and tracking of underwater objects, using image sequences from an electrically scanned high-resolution sonar. The use of a high resolution sonar provides a good estimate of the location of the objects, but strains the computers on board, because of the high rate of raw data. The amount of data can be cut down by decreasing the scanned area, but this reduces the possibility of planning an optimal path. In the paper methods are described, that maintains the wide area of detection, without significant loss of precision or speed. This is done by using different scanning patterns for each sample. The detection is based on a two level threshold, making processing fast. Once detected the objects are followed through consecutive sonar images, and by use of an observer the estimation errors on position and velocities are reduced. Intensive use of different on-board sensors also makes it possible to scan a map of a larger area of the seabed in world coordinates. The work is in collaboration with partners under MAST-C-T90-0059

  7. Object-Based Classification of Urban Airborne LIDAR Point Clouds with Multiple Echoes Using Svm

    Science.gov (United States)

    Zhang, J. X.; Lin, X. G.

    2012-07-01

    Airborne LiDAR point clouds classification is meaningful for various applications. In this paper, an object-based analysis method is proposed to classify the point clouds in urban areas. In the process of classification, outliers in the point clouds are first removed. Second, surface growing algorithm is employed to segment the point clouds into different clusters. The above point cloud segmentation is helpful to derive useful features such as average height, size/area, proportion of multiple echoes, slope/orientation, elevation difference, rectangularity, ratio of length to width, and compactness. At last, SVM-based classification is performed on the segmented point clouds with radial basis function as kernel. Two datasets with high point densities are employed to test the proposed method, and three classes are predefined. The results suggest that our method will produce the overall classification accuracy larger than 97% and the Kappa coefficient larger than 0.95.

  8. ARTIFICIAL NEURAL NETWORK BASED DISCRIMINATION OF MINELIKE OBJECTS IN INFRARED IMAGES

    Directory of Open Access Journals (Sweden)

    G.Suganthi

    2014-09-01

    Full Text Available An artificial neural network (ANN model with a simple architecture containing a single hidden layer is presented to discriminate the landmine objects from the acquired infrared images. The proposed method consists of preprocessing, segmentation, feature extraction and ANN based classification. Texture features based on gray level co-occurrence matrix (GLCM are considered as inputs to the neural network classifier. The proposed method is tested on the infrared images acquired from two different soil types namely black cotton soil and Maharashtra sand. The ability of the back propagation neural network in discriminating the landmines from the clutters in the infrared images acquired from inhomogeneous soil is discussed. The results of the field experiments carried out at the outdoor land mine detection test facility, DRDO, Pune are presented. The results are encouraging.

  9. A 3D City Model with Dynamic Behaviour Based on Geospatial Managed Objects

    DEFF Research Database (Denmark)

    Kjems, Erik; Kolá?, Jan

    2014-01-01

    One of the major development efforts within the GI Science domain are pointing at real time information coming from geographic referenced features in general. At the same time 3D City models are mostly justified as being objects for visualization purposes rather than constituting the foundation of a geographic data representation of the world. The combination of 3D city models and real time information based systems though can provide a whole new setup for data fusion within an urban environment and provide time critical information preserving our limited resources in the most sustainable way. Using 3D models with consistent object definitions give us the possibility to avoid troublesome abstractions of reality, and design even complex urban systems fusing information from various sources of data. These systems are difficult to design with the traditional software development approach based on major software packages and traditional data exchange. The data stream is varying from domain to domain and from system to system why it is almost impossible to design an unifying system taking care of all thinkable instances now and in the future within one constraint software design complex. On several occasions we have been advocating for a new and advanced formulation of real world features using the concept of Geospatial Managed Objects (GMO). This chapter presents the outcome of the InfraWorld project, a 4 million Euro project financed primarily by the Norwegian Research Council where the concept of GMO’s have been applied in various situations on various running platforms of an urban system. The paper will be focusing on user experiences and interfaces rather then core technical and developmental issues. The project was primarily focusing on prototyping rather than realistic implementations.

  10. Data Mining for Knowledge Discovery from Object-Based Segmentation of Vhr Remotely Sensed Imagery

    Science.gov (United States)

    Djerriri, K.; Malki, M.

    2013-04-01

    The success of the object-based image analysis (OBIA) paradigm can be attributed to the fact that regions obtained by means of segmentation process are depicted with a variety of spectral, shape, texture and context characteristics. These representative objectsattributes can be assigned to different land-cover/land-use types by means of two options. The first is to use supervised classifiers such as K-nearest neighbors (KNN) and Support Vector Machine (SVM), the second is to create classification rules. Supervised classifiers perform very well and have generally higher accuracies. However one of their drawbacks is that they provide no explicit knowledge in understandable and interpretable forms. The building of the rule set is generally based on the domain expert knowledge when dealing with a small number of classes and a small number of attributes, but having a dozens of continuously valued attributes attached to each image object makes it a tedious task and experts quickly get overwhelmed and become totally helpless. This is where data mining techniques for knowledge discovering help to understand the hidden relationships between classes and their attached attributes. The aim of this paper is to highlight the benefits of using knowledge discovery and data-mining tools, especially rule induction algorithms for useful and accurate information extraction from high spatial resolution remotely sensed imagery.

  11. Synergy of Classical and Model-Based Object-Oriented (OO Metrics in Reducing Test Costs

    Directory of Open Access Journals (Sweden)

    M. Raviraja Holla

    2014-05-01

    Full Text Available Software testing and maintenance being interleaved phases span more in software life cycle. The efforts to minimize this span rely obviously on testing when maintenance is natural. The features of Object-Oriented (OO software systems, when compared to the classical systems, claim much reducing the maintenance costwithout necessarily thepossibility of maintenance itself. It is natural that even such systems evolve due to many reasons. Though the specific reasons leading to the maintenance differ, the general rationale behind maintenance is to enhance the life-cycleand possibly the value of the existing system. Hence testing effort is more natural and significant even then. Moreover, the salient features of OO software systems furtherance the testing span despite their claim on maintenance. However, the availability of classical OO software metrics aid better early quality testing of OO systems. They exploit the critical parts of OO software systems thereby offering timely, thorough, and effective assurance. However there is not yet a common metric model in this regard. On the other hand, it is expected that the evolved model-based OO software metrics help define the subjective features more objectively facilitating users to perform metrics activities. The conflation of both classical and model-based metrics mutually alleviates their limitations and brings more synergy in reducing the test costs of OO software systems.

  12. An object based approach for coastline extraction from Quickbird multispectral images

    Directory of Open Access Journals (Sweden)

    Massimiliano Basile Giannini

    2014-12-01

    Full Text Available Because of the reduced dimensions of pixels, in the last years high resolution satellite images (Quickbird, IKONOS, GeoEye, ….. are considered very important data to extract information for coastline monitoring and engineering opera planning. They can integrate detail topographic maps and aerial photos so to contribute to modifications recognition and coastal dynamics reconstruction. Many studies have been carried out on coastline detection from high resolution satellite images: unsupervised and supervised classification, segmentation, NDVI (Normalized Difference Vegetation Index and NDWI (Normalized Difference Water Index are only some of the methodological aspects that have been already considered and experimented. This paper is aimed to implement an object based approach to extract coastline from Quickbird multispectral imagery. Domitian area near Volturno River mouth in Campania Region (Italy, an interesting zone for its dynamics and evolution, is considered. Object based approach is developed for automatic detection of coastline from Quickbird imagery using the Feature Extraction Workflow implemented in ENVI Zoom software. The resulting vector polyline is performed using the smoothing algorithm named PAEK (Polynomial Approximation with Exponential Kernel.

  13. Object-based approach to national land cover mapping using HJ satellite imagery

    Science.gov (United States)

    Zhang, Lei; Li, Xiaosong; Yuan, Quanzhi; Liu, Yu

    2014-01-01

    To meet the carbon storage estimate in ecosystems for a national carbon strategy, we introduce a consistent database of China land cover. The Chinese Huan Jing (HJ) satellite is proven efficient in the cloud-free acquisition of seasonal image series in a monsoon region and in vegetation identification for mesoscale land cover mapping. Thirty-eight classes of level II land cover are generated based on the Land Cover Classification System of the United Nations Food and Agriculture Organization that follows a standard and quantitative definition. Twenty-four layers of derivative spectral, environmental, and spatial features compose the classification database. Object-based approach characterizing additional nonspectral features is conducted through mapping, and multiscale segmentations are applied on object boundary match to target real-world conditions. This method sufficiently employs spatial information, in addition to spectral characteristics, to improve classification accuracy. The algorithm of hierarchical classification is employed to follow step-by-step procedures that effectively control classification quality. This algorithm divides the dual structures of universal and local trees. Consistent universal trees suitable to most regions are performed first, followed by local trees that depend on specific features of nine climate stratifications. The independent validation indicates the overall accuracy reaches 86%.

  14. Evidence-based robust design of deflection actions for near Earth objects

    Science.gov (United States)

    Zuiani, Federico; Vasile, Massimiliano; Gibbings, Alison

    2012-10-01

    This paper presents a novel approach to the robust design of deflection actions for near Earth objects (NEO). In particular, the case of deflection by means of solar-pumped laser ablation is studied here in detail. The basic idea behind laser ablation is that of inducing a sublimation of the NEO surface, which produces a low thrust thereby slowly deviating the asteroid from its initial Earth threatening trajectory. This work investigates the integrated design of the space-based laser system and the deflection action generated by laser ablation under uncertainty. The integrated design is formulated as a multi-objective optimisation problem in which the deviation is maximised and the total system mass is minimised. Both the model for the estimation of the thrust produced by surface laser ablation and the spacecraft system model are assumed to be affected by epistemic uncertainties (partial or complete lack of knowledge). Evidence Theory is used to quantify these uncertainties and introduce them in the optimisation process. The propagation of the trajectory of the NEO under the laser-ablation action is performed with a novel approach based on an approximated analytical solution of Gauss' variational equations. An example of design of the deflection of asteroid Apophis with a swarm of spacecraft is presented.

  15. Object based change detection of Central Asian Tugai vegetation with very high spatial resolution satellite imagery

    Science.gov (United States)

    Gärtner, Philipp; Förster, Michael; Kurban, Alishir; Kleinschmit, Birgit

    2014-09-01

    Ecological restoration of degraded riparian Tugai forests in north-western China is a key driver to combat desertification in this region. Recent restoration efforts attempt to recover the forest along with its most dominant tree species, Populus euphratica. The present research observed the response of natural vegetation using an object based change detection method on QuickBird (2005) and WorldView2 (2011) data. We applied the region growing approach to derived Normalized Difference Vegetation Index (NDVI) values in order to identify single P. euphratica trees, delineate tree crown areas and quantify crown diameter changes. Results were compared to 59 reference trees. The findings confirmed a positive tree crown growth and suggest a crown diameter increase of 1.14 m, on average. On a single tree basis, tree crown diameters of larger crowns were generally underestimated. Small crowns were slightly underestimated in QuickBird and overestimated in Worldview2 images. The results of the automated tree crown delineation show a moderate relation to field reference data with R20052: 0.36 and R20112: 0.48. The object based image analysis (OBIA) method proved to be applicable in sparse riparian Tugai forests and showed great suitability to evaluate ecological restoration efforts in an endangered ecosystem.

  16. Application of In-Segment Multiple Sampling in Object-Based Classification

    Directory of Open Access Journals (Sweden)

    Nataša ?uri?

    2014-12-01

    Full Text Available When object-based analysis is applied to very high-resolution imagery, pixels within the segments reveal large spectral inhomogeneity; their distribution can be considered complex rather than normal. When normality is violated, the classification methods that rely on the assumption of normally distributed data are not as successful or accurate. It is hard to detect normality violations in small samples. The segmentation process produces segments that vary highly in size; samples can be very big or very small. This paper investigates whether the complexity within the segment can be addressed using multiple random sampling of segment pixels and multiple calculations of similarity measures. In order to analyze the effect sampling has on classification results, statistics and probability value equations of non-parametric two-sample Kolmogorov-Smirnov test and parametric Student’s t-test are selected as similarity measures in the classification process. The performance of both classifiers was assessed on a WorldView-2 image for four land cover classes (roads, buildings, grass and trees and compared to two commonly used object-based classifiers—k-Nearest Neighbor (k-NN and Support Vector Machine (SVM. Both proposed classifiers showed a slight improvement in the overall classification accuracies and produced more accurate classification maps when compared to the ground truth image.

  17. A Step Forward To Component-based Software Cost Estimation in Object-oriented Environment

    CERN Document Server

    Ahmed, Nadeem; Qureshi, M Rizwan Jameel

    2012-01-01

    Software cost estimation (SCE) of a project is pivotal to the acceptance or rejection of the development of software project. Various SCE techniques have been in practice with their own strengths and limitations. The latest of these is object-oriented one. Currently object-oriented approach for SCE is based on Line of Code (LOC), function points, functions and classes etc. Relatively less attention has been paid to the SCE in component-based software engineering (CBSE). So there is a pressing need to search parameters/variables that have a vital role for the SCE using CBSE which is taken up in this paper. This paper further looks at level of significance of all the parameters/variables thus searched. The time is being used as an independent variable because time is a parameter which is almost, all previous in one. Therefore this approach may be in a way an alternate of all previous approaches. Infact the underlying research ultimately may lead towards SCE of complex systems, using CBSE, in a scientific, syste...

  18. Development of the competency-based objective resident education using virtual patients system

    Directory of Open Access Journals (Sweden)

    Christopher Becket Mahnke

    2011-01-01

    Full Text Available The Accreditation Council for Graduate Medical Education (ACGME requires U.S. physician training programs to teach and evaluate their trainees in six core competencies. Developing innovative methods to meet the ACGME requirements is an ongoing area of research in medical education. Here we describe the development of the Competency-based Objective Resident Education using Virtual Patients (CORE-VP system, a web-based virtual patient simulator to teach and measure the ACGME core competencies. The user interface was built on Wavemaker technology including AJAX and javascript. A Flash component allows graphical navigation of the physical exam and linking of digital images and video to desired anatomic areas. The system contains tools for case authorship, management and execution and permits linking of files or web-based hypermedia content. Each case is designed to mimic a real-life patient encounter and includes history, physical exam, laboratory/ radiology, diagnosis and management. Automa­ted, multi-factorial, evaluation metrics were developed for each ACGME core competency. Upon completion of a case trainees receive immediate feedback in the form of an automated Performance Summary. We have developed a web-based virtual patient simulator called CORE-VP to teach and measure the ACGME core competencies. Work is currently underway to test and validate the system.

  19. Informatics in radiology: use of CouchDB for document-based storage of DICOM objects.

    Science.gov (United States)

    Rascovsky, Simón J; Delgado, Jorge A; Sanz, Alexander; Calvo, Víctor D; Castrillón, Gabriel

    2012-01-01

    Picture archiving and communication systems traditionally have depended on schema-based Structured Query Language (SQL) databases for imaging data management. To optimize database size and performance, many such systems store a reduced set of Digital Imaging and Communications in Medicine (DICOM) metadata, discarding informational content that might be needed in the future. As an alternative to traditional database systems, document-based key-value stores recently have gained popularity. These systems store documents containing key-value pairs that facilitate data searches without predefined schemas. Document-based key-value stores are especially suited to archive DICOM objects because DICOM metadata are highly heterogeneous collections of tag-value pairs conveying specific information about imaging modalities, acquisition protocols, and vendor-supported postprocessing options. The authors used an open-source document-based database management system (Apache CouchDB) to create and test two such databases; CouchDB was selected for its overall ease of use, capability for managing attachments, and reliance on HTTP and Representational State Transfer standards for accessing and retrieving data. A large database was created first in which the DICOM metadata from 5880 anonymized magnetic resonance imaging studies (1,949,753 images) were loaded by using a Ruby script. To provide the usual DICOM query functionality, several predefined "views" (standard queries) were created by using JavaScript. For performance comparison, the same queries were executed in both the CouchDB database and a SQL-based DICOM archive. The capabilities of CouchDB for attachment management and database replication were separately assessed in tests of a similar, smaller database. Results showed that CouchDB allowed efficient storage and interrogation of all DICOM objects; with the use of information retrieval algorithms such as map-reduce, all the DICOM metadata stored in the large database were searchable with only a minimal increase in retrieval time over that with the traditional database management system. Results also indicated possible uses for document-based databases in data mining applications such as dose monitoring, quality assurance, and protocol optimization. PMID:22403116

  20. Enhanced Genetic Algorithm based computation technique for multi-objective Optimal Power Flow solution

    Energy Technology Data Exchange (ETDEWEB)

    Kumari, M. Sailaja; Maheswarapu, Sydulu [Department of Electrical Engineering, National Institute of Technology, Warangal (India)

    2010-07-15

    Optimal Power Flow (OPF) is used for developing corrective strategies and to perform least cost dispatches. In order to guide the decision making of power system operators a more robust and faster OPF algorithm is needed. OPF can be solved for minimum generation cost, that satisfies the power balance equations and system constraints. But, cost based OPF solutions usually result in unattractive system losses and voltage profiles. In the present paper the OPF problem is formulated as a multi-objective optimization problem, where optimal control settings for simultaneous minimization of fuel cost and loss, loss and voltage stability index, fuel cost and voltage stability index and finally fuel cost, loss and voltage stability index are obtained. The present paper combines a new Decoupled Quadratic Load Flow (DQLF) solution with Enhanced Genetic Algorithm (EGA) to solve the OPF problem. A Strength Pareto Evolutionary Algorithm (SPEA) based approach with strongly dominated set of solutions is used to form the pareto-optimal set. A hierarchical clustering technique is employed to limit the set of trade-off solutions. Finally a fuzzy based approach is used to obtain the optimal solution from the tradeoff curve. The proposed multi-objective evolutionary algorithm with EGA-DQLF model for OPF solution determines diverse pareto optimal front in just 50 generations. IEEE 30 bus system is used to demonstrate the behavior of the proposed approach. The obtained final optimal solution is compared with that obtained using Particle Swarm Optimization (PSO) and Fuzzy satisfaction maximization approach. The results using EGA-DQLF with SPEA approach show their superiority over PSO-Fuzzy approach. (author)

  1. Design based Object-Oriented Metrics to Measure Coupling and Cohesion

    Directory of Open Access Journals (Sweden)

    PREETI GULIA

    2011-11-01

    Full Text Available The object oriented design and object oriented development environment are currently popular in software organizations due to the object oriented programming languages. As the object oriented technology enters into software organizations, it has created new challenges for the companies which used only product metrics as atool for monitoring, controlling and maintaining the software product. This paper presents the new object oriented metrics namely for coupling of class by counting the number of associated classes within a class & total associated class and cohesion at the method and function level for cohesion to estimates object oriented software. In order to this, we discuss in this paper object oriented issues and measures with analysis of object oriented metrics through coupling and cohesion to check the complexity with weight count method. We also discuses the estimation process after analysis of proposed object oriented metrics to measures and check the better performance of object oriented metrics in comparison to other object oriented metrics.

  2. Objektno usmerjena analiza podatkov daljinskega zaznavanja : Object-based image analysis of remote sensing data

    Directory of Open Access Journals (Sweden)

    Krištof Oštir

    2011-01-01

    Full Text Available Na podro?ju daljinskega zaznavanja se razvijajo razli?ne metode in tehnologije za brezkontaktno in stroškovno u?inkovito izdelavo kart pokrovnosti/rabe tal na velikih obmo?jih ter drugih tematskih kart. Osrednjega pomena za zadostno razpoložljivost in zanesljivost takšnih kart za raziskave zemeljskega površja je razvoj u?inkovitih postopkov analize in klasifikacije posnetkov. Za klasifikacijo satelitskih posnetkov nizke in srednje lo?ljivosti (njihova prostorska lo?ljivost je kve?jemu primerljiva z velikostjo geografskih objektov zadostuje uporaba pikselsko usmerjene klasifikacije, pri kateri posami?ni piksel razvrstimo v najprimernejši razred na podlagi njegovih spektralnih lastnosti. Ko pove?ujemo prostorsko lo?ljivost posnetkov, pikselska klasifikacija ni ve? u?inkovita. Bistveno se namre? spremeni razmerje med velikostjo piksla na eni ter razsežnostjo in detajlom opazovanih elementov (objektov geografske stvarnosti na drugi strani. V zadnjem desetletju se zato vse bolj uveljavlja objektno usmerjen pristop obdelave podob. Ta združuje segmentacijo, ki je temeljna faza za razmejevanje geografskih elementov, in klasifikacijo, ki je semanti?no (kontekstualno podprta. Segmentacija razdeli podobo na homogene skupine pikslov (segmente, semanti?na klasifikacija pa jih nato razvrš?a v razrede na podlagi njihovih spektralnih, geometri?nih, teksturnih in drugih lastnosti. Namen prispevka je predstaviti teoreti?no utemeljitev in metodologijo objektno usmerjene obdelave v daljinskem zaznavanju, podati pregled stanja na podro?ju ter opozoriti na nekatere omejitve tehni?nih rešitev ; Remote sensing has developed various methods and technologies for contactless and cost-effective mapping of large area land cover/land use maps and other thematic maps. The key factor for the availability and reliability of these maps for use in Earth sciences is the development of effective procedures for satellite data analysis and classification. The most appropriate approach for classifying low and medium resolution satellite images (pixel size is coarser than, or at best similar to, the size of geographical objects is pixel-based classification in which an individual pixel is classified into the closest class based on its spectral similarity. With increasing spatial resolution, pixel-based classification methods became less effective, since the relationship between the pixel size and the dimension of the observed objects on the Earth's surface has changed significantly. Therefore object-oriented classification has become increasingly popular over the past decade. This combines segmentation (which is a fundamental phase of the approach and contextual classification. Segmentation divides the image into homogeneous pixel groups (segments, which are – during the semantic classification process - arranged into classes based on their spectral, geometric, textural and other features during. The intent of this paper is to present the theoretical argumentation and methodology of object-based image analysis of remote sensing data, provide an overview of the field and point out certain restrictions as regards the current operational solutions.

  3. Object-based image analysis of remote sensing data ; Objektno usmerjena analiza podatkov daljinskega zaznavanja

    Directory of Open Access Journals (Sweden)

    Tatjana Veljanovski

    2011-01-01

    Full Text Available Na podro?ju daljinskega zaznavanja se razvijajo razli?ne metode in tehnologije za brezkontaktno in stroškovno u?inkovito izdelavo kart pokrovnosti/rabe tal na velikih obmo?jih ter drugih tematskih kart. Osrednjega pomena za zadostno razpoložljivost in zanesljivost takšnih kart za raziskave zemeljskega površja je razvoj u?inkovitih postopkov analize in klasifikacije posnetkov. Za klasifikacijo satelitskih posnetkov nizke in srednje lo?ljivosti (njihova prostorska lo?ljivost je kve?jemu primerljiva z velikostjo geografskih objektov zadostuje uporaba pikselsko usmerjene klasifikacije, pri kateri posami?ni piksel razvrstimo v najprimernejši razred na podlagi njegovih spektralnih lastnosti. Ko pove?ujemo prostorsko lo?ljivost posnetkov, pikselska klasifikacija ni ve? u?inkovita. Bistveno se namre? spremeni razmerje med velikostjo piksla na eni ter razsežnostjo in detajlom opazovanih elementov (objektov geografske stvarnosti na drugi strani. V zadnjem desetletju se zato vse bolj uveljavlja objektno usmerjen pristop obdelave podob. Ta združuje segmentacijo, ki je temeljna faza za razmejevanje geografskih elementov, in klasifikacijo, ki je semanti?no (kontekstualno podprta. Segmentacija razdeli podobo na homogene skupine pikslov (segmente, semanti?na klasifikacija pa jih nato razvrš?a v razrede na podlagi njihovih spektralnih, geometri?nih, teksturnih in drugih lastnosti. Namen prispevka je predstaviti teoreti?no utemeljitev in metodologijo objektno usmerjene obdelave v daljinskem zaznavanju, podati pregled stanja na podro?ju ter opozoriti na nekatere omejitve tehni?nih rešitev ; Remote sensing has developed various methods and technologies for contactless and cost-effective mapping of large area land cover/land use maps and other thematic maps. The key factor for the availability and reliability of these maps for use in Earth sciences is the development of effective procedures for satellite data analysis and classification. The most appropriate approach for classifying low and medium resolution satellite images (pixel size is coarser than, or at best similar to, the size of geographical objects is pixel-based classification in which an individual pixel is classified into the closest class based on its spectral similarity. With increasing spatial resolution, pixel-based classification methods became less effective, since the relationship between the pixel size and the dimension of the observed objects on the Earth's surface has changed significantly. Therefore object-oriented classification has become increasingly popular over the past decade. This combines segmentation (which is a fundamental phase of the approach and contextual classification. Segmentation divides the image into homogeneous pixel groups (segments, which are – during the semantic classification process - arranged into classes based on their spectral, geometric, textural and other features during. The intent of this paper is to present the theoretical argumentation and methodology of object-based image analysis of remote sensing data, provide an overview of the field and point out certain restrictions as regards the current operational solutions.

  4. Mapping Arctic Ocean Coastline Change With Landsat Archive Data And Object-Based Image Analysis

    Science.gov (United States)

    Hulslander, D.

    2010-12-01

    The melting of arctic permafrost is a significant effect of climate change. The combination of rising sea level, longer periods of ice-free conditions in the Arctic Ocean and melting permafrost can greatly accelerate coastline changes in general and arctic coastal erosion in particular. Anderson et al. (2009; Geology News) have measured erosion rates of 15 m per year at sites along the Alaskan Arctic Ocean coastline dominated by ice-cemented peats and silt-rich permafrost. With over 45,000 km of Arctic Ocean coastline, it is important that coastline movement and transgressive oceanic regimes be mapped and tracked with accurate data. Determining historic coastal erosion rates for this region is as important as mapping the current extent of the phenomenon to create as complete a picture as possible and locate where rapid erosion is an emergent process. The extent of the area involved combined with its inaccessibility and inhospitable conditions makes geologic remote sensing an appropriate tool for characterizing Arctic Ocean coastal erosion. Traditional weaknesses associated with using remote sensing in the geosciences have included a lack of historical data or baseline information as well as difficulties in systematization of feature mapping. Using object-based image analysis on Landsat archive data can overcome these issues and may allow for a potential multi-decadal map of Arctic Ocean coastline changes. The Landsat family of sensors (MSS 1-3 and TM/ETM 4, 5, and 7) have been providing imagery as frequently as every 16 days since July 1972. The frequent revisits maximize the chance of getting cloud-free imagery at least once per year in most study areas. Also, Landsat data are well characterized, extensively studied, and freely available from the USGS EROS Data Center Archive, making it an ideal and stable source of data for mapping the Arctic Ocean coastline. Delineating large sections of coastline from imagery by hand digitization would be impractical due to the time, labor and expense involved with manual polyline and map layer creation. Furthermore, differences in interpretation by analysts can create data quality and reliability issues. Object-based image analysis techniques have been shown (Hulslander et al., 2008; GEOBIA 2008 Proceedings) to produce results comparable to those from analysts, but can also do so in a reproducible fashion that can be automated. Here, results indicate that using object-based image analysis on Landsat archive data can produce coastline maps in the arctic which clearly show coastline dynamics and trends over decades. Furthermore, these preliminary results also show that a pan-Arctic Ocean coastline map could be produced on a roughly triennial basis for the past 30-plus years using these techniques.

  5. A Python-Based Open Source System for Geographic Object-Based Image Analysis (GEOBIA Utilizing Raster Attribute Tables

    Directory of Open Access Journals (Sweden)

    Daniel Clewley

    2014-06-01

    Full Text Available A modular system for performing Geographic Object-Based Image Analysis (GEOBIA, using entirely open source (General Public License compatible software, is presented based around representing objects as raster clumps and storing attributes as a raster attribute table (RAT. The system utilizes a number of libraries, developed by the authors: The Remote Sensing and GIS Library (RSGISLib, the Raster I/O Simplification (RIOS Python Library, the KEA image format and TuiView image viewer. All libraries are accessed through Python, providing a common interface on which to build processing chains. Three examples are presented, to demonstrate the capabilities of the system: (1 classification of mangrove extent and change in French Guiana; (2 a generic scheme for the classification of the UN-FAO land cover classification system (LCCS and their subsequent translation to habitat categories; and (3 a national-scale segmentation for Australia. The system presented provides similar functionality to existing GEOBIA packages, but is more flexible, due to its modular environment, capable of handling complex classification processes and applying them to larger datasets.

  6. Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation

    Directory of Open Access Journals (Sweden)

    Li Honglin

    2009-03-01

    Full Text Available Abstract Background Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem, ranging from deterministic to non-deterministic and systemic to stochastic ones. In this work, we described an efficient conformation sampling method named Cyndi, which is based on multi-objective evolution algorithm. Results The conformational perturbation is subjected to evolutionary operation on the genome encoded with dihedral torsions. Various objectives are designated to render the generated Pareto optimal conformers to be energy-favoured as well as evenly scattered across the conformational space. An optional objective concerning the degree of molecular extension is added to achieve geometrically extended or compact conformations which have been observed to impact the molecular bioactivity (J Comput -Aided Mol Des 2002, 16: 105–112. Testing the performance of Cyndi against a test set consisting of 329 small molecules reveals an average minimum RMSD of 0.864 Å to corresponding bioactive conformations, indicating Cyndi is highly competitive against other conformation generation methods. Meanwhile, the high-speed performance (0.49 ± 0.18 seconds per molecule renders Cyndi to be a practical toolkit for conformational database preparation and facilitates subsequent pharmacophore mapping or rigid docking. The copy of precompiled executable of Cyndi and the test set molecules in mol2 format are accessible in Additional file 1. Conclusion On the basis of MOEA algorithm, we present a new, highly efficient conformation generation method, Cyndi, and report the results of validation and performance studies comparing with other four methods. The results reveal that Cyndi is capable of generating geometrically diverse conformers and outperforms other four multiple conformer generators in the case of reproducing the bioactive conformations against 329 structures. The speed advantage indicates Cyndi is a powerful alternative method for extensive conformational sampling and large-scale conformer database preparation.

  7. Fault Management in an Objectives-Based/Risk-Informed View of Safety and Mission Success

    Science.gov (United States)

    Groen, Frank

    2012-01-01

    Theme of this talk: (1) Net-benefit of activities and decisions derives from objectives (and their priority) -- similarly: need for integration, value of technology/capability. (2) Risk is a lack of confidence that objectives will be met. (2a) Risk-informed decision making requires objectives. (3) Consideration of objectives is central to recent guidance.

  8. A hybrid biomechanical model-based image registration method for sliding objects

    Science.gov (United States)

    Han, Lianghao; Hawkes, David; Barratt, Dean

    2014-03-01

    The sliding motion between two anatomic structures, such as lung against chest wall, liver against surrounding tissues, produces a discontinuous displacement field between their boundaries. Capturing the sliding motion is quite challenging for intensity-based image registration methods in which a smoothness condition has commonly been applied to ensure the deformation consistency of neighborhood voxels. Such a smoothness constraint contradicts motion physiology at the boundaries of these anatomic structures. Although various regularisation schemes have been developed to handle sliding motion under the framework of non-rigid intensity-based image registration, the recovered displacement field may still not be physically plausible. In this study, a new framework that incorporates a patient-specific biomechanical model with a non-rigid image registration scheme for motion estimation of sliding objects has been developed. The patient-specific model provides the motion estimation with an explicit simulation of sliding motion, while the subsequent non-rigid image registration compensates for smaller residuals of the deformation due to the inaccuracy of the physical model. The algorithm was tested against the results of the published literature using 4D CT data from 10 lung cancer patients. The target registration error (TRE) of 3000 landmarks with the proposed method (1.37+/-0.89 mm) was significantly lower than that with the popular B-spline based free form deformation (FFD) registration (4.5+/-3.9 mm), and was smaller than that using the B-spline based FFD registration with the sliding constraint (1.66+/-1.14 mm) or using the B-spline based FFD registration on segmented lungs (1.47+/-1.1 mm). A paired t-test showed that the improvement of registration performance with the proposed method was significant (p<0.01). The propose method also achieved the best registration performance on the landmarks near lung surfaces. Since biomechanical models captured most of the lung deformation, the final estimated deformation field was more physically plausible.

  9. ETEA: a Euclidean minimum spanning tree-based evolutionary algorithm for multi-objective optimization.

    Science.gov (United States)

    Li, Miqing; Yang, Shengxiang; Zheng, Jinhua; Liu, Xiaohui

    2014-01-01

    The Euclidean minimum spanning tree (EMST), widely used in a variety of domains, is a minimum spanning tree of a set of points in space where the edge weight between each pair of points is their Euclidean distance. Since the generation of an EMST is entirely determined by the Euclidean distance between solutions (points), the properties of EMSTs have a close relation with the distribution and position information of solutions. This paper explores the properties of EMSTs and proposes an EMST-based evolutionary algorithm (ETEA) to solve multi-objective optimization problems (MOPs). Unlike most EMO algorithms that focus on the Pareto dominance relation, the proposed algorithm mainly considers distance-based measures to evaluate and compare individuals during the evolutionary search. Specifically, in ETEA, four strategies are introduced: (1) An EMST-based crowding distance (ETCD) is presented to estimate the density of individuals in the population; (2) A distance comparison approach incorporating ETCD is used to assign the fitness value for individuals; (3) A fitness adjustment technique is designed to avoid the partial overcrowding in environmental selection; (4) Three diversity indicators-the minimum edge, degree, and ETCD-with regard to EMSTs are applied to determine the survival of individuals in archive truncation. From a series of extensive experiments on 32 test instances with different characteristics, ETEA is found to be competitive against five state-of-the-art algorithms and its predecessor in providing a good balance among convergence, uniformity, and spread. PMID:23746293

  10. Ecosystem-based management objectives for the North Sea : riding the forage fish rollercoaster

    DEFF Research Database (Denmark)

    Dickey-Collas, M.; Engelhard, G. H.

    2014-01-01

    The North Sea provides a useful model for considering forage fish (FF) within ecosystem-based management as it has a complex assemblage of FF species. This paper is designed to encourage further debate and dialogue between stakeholders about management objectives. Changing the management of fisheries on FF will have economic consequences for all fleets in the North Sea. The predators that are vulnerable to the depletion of FF are Sandwich terns, great skua and common guillemots, and to a lesser extent, marine mammals. Comparative evaluations of management strategies are required to consider whether maintaining the reserves of prey biomass or a more integral approach of monitoring mortality rates across the trophic system is more robust under the ecosystem approach. In terms of trophic energy transfer, stability, and resilience of the ecosystem, FF should be considered as both a sized-based pool of biomass and as species components of the system by managers and modellers. Policy developers should not consider the knowledge base robust enough to embark on major projects of ecosystem engineering. Management plans appear able to maintain sustainable exploitation in the short term. Changes in the productivity of FF populations are inevitable so management should remain responsive and adaptive.

  11. A supervised method for object-based 3D building change detection on aerial stereo images

    Science.gov (United States)

    Qin, R.; Gruen, A.

    2014-08-01

    There is a great demand for studying the changes of buildings over time. The current trend for building change detection combines the orthophoto and DSM (Digital Surface Models). The pixel-based change detection methods are very sensitive to the quality of the images and DSMs, while the object-based methods are more robust towards these problems. In this paper, we propose a supervised method for building change detection. After a segment-based SVM (Support Vector Machine) classification with features extracted from the orthophoto and DSM, we focus on the detection of the building changes of different periods by measuring their height and texture differences, as well as their shapes. A decision tree analysis is used to assess the probability of change for each building segment and the traffic lighting system is used to indicate the status "change", "non-change" and "uncertain change" for building segments. The proposed method is applied to scanned aerial photos of the city of Zurich in 2002 and 2007, and the results have demonstrated that our method is able to achieve high detection accuracy.

  12. Task Scheduling Model Based on Multi-Agent and Multi-Objective Dynamical Scheduling Algorithm

    Directory of Open Access Journals (Sweden)

    Zhanjie Wang

    2014-06-01

    Full Text Available With the increasing number of nodes in distributed systems, the complexity of task scheduling also increases. Therefore, how to schedule tasks reasonably is becoming more and more significant. Most traditional algorithms only consider a single condition without thinking over dynamic characteristic of system and tasks and lack of comprehensive measures. Therefore they cannot meet the needs of distributed systems. To solve these problems, we establish a distributed task scheduling model based on multi-agent in this paper, build a negotiation scheduling mechanism based on the model and propose distributed multi-objective dynamical scheduling algorithm (DMOD. In the algorithm, each node is capable of independent decision-making and dynamical evaluation rules make a comprehensive evaluation of task completion time, system load and communication traffic. DMOD, MinMin and the algorithm based on tree structure (BTS are compared through simulation experiments. Experimental results show that DMOD reduces communication traffic without increasing task completion time, avoids performance degradation caused by sharp increase of system load and communication traffic in distributed system and therefore improves system stability and task execution efficiency

  13. Ecosystem-based management objectives for the North Sea: riding the forage fish rollercoaster

    DEFF Research Database (Denmark)

    Dickey-Collas, Mark; Engelhard, Georg H.

    2014-01-01

    The North Sea provides a useful model for considering forage fish (FF) within ecosystem-based management as it has a complex assemblage of FF species. This paper is designed to encourage further debate and dialogue between stakeholders about management objectives. Changing the management of fisheries on FF will have economic consequences for all fleets in the North Sea. The predators that are vulnerable to the depletion of FF are Sandwich terns, great skua and common guillemots, and to a lesser extent, marine mammals. Comparative evaluations of management strategies are required to consider whether maintaining the reserves of prey biomass or a more integral approach of monitoring mortality rates across the trophic system is more robust under the ecosystem approach. In terms of trophic energy transfer, stability, and resilience of the ecosystem, FF should be considered as both a sized-based pool of biomass and as species components of the system by managers and modellers. Policy developers should not consider the knowledge base robust enough to embark on major projects of ecosystem engineering. Management plans appear able to maintain sustainable exploitation in the short term. Changes in the productivity of FF populations are inevitable so management should remain responsive and adaptive

  14. Road Network Extraction from High Resolution Multispectral Satellite Imagery Based on Object Oriented Techniques

    Science.gov (United States)

    Kumar, M.; Singh, R. K.; Raju, P. L. N.; Krishnamurthy, Y. V. N.

    2014-11-01

    High Resolution satellite Imagery is an important source for road network extraction for urban road database creation, refinement and updating. However due to complexity of the scene in an urban environment, automated extraction of such features using various line and edge detection algorithms is limited. In this paper we present an integrated approach to extract road network from high resolution space imagery. The proposed approach begins with segmentation of the scene with Multi-resolution Object Oriented segmentation. This step focuses on exploiting both spatial and spectral information for the target feature extraction. The road regions are automatically identified using a soft fuzzy classifier based on a set of predefined membership functions. A number of shape descriptors are computed to reduce the misclassifications between road and other spectrally similar objects. The detected road segments are further refined using morphological operations to form final road network, which is then evaluated for its completeness, correctness and quality. The experiments were carried out of fused IKONOS 2 , Quick bird ,Worldview 2 Products with fused resolution's ranging from 0.5m to 1 m. Results indicate that the proposed methodology is effective in extracting accurate road networks from high resolution imagery.

  15. TRENCADIS - secure architecture to share and manage DICOM objects in a ontological framework based on OGSA.

    Science.gov (United States)

    Blanquer, Ignacio; Hernandez, Vicente; Segrelles, Damià; Torres, Erik

    2007-01-01

    Today most European healthcare centers use the digital format for their databases of images. TRENCADIS is a software architecture comprising a set of services as a solution for interconnecting, managing and sharing selected parts of medical DICOM data for the development of training and decision support tools. The organization of the distributed information in virtual repositories is based on semantic criteria. Different groups of researchers could organize themselves to propose a Virtual Organization (VO). These VOs will be interested in specific target areas, and will share information concerning each area. Although the private part of the information to be shared will be removed, special considerations will be taken into account to avoid the access by non-authorized users. This paper describes the security model implemented as part of TRENCADIS. The paper is organized as follows. First introduces the problem and presents our motivations. Section 1 defines the objectives. Section 2 presents an overview of the existing proposals per objective. Section 3 outlines the overall architecture. Section 4 describes how TRENCADIS is architected to realize the security goals discussed in the previous sections. The different security services and components of the infrastructure are briefly explained, as well as the exposed interfaces. Finally, Section 5 concludes and gives some remarks on our future work. PMID:17476054

  16. Objective Probabilistic Forecasts of Future Climate Based on Jeffreys' Prior: the Case of Correlated Observables

    CERN Document Server

    Jewson, Stephen; Allen, Myles

    2010-01-01

    To include parameter uncertainty into probabilistic climate forecasts one must first specify a prior. We advocate the use of objective priors, and, in particular, the Jeffreys' Prior. In previous work we have derived expressions for the Jeffreys' Prior for the case in which the observations are independent and normally distributed. These expressions make the calculation of the prior much simpler than evaluation directly from the definition. In this paper, we now relax the independence assumption and derive expressions for the Jeffreys' Prior for the case in which the observations are distributed with a multivariate normal distribution with constant covariances. Again, these expressions simplify the calculation of the prior: in this case they reduce it to the calculation of the differences between the ensemble means of climate model ensembles based on different parameter settings. These calculations are simple enough to be applied to even the most complex climate models.

  17. Inference and Plausible Reasoning in a Natural Language Understanding System Based on Object-Oriented Semantics

    CERN Document Server

    Ostapov, Yuriy

    2012-01-01

    Algorithms of inference in a computer system oriented to input and semantic processing of text information are presented. Such inference is necessary for logical questions when the direct comparison of objects from a question and database can not give a result. The following classes of problems are considered: a check of hypotheses for persons and non-typical actions, the determination of persons and circumstances for non-typical actions, planning actions, the determination of event cause and state of persons. To form an answer both deduction and plausible reasoning are used. As a knowledge domain under consideration is social behavior of persons, plausible reasoning is based on laws of social psychology. Proposed algorithms of inference and plausible reasoning can be realized in computer systems closely connected with text processing (criminology, operation of business, medicine, document systems).

  18. Video object segmentation via adaptive threshold based on background model diversity

    Science.gov (United States)

    Boubekeur, Mohamed Bachir; Luo, SenLin; Labidi, Hocine; Benlefki, Tarek

    2015-03-01

    The background subtraction could be presented as classification process when investigating the upcoming frames in a video stream, taking in consideration in some cases: a temporal information, in other cases the spatial consistency, and these past years both of the considerations above. The classification often relied in most of the cases on a fixed threshold value. In this paper, a framework for background subtraction and moving object detection based on adaptive threshold measure and short/long frame differencing procedure is proposed. The presented framework explored the case of adaptive threshold using mean squared differences for a sampled background model. In addition, an intuitive update policy which is neither conservative nor blind is presented. The algorithm succeeded on extracting the moving foreground and isolating an accurate background.

  19. EVALUATION OF SUSTAINABLE DEVELOPMENT INDICATORS WITH FUZZY TOPSIS BASED ON SUBJECTIVE AND OBJECTIVE WEIGHTS

    Directory of Open Access Journals (Sweden)

    Nang Idayu Nik Zahari

    2012-04-01

    Full Text Available Sustainable development aims at improving and maintaining the well-being of people and the ecology. However, this paper focuses only on the ecological aspects. The selection of the proper ecological protection determinant plays a very important role in improving the environment of Malaysia. This paper will propose a method from Wang and Lee (2009, and Yong (2006 which applies a fuzzy TOPSIS method -- based on subjective and objective weights – to make the required selection. Four alternatives will be tested which are: prevent pollution (A1, conservation (A2, well-manage (A3, and public awareness (A4. Along with these, four criteria need to be considered: water quality factor (C1, land integrity factor (C2, air quality factor (C3, and biodiversity factor (C4. Finally, a numerical example of ecological protection determinant selection is used to illustrate the proposed method.

  20. AN APPROACH FOR OBJECT FINDING USING MOBILE ROBOTS BASED ON ACO

    Directory of Open Access Journals (Sweden)

    Amita.PMeshram

    2011-12-01

    Full Text Available In this paper, we propose Ant Colony Optimization (ACO for mobile robot. This paper describes theanalysis and design of a new class of mobile robots. These small robots are intended to be simple andinexpensive, and will all be physically identical, thus constituting a homogeneous team of robots. Theyderive their usefulness from their group actions, performing physical tasks and making cooperativedecisions as a Coordinated Team. This method based on heuristic concept is used to obtain globalsearch. Since the proposed method is very efficient, thus it can perform object finding very quickly. In theprocess of doing so, we first use ACO to obtain the shortest obstructed distance, which is an effectivemethod for arbitrary shape obstacles.

  1. A feature-based object-oriented expert system to model and support product design

    Scientific Electronic Library Online (English)

    Nilson Luiz, Maziero; João Carlos Espíndola, Ferreira; Fernando Santana, Pacheco; Marcelo Fabrício, Prim.

    Full Text Available In this paper a computer program to model and support product design is presented. The product is represented through a hierarchical structure that allows the user to navigate across the product’s components, and it aims at facilitating each step of the detail design process. A graphical interface w [...] as also developed, which shows visually to the user the contents of the product structure. Features are used as building blocks for the parts that compose the product, and object-oriented methodology was used as a means to implement the product structure. Finally, an expert system was also implemented, whose knowledge base rules help the user design a product that meets design and manufacturing requirements.

  2. A feature-based object-oriented expert system to model and support product design

    Directory of Open Access Journals (Sweden)

    Maziero Nilson Luiz

    2000-01-01

    Full Text Available In this paper a computer program to model and support product design is presented. The product is represented through a hierarchical structure that allows the user to navigate across the product?s components, and it aims at facilitating each step of the detail design process. A graphical interface was also developed, which shows visually to the user the contents of the product structure. Features are used as building blocks for the parts that compose the product, and object-oriented methodology was used as a means to implement the product structure. Finally, an expert system was also implemented, whose knowledge base rules help the user design a product that meets design and manufacturing requirements.

  3. Practical Study on HVAC Control Technology Based on the Learning Function and Optimum Multiple Objective Processes

    Science.gov (United States)

    Ueda, Haruka; Dazai, Ryota; Kaseda, Chosei; Ikaga, Toshiharu; Kato, Akihiro

    Demand among large office buildings for the energy-saving benefits of the HVAC (Heating, Ventilating and Air-Conditioning) System are increasing as more and more people become concerned with global environmental issues. However, immoderate measures taken in the interest of energy conservation may encroach on the thermal comfort and productivity level of office workers. Building management should satisfy both indoor thermal comfort and energy conservation while adapting to the many regulatory, social, climate, and other changes that occur during the lifespan of the building. This paper demonstrates how optimal control of the HVAC system, based on data modeling and the multi-objective optimal method, achieves an efficient equilibrium between thermal comfort and energy conservation.

  4. Intra-Inter Triplet Object Interaction Mechanism in Triplet-Based Hierarchical Interconnection Network

    OpenAIRE

    Shahnawaz Talpur; Imran Ali Qureshi; Shahnawaz Farhan Khahro

    2013-01-01

    Object oriented languages usually avoid direct message passing, due to its complicated implementation, though that is the promising way to communicate in concurrently inherited objects. With the advancement in the high performance computing system, interaction between parallel application objects onto physical cores becomes one of the significant issues, which is not fully explored yet. In object oriented programming attribute data is included in objects and their state can be changed using t...

  5. Mapping seabed sediments: Comparison of manual, geostatistical, object-based image analysis and machine learning approaches

    Science.gov (United States)

    Diesing, Markus; Green, Sophie L.; Stephens, David; Lark, R. Murray; Stewart, Heather A.; Dove, Dayton

    2014-08-01

    Marine spatial planning and conservation need underpinning with sufficiently detailed and accurate seabed substrate and habitat maps. Although multibeam echosounders enable us to map the seabed with high resolution and spatial accuracy, there is still a lack of fit-for-purpose seabed maps. This is due to the high costs involved in carrying out systematic seabed mapping programmes and the fact that the development of validated, repeatable, quantitative and objective methods of swath acoustic data interpretation is still in its infancy. We compared a wide spectrum of approaches including manual interpretation, geostatistics, object-based image analysis and machine-learning to gain further insights into the accuracy and comparability of acoustic data interpretation approaches based on multibeam echosounder data (bathymetry, backscatter and derivatives) and seabed samples with the aim to derive seabed substrate maps. Sample data were split into a training and validation data set to allow us to carry out an accuracy assessment. Overall thematic classification accuracy ranged from 67% to 76% and Cohen's kappa varied between 0.34 and 0.52. However, these differences were not statistically significant at the 5% level. Misclassifications were mainly associated with uncommon classes, which were rarely sampled. Map outputs were between 68% and 87% identical. To improve classification accuracy in seabed mapping, we suggest that more studies on the effects of factors affecting the classification performance as well as comparative studies testing the performance of different approaches need to be carried out with a view to developing guidelines for selecting an appropriate method for a given dataset. In the meantime, classification accuracy might be improved by combining different techniques to hybrid approaches and multi-method ensembles.

  6. Object based image analysis for the classification of the growth stages of Avocado crop, in Michoacán State, Mexico

    Science.gov (United States)

    Gao, Yan; Marpu, Prashanth; Morales Manila, Luis M.

    2014-11-01

    This paper assesses the suitability of 8-band Worldview-2 (WV2) satellite data and object-based random forest algorithm for the classification of avocado growth stages in Mexico. We tested both pixel-based with minimum distance (MD) and maximum likelihood (MLC) and object-based with Random Forest (RF) algorithm for this task. Training samples and verification data were selected by visual interpreting the WV2 images for seven thematic classes: fully grown, middle stage, and early stage of avocado crops, bare land, two types of natural forests, and water body. To examine the contribution of the four new spectral bands of WV2 sensor, all the tested classifications were carried out with and without the four new spectral bands. Classification accuracy assessment results show that object-based classification with RF algorithm obtained higher overall higher accuracy (93.06%) than pixel-based MD (69.37%) and MLC (64.03%) method. For both pixel-based and object-based methods, the classifications with the four new spectral bands (overall accuracy obtained higher accuracy than those without: overall accuracy of object-based RF classification with vs without: 93.06% vs 83.59%, pixel-based MD: 69.37% vs 67.2%, pixel-based MLC: 64.03% vs 36.05%, suggesting that the four new spectral bands in WV2 sensor contributed to the increase of the classification accuracy.

  7. Differentiating spatial and object-based effects on attention: an event-related brain potential study with peripheral cueing.

    OpenAIRE

    He, X.; Humphreys, G.; Fan, S.; Chen, L.; Han, S.

    2008-01-01

    Do spatial attention and object attention modulate visual processing in similar ways? Previously we have found a dissociation between these two forms of attention on ERP measures of sensory processing under conditions of peripheral cueing, with spatial attention effects associated with changes over anterior scalp regions and object attention effects associated with changes over posterior regions (He, X., Fan, S., Zhou, K., Chen, L., 2004. Cue validity and object-based attention. J. Cogn. Neur...

  8. Coastal aquifer management based on surrogate models and multi-objective optimization

    Science.gov (United States)

    Mantoglou, A.; Kourakos, G.

    2011-12-01

    The demand for fresh water in coastal areas and islands can be very high, especially in summer months, due to increased local needs and tourism. In order to satisfy demand, a combined management plan is proposed which involves: i) desalinization (if needed) of pumped water to a potable level using reverse osmosis and ii) injection of biologically treated waste water into the aquifer. The management plan is formulated into a multiobjective optimization framework, where simultaneous minimization of economic and environmental costs is desired; subject to a constraint to satisfy demand. The method requires modeling tools, which are able to predict the salinity levels of the aquifer in response to different alternative management scenarios. Variable density models can simulate the interaction between fresh and saltwater; however, they are computationally intractable when integrated in optimization algorithms. In order to alleviate this problem, a multi objective optimization algorithm is developed combining surrogate models based on Modular Neural Networks [MOSA(MNN)]. The surrogate models are trained adaptively during optimization based on a Genetic Algorithm. In the crossover step of the genetic algorithm, each pair of parents generates a pool of offspring. All offspring are evaluated based on the fast surrogate model. Then only the most promising offspring are evaluated based on the exact numerical model. This eliminates errors in Pareto solution due to imprecise predictions of the surrogate model. Three new criteria for selecting the most promising offspring were proposed, which improve the Pareto set and maintain the diversity of the optimum solutions. The method has important advancements compared to previous methods, e.g. alleviation of propagation of errors due to surrogate model approximations. The method is applied to a real coastal aquifer in the island of Santorini which is a very touristy island with high water demands. The results show that the algorithm is capable of solving complex multi-objective optimization problems effectively with significant reduction in computational time compared to previous methods (it requires only 5% of the NSGA -II algorithm time). Further, as indicated in the figure below, the Pareto solution obtained by the much faster MOSA(MNN) algorithm, is better than the solution obtained by the NSGA-II algorithm.

  9. A hybrid evolutionary algorithm for multi-objective anatomy-based dose optimization in high-dose-rate brachytherapy

    International Nuclear Information System (INIS)

    Multiple objectives must be considered in anatomy-based dose optimization for high-dose-rate brachytherapy and a large number of parameters must be optimized to satisfy often competing objectives. For objectives expressed solely in terms of dose variances, deterministic gradient-based algorithms can be applied and a weighted sum approach is able to produce a representative set of non-dominated solutions. As the number of objectives increases, or non-convex objectives are used, local minima can be present and deterministic or stochastic algorithms such as simulated annealing either cannot be used or are not efficient. In this case we employ a modified hybrid version of the multi-objective optimization algorithm NSGA-II. This, in combination with the deterministic optimization algorithm, produces a representative sample of the Pareto set. This algorithm can be used with any kind of objectives, including non-convex, and does not require artificial importance factors. A representation of the trade-off surface can be obtained with more than 1000 non-dominated solutions in 2-5 min. An analysis of the solutions provides information on the possibilities available using these objectives. Simple decision making tools allow the selection of a solution that provides a best fit for the clinical goals. We show an example with a prostate implant and compare results obtained by variance and dose-volume histogram (DVH) based objectives

  10. Analysis of uncertainty in multi-temporal object-based classification

    Science.gov (United States)

    Löw, Fabian; Knöfel, Patrick; Conrad, Christopher

    2015-07-01

    Agricultural management increasingly uses crop maps based on classification of remotely sensed data. However, classification errors can translate to errors in model outputs, for instance agricultural production monitoring (yield, water demand) or crop acreage calculation. Hence, knowledge on the spatial variability of the classier performance is important information for the user. But this is not provided by traditional assessments of accuracy, which are based on the confusion matrix. In this study, classification uncertainty was analyzed, based on the support vector machines (SVM) algorithm. SVM was applied to multi-spectral time series data of RapidEye from different agricultural landscapes and years. Entropy was calculated as a measure of classification uncertainty, based on the per-object class membership estimations from the SVM algorithm. Permuting all possible combinations of available images allowed investigating the impact of the image acquisition frequency and timing, respectively, on the classification uncertainty. Results show that multi-temporal datasets decrease classification uncertainty for different crops compared to single data sets, but there was no "one-image-combination-fits-all" solution. The number and acquisition timing of the images, for which a decrease in uncertainty could be realized, proved to be specific to a given landscape, and for each crop they differed across different landscapes. For some crops, an increase of uncertainty was observed when increasing the quantity of images, even if classification accuracy was improved. Random forest regression was employed to investigate the impact of different explanatory variables on the observed spatial pattern of classification uncertainty. It was strongly influenced by factors related with the agricultural management and training sample density. Lower uncertainties were revealed for fields close to rivers or irrigation canals. This study demonstrates that classification uncertainty estimates by the SVM algorithm provide a valuable addition to traditional accuracy assessments. This allows analyzing spatial variations of the classifier performance in maps and also differences in classification uncertainty within the growing season and between crop types, respectively.

  11. Estimation of Trees Outside Forests using IRS High Resolution data by Object Based Image Analysis

    Science.gov (United States)

    Pujar, G. S.; Reddy, P. M.; Reddy, C. S.; Jha, C. S.; Dadhwal, V. K.

    2014-11-01

    Assessment of Trees outside forests (TOF) is widely being recognized as a pivotal theme, in sustainable natural resource management, due to their role in offering variety of goods, such as timber, fruits and fodder as well as services like water, carbon, biodiversity. Forest Conservation efforts involving reduction of deforestation and degradation may have to increasingly rely on alternatives provided by TOF in catering to economic demands in forest edges. Spatial information systems involving imaging, analysis and monitoring to achieve objectives under protocols like REDD+, require incorporation of information content from areas under forest as well as trees outside forests, to aid holistic decisions. In this perspective, automation in retrieving information on area under trees, growing outside forests, using high resolution imaging is essential so that measuring and verification of extant carbon pools, are strengthened. Retrieval of this tree cover is demonstrated herewith, using object based image analysis in a forest edge of dry deciduous forests of Eastern Ghats, in Khammam district of Telangana state of India. IRS high resolution panchromatic 2.5 m data (Cartosat-1 Orthorectified) used in tandem with 5.8 m multispectral LISS IV data, discerns tree crowns and clusters at a detailed scale and hence semi-automated approach is attempted to classify TOF from a pair of image from relatively crop and cloud free season. Object based image analysis(OBIA) approach as implemented in commercial suite of e-Cognition (Ver 8.9) consists of segmentation at user defined scale followed by application of wide range of spectral, textural and object geometry based parameters for classification. Software offers innovative blend of raster and vector features that can be juxtaposed flexibly, across scales horizontally or vertically. Segmentation was carried out at multiple scales to discern first the major land covers, such as forest, water, agriculture followed by that at a finer scale, within cultivated landscape. Latter scale aimed to segregate TOF in configurations such as individual or scattered crowns, linear formations and patch TOF. As per the adopted norms in India for defining tree cover, units up to 1 ha area were considered as candidate TOF. Classification of fine scale (at 10) segments was accomplished using size, shape and texture. A customised parameter involving ratio of area of segment to its main skeleton length discerned linear formations consistently. Texture of Cartosat-1 2.5 m data was also used segregate tree cover from smoother crop patches in patch TOF category. In view of the specificity of the landscape character, continuum of cultivated area (b) and pockets of cultivation within forest (c) as well as the entire study area (a) were considered as three envelopes for evaluating the accuracy of the method. Accuracies not less than 75.1 per cent were reported in all the envelopes with a kappa accuracy of not less than 0.58. Overall accuracy of entire study area was 75.9 per cent with Kappa of 0.59 followed by 75.1 per cent ( Kappa: 0.58 ) of agricultural landscape (b). In pockets of cultivation context(c) accuracy was higher at 79.2 per cent ( Kappa: 0.64 ) possibly due to smaller population. Assessment showed that 1,791 ha of 24,140 ha studied (7.42 %) was under tree cover as per the definitions adopted. Strength of accuracy demonstrated obviously points to the potential of IRS high resolution data combination in setting up procedures to monitor the TOF in Indian context using OBIA approach so as to cater to the evolving demands of resource assessment and monitoring.

  12. Mapping gully-affected areas in the region of Taroudannt, Morocco based on Object-Based Image Analysis (OBIA)

    Science.gov (United States)

    d'Oleire-Oltmanns, Sebastian; Marzolff, Irene; Tiede, Dirk; Blaschke, Thomas

    2015-04-01

    The need for area-wide landform mapping approaches, especially in terms of land degradation, can be ascribed to the fact that within area-wide landform mapping approaches, the (spatial) context of erosional landforms is considered by providing additional information on the physiography neighboring the distinct landform. This study presents an approach for the detection of gully-affected areas by applying object-based image analysis in the region of Taroudannt, Morocco, which is highly affected by gully erosion while simultaneously representing a major region of agro-industry with a high demand of arable land. Various sensors provide readily available high-resolution optical satellite data with a much better temporal resolution than 3D terrain data which lead to the development of an area-wide mapping approach to extract gully-affected areas using only optical satellite imagery. The classification rule-set was developed with a clear focus on virtual spatial independence within the software environment of eCognition Developer. This allows the incorporation of knowledge about the target objects under investigation. Only optical QuickBird-2 satellite data and freely-available OpenStreetMap (OSM) vector data were used as input data. The OSM vector data were incorporated in order to mask out plantations and residential areas. Optical input data are more readily available for a broad range of users compared to terrain data, which is considered to be a major advantage. The methodology additionally incorporates expert knowledge and freely-available vector data in a cyclic object-based image analysis approach. This connects the two fields of geomorphology and remote sensing. The classification results allow conclusions on the current distribution of gullies. The results of the classification were checked against manually delineated reference data incorporating expert knowledge based on several field campaigns in the area, resulting in an overall classification accuracy of 62%. The error of omission accounts for 38% and the error of commission for 16%, respectively. Additionally, a manual assessment was carried out to assess the quality of the applied classification algorithm. The limited error of omission contributes with 23% to the overall error of omission and the limited error of commission contributes with 98% to the overall error of commission. This assessment improves the results and confirms the high quality of the developed approach for area-wide mapping of gully-affected areas in larger regions. In the field of landform mapping, the overall quality of the classification results is often assessed with more than one method to incorporate all aspects adequately.

  13. Comparison of support vector machine and object based classification methods for coastline detection

    Science.gov (United States)

    Kalkan, K.; Bayram, B.; Maktav, D.; Sunar, F.

    2013-10-01

    Detection of coastline is an important procedure for management of coastal zones. According to the International Geographic Data Committee (IGDC), coastlines are one of the most important environmental heritages on the earth's surface. In the coastal areas, main challenge is to understand the present coastline dynamics and to predict its future developments. Therefore the coastal zone monitoring is an essential process for sustainable coastal management and environmental protection. Shoreline extraction is an important issue for coastal zone monitoring. In this study, efficiency of two different methods for detection of coastline features from satellite images, which cover Lakeland region of Turkey, has been tested. Firstly, object based classification method (OBC) has been used to extract shoreline automatically. Developed process based rule set extracts coastline as a vector file from satellite imagery. As a second method, support vector machine (SVM) algorithm has been used to extract coastline. For the application of these two different methods, Landsat 8 data have been used. The results of these two automatic coastline extraction methods were compared with the results derived from manual digitization process. Random control points over the coastline were used in the evaluation. Results showed that both methods have a sub-pixel accuracy to detect coastline features from Landsat 8 imagery.

  14. An Object-Based Approach for Fire History Reconstruction by Using Three Generations of Landsat Sensors

    Directory of Open Access Journals (Sweden)

    Thomas Katagis

    2014-06-01

    Full Text Available In this study, the capability of geographic object-based image analysis (GEOBIA in the reconstruction of the recent fire history of a typical Mediterranean area was investigated. More specifically, a semi-automated GEOBIA procedure was developed and tested on archived and newly acquired Landsat Multispectral Scanner (MSS, Thematic Mapper (TM, and Operational Land Imager (OLI images in order to accurately map burned areas in the Mediterranean island of Thasos. The developed GEOBIA ruleset was built with the use of the TM image and then applied to the other two images. This process of transferring the ruleset did not require substantial adjustments or any replacement of the initially selected features used for the classification, thus, displaying reduced complexity in processing the images. As a result, burned area maps of very high accuracy (over 94% overall were produced. In addition to the standard error matrix, the employment of additional measures of agreement between the produced maps and the reference data revealed that “spatial misplacement” was the main source of classification error. It can be concluded that the proposed approach can be potentially used for reconstructing the recent (40-year fire history in the Mediterranean, based on extended time series of Landsat or similar data.

  15. Discussion of related problems in herbal prescription science based on objective indications of herbs

    Directory of Open Access Journals (Sweden)

    Xing-jiang XIONG

    2010-01-01

    Full Text Available Herbal prescription science is a bridge between basic and clinical subjects in traditional Chinese medicine (TCM. In studying the doctrines in the general textbook Herbal Prescription Science and applying them to clinical practice, it was found that they are imprecise and inapplicable. Based on the analysis of Suanzaoren Decoction, Xiaoqinglong Decoction, Jichuan Decoction, etc., the authors point out that this problem is due to the current pathogenesis-based research approach of the herbal prescription science. It is proposed that correspondence between formula and syndrome is the core of the herbal prescription science. In order to solve such a problem, searching for corresponding relationship between an herb or a formula and the signs and symptoms of a syndrome or disease should be the most important task in research of herbal prescription science, for emphasis on attention to the objective indications and evidence in clinical utilization of herbal formulas is the major feature of the herbal prescription science according to medication experience in the long history of TCM.

  16. Colour-based Object Detection and Tracking for Autonomous Quadrotor UAV

    Science.gov (United States)

    Kadouf, Hani Hunud A.; Mohd Mustafah, Yasir

    2013-12-01

    With robotics becoming a fundamental aspect of modern society, further research and consequent application is ever increasing. Aerial robotics, in particular, covers applications such as surveillance in hostile military zones or search and rescue operations in disaster stricken areas, where ground navigation is impossible. The increased visual capacity of UAV's (Unmanned Air Vehicles) is also applicable in the support of ground vehicles to provide supplies for emergency assistance, for scouting purposes or to extend communication beyond insurmountable land or water barriers. The Quadrotor, which is a small UAV has its lift generated by four rotors and can be controlled by altering the speeds of its motors relative to each other. The four rotors allow for a higher payload than single or dual rotor UAVs, which makes it safer and more suitable to carry camera and transmitter equipment. An onboard camera is used to capture and transmit images of the Quadrotor's First Person View (FPV) while in flight, in real time, wirelessly to a base station. The aim of this research is to develop an autonomous quadrotor platform capable of transmitting real time video signals to a base station for processing. The result from the image analysis will be used as a feedback in the quadrotor positioning control. To validate the system, the algorithm should have the capacity to make the quadrotor identify, track or hover above stationary or moving objects.

  17. A modified teaching–learning based optimization for multi-objective optimal power flow problem

    International Nuclear Information System (INIS)

    Highlights: • A new modified teaching–learning based algorithm is proposed. • A self-adaptive wavelet mutation strategy is used to enhance the performance. • To avoid reaching a large repository size, a fuzzy clustering technique is used. • An efficiently smart population selection is utilized. • Simulations show the superiority of this algorithm compared with other ones. - Abstract: In this paper, a modified teaching–learning based optimization algorithm is analyzed to solve the multi-objective optimal power flow problem considering the total fuel cost and total emission of the units. The modified phase of the optimization algorithm utilizes a self-adapting wavelet mutation strategy. Moreover, a fuzzy clustering technique is proposed to avoid extremely large repository size besides a smart population selection for the next iteration. These techniques make the algorithm searching a larger space to find the optimal solutions while speed of the convergence remains good. The IEEE 30-Bus and 57-Bus systems are used to illustrate performance of the proposed algorithm and results are compared with those in literatures. It is verified that the proposed approach has better performance over other techniques

  18. A Geographical Information Systems for Transportation (GIS-T) Object Based Data Model for Road Infrastructure Maintenance in Uganda

    OpenAIRE

    Ndandiko, Lydia

    2013-01-01

    This paper presents an object based Geographical Information Systems for Transportation (GIS-T) data model for road maintenance in Uganda. It is a result of a PhD undertaking whose main objective was to develop a framework within which the use of Geographic Information Technologies could be enhanced as decision support tools for road infrastructure maintenance in Uganda. The model is based on data requirements of the road maintenance sector and is a means towards estab...

  19. Evaluation of a Learning Object Based Learning Environment in Different Dimensions

    Directory of Open Access Journals (Sweden)

    Ünal Çak?ro?lu

    2009-11-01

    Full Text Available Learning Objects (LOs are web based learning resources presented by Learning Object Repositories (LOR. For recent years LOs have begun to take place on web and it is suggested that appropriate design of LOs can make positive impact on learning. In order to support learning, research studies recommends LOs should have been evaluated pedagogically and technologically, and the content design created by using LOs should have been designed through appropriate instructional models. Since the use of LOs have recently begun, an exact pedagogical model about efficient use of LOs has not been developed. In this study a LOR is designed in order to be used in mathematics education. The LOs in this LOR have been evaluated pedagogically and technologically by mathematics teachers and field experts. In order to evaluate the designed LO based environment, two different questionnaires have been used. These questionnaires are developed by using the related literature about web based learning environments evaluation criteria and also the items are discussed with the field experts for providing the validity. The reliability of the questionnaires is calculated cronbach alpha = 0.715 for the design properties evaluation survey and cronbach alpha =0.726 for pedagogic evaluation. Both of two questionnaires are five point Likert type. The first questionnaire has the items about “Learning Support of LOs, Competency of LOR, The importance of LOs in mathematics education, the usability of LOs by students”. “The activities on LOs are related to outcomes of subjects, there are activities for students have different learning styles. There are activities for wondering students.” are examples for items about learning support of LOs. “System helps for exploration of mathematical relations”, “I think teaching mathematics with this system will be enjoyable.” are example items for importance of LOs in mathematics education. In the competency of LOR title, “System can be used in problem design about daily life.”, “Using systems can take much time for teachers” and in the title Students? using of LOR, “System is not appropriate for collaboration”, “The learning environment can help communication between students.” are the example items. In the technological dimension, the title design principles consist of items like; “The text and tables on the LOs are readable. The design of the menus makes the system usable. , The design is original.” In technological consistency title “LOs can be found by search options.”, “The tools are used for users to continue on the system.” , “Many kinds of files can be uploaded in to the system.” and in security title, the questionnaire has items like; the upload and download systems do not have problems, the user control system works confident. By using these surveys 64 educators in the field and mathematics teacher evaluated the LOR in pedagogy and content dimensions, and 46 material design expert and web expert evaluated LOR in design, technology and security dimensions. As a result of pedagogical and content evaluation, the participants revealed positive views about the LO based learning environment. In pedagogical dimension; it is found that the number of LOs is enough, the content design system must be eliminated from the details, the LOs have enough interaction, LOs can help exploring mathematical relations, and the activities related affective domain must be increased and by using of LOs an exciting and funny learning environment may be designed. In addition; according to the design experts, the learning environment is basic and useful, also most of them agreed on the system that it is complied with design criteria. Besides experts evaluated the security options are feasible. By the results of this study, the LOR will be updated and revised to a form a web based learning environment for mathematics education and the real impact of LO based mathematics learning environment will be investigated in future studies.

  20. Search in the real world : Active visual object search based on spatial relations

    OpenAIRE

    Aydemir, Alper; Sjo?o?, Kristoffer; Folkesson, John; Pronobis, Andrzej; Jensfelt, Patric

    2011-01-01

    Objects are integral to a robot’s understandingof space. Various tasks such as semantic mapping, pick-andcarrymissions or manipulation involve interaction with objects.Previous work in the field largely builds on the assumption thatthe object in question starts out within the ready sensory reachof the robot. In this work we aim to relax this assumptionby providing the means to perform robust and large-scaleactive visual object search. Presenting spatial relations thatdescribe topological re...

  1. Development of a Relap based Nuclear Plant Analyser with 3-D graphics using OpenGL and Object Relap

    International Nuclear Information System (INIS)

    A 3-D Graphic Nuclear Plant Analyzer (NPA) program was developed using GLScene and the TRelap. GLScene is an OpenGL based 3D graphics library for the Delphi object-oriented program language, and it implements the OpenGL functions in forms suitable for programming with Delphi. TRelap is an object wrapper developed by the author to easily implement the Relap5 thermal hydraulic code under object oriented programming environment. The 3-D Graphic NPA was developed to demonstrate the superiority of the object oriented programming approach in developing complex programs

  2. Object-oriented analysis and design of a GEANT based detector simulator

    International Nuclear Information System (INIS)

    The authors give a status report of the project to design a detector simulation program by reengineering GEANT with the object-oriented methodology. They followed the Object Modeling Technique. They explain the object model they constructed. Also problems of the technique found during their study are discussed

  3. IMAGING-BASED OPTICAL CALIPER FOR OBJECTS IN HOT MANUFACTURING PROCESSES

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Howard

    2013-04-03

    OG Technologies, Inc. (OGT), in conjunction with its industrial and academic partners, proposes to develop an �Imaging-Based Optical Caliper (hereafter referred to as �OC�) for Objects in Hot Manufacturing Processes�. The goal is to develop and demonstrate the OC with the synergy of OGT�s current technological pool and other innovations to provide a light weight, robust, safe and accurate portable dimensional measurement device for hot objects with integrated wireless communication capacity to enable real time process control. The technical areas of interest in this project are the combination of advanced imaging, Sensor Fusion, and process control. OGT believes that the synergistic interactions between its current set of technologies and other innovations could deliver products that are viable and have high impact in the hot manufacture processes, such as steel making, steel rolling, open die forging, and glass industries, resulting in a new energy efficient control paradigm in the operations through improved yield, prolonged tool life and improved quality. In-line dimension measurement and control is of interest to the steel makers, yet current industry focus is on the final product dimension only instead of whole process due to the limit of man power, system cost and operator safety concerns. As sensor technologies advances, the industry started to see the need to enforce better dimensional control throughout the process, but lack the proper tools to do so. OGT along with its industrial partners represent the indigenous effort of technological development to serve the US steel industry. The immediate market that can use and get benefited from the proposed OC is the Steel Industry. The deployment of the OC has the potential to provide benefits in reduction of energy waste, CO2 emission, waste water amount, toxic waste, and so forth. The potential market after further expended function includes Hot Forging and Freight Industries. The OC prototypes were fabricated, and were progressively tested on-site in several steel mill and hot forging facilities for evaluation. Software refinements and new calibration procedures were also carried out to overcome the discovered glitches. Progress was presented to the hot manufacture facilities worldwide. Evidence showed a great interest and practical need for this product. OGT is in the pilot commercialization mode for this new development. The R&D team also successfully developed a 3D measurement function with no additional investment of hardware or equipment to measure low or room temperature object dimensions. Several tests were conducted in the reality environment to evaluate the measurement results. This new application will require additional development in product design.

  4. Environmental perceptions and objective walking trail audits inform a community-based participatory research walking intervention

    Directory of Open Access Journals (Sweden)

    Zoellner Jamie

    2012-01-01

    Full Text Available Abstract Background Given the documented physical activity disparities that exist among low-income minority communities and the increased focused on socio-ecological approaches to address physical inactivity, efforts aimed at understanding the built environment to support physical activity are needed. This community-based participatory research (CBPR project investigates walking trails perceptions in a high minority southern community and objectively examines walking trails. The primary aim is to explore if perceived and objective audit variables predict meeting recommendations for walking and physical activity, MET/minutes/week of physical activity, and frequency of trail use. Methods A proportional sampling plan was used to survey community residents in this cross-sectional study. Previously validated instruments were pilot tested and appropriately adapted and included the short version of the validated International Physical Activity Questionnaire, trail use, and perceptions of walking trails. Walking trails were assessed using the valid and reliable Path Environmental Audit Tool which assesses four content areas including: design features, amenities, maintenance, and pedestrian safety from traffic. Analyses included Chi-square, one-way ANOVA's, multiple linear regression, and multiple logistic models. Results Numerous (n = 21 high quality walking trails were available. Across trails, there were very few indicators of incivilities and safety features rated relatively high. Among the 372 respondents, trail use significantly predicted meeting recommendations for walking and physical activity, and MET/minutes/week. While controlling for other variables, significant predictors of trail use included proximity to trails, as well as perceptions of walking trail safety, trail amenities, and neighborhood pedestrian safety. Furthermore, while controlling for education, gender, and income; for every one time per week increase in using walking trails, the odds for meeting walking recommendations increased 1.27 times, and the odds for meeting PA recommendation increased 3.54 times. Perceived and objective audit variables did not predict meeting physical activity recommendations. Conclusions To improve physical activity levels, intervention efforts are needed to maximize the use of existing trails, as well as improve residents' perceptions related to incivilities, safety, conditions of trail, and amenities of the walking trails. This study provides important insights for informing development of the CBPR walking intervention and informing local recreational and environmental policies in this southern community.

  5. Error analysis of marker-based object localization using a single-plane XRII

    International Nuclear Information System (INIS)

    The role of imaging and image guidance is increasing in surgery and therapy, including treatment planning and follow-up. Fluoroscopy is used for two-dimensional (2D) guidance or localization; however, many procedures would benefit from three-dimensional (3D) guidance or localization. Three-dimensional computed tomography (CT) using a C-arm mounted x-ray image intensifier (XRII) can provide high-quality 3D images; however, patient dose and the required acquisition time restrict the number of 3D images that can be obtained. C-arm based 3D CT is therefore limited in applications for x-ray based image guidance or dynamic evaluations. 2D-3D model-based registration, using a single-plane 2D digital radiographic system, does allow for rapid 3D localization. It is our goal to investigate - over a clinically practical range - the impact of x-ray exposure on the resulting range of 3D localization precision. In this paper it is assumed that the tracked instrument incorporates a rigidly attached 3D object with a known configuration of markers. A 2D image is obtained by a digital fluoroscopic x-ray system and corrected for XRII distortions (±0.035 mm) and mechanical C-arm shift (±0.080 mm). A least-square projection-Procrustes analysis is then used to calculate the 3D position using the measured 2D marker locations. The effect of x-ray exposure on the precision of 2D marker localization and on 3D object localization was investigated using numerical simulations and x-ray experimenumerical simulations and x-ray experiments. The results show a nearly linear relationship between 2D marker localization precision and the 3D localization precision. However, a significant amplification of error, nonuniformly distributed among the three major axes, occurs, and that is demonstrated. To obtain a 3D localization error of less than ±1.0 mm for an object with 20 mm marker spacing, the 2D localization precision must be better than ±0.07 mm. This requirement was met for all investigated nominal x-ray exposures at 28 cm FOV, and for all but the lowest two at 40 cm FOV. However, even for those two nominal exposures, the expected 3D localization error is less than ±1.2 mm. The tracking precision was ±0.65 mm for the out-of-plane translations, ±0.05 mm for in-plane translations, and ±0.05 deg. for the rotations. The root mean square (RMS) difference between the true and projection-Procrustes calculated location was 1.07 mm. It is believed these results show the potential of this technique for dynamic evaluations or real-time image guidance using a single x-ray source and XRII detector.

  6. Distribution Network Expansion Planning Based on Multi-objective PSO Algorithm

    DEFF Research Database (Denmark)

    Zhang, Chunyu; Ding, Yi

    2013-01-01

    This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO algorithm was proposed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective PSO have been verified by the 18-node typical system.

  7. Robust Mobile Object Tracking Based on Multiple Feature Similarity and Trajectory Filtering

    CERN Document Server

    Chau, Duc Phu; Thonnat, Monique; Corvee, Etienne

    2011-01-01

    This paper presents a new algorithm to track mobile objects in different scene conditions. The main idea of the proposed tracker includes estimation, multi-features similarity measures and trajectory filtering. A feature set (distance, area, shape ratio, color histogram) is defined for each tracked object to search for the best matching object. Its best matching object and its state estimated by the Kalman filter are combined to update position and size of the tracked object. However, the mobile object trajectories are usually fragmented because of occlusions and misdetections. Therefore, we also propose a trajectory filtering, named global tracker, aims at removing the noisy trajectories and fusing the fragmented trajectories belonging to a same mobile object. The method has been tested with five videos of different scene conditions. Three of them are provided by the ETISEO benchmarking project (http://www-sop.inria.fr/orion/ETISEO) in which the proposed tracker performance has been compared with other seven...

  8. Object-Based Classification of Multi-temporal Images for Agricultural Crop Mapping in Karacabey Plain, Turkey

    Science.gov (United States)

    Ozdarici-Ok, A.; Akyurek, Z.

    2014-09-01

    The objective of this research is to classify major crop types cultivated in Karacabey Plain of north western Turkey using multitemporal Kompsat-2 and Envisat ASAR data with an object-based methodology. First a pansharpening algorithm is applied to each panchromatic and multispectral Kompsat-2 data to produce colour images having 1m spatial resolution. Next, Mean-Shift image segmentation procedure is applied to the pansharpened Kompsat-2 data with multiple parameter combinations. Multiple goodness measures are utilized to evaluate the object-based results. The optimum objects are then employed in object-based classifications of the single-date images. Next, single-date multispectral (MS) Kompsat-2 images and Kompsat-2 images along with the Envisat ASAR data are classified with the Support Vector Machines (SVMs) method. The training samples are provided automatically by the selected objects based on spatial statistical properties. Next, probability maps are generated for each image in pixel-based manner during the image classification operations. The maximum probabilities are then assigned to the pixels as class labels and the combined thematic maps (June-July, June-August, June-July-August) are generated in pixel-based and object-based manners. The produced thematic maps are evaluated through the confusion matrices and compared also with the results of parcel-based classifications using original agricultural parcels. Results indicate that the combined thematic maps of June-August and June-July- August provide the highest overall accuracy and kappa value approximately 92 % and 0.90, respectively.

  9. Neural Dynamics of Object-Based Multifocal Visual Spatial Attention and Priming: Object Cueing, Useful-Field-of-View, and Crowding

    Science.gov (United States)

    Foley, Nicholas C.; Grossberg, Stephen; Mingolla, Ennio

    2012-01-01

    How are spatial and object attention coordinated to achieve rapid object learning and recognition during eye movement search? How do prefrontal priming and parietal spatial mechanisms interact to determine the reaction time costs of intra-object attention shifts, inter-object attention shifts, and shifts between visible objects and covertly cued…

  10. Detecting Slums from SPOT Data in Casablanca Morocco Using an Object Based Approach

    Directory of Open Access Journals (Sweden)

    Hassan Rhinane

    2011-07-01

    Full Text Available Casablanca, Morocco's economic capital continues today to fight against the proliferation of informal settle- ments affecting its urban fabric illustrated especially by the slums. Actually Casablanca represents 25% of the total slums of Morocco [1]. These are the habitats of all deprived of healthy sanitary conditions and judged precarious from the perspective humanitarian and below the acceptable. The majority of the inhabi- tants of these slums are from the rural exodus with insufficient income to meet the basic needs of daily life. Faced with this situation and to eradicate these habitats, the Moroccan government has launched since 2004 an entire program to create cities without slums (C.W.S. to resettle or relocate families. Indeed the process control and monitoring of this program requires first identifying and detecting spatial habitats. To achieve these tasks, conventional methods such as information gathering, mapping, use of databases and statistics often have shown their limits and are sometimes outdated. It is within this framework and that of the great German Morocco project “Urban agriculture as an integrative factor of development that fits our project de- tection of slums in Casablanca. The use of satellite imagery, particulary the HSR, has the advantage of providing the physical coverage of urban land but it raises the difficulty of choosing the appropriate method to apply.This paper is actually to develop new approaches based mainly on object-oriented classification of high spatial resolution satellite images for the detection of slums.This approach has been developed for mapping the urban land through by integration of several types of information (spectral, spatial, contextual ... (Hofmann, P ., 2001, Herold et al. 2002b; Van Der Sande et al., 2003, Benz et al., 2004, Nobrega et al., 2006. In order to refine the result of classification, we applied mathematical morphology and in particular the closing filter. The data from this classification (binary image, which then will be used in a spatial data- base (ArcGIS.

  11. Monitoring Urban Tree Cover Using Object-Based Image Analysis and Public Domain Remotely Sensed Data

    Directory of Open Access Journals (Sweden)

    Meghan Halabisky

    2011-10-01

    Full Text Available Urban forest ecosystems provide a range of social and ecological services, but due to the heterogeneity of these canopies their spatial extent is difficult to quantify and monitor. Traditional per-pixel classification methods have been used to map urban canopies, however, such techniques are not generally appropriate for assessing these highly variable landscapes. Landsat imagery has historically been used for per-pixel driven land use/land cover (LULC classifications, but the spatial resolution limits our ability to map small urban features. In such cases, hyperspatial resolution imagery such as aerial or satellite imagery with a resolution of 1 meter or below is preferred. Object-based image analysis (OBIA allows for use of additional variables such as texture, shape, context, and other cognitive information provided by the image analyst to segment and classify image features, and thus, improve classifications. As part of this research we created LULC classifications for a pilot study area in Seattle, WA, USA, using OBIA techniques and freely available public aerial photography. We analyzed the differences in accuracies which can be achieved with OBIA using multispectral and true-color imagery. We also compared our results to a satellite based OBIA LULC and discussed the implications of per-pixel driven vs. OBIA-driven field sampling campaigns. We demonstrated that the OBIA approach can generate good and repeatable LULC classifications suitable for tree cover assessment in urban areas. Another important finding is that spectral content appeared to be more important than spatial detail of hyperspatial data when it comes to an OBIA-driven LULC.

  12. Interactive Application Development Policy Object 3D Virtual Tour History Pacitan District based Multimedia

    Directory of Open Access Journals (Sweden)

    Bambang Eka Purnama

    2013-04-01

    Full Text Available Pacitan has a wide range of tourism activity. One of the tourism district is Pacitan historical attractions. These objects have a history tour of the educational values, history and culture, which must be maintained and preserved as one tourism asset Kabupeten Pacitan. But the history of the current tour the rarely visited and some of the students also do not understand the history of each of these historical attractions. Hence made a information media of 3D virtual interactive applications Pacitan tour history in the form of interactive CD applications. The purpose of the creation of interactive applications is to introduce Pacitan history tours to students and the community. Creating interactive information media that can provide an overview of the history of the existing tourist sites in Pacitan The benefits of this research is the students and the public will get to know the history of historical attractions Pacitan. As a media introduction of historical attractions and as a medium of information to preserve the historical sights. Band is used in the manufacturing methods Applications 3D Virtual Interactive Attractions: History-Based Multimedia Pacitan authors used the method library, observation and interviews. Design using 3ds Max 2010, Adobe Director 11.5, Adobe Photoshop CS3 and Corel Draw. The results of this research is the creation of media interakif information that can provide knowledge about the history of Pacitan.

  13. Fully automated objective-based method for master recession curve separation.

    Science.gov (United States)

    Posavec, Kristijan; Parlov, Jelena; Naki?, Zoran

    2010-01-01

    The fully automated objective-based method for master recession curve (MRC) separation was developed by using Microsoft Excel spreadsheet and Visual Basic for Applications (VBA) code. The core of the program code is used to construct an MRC by using the adapted matching strip method (Posavec et al. 2006). Criteria for separating the MRC into two or three segments are determined from the flow-duration curve and are represented as the probable range of percent of flow rate duration. Successive separations are performed automatically on two and three MRCs using sets of percent of flow rate duration from selected ranges and an optimal separation model scenario, having the highest average coefficient of determination R(2), is selected as the most appropriate one. The resulting separated master recession curves are presented graphically, whereas the statistics are presented numerically, all in separate sheets. Examples of field data obtained from two springs in Istria, Croatia, are used to illustrate its application. The freely available Excel spreadsheet and VBA program ensures the ease of use and applicability for larger data sets. PMID:20100291

  14. Employing Measures of Heterogeneity and an Object-Based Approach to Extrapolate Tree Species Distribution Data

    Directory of Open Access Journals (Sweden)

    Trevor G. Jones

    2014-07-01

    Full Text Available Information derived from high spatial resolution remotely sensed data is critical for the effective management of forested ecosystems. However, high spatial resolution data-sets are typically costly to acquire and process and usually provide limited geographic coverage. In contrast, moderate spatial resolution remotely sensed data, while not able to provide the spectral or spatial detail required for certain types of products and applications, offer inexpensive, comprehensive landscape-level coverage. This study assessed using an object-based approach to extrapolate detailed tree species heterogeneity beyond the extent of hyperspectral/LiDAR flightlines to the broader area covered by a Landsat scene. Using image segments, regression trees established ecologically decipherable relationships between tree species heterogeneity and the spectral properties of Landsat segments. The spectral properties of Landsat bands 4 (i.e., NIR: 0.76–0.90 µm, 5 (i.e., SWIR: 1.55–1.75 µm and 7 (SWIR: 2.08–2.35 µm were consistently selected as predictor variables, explaining approximately 50% of variance in richness and diversity. Results have important ramifications for ongoing management initiatives in the study area and are applicable to wide range of applications.

  15. Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis

    Directory of Open Access Journals (Sweden)

    Jane Southworth

    2010-12-01

    Full Text Available Savanna ecosystems are an important component of dryland regions and yet are exceedingly difficult to study using satellite imagery. Savannas are composed are varying amounts of trees, shrubs and grasses and typically traditional classification schemes or vegetation indices cannot differentiate across class type. This research utilizes object based classification (OBC for a region in Namibia, using IKONOS imagery, to help differentiate tree canopies and therefore woodland savanna, from shrub or grasslands. The methodology involved the identification and isolation of tree canopies within the imagery and the creation of tree polygon layers had an overall accuracy of 84%. In addition, the results were scaled up to a corresponding Landsat image of the same region, and the OBC results compared to corresponding pixel values of NDVI. The results were not compelling, indicating once more the problems of these traditional image analysis techniques for savanna ecosystems. Overall, the use of the OBC holds great promise for this ecosystem and could be utilized more frequently in studies of vegetation structure.

  16. A Genetic Algorithm Based Multi Objective Service Restoration in Distribution Systems

    Directory of Open Access Journals (Sweden)

    Sathish K. Kannaiah

    2011-01-01

    Full Text Available Problem statement: A Genetic Algorithm (GA used here to find exact or approximate solutions to optimization and search problems. Genetic algorithms are a particular class of evolutionary algorithms that use techniques inspired by evolutionary biology such as inheritance, mutation, selection and crossover. Approach: GA is a method for search and optimization based on the process of natural selection and evolution. In this approach, several modifications are done for effective implementation of GA to solve the Electric Power Service Restoration Problem. Results: The problem statement includes all the objectives and constraints required for a practical supply restoration scheme. GA is used here to obtain the better result compared with other methods. GA starts with number of solutions to a problem, encoded as a string of status of sectionalizing and tie switches. Conclusion: The status of the switch ?1? and ?0? has been considered as ?close? and ?open? condition of the switch. The string that encodes each string is ?chromosome? and the set of solutions are termed as population. Obtained results are good and this technique is recommended here for future study.

  17. Object-based attention benefits reveal selective abnormalities of visual integration in autism.

    Science.gov (United States)

    Falter, Christine M; Grant, Kate C Plaisted; Davis, Greg

    2010-06-01

    A pervasive integration deficit could provide a powerful and elegant account of cognitive processing in autism spectrum disorders (ASD). However, in the case of visual Gestalt grouping, typically assessed by tasks that require participants explicitly to introspect on their own grouping perception, clear evidence for such a deficit remains elusive. To resolve this issue, we adopt an index of Gestalt grouping from the object-based attention literature that does not require participants to assess their own grouping perception. Children with ASD and mental- and chronological-age matched typically developing children (TD) performed speeded orientation discriminations of two diagonal lines. The lines were superimposed on circles that were either grouped together or segmented on the basis of color, proximity or these two dimensions in competition. The magnitude of performance benefits evident for grouped circles, relative to ungrouped circles, provided an index of grouping under various conditions. Children with ASD showed comparable grouping by proximity to the TD group, but reduced grouping by similarity. ASD seems characterized by a selective bias away from grouping by similarity combined with typical levels of grouping by proximity, rather than by a pervasive integration deficit. PMID:20578070

  18. Bi-Objective Optimization Based on Compromise Method for Horizontal Fragmentation in Relational Data Warehouses

    Directory of Open Access Journals (Sweden)

    Mohamed Barr

    2013-06-01

    Full Text Available Generally, research that dealt with the selection problems for optimization techniques or structures in relational data ware houses supports these problems by considering only a single criterion of optimization. The optimization criteria may be the response time of query execution, the number of inputs/outputs between the main memory and the disk, the space allocated to store the index or materialized views, or the number fragments required by the administrator of the data warehouse when using the fragmentation technique. The present work deals with the problem of selecting the horizontal fragmentation technique while considering both the number of I/O between memory and disk during decisional queries and the number of fragments, as two objective functions to minimize. To reduce the scope of choice solutions, we are based on a scalar method, called compromise method. The method is complemented by the principle of Pareto front to infer the best solutions. The study has been experimented on APB1 benchmark of data warehouse.

  19. Design and implementation of an XML based object-oriented detector description database for CMS

    International Nuclear Information System (INIS)

    This thesis deals with the development of a detector description database (DDD) for the compact muon solenoid (CMS) experiment at the large hadron collider (LHC) located at the European organization for nuclear research (CERN). DDD is a fundamental part of the CMS offline software with its main applications, simulation and reconstruction. Both are in need of different models of the detector in order to efficiently solve their specific tasks. In the thesis the requirements to a detector description database are analyzed and the chosen solution is described in detail. It comprises the following components: an XML based detector description language, a runtime system that implements an object-oriented transient representation of the detector, and an application programming interface to be used by client applications. One of the main aspects of the development is the design of the DDD components. The starting point is a domain model capturing concisely the characteristics of the problem domain. The domain model is transformed into several implementation models according to the guidelines of the model driven architecture (MDA). Implementation models and appropriate refinements thereof are foundation for adequate implementations. Using the MDA approach, a fully functional prototype was realized in C++ and XML. The prototype was successfully tested through seamless integration into both the simulation and the reconstruction framework of CMS. (author) of CMS. (author)

  20. Robust Stereo-Vision Based 3D Object Reconstruction for the Assistive Robot FRIEND

    Directory of Open Access Journals (Sweden)

    COJBASIC, Z.

    2011-11-01

    Full Text Available A key requirement of assistive robot vision is the robust 3D object reconstruction in complex environments for reliable autonomous object manipulation. In this paper the idea is presented of achieving high robustness of a complete robot vision system against external influences such as variable illumination by including feedback control of the object segmentation in stereo images. The approach used is to change the segmentation parameters in closed-loop so that object features extraction is driven to a desired result. Reliable feature extraction is necessary to fully exploit a neuro-fuzzy classifier which is the core of the proposed 2D object recognition method, predecessor of 3D object reconstruction. Experimental results on the rehabilitation assistive robotic system FRIEND demonstrate the effectiveness of the proposed method.

  1. An efficient hybrid evolutionary algorithm based on PSO and HBMO algorithms for multi-objective Distribution Feeder Reconfiguration

    International Nuclear Information System (INIS)

    This paper introduces a robust searching hybrid evolutionary algorithm to solve the multi-objective Distribution Feeder Reconfiguration (DFR). The main objective of the DFR is to minimize the real power loss, deviation of the nodes' voltage, the number of switching operations, and balance the loads on the feeders. Because of the fact that the objectives are different and no commensurable, it is difficult to solve the problem by conventional approaches that may optimize a single objective. This paper presents a new approach based on norm3 for the DFR problem. In the proposed method, the objective functions are considered as a vector and the aim is to maximize the distance (norm2) between the objective function vector and the worst objective function vector while the constraints are met. Since the proposed DFR is a multi objective and non-differentiable optimization problem, a new hybrid evolutionary algorithm (EA) based on the combination of the Honey Bee Mating Optimization (HBMO) and the Discrete Particle Swarm Optimization (DPSO), called DPSO-HBMO, is implied to solve it. The results of the proposed reconfiguration method are compared with the solutions obtained by other approaches, the original DPSO and HBMO over different distribution test systems.

  2. Age-Based Hiring Discrimination as a Function of Equity Norms and Self-Perceived Objectivity

    OpenAIRE

    Lindner, Nicole M.; Graser, Alexander; Nosek, Brian A.

    2014-01-01

    Participants completed a questionnaire priming them to perceive themselves as either objective or biased, either before or after evaluating a young or old job applicant for a position linked to youthful stereotypes. Participants agreed that they were objective and tended to disagree that they were biased. Extending past research, both the objective and bias priming conditions led to an increase in age discrimination compared to the control condition. We also investigated whether equity norms ...

  3. Modelling Mobile Object Activities Based on Trajectory Ontology Rules Considering Spatial Relationship Rules

    OpenAIRE

    Wannous, Rouaa; Malki, Jamal; Bouju, Alain; Vincent, Cécile

    2013-01-01

    Several applications use devices and capture systems to record trajectories of mobile objects. To exploit these raw trajectories, we need to enhance them with semantic information. Temporal, spatial and domain related information are fundamental sources used to upgrade trajectories. The objective of semantic trajectories is to help users validating and acquiring more knowledge about mobile objects. In particular, temporal and spatial analysis of semantic trajectories is very important to unde...

  4. Semi-Automatic Objects Recognition in Urban Areas Based on Fuzzy Logic

    OpenAIRE

    Federico Prandi; Raffaella Brumana; Francesco Fassi

    2010-01-01

    Three dimensional object extraction and recognition (OER) from geographic data has been definitely one of more important topic in photogrammetry for quite a long time. Today, the capability of rapid generating high-density DSM increases the supply of geographic information but the discrete nature of the measuring makes more difficult to recognize correctly and to extract 3D objects from these surface. The proposed methodology wants to semi-automate some geographic objects clustering operation...

  5. A Training Program to Improve IFSP/IEP Goals and Objectives through the Routines-Based Interview

    Science.gov (United States)

    Boavida, Tânia; Aguiar, Cecília; McWilliam, R. A.

    2014-01-01

    The authors describe a training program designed to improve the knowledge and skills of early childhood interventionists. Within the context of using the Routines-Based Early Intervention approach, this training focused on improving the quality of goals and objectives on individualized plans, through the Routines-Based Interview. We structured the…

  6. A combined object-tracking algorithm for omni-directional vision-based AGV navigation

    Science.gov (United States)

    Yuan, Wei; Sun, Jie; Cao, Zuo-Liang; Tian, Jing; Yang, Ming

    2010-03-01

    A combined object-tracking algorithm that realizes the realtime tracking of the selected object through the omni-directional vision with a fisheye lens is presented. The new method combines the modified continuously adaptive mean shift algorithm with the Kalman filter method. With the proposed method, the object-tracking problem when the object reappears after being sheltered completely or moving out of the field of view is solved. The experimental results perform well, and the algorithm proposed here improves the robustness and accuracy of the tracking in the omni-directional vision.

  7. An Assistant for Loading Learning Object Metadata: An Ontology Based Approach

    Science.gov (United States)

    Casali, Ana; Deco, Claudia; Romano, Agustín; Tomé, Guillermo

    2013-01-01

    In the last years, the development of different Repositories of Learning Objects has been increased. Users can retrieve these resources for reuse and personalization through searches in web repositories. The importance of high quality metadata is key for a successful retrieval. Learning Objects are described with metadata usually in the standard…

  8. Design and development of object-oriented software based on Qt

    International Nuclear Information System (INIS)

    Qt is a popular object-oriented C++ class library under Linux environment. The authors will introduce the object-oriented technology, the Qt library and the IDE to develop Qt software. An example of Qt software is shown in detail. (authors)

  9. Visual Object Servo Tracking Based on the Particle Filter Method Using a Pan-Tilt-Zoom Camera

    Directory of Open Access Journals (Sweden)

    Cao Songxiao

    2012-10-01

    Full Text Available We present a servo control model in a particle filter to realize robust visual object tracking using Pan?Tilt?Zoom (PTZ camera. The particle filter method has attracted much attention due to its robust tracking performance in cluttered environments. However, most methods are in the mode of moving object and stationary camera, as a result, the tracking will end in failure if the object goes out of the field of view of the camera. In this paper, a closed?loop control model based on speed regulation is proposed to drive the PTZ camera to keep the target at the centre of the camera angle. The experiment results show that our system can track the moving object well and can always keep the object in the middle of the field of view. The system is computationally efficient and can run in real?time completely.

  10. A multi-objective optimization approach based on simulated annealing and its application to nuclear fuel management

    International Nuclear Information System (INIS)

    As far as stochastic optimization methods are concerned, Simulated Annealing (SA) and Genetic Algorithms (GA) have been successfully applied to fuel management, when using a single objective function. Recent work has shown that it is possible to use a true multi-objective approach (e.g. fresh fuel enrichment minimization and cycle length maximization,...) based on GA. In that approach, ranking the individuals of the population is based on the non-dominance principle. It is shown that a similar approach can be applied to SA, which is traditionally single objective. In this approach, every time a solution using is accepted, it is compared to other archived solutions using the non-dominance principle. At the end of the optimization search, one ends up with an archived population which actually represents the trade-off surface between all the objective functions of interest, among which the expert will then choose the best solution according to his priorities. (author)

  11. A robust mean-shift tracking through occlusion and scale based on object trajectory for surveillance camera

    Science.gov (United States)

    Labidi, Hocine; Luo, Sen-Lin; Boubekeur, Mohamed Bachir

    2015-03-01

    Object tracking is an important part in surveillance systems, One of the algorithms used for this task is the meanshift algorithm due to the robustness, computational efficiency and implementation ease. However the traditional meanshift cannot effectively track the moving object when the scale changes, because of the fixed size of the tracking window, and can lose the target while an occlusion, In this study a method based on the trajectory direction of the moving object is presented to deal with the problem of scale change. Furthermore a histogram similarity metric is used to detect when target occlusion occurs, and a method based on multi kernel is proposed, to estimate which part is not in occlusion and this part will be used to extrapolate the motion of the object and gives an estimation of its position, Experimental results show that the improved methods have a good adaptability to the scale and occlusion of the target.

  12. Operational Automatic Remote Sensing Image Understanding Systems: Beyond Geographic Object-Based and Object-Oriented Image Analysis (GEOBIA/GEOOIA. Part 1: Introduction

    Directory of Open Access Journals (Sweden)

    Andrea Baraldi

    2012-09-01

    Full Text Available According to existing literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA systems and three-stage iterative geographic object-oriented image analysis (GEOOIA systems, where GEOOIA/GEOBIA, remain affected by a lack of productivity, general consensus and research. To outperform the degree of automation, accuracy, efficiency, robustness, scalability and timeliness of existing GEOBIA/GEOOIA systems in compliance with the Quality Assurance Framework for Earth Observation (QA4EO guidelines, this methodological work is split into two parts. The present first paper provides a multi-disciplinary Strengths, Weaknesses, Opportunities and Threats (SWOT analysis of the GEOBIA/GEOOIA approaches that augments similar analyses proposed in recent years. In line with constraints stemming from human vision, this SWOT analysis promotes a shift of learning paradigm in the pre-attentive vision first stage of a remote sensing (RS image understanding system (RS-IUS, from sub-symbolic statistical model-based (inductive image segmentation to symbolic physical model-based (deductive image preliminary classification. Hence, a symbolic deductive pre-attentive vision first stage accomplishes image sub-symbolic segmentation and image symbolic pre-classification simultaneously. In the second part of this work a novel hybrid (combined deductive and inductive RS-IUS architecture featuring a symbolic deductive pre-attentive vision first stage is proposed and discussed in terms of: (a computational theory (system design; (b information/knowledge representation; (c algorithm design; and (d implementation. As proof-of-concept of symbolic physical model-based pre-attentive vision first stage, the spectral knowledge-based, operational, near real-time Satellite Image Automatic Mapper™ (SIAM™ is selected from existing literature. To the best of these authors’ knowledge, this is the first time a symbolic syntactic inference system, like SIAM™, is made available to the RS community for operational use in a RS-IUS pre-attentive vision first stage, to accomplish multi-scale image segmentation and multi-granularity image pre-classification simultaneously, automatically and in near real-time.

  13. Object-Based Mapping of the Circumpolar Taiga-Tundra Ecotone with MODIS Tree Cover

    Science.gov (United States)

    Ranson, K. J.; Montesano, P. M.; Nelson, R.

    2011-01-01

    The circumpolar taiga tundra ecotone was delineated using an image-segmentation-based mapping approach with multi-annual MODIS Vegetation Continuous Fields (VCF) tree cover data. Circumpolar tree canopy cover (TCC) throughout the ecotone was derived by averaging MODIS VCF data from 2000 to 2005 and adjusting the averaged values using linear equations relating MODIS TCC to Quickbird-derived tree cover estimates. The adjustment helped mitigate VCF's overestimation of tree cover in lightly forested regions. An image segmentation procedure was used to group pixels representing similar tree cover into polygonal features (segmentation objects) that form the map of the transition zone. Each polygon represents an area much larger than the 500 m MODIS pixel and characterizes the patterns of sparse forest patches on a regional scale. Those polygons near the boreal/tundra interface with either (1) mean adjusted TCC values from5 to 20%, or (2) mean adjusted TCC values greater than 5% but with a standard deviation less than 5% were used to identify the ecotone. Comparisons of the adjusted average tree cover data were made with (1) two existing tree line definitions aggregated for each 1 degree longitudinal interval in North America and Eurasia, (2) Landsat-derived Canadian proportion of forest cover for Canada, and (3) with canopy cover estimates extracted from airborne profiling lidar data that transected 1238 of the TCC polygons. The adjusted TCC from MODIS VCF shows, on average, less than 12% TCC for all but one regional zone at the intersection with independently delineated tree lines. Adjusted values track closely with Canadian proportion of forest cover data in areas of low tree cover. A comparison of the 1238 TCC polygons with profiling lidar measurements yielded an overall accuracy of 67.7%.

  14. Visual Perception Based Objective Stereo Image Quality Assessment for 3D Video Communication

    Directory of Open Access Journals (Sweden)

    Gangyi Jiang

    2014-04-01

    Full Text Available Stereo image quality assessment is a crucial and challenging issue in 3D video communication. One of major difficulties is how to weigh binocular masking effect. In order to establish the assessment mode more in line with the human visual system, Watson model is adopted, which defines visibility threshold under no distortion composed of contrast sensitivity, masking effect and error in this study. As a result, we propose an Objective Stereo Image Quality Assessment method (OSIQA, organically combining a new Left-Right view Image Quality Assessment (LR-IQA metric and Depth Perception Image Quality Assessment (DP-IQA metric. The new LR-IQA metric is first given to calculate the changes of perception coefficients in each sub-band utilizing Watson model and human visual system after wavelet decomposition of left and right images in stereo image pair, respectively. Then, a concept of absolute difference map is defined to describe abstract differential value between the left and right view images and the DP-IQA metric is presented to measure structure distortion of the original and distorted abstract difference maps through luminance function, error sensitivity and contrast function. Finally, an OSIQA metric is generated by using multiplicative fitting of the LR-IQA and DP-IQA metrics based on weighting. Experimental results shows that the proposed method are highly correlated with human visual judgments (Mean Opinion Score and the correlation coefficient and monotony are more than 0.92 under five types of distortions such as Gaussian blur, Gaussian noise, JP2K compression, JPEG compression and H.264 compression.

  15. Support Vector Machine Classification of Object-Based Data for Crop Mapping, Using Multi-Temporal Landsat Imagery

    Science.gov (United States)

    Devadas, R.; Denham, R. J.; Pringle, M.

    2012-07-01

    Crop mapping and time series analysis of agronomic cycles are critical for monitoring land use and land management practices, and analysing the issues of agro-environmental impacts and climate change. Multi-temporal Landsat data can be used to analyse decadal changes in cropping patterns at field level, owing to its medium spatial resolution and historical availability. This study attempts to develop robust remote sensing techniques, applicable across a large geographic extent, for state-wide mapping of cropping history in Queensland, Australia. In this context, traditional pixel-based classification was analysed in comparison with image object-based classification using advanced supervised machine-learning algorithms such as Support Vector Machine (SVM). For the Darling Downs region of southern Queensland we gathered a set of Landsat TM images from the 2010-2011 cropping season. Landsat data, along with the vegetation index images, were subjected to multiresolution segmentation to obtain polygon objects. Object-based methods enabled the analysis of aggregated sets of pixels, and exploited shape-related and textural variation, as well as spectral characteristics. SVM models were chosen after examining three shape-based parameters, twenty-three textural parameters and ten spectral parameters of the objects. We found that the object-based methods were superior to the pixel-based methods for classifying 4 major landuse/land cover classes, considering the complexities of within field spectral heterogeneity and spectral mixing. Comparative analysis clearly revealed that higher overall classification accuracy (95%) was observed in the object-based SVM compared with that of traditional pixel-based classification (89%) using maximum likelihood classifier (MLC). Object-based classification also resulted speckle-free images. Further, object-based SVM models were used to classify different broadacre crop types for summer and winter seasons. The influence of different shape, textural and spectral variables, and their weights on crop-mapping accuracy, was also examined. Temporal change in the spectral characteristics, specifically through vegetation indices derived from multi-temporal Landsat data, was found to be the most critical information that affects the accuracy of classification. However, use of these variables was constrained by the data availability and cloud cover.

  16. Weed Mapping in Early-Season Maize Fields Using Object-Based Analysis of Unmanned Aerial Vehicle (UAV) Images

    OpenAIRE

    Pen?a Barraga?n, Jose? Manuel; Torres-sa?nchez, Jorge; Castro, Ana Isabel; Kelly, Maggi; Lo?pez Granados, Francisca

    2013-01-01

    The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a w...

  17. Unsupervised Object Discovery and Localization in the Wild: Part-based Matching with Bottom-up Region Proposals

    OpenAIRE

    Cho, Minsu; Kwak, Suha; Schmid, Cordelia; Ponce, Jean

    2015-01-01

    This paper addresses unsupervised discovery and localization of dominant objects from a noisy image collection with multiple object classes. The setting of this problem is fully unsupervised, without even image-level annotations or any assumption of a single dominant class. This is far more general than typical colocalization, cosegmentation, or weakly-supervised localization tasks. We tackle the discovery and localization problem using a part-based region matching approach:...

  18. An X window based graphics user interface for radiation information processing system developed with object-oriented programming technology

    International Nuclear Information System (INIS)

    X Window is a network-oriented and network transparent windowing system, and now dominant in the Unix domain. The object-oriented programming technology can be used to change the extensibility of a software system remarkably. An introduction to graphics user interface is given. And how to develop a graphics user interface for radiation information processing system with object-oriented programming technology, which is based on X Window and independent of application is described briefly

  19. A multi-objective-ACO-based data association method for bearings-only multi-target tracking

    Science.gov (United States)

    Benlian, Xu; Zhiquan, Wang

    2007-12-01

    The study is concerned with data association of bearings-only multi-target tracking using two stationary observers in a 2-D scenario. In view of each target moving with a constant speed, two objective functions, i.e., distance and slope differences, are proposed and a multi-objective-ant-colony-optimization-based algorithm is then introduced to execute data association by minimizing the two objective functions. Numerical simulations are conducted to evaluate the effectiveness of the proposed algorithm in comparison with the data association results of the joint maximum likelihood (ML) method under different noise levels and track figurations.

  20. An adaptive evolutionary multi-objective approach based on simulated annealing.

    Science.gov (United States)

    Li, H; Landa-Silva, D

    2011-01-01

    A multi-objective optimization problem can be solved by decomposing it into one or more single objective subproblems in some multi-objective metaheuristic algorithms. Each subproblem corresponds to one weighted aggregation function. For example, MOEA/D is an evolutionary multi-objective optimization (EMO) algorithm that attempts to optimize multiple subproblems simultaneously by evolving a population of solutions. However, the performance of MOEA/D highly depends on the initial setting and diversity of the weight vectors. In this paper, we present an improved version of MOEA/D, called EMOSA, which incorporates an advanced local search technique (simulated annealing) and adapts the search directions (weight vectors) corresponding to various subproblems. In EMOSA, the weight vector of each subproblem is adaptively modified at the lowest temperature in order to diversify the search toward the unexplored parts of the Pareto-optimal front. Our computational results show that EMOSA outperforms six other well established multi-objective metaheuristic algorithms on both the (constrained) multi-objective knapsack problem and the (unconstrained) multi-objective traveling salesman problem. Moreover, the effects of the main algorithmic components and parameter sensitivities on the search performance of EMOSA are experimentally investigated. PMID:21417745