WorldWideScience

Sample records for ladar based object

  1. Supercomputer based ladar signature simulator

    Science.gov (United States)

    Welliver, Marc; Nichols, Terry; Gatt, Philip; Willis, Carla; Bunte, Steven

    2005-05-01

    Constantly improving ladar sensor technology has pushed simulation capabilities required for hardware-in-the-loop sensor testing and algorithm development beyond the capabilities of standard desktop PCs. Robust ladar computations require transport and manipulation of large, complex, multi-dimensional datasets containing range, irradiance, micro-Doppler, polarization, speckle decorrelation, and other information. Coherent Technologies, Inc. (CTI) is developing a portable, scalable software architecture for implementing ladar imaging simulation calculations on large cluster-based supercomputers. This architecture takes advantage of both line-of-sight and transverse modes of parallelization for the various stages of computation encountered in typical ladar calculations. In order to assure portability of software, this effort has followed ANSI coding standards for C/C++ and parallel data control is implemented using the Message Passing Interface (MPI). Using this rather general coding framework, CTI researchers have realized parallel efficiencies in excess of 50%, or fixed problem speedups of up to 19x on 32 processors. As increased fidelity is incorporated into the simulator, parallel efficiency is expected to improve even further.

  2. Microdoppler ladar systems

    Science.gov (United States)

    Otaguro, Wil; Hayes, Cecil

    2000-10-01

    Modern microdoppler ladars systems are capable of measuring a surface displacement velocity as small as 10 micrometers per second. The Precision Targeting and Identification ACTD is transitioning microdoppler ladars onto surveillance and tactical fighter platforms. They are being used to classify and identify airborne targets based on the vibration signatures of the target's power plant at ranges beyond 20 km. Derivative uses include detection/classification of operational, camouflaged surface and buried objects and an adjunct to optical imaging for space object identification. As the cost, size, and complexity of the micro-doppler ladars is reduced with the transition from the gas laser to solid state devices, microdoppler ladars will provide an affordable, operationally effective alternative to imaging sensors. This paper will discuss the status of microdoppler ladars developments and several applications including tactical airborne combat ID, detection of surface/buried targets, and space object identification.

  3. Image quality analysis and improvement of Ladar reflective tomography for space object recognition

    Science.gov (United States)

    Wang, Jin-cheng; Zhou, Shi-wei; Shi, Liang; Hu, Yi-Hua; Wang, Yong

    2016-01-01

    Some problems in the application of Ladar reflective tomography for space object recognition are studied in this work. An analytic target model is adopted to investigate the image reconstruction properties with limited relative angle range, which are useful to verify the target shape from the incomplete image, analyze the shadowing effect of the target and design the satellite payloads against recognition via reflective tomography approach. We proposed an iterative maximum likelihood method basing on Bayesian theory, which can effectively compress the pulse width and greatly improve the image resolution of incoherent LRT system without loss of signal to noise ratio.

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

    OpenAIRE

    Mateo, Ana Baselga; Barber, Zeb W.

    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 est...

  5. 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.

  6. Model-based recognition of 3D articulated target using ladar range data.

    Science.gov (United States)

    Lv, Dan; Sun, Jian-Feng; Li, Qi; Wang, Qi

    2015-06-10

    Ladar is suitable for 3D target recognition because ladar range images can provide rich 3D geometric surface information of targets. In this paper, we propose a part-based 3D model matching technique to recognize articulated ground military vehicles in ladar range images. The key of this approach is to solve the decomposition and pose estimation of articulated parts of targets. The articulated components were decomposed into isolate parts based on 3D geometric properties of targets, such as surface point normals, data histogram distribution, and data distance relationships. The corresponding poses of these separate parts were estimated through the linear characteristics of barrels. According to these pose parameters, all parts of the target were roughly aligned to 3D point cloud models in a library and fine matching was finally performed to accomplish 3D articulated target recognition. The recognition performance was evaluated with 1728 ladar range images of eight different articulated military vehicles with various part types and orientations. Experimental results demonstrated that the proposed approach achieved a high recognition rate. PMID:26192838

  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. Optical image processing for synthetic-aperture imaging ladar based on two-dimensional Fourier transform.

    Science.gov (United States)

    Sun, Zhiwei; Hou, Peipei; Zhi, Ya'nan; Sun, Jianfeng; Zhou, Yu; Xu, Qian; Lu, Zhiyong; Liu, Liren

    2014-03-20

    A two-dimensional (2D) Fourier transform algorithm for the image reconstruction of synthetic-aperture imaging ladar (SAIL) collected data is suggested. This algorithm consists of quadratic phase compensation in azimuth direction and 2D fast Fourier transform. Based on this algorithm and the parallel 2D Fourier transform capability of spherical lens, an optical principle scheme that processes the SAIL data is proposed. The basic principle, design equations, and necessary analysis are presented. To verify this principle scheme, an experimental optical SAIL processor setup is constructed. The imaging results of SAIL data obtained by our SAIL demonstrator are presented. The optical processor is compact, lightweight, and consumes low power. This optical processor can also provide inherent parallel and speed-of-light computing capability, and thus has potential applications in on-board and satellite-borne SAIL systems. PMID:24663462

  9. EO Scanned Micro-LADAR Project

    Data.gov (United States)

    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

    Data.gov (United States)

    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. Precision and accuracy testing of FMCW ladar-based length metrology.

    Science.gov (United States)

    Mateo, Ana Baselga; Barber, Zeb W

    2015-07-01

    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 FMCW ladar length measurement systems by use of spectroscopy of molecular frequency references HCN (C-band) or CO (L-band) to calibrate the chirp rate of the FMCW sources. Propagating the stated uncertainties from the molecular calibrations provided by NIST and measurement errors provide 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 uncertainties of the FMCW system and interferometer. PMID:26193146

  12. Research on key technologies of LADAR echo signal simulator

    Science.gov (United States)

    Xu, Rui; Shi, Rui; Ye, Jiansen; Wang, Xin; Li, Zhuo

    2015-10-01

    LADAR echo signal simulator is one of the most significant components of hardware-in-the-loop (HWIL) simulation systems for LADAR, which is designed to simulate the LADAR return signal in laboratory conditions. The device can provide the laser echo signal of target and background for imaging LADAR systems to test whether it is of good performance. Some key technologies are investigated in this paper. Firstly, the 3D model of typical target is built, and transformed to the data of the target echo signal based on ranging equation and targets reflection characteristics. Then, system model and time series model of LADAR echo signal simulator are established. Some influential factors which could induce fixed delay error and random delay error on the simulated return signals are analyzed. In the simulation system, the signal propagating delay of circuits and the response time of pulsed lasers are belong to fixed delay error. The counting error of digital delay generator, the jitter of system clock and the desynchronized between trigger signal and clock signal are a part of random delay error. Furthermore, these system insertion delays are analyzed quantitatively, and the noisy data are obtained. The target echo signals are got by superimposing of the noisy data and the pure target echo signal. In order to overcome these disadvantageous factors, a method of adjusting the timing diagram of the simulation system is proposed. Finally, the simulated echo signals are processed by using a detection algorithm to complete the 3D model reconstruction of object. The simulation results reveal that the range resolution can be better than 8 cm.

  13. Integration and demonstration of MEMS-scanned LADAR for robotic navigation

    Science.gov (United States)

    Stann, Barry L.; Dammann, John F.; Del Giorno, Mark; DiBerardino, Charles; Giza, Mark M.; Powers, Michael A.; Uzunovic, Nenad

    2014-06-01

    LADAR is among the pre-eminent sensor modalities for autonomous vehicle navigation. Size, weight, power and cost constraints impose significant practical limitations on perception systems intended for small ground robots. In recent years, the Army Research Laboratory (ARL) developed a LADAR architecture based on a MEMS mirror scanner that fundamentally improves the trade-offs between these limitations and sensor capability. We describe how the characteristics of a highly developed prototype correspond to and satisfy the requirements of autonomous navigation and the experimental scenarios of the ARL Robotics Collaborative Technology Alliance (RCTA) program. In particular, the long maximum and short minimum range capability of the ARL MEMS LADAR makes it remarkably suitable for a wide variety of scenarios from building mapping to the manipulation of objects at close range, including dexterous manipulation with robotic arms. A prototype system was applied to a small (approximately 50 kg) unmanned robotic vehicle as the primary mobility perception sensor. We present the results of a field test where the perception information supplied by the LADAR system successfully accomplished the experimental objectives of an Integrated Research Assessment (IRA).

  14. Miniature Ground Mapping LADAR Project

    Data.gov (United States)

    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...

  15. Anomaly Detection in Clutter using Spectrally Enhanced Ladar

    CERN Document Server

    Chhabra, Puneet S; Hopgood, James R

    2016-01-01

    Discrete return (DR) Laser Detection and Ranging (Ladar) systems provide a series of echoes that reflect from objects in a scene. These can be first, last or multi-echo returns. In contrast, Full-Waveform (FW)-Ladar systems measure the intensity of light reflected from objects continuously over a period of time. In a camouflaged scenario, e.g., objects hidden behind dense foliage, a FW-Ladar penetrates such foliage and returns a sequence of echoes including buried faint echoes. The aim of this paper is to learn local-patterns of co-occurring echoes characterised by their measured spectra. A deviation from such patterns defines an abnormal event in a forest/tree depth profile. As far as the authors know, neither DR or FW-Ladar, along with several spectral measurements, has not been applied to anomaly detection. This work presents an algorithm that allows detection of spectral and temporal anomalies in FW-Multi Spectral Ladar (FW-MSL) data samples. An anomaly is defined as a full waveform temporal and spectral ...

  16. Nonscanned ladar imaging and applications

    Science.gov (United States)

    Anthes, John P.; Garcia, Philip; Pierce, Joe T.; Dressendorfer, Paul V.

    1993-10-01

    A scannerless laser detection and ranging (LADAR) system is presently in development for applications at Sandia National Laboratories. This LADAR design eliminates the need for a mechanical laser beam scanner which is often the system component that limits the use of laser radars for many applications. Range to the target scene is determined in this approach by measuring the phase shift of the intensity modulation on the received optical return compared to the reference. The approach used in this LADAR is unique because the method used to detect this phase shift is an array of time integrating detectors that also records the image of the target scene. An analytical model is presented that describes the LADAR system performance. Applications of this LADAR system also are reviewed. They include terminal guidance of advanced conventional munitions, perimeter surveillance of secure facilities, mapping potholes/cracks in the U.S. highway system for improved maintenance scheduling, active collision avoidance of commercial/private vehicles, robotic vision integrated into advanced manufacturing concepts, and a novel airborne multi-sensor system containing LADAR, SAR, and LIDAR to locate and measure the thickness of ocean oil spills.

  17. Extracting and analyzing micro-Doppler from ladar signatures

    Science.gov (United States)

    Tahmoush, Dave

    2015-05-01

    Ladar and other 3D imaging modalities have the capability of creating 3D micro-Doppler to analyze the micro-motions of human subjects. An additional capability to the recognition of micro-motion is the recognition of the moving part, such as the hand or arm. Combined with measured RCS values of the body, ladar imaging can be used to ground-truth the more sensitive radar micro-Doppler measurements and associate the moving part of the subject with the measured Doppler and RCS from the radar system. The 3D ladar signatures can also be used to classify activities and actions on their own, achieving an 86% accuracy using a micro-Doppler based classification strategy.

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

    Data.gov (United States)

    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...

  19. Small SWAP 3D imaging flash ladar for small tactical unmanned air systems

    Science.gov (United States)

    Bird, Alan; Anderson, Scott A.; Wojcik, Michael; Budge, Scott E.

    2015-05-01

    The Space Dynamics Laboratory (SDL), working with Naval Research Laboratory (NRL) and industry leaders Advanced Scientific Concepts (ASC) and Hood Technology Corporation, has developed a small SWAP (size, weight, and power) 3D imaging flash ladar (LAser Detection And Ranging) sensor system concept design for small tactical unmanned air systems (STUAS). The design utilizes an ASC 3D flash ladar camera and laser in a Hood Technology gyro-stabilized gimbal system. The design is an autonomous, intelligent, geo-aware sensor system that supplies real-time 3D terrain and target images. Flash ladar and visible camera data are processed at the sensor using a custom digitizer/frame grabber with compression. Mounted in the aft housing are power, controls, processing computers, and GPS/INS. The onboard processor controls pointing and handles image data, detection algorithms and queuing. The small SWAP 3D imaging flash ladar sensor system generates georeferenced terrain and target images with a low probability of false return and Simulink®- based ladar system simulator designed and developed by the Center for Advanced Imaging Ladar (CAIL) at Utah State University. We will present the concept design and modeled performance predictions.

  20. 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.

  1. Monostatic all-fiber scanning LADAR system.

    Science.gov (United States)

    Leach, Jeffrey H; Chinn, Stephen R; Goldberg, Lew

    2015-11-20

    A compact scanning LADAR system based on a fiber-coupled, monostatic configuration which transmits (TX) and receives (RX) through the same aperture has been developed. A small piezo-electric stripe actuator was used to resonantly vibrate a fiber cantilever tip and scan the transmitted near-single-mode optical beam and the cladding mode receiving aperture. When compared to conventional bi-static systems with polygon, galvo, or Risley-prism beam scanners, the described system offers several advantages: the inherent alignment of the receiver field-of-view (FOV) relative to the TX beam angle, small size and weight, and power efficiency. Optical alignment of the system was maintained at all ranges since there is no parallax between the TX beam and the receiver FOV. A position-sensing detector (PSD) was used to sense the instantaneous fiber tip position. The Si PSD operated in a two-photon absorption mode to detect the transmitted 1.5 ?m pulses. The prototype system collected 50,000 points per second with a 6° full scan angle and a 27 mm clear aperture/40 mm focal length TX/RX lens, had a range precision of 4.7 mm, and was operated at a maximum range of 26 m. PMID:26836533

  2. Random subspace ensemble for target recognition of ladar range image

    Science.gov (United States)

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

    2013-02-01

    Laser detection and ranging (ladar) range images have attracted considerable attention in the field of automatic target recognition. Generally, it is difficult to collect a mass of range images for ladar in real applications. However, with small samples, the Hughes effect may occur when the number of features is larger than the size of the training samples. A random subspace ensemble of support vector machine (RSE-SVM) is applied to solve the problem. Three experiments were performed: (1) the performance comparison among affine moment invariants (AMIs), Zernike moment invariants (ZMIs) and their combined moment invariants (CMIs) based on different size training sets using single SVM; (2) the impact analysis of the different number of features about the RSE-SVM and semi-random subspace ensemble of support vector machine; (3) the performance comparison between the RSE-SVM and the CMIs with SVM ensembles. The experiment's results demonstrate that the RSE-SVM is able to relieve the Hughes effect and perform better than ZMIs with single SVM and CMIs with SVM ensembles.

  3. 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.

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

    Data.gov (United States)

    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...

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

    Data.gov (United States)

    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...

  6. 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)

  7. Crossmodal Object-Based Attention: Auditory Objects Affect Visual Processing

    Science.gov (United States)

    Turatto, M.; Mazza, V.; Umilta, C.

    2005-01-01

    According to the object-based view, visual attention can be deployed to ''objects'' or perceptual units, regardless of spatial locations. Recently, however, the notion of object has also been extended to the auditory domain, with some authors suggesting possible interactions between visual and auditory objects. Here we show that task-irrelevant…

  8. Flight test results of ladar brownout look-through capability

    Science.gov (United States)

    Stelmash, Stephen; Münsterer, Thomas; Kramper, Patrick; Samuelis, Christian; Bühler, Daniel; Wegner, Matthias; Sheth, Sagar

    2015-06-01

    The paper discusses recent results of flight tests performed with the Airbus Defence and Space ladar system at Yuma Proving Grounds. The ladar under test was the SferiSense® system which is in operational use as an in-flight obstacle warning and avoidance system on the NH90 transport helicopter. Just minor modifications were done on the sensor firmware to optimize its performance in brownout. Also a new filtering algorithm fitted to segment dust artefacts out of the collected 3D data in real-time was employed. The results proved that this ladar sensor is capable to detect obstacles through brownout dust clouds with a depth extending up to 300 meters from the landing helicopter.

  9. Enhanced resolution edge and surface estimation from ladar point clouds containing multiple return data

    Science.gov (United States)

    Neilsen, Kevin D.; Budge, Scott E.

    2013-11-01

    Signal processing enables the detection of more returns in a digital ladar waveform by computing the surface response. Prior work has shown that obtaining the surface response can improve the range resolution by a factor of 2. However, this advantage presents a problem when forming a range image-each ladar shot crossing an edge contains multiple values. To exploit this information, the location of each return inside the spatial beam footprint is estimated by dividing the footprint into sections that correspond to each return and assigning the coordinates of the return to the centroid of the region. Increased resolution results on the edges of targets where multiple returns occur. Experiments focus on angled and slotted surfaces for both simulated and real data. Results show that the angle of incidence on a 75-deg surface is computed only using a single waveform with an error of 1.4 deg and that the width of a 19-cm-wide by 16-cm-deep slot is estimated with an error of 3.4 cm using real data. Point clouds show that the edges of the slotted surface are sharpened. These results can be used to improve features extracted from objects for applications such as automatic target recognition.

  10. A ?-type soft-aperture LADAR SNR improvement with quantum-enhanced receiver

    Science.gov (United States)

    Yang, Song; Ruan, Ningjuan; Lin, Xuling; Wu, Zhiqiang

    2015-08-01

    A quantum-enhanced receiver that uses squeezed vacuum injection (SVI) and phase sensitive amplification (PSA) is in principle capable of obtaining effective signal to noise ratio (SNR) improvement in a soft-aperture homodyne-detection LAser Detection And Ranging (LADAR) system over the classical homodyne LADAR to image a far-away target. Here we investigate the performance of quantum-enhanced receiver in ?-type soft aperture LADAR for target imaging. We also use fast Fourier transform (FFT) Algorithm to simulate LADAR intensity image, and give a comparison of the SNR improvement of soft aperture case and hard aperture case.

  11. Simulation of a Geiger-Mode Imaging LADAR System for Performance Assessment

    Directory of Open Access Journals (Sweden)

    Yong Joon Kwon

    2013-07-01

    Full Text Available As LADAR systems applications gradually become more diverse, new types of systems are being developed. When developing new systems, simulation studies are an essential prerequisite. A simulator enables performance predictions and optimal system parameters at the design level, as well as providing sample data for developing and validating application algorithms. The purpose of the study is to propose a method for simulating a Geiger-mode imaging LADAR system. We develop simulation software to assess system performance and generate sample data for the applications. The simulation is based on three aspects of modeling—the geometry, radiometry and detection. The geometric model computes the ranges to the reflection points of the laser pulses. The radiometric model generates the return signals, including the noises. The detection model determines the flight times of the laser pulses based on the nature of the Geiger-mode detector. We generated sample data using the simulator with the system parameters and analyzed the detection performance by comparing the simulated points to the reference points. The proportion of the outliers in the simulated points reached 25.53%, indicating the need for efficient outlier elimination algorithms. In addition, the false alarm rate and dropout rate of the designed system were computed as 1.76% and 1.06%, respectively.

  12. Ontology Based Complex Object Recognition

    OpenAIRE

    Maillot, Nicolas; Thonnat, Monique

    2008-01-01

    This paper presents a new approach for object categorization involving the following aspects of cognitive vision: learning, recognition and knowledge representation.A major element of our approach is a visual concept ontology composed of several types of concepts (spatial concepts and relations, color concepts and texture concepts). Visual concepts contained in this ontology can be seen as an intermediate layer between domain knowledge and image processing procedures. Machine learning techniq...

  13. 3D-LZ helicopter ladar imaging system

    Science.gov (United States)

    Savage, James; Harrington, Walter; McKinley, R. Andrew; Burns, H. N.; Braddom, Steven; Szoboszlay, Zoltan

    2010-04-01

    A joint-service team led by the Air Force Research Laboratory's Munitions and Sensors Directorates completed a successful flight test demonstration of the 3D-LZ Helicopter LADAR Imaging System. This was a milestone demonstration in the development of technology solutions for a problem known as "helicopter brownout", the loss of situational awareness caused by swirling sand during approach and landing. The 3D-LZ LADAR was developed by H.N. Burns Engineering and integrated with the US Army Aeroflightdynamics Directorate's Brown-Out Symbology System aircraft state symbology aboard a US Army EH-60 Black Hawk helicopter. The combination of these systems provided an integrated degraded visual environment landing solution with landing zone situational awareness as well as aircraft guidance and obstacle avoidance information. Pilots from the U.S. Army, Air Force, Navy, and Marine Corps achieved a 77% landing rate in full brownout conditions at a test range at Yuma Proving Ground, Arizona. This paper will focus on the LADAR technology used in 3D-LZ and the results of this milestone demonstration.

  14. 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

  15. Object-based attention influences saccade latency.

    Science.gov (United States)

    Senturk, Gozde; Greenberg, Adam; Liu, Taosheng

    2015-09-01

    In the influential two-rectangle paradigm, attention is preferentially allocated to cued objects over noncued objects (Egly et al, 1994). Improved performance within the cued object manifests itself as a manual reaction time and accuracy advantage. However, no study to date has systematically investigated how saccadic reaction time is affected by object-based attention. Our goal is to determine whether saccade latencies are affected by space-based attention alone or whether object-based attention also plays a role. We employed a modified version of the classic two-rectangle paradigm coupled with a saccade reaction time task. Two horizontal or vertical rectangles (orientation blocked), were presented with an exogenous spatial cue flashed at one end of one rectangle. A target gray disk then appeared at one end of one object on 80% of trials (20% target absent). Of target present trials, 75% were valid trials in which the target appeared at the cued location, and on invalid trials (25%) the target appeared equally likely at the uncued end of the cued object (invalid-same object), or at an equidistant location on the uncued object (invalid-different object). Participants were instructed to make a single saccade to the target. Results showed that the saccadic latency was fastest on valid trials. Moreover, saccadic latency was significantly faster during invalid-same object trials versus invalid-different object trials. This effect was found for both the vertical and horizontal rectangle configurations. These results indicate that the oculomotor system is not only involved in location-based saccade preparation, but it is also guided by object-based attention. The eye-movement planning system may, therefore, be subject to the same boundary conditions that determine the representational basis of attentional selection in the visual scene. Meeting abstract presented at VSS 2015. PMID:26326950

  16. Demonstrated resolution enhancement capability of a stripmap holographic aperture ladar system.

    Science.gov (United States)

    Venable, Samuel M; Duncan, Bradley D; Dierking, Matthew P; Rabb, David J

    2012-08-01

    Holographic aperture ladar (HAL) is a variant of synthetic aperture ladar (SAL). The two processes are related in that they both seek to increase cross-range (i.e., the direction of the receiver translation) image resolution through the synthesis of a large effective aperture. This is in turn achieved via the translation of a receiver aperture and the subsequent coherent phasing and correlation of multiple received signals. However, while SAL imaging incorporates a translating point detector, HAL takes advantage of a two-dimensional translating sensor array. For the research presented in this article, a side-looking stripmap HAL geometry was used to sequentially image a set of Ronchi ruling targets. Prior to this, theoretical calculations were performed to determine the baseline, single subaperture resolution of our experimental, laboratory-based system. Theoretical calculations were also performed to determine the ideal modulation transfer function (MTF) and expected cross-range HAL image sharpening ratio corresponding to the geometry of our apparatus. To verify our expectations, we first sequentially captured an oversampled collection of pupil plane field segments for each Ronchi ruling. A HAL processing algorithm incorporating a high-precision speckle field registration process was then employed to phase-correct and reposition the field segments. Relative interframe piston phase errors were also removed prior to final synthetic image formation. By then taking the Fourier transform of the synthetic image intensity and examining the fundamental spatial frequency content, we were able to produce experimental modulation transfer function curves, which we then compared with our theoretical expectations. Our results show that we are able to achieve nearly diffraction-limited results for image sharpening ratios as high as 6.43. PMID:22859045

  17. A 32x32 pixel focal plane array ladar system using chirped amplitude modulation

    Science.gov (United States)

    Stann, Barry L.; Aliberti, Keith; Carothers, Daniel; Dammann, John; Dang, Gerard; Giza, Mark M.; Lawler, William B.; Redman, Brian C.; Simon, Deborah R.

    2004-09-01

    The Army Research Laboratory is researching system architectures and components required to build a 32x32 pixel scannerless ladar breadboard. 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 (i.e. chirped amplitude modulation). The backscattered light 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. Pixel read-out is achieved using code division multiple access techniques as opposed to the usual time-multiplexed techniques to attain high effective frame rates. The raw data is captured with analog-to-digital converters and fed into a PC to demux the pixel data, compute the target ranges, and display the imagery. Last year we demonstrated system proof-of-principle for the first time and displayed an image of a scene collected in the lab that was somewhat corrupted by pixel-to-pixel cross-talk. This year we report on system modifications that reduced pixel-to-pixel cross-talk and new hardware and display codes that enable near real-time stereo display of imagery on the ladar's control computer. The results of imaging tests in the laboratory will also be presented.

  18. 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

  19. Object-based sound source modeling

    OpenAIRE

    Tolonen, Tero

    2000-01-01

    This thesis proposes techniques for object-based audio and music. The work can be divided into two parts corresponding to model-based synthesis of musical instruments and computational analysis of audio and music. The contributions of this work are in signal and auditory analysis, sound object modeling, and sound signal synthesis. The first half of the thesis considers linear and particularly nonlinear discrete-time modeling of plucked string instruments. The nonlinear tension modulation ...

  20. Coding Transparency in Object-Based Video

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Søren

    A novel algorithm for coding gray level alpha planes in object-based video is presented. The scheme is based on segmentation in multiple layers. Different coders are specifically designed for each layer. In order to reduce the bit rate, cross-layer redundancies as well as temporal correlation are...

  1. 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...

  2. Object-based neglect in number processing

    Directory of Open Access Journals (Sweden)

    Klein Elise

    2013-01-01

    Full Text Available Abstract Recent evidence suggests that neglect patients seem to have particular problems representing relatively smaller numbers corresponding to the left part of the mental number line. However, while this indicates space-based neglect for representational number space little is known about whether and - if so - how object-based neglect influences number processing. To evaluate influences of object-based neglect in numerical cognition, a group of neglect patients and two control groups had to compare two-digit numbers to an internally represented standard. Conceptualizing two-digit numbers as objects of which the left part (i.e., the tens digit should be specifically neglected we were able to evaluate object-based neglect for number magnitude processing. Object-based neglect was indicated by a larger unit-decade compatibility effect actually reflecting impaired processing of the leftward tens digits. Additionally, faster processing of within- as compared to between-decade items provided further evidence suggesting particular difficulties in integrating tens and units into the place-value structure of the Arabic number system. In summary, the present study indicates that, in addition to the spatial representation of number magnitude, also the processing of place-value information of multi-digit numbers seems specifically impaired in neglect patients.

  3. Spatio-activity based object detection

    CERN Document Server

    Springett, Jarrad

    2008-01-01

    We present the SAMMI lightweight object detection method which has a high level of accuracy and robustness, and which is able to operate in an environment with a large number of cameras. Background modeling is based on DCT coefficients provided by cameras. Foreground detection uses similarity in temporal characteristics of adjacent blocks of pixels, which is a computationally inexpensive way to make use of object coherence. Scene model updating uses the approximated median method for improved performance. Evaluation at pixel level and application level shows that SAMMI object detection performs better and faster than the conventional Mixture of Gaussians method.

  4. Object Recognition Based on Wave Atom Transform

    Directory of Open Access Journals (Sweden)

    Thambu Gladstan

    2014-10-01

    Full Text Available This study presents an efficient method for recognizing object in an image based on Wave Atom Trans-form (WAT. Object recognition is achieved by extracting the energies from all coefficients of WAT. The original image is decomposed by using the WAT. All coefficients are considered as features for the classification process. The extracted features are given as an input to the K-Nearest Neighbor (K-NN classifier to recognize the object. The evaluation of the system is carried on using Columbia Object Image Library Dataset (COIL-100 database. The classification performance of the proposed system is evaluated by using classification rate in percentage, which is achieved by varying the angle between the views.

  5. Behavioral Simulation Based on Knowledge Objects

    Science.gov (United States)

    Maruichi, Takeo; Uchiki, Tetsuya; Tokoro, Mario

    The purpose of behavioral simulation is to simulate the behavior of the characters having behavior rules in the surrounding environment. This kind of simulation, which differs from the traditional simulation baaed on a statistical model of the world, provides us with a more precise simulation with regard to individuals. Because of the nature of behavioral simulation, characters, the environment in which the characters exist, and messages which are passed among characters, are the main elements that should be considered. The notion of object-orientation is one of the most attractive computational models for providing the basis of behavioral simulation. Specifically, we employ the notion of knowledge objects which are objects having knowledge contained within themselves. We fist establish a behavioral simulation model based on the notion of knowledge objects, then design and implement a behavioral simulation system PARADISE. To demonstrate the capability and effectiveness of this Simulation model, barracuda and herring school is used as an example of this simulation system.

  6. Advances in ladar components and subsystems at Raytheon

    Science.gov (United States)

    Jack, Michael; Chapman, George; Edwards, John; Mc Keag, 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

    2012-06-01

    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 MMSS) program and (2) staring 256 × 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.

  7. Object tracking based on bit-planes

    Science.gov (United States)

    Li, Na; Zhao, Xiangmo; Liu, Ying; Li, Daxiang; Wu, Shiqian; Zhao, Feng

    2016-01-01

    Visual object tracking is one of the most important components in computer vision. The main challenge for robust tracking is to handle illumination change, appearance modification, occlusion, motion blur, and pose variation. But in surveillance videos, factors such as low resolution, high levels of noise, and uneven illumination further increase the difficulty of tracking. To tackle this problem, an object tracking algorithm based on bit-planes is proposed. First, intensity and local binary pattern features represented by bit-planes are used to build two appearance models, respectively. Second, in the neighborhood of the estimated object location, a region that is most similar to the models is detected as the tracked object in the current frame. In the last step, the appearance models are updated with new tracking results in order to deal with environmental and object changes. Experimental results on several challenging video sequences demonstrate the superior performance of our tracker compared with six state-of-the-art tracking algorithms. Additionally, our tracker is more robust to low resolution, uneven illumination, and noisy video sequences.

  8. Object Based Video Analysis, Interpretation and Tracking

    Directory of Open Access Journals (Sweden)

    A. Umamakeswari

    2007-01-01

    Full Text Available The role of computers in different facets of human life is increasing everyday, from one of supplementing his needs to one of integrating in the different activities, he is involved. This has become more predominant with the prolific developments in communication and internet. This brings in a need to raise the level of computers to the level of human beings and a paradigm shift from hard computing to soft computing towards the turn of this century has reinforced this. The present focus of the study is on implementing visual capabilities in computers so that involvement and interaction with humans are easier. The paper presents the details of object based video analysis for conventional engineering applications.

  9. 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 faile...

  10. Invariant object recognition based on extended fragments

    OpenAIRE

    Bart, Evgeniy; Hegdé, Jay

    2012-01-01

    Visual appearance of natural objects is profoundly affected by viewing conditions such as viewpoint and illumination. Human subjects can nevertheless compensate well for variations in these viewing conditions. The strategies that the visual system uses to accomplish this are largely unclear. Previous computational studies have suggested that in principle, certain types of object fragments (rather than whole objects) can be used for invariant recognition. However, whether the human visual syst...

  11. MATHEMATICAL BASED APPROACH FOR OBJECT CLASSIFICATION

    OpenAIRE

    Prakash, K; Dr. B. Nagarajan

    2014-01-01

    The goal of this study is to build a system that detects and classifies the bike objects amidst background clutter and mild occlusion. This study addresses the issues to classify objects of real world images containing side views of the bike with cluttered background with that of non-bike images with natural scenes. The threshold technique with background subtraction is used to segment the background region to extract the object of interest. The background segmented image with region of inter...

  12. Unambiguous range-Doppler LADAR processing using 2 giga-sample-per-second noise waveforms

    International Nuclear Information System (INIS)

    We demonstrate sub-nanosecond range and unambiguous sub-50-Hz Doppler resolved laser radar (LADAR) measurements using spectral holographic processing in rare-earth ion doped crystals. The demonstration utilizes pseudo-random-noise 2 giga-sample-per-second baseband waveforms modulated onto an optical carrier

  13. 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.

  14. Interval-based Specification of Concurrent Objects

    DEFF Research Database (Denmark)

    Løvengreen, Hans Henrik; Sørensen, Morten U.

    We propose a logic for specifying the behaviour of concurrent objects, ie. concurrent entities that invoke operation of each other. The logic is an interval logic whith operation invocatins as primitive formulas. The strengths and deficiencies of the logic are illustrated by specifying a variety of...

  15. 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.

  16. Exploring the relationship between object realism and object-based attention effects.

    Science.gov (United States)

    Roque, Nelson; Boot, Walter R

    2015-09-01

    Visual attention prioritizes processing of locations in space, and evidence also suggests that the benefits of attention can be shaped by the presence of objects (object-based attention). However, the prevalence of object-based attention effects has been called into question recently by evidence from a large-sampled study employing classic attention paradigms (Pilz et al., 2012). We conducted two experiments to explore factors that might determine when and if object-based attention effects are observed, focusing on the degree to which the concreteness and realism of objects might contribute to these effects. We adapted the classic attention paradigm first reported by Egly, Driver, and Rafal (1994) by replacing abstract bar stimuli in some conditions with objects that were more concrete and familiar to participants: items of silverware. Furthermore, we varied the realism of these items of silverware, presenting either cartoon versions or photo-realistic versions. Contrary to predictions, increased realism did not increase the size of object-based effects. In fact, no clear object-based effects were observed in either experiment, consistent with previous failures to replicate these effects in similar paradigms. While object-based attention may exist, and may have important influences on how we parse the visual world, these and other findings suggest that the two-object paradigm typically relied upon to study object-based effects may not be the best paradigm to investigate these issues. PMID:26256694

  17. Ellipse Fitting Based Approach for Extended Object Tracking

    OpenAIRE

    Borui Li; Chundi Mu; Yongqiang Bai; Jianquan Bi; Lei Wang

    2014-01-01

    With the increase of sensors’ resolution, traditional object tracking technology, which ignores object’s physical extension, gradually becomes inappropriate. Extended object tracking (EOT) technology is able to obtain more information about the object through jointly estimating both centroid’s dynamic state and physical extension of the object. Random matrix based approach is a promising method for EOT. It uses ellipse/ellipsoid to describe the physical extension of the object. In order to re...

  18. Object-based selection of irrelevant features is not confined to the attended object

    OpenAIRE

    Böhler, Nico; Schoenfeld, Mircea-A; Heinze, Hans-Jochen; Hopf, Jens-Max

    2011-01-01

    Attention to one feature of an object can bias the processing of unattended features of that object. Here we demonstrate with ERPs in visual search that this object-based bias for an irrelevant feature also appears in an unattended object when it shares that feature with the target object. Specifically, we show that the ERP response elicited by a distractor object in one visual field is modulated as a function of whether a task-irrelevant color of that distractor is also present in the target...

  19. 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

  20. 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...

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  2. Fast Moving Object Segmentation Based On Active Contours

    OpenAIRE

    Huimin Zhang; Zhiyong Duan; Zhongjie Zhu; Yuer Wang

    2012-01-01

    Active contour method is widely used in the image processing field. Recently, it has been used in object segmentation and has attracted great attention. However, most of the existing object segmentation methods based on active contours are complex and time-consuming. They cannot be used in some real-time applications. Hence, in this paper, a fast and efficient moving object segmentation algorithm based on an improved active contour model is proposed. Firstly, moving regions are detected based...

  3. Context based Coding of Quantized Alpha Planes for Video Objects

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Søren

    In object based video, each frame is a composition of objects that are coded separately. The composition is performed through the alpha plane that represents the transparency of the object. We present an alternative to MPEG-4 for coding of alpha planes that considers their specific properties...

  4. Fast Moving Object Segmentation Based On Active Contours

    Directory of Open Access Journals (Sweden)

    Huimin Zhang

    2012-04-01

    Full Text Available Active contour method is widely used in the image processing field. Recently, it has been used in object segmentation and has attracted great attention. However, most of the existing object segmentation methods based on active contours are complex and time-consuming. They cannot be used in some real-time applications. Hence, in this paper, a fast and efficient moving object segmentation algorithm based on an improved active contour model is proposed. Firstly, moving regions are detected based on frame differences. Then their boundaries are extracted and used as the coarse objects’ contours for the next segmentation based on active contour model. Thirdly, an improved active contour method is introduced to extract the final objects with the coarse objects’ contours as initial values. Experiments are implemented and the results show that the proposed algorithm can segment and track moving targets quickly and correctly.

  5. 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.

  6. Stereovision-Based Object Segmentation for Automotive Applications

    OpenAIRE

    Fu Shan; Thompson Chris; Huang Yingping

    2005-01-01

    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 i...

  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. Content-Based Object Movie Retrieval and Relevance Feedbacks

    Directory of Open Access Journals (Sweden)

    Lee Greg C

    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.

  9. 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.

  10. Monocular model-based 3D tracking of rigid objects

    CERN Document Server

    Lepetit, Vincent

    2014-01-01

    Many applications require tracking complex 3D objects. These include visual serving of robotic arms on specific target objects, Augmented Reality systems that require real time registration of the object to be augmented, and head tracking systems that sophisticated interfaces can use. Computer vision offers solutions that are cheap, practical and non-invasive. ""Monocular Model-Based 3D Tracking of Rigid Objects"" reviews the different techniques and approaches that have been developed by industry and research. First, important mathematical tools are introduced: camera representation, robust e

  11. G-CNN: an Iterative Grid Based Object Detector

    OpenAIRE

    Najibi, Mahyar; Rastegari, Mohammad; Davis, Larry S.

    2015-01-01

    We introduce G-CNN, an object detection technique based on CNNs which works without proposal algorithms. G-CNN starts with a multi-scale grid of fixed bounding boxes. We train a regressor to move and scale elements of the grid towards objects iteratively. G-CNN models the problem of object detection as finding a path from a fixed grid to boxes tightly surrounding the objects. G-CNN with around 180 boxes in a multi-scale grid performs comparably to Fast R-CNN which uses around 2K bounding boxe...

  12. 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.

  13. 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.

  14. Object-based detection of vehicles in airborne data

    Science.gov (United States)

    Schilling, Hendrik; Bulatov, Dimitri; Middelmann, Wolfgang

    2015-10-01

    Robust detection of vehicles in airborne data is a challenging task since a high variation in the object signatures - depending on data resolution - and often a small contrast between objects and background lead to high false classification rates and missed detections. Despite these facts, many applications require reliable results which can be obtained in a short time. In this paper, an object-based approach for vehicle detection in airborne laser scans (ALS) and photogrammetrically reconstructed 2.5D data is described. The focus of this paper lies on a robust object segmentation algorithm as well as the identification of features for a reliable separation between vehicles and background (all nonevehicle objects) on different scenes. The described method is based on three consecutive steps, namely, object segmentation, feature extraction and supervised classification. In the first step, the 2.5D data is segmented and possible targets are identified. The segmentation progress is based on the morphological top-hat filtering, which leaves areas that are smaller than a given filter size and higher (brighter) than their surroundings. The approach is chosen due to the low computational effort of this filter, which allows a fast computation even for large areas. The next step is feature extraction. Based on the initial segmentation, features for every identified object are extracted. In addition to frequently used features like height above ground, object area, or point distribution, more complex features like object planarity, entropy in the intensity image, and lineness measures are used. The last step contains classification of each object. For this purpose, a random forest classifier (RF) using the normalized features extracted in the previous step is chosen. RFs are suitable for high dimensional and nonlinear problems. In contrast to other approaches (e.g. maximum likelihood classifier), RFs achieves good results even with relatively small training samples.

  15. 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

  16. Object Tracking Based on Local Sparse Appearance Model

    Directory of Open Access Journals (Sweden)

    Jihong Deng

    2015-08-01

    Full Text Available Because of the algorithm of object tracking based on features matching cannot process the images whose texture is not abundant and L1 tracking cannot handle the drifting problem, we propose a new tracking algorithm of object tracking based on local sparse appearance model. The object appearance model is obtained by sparse representation and pooling across the local patches and the method of alignment-pooling is used to get the vector of the candidate. Both incremental subspace learning and sparse representation are employed to update the templates. Within the Bayesian inference framework, object tracking is a problem by finding the MAP. The framework of the algorithm includes four parts which are constructing a dictionary, sparse appearance model of candidates, calculating posterior probability and template updating. Numerous experiments demonstrate that the algorithm has achieved good results in many classical videos.

  17. Human Object Detection based on Context Awareness in the Surroundings

    Directory of Open Access Journals (Sweden)

    Nguyen Thanh Binh

    2015-08-01

    Full Text Available Surveillance system has been applied in providing public security for many complex places like railway stations, bus stops, etc. In most cases, human object detection is an important task in surveillance system. In the case that human objects are occlusion or outdoor environment, human objects detection is a challenging problem. In this paper, we propose a method to implement for human object detection based on context awareness in new wavelet generation domain in outdoor environment. We use curvelet transform based on context awareness combined with support vector machines as a classifier for human detection. The proposed method was tested on a standard dataset like PEST2001 dataset. For demonstrating the superiority of the proposed method, we have compared the results with the other recent methods available in literature.

  18. A New Approach to Object Based Fuzzy Database Modeling

    Directory of Open Access Journals (Sweden)

    Debasis Dwibedy

    2013-03-01

    Full Text Available The requirements in diversified application domains like Engineering, Scientific technology, Multimedia, Knowledge management in expert systems etc shift the momentum of current trends in designing database models to an innovative concept of Object Based fuzzy Database Model. The ongoing research concentrates on representing the imprecise information by taking object modelling methodology and fuzzy techniques through different levels of class hierarchy and abstractions. Still, a formal definition of fuzzy class is not yet given by which we can represent all standards of fuzzy objects and attributes. In this paper, we redefine the fuzzy class in an efficient manner and propose the structure of the fuzzy class using more effective generalized techniques to develop a new object based fuzzy data model in order to manipulate imprecise information and exposed to wider range of applicability. Also, we define a formal framework for generalized fuzzy constraints which can be applied effectively to fuzzy specialized classes in fuzzy class hierarchy.

  19. Multi-Objective Community Detection Based on Memetic Algorithm

    OpenAIRE

    WU, PENG; Pan, Li

    2015-01-01

    Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global sear...

  20. Geophysics-based method of locating a stationary earth object

    Science.gov (United States)

    Daily, Michael R. (Albuquerque, NM); Rohde, Steven B. (Corrales, NM); Novak, James L. (Albuquerque, NM)

    2008-05-20

    A geophysics-based method for determining the position of a stationary earth object uses the periodic changes in the gravity vector of the earth caused by the sun- and moon-orbits. Because the local gravity field is highly irregular over a global scale, a model of local tidal accelerations can be compared to actual accelerometer measurements to determine the latitude and longitude of the stationary object.

  1. BOSD: Business Object Based Flexible Software Development for Enterprises

    OpenAIRE

    Xiaofei Xu; Jindan Feng; Dechen Zhan; Lanshun Nie

    2010-01-01

    The enterprise software need adapt to new requirements from the continuous change management. The recent development methods have increased the flexibility of software. However, previous studies have ignored the stability of business object and the particular business relationships to support the software development. In this paper, a coarse-grained business object based software development, BOSD, is presented to resolve this problem. By analyzing the characteristics of variable requirement,...

  2. Multi-objective Optimization using Chaos Based PSO

    Directory of Open Access Journals (Sweden)

    Weizhou Zhong

    2011-01-01

    Full Text Available As a novel optimization method, chaos has gained lots of attentions and applications in the past few years. Chaos movement can go through all states unrepeated according to the rule of itself in some area. It was introduced into the optimization strategy to accelerate the optimum seeking operation in this study. A chaos based particle swarm optimization strategy was developed to solve multi-objective optimization problems. The proposed approach is validated using several benchmark test functions and metrics on evolutionary multi-objective optimization. Results demonstrate the effectiveness and efficiency of the proposed strategy and that can be considered a viable alternative to solve multi-objective optimization problems.

  3. A General Polygon-based Deformable Model for Object Recognition

    DEFF Research Database (Denmark)

    Jensen, Rune Fisker; Carstensen, Jens Michael

    We propose a general scheme for object localization and recognition based on a deformable model. The model combines shape and image properties by warping a arbitrary prototype intensity template according to the deformation in shape. The shape deformations are constrained by a probabilistic...... distribution, which combined with a match of the warped intensity template and the image form the final criteria used for localization and recognition of a given object. The chosen representation gives the model an ability to model an almost arbitrary object. Beside the actual model a full general scheme for...

  4. Segmentation of object-based video of gaze communication

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Stegmann, Mikkel Bille; Forchhammer, Søren; Ersbøll, Bjarne Kjær

    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. Video Based Moving Object Tracking by Particle Filter

    Directory of Open Access Journals (Sweden)

    Md. Zahidul Islam

    2009-03-01

    Full Text Available Usually, the video based object tracking deal with non-stationary image stream that changes over time. Robust and Real time moving object tracking is a problematic issue in computer vision research area. Most of the existing algorithms are able to track only inpredefined and well controlled environment. Some cases, they don’t consider non-linearity problem. In our paper, we develop such a system which considers color information, distance transform (DT based shape information and also nonlinearity. Particle filtering has been proven very successful for non-gaussian and non-linear estimation problems. We examine the difficulties of video based tracking and step by step we analyze these issues. In our firstapproach, we develop the color based particle filter tracker that relies on the deterministic search of window, whose color content matches a reference histogram model. A simple HSV histogram-based color model is used to develop this observation system. Secondly, wedescribe a new approach for moving object tracking with particle filter by shape information. The shape similarity between a template and estimated regions in the video scene is measured by their normalized cross-correlation of distance transformed images. Our observation system of particle filter is based on shape from distance transformed edge features. Template is created instantly by selecting any object from the video scene by a rectangle. Finally, inthis paper we illustrate how our system is improved by using both these two cues with non linearity.

  6. 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.

  7. 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.

  8. 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.

  9. Ground-based optical observation system for LEO objects

    Science.gov (United States)

    Yanagisawa, T.; Kurosaki, H.; Oda, H.; Tagawa, M.

    2015-08-01

    We propose a ground-based optical observation system for monitoring LEO objects, which uses numerous optical sensors to cover a vast region of the sky. Its potential in terms of detection and orbital determination were examined. About 30 cm LEO objects at 1000 km altitude are detectable using an 18 cm telescope, a CCD camera and the analysis software developed. Simulations and a test observation showed that two longitudinally separate observation sites with arrays of optical sensors can identify the same objects from numerous data sets and determine their orbits precisely. The proposed system may complement or replace the current radar observation system for monitoring LEO objects, like space-situation awareness, in the near future.

  10. Object-based effects in visual change detection

    Directory of Open Access Journals (Sweden)

    Dagmar Mueller

    2009-03-01

    Full Text Available There is an ongoing debate whether or not visual object representations can be formed outside the focus of voluntary attention. Implicit behavioral measures seem to support theories of pre-attentive object formation. However, with these implicit measures the supposedly task-irrelevant elements forming the objects were still usually related to the task-relevant stimuli in some way. We developed a paradigm based on the visual mismatch negativity (vMMN ERP component that allows to test visual grouping when neither the objects nor their constituents are related to the participant’s task. Our stimuli consisted of four pairs of colored discs which were evenly distributed around the fixation point. Pairs were formed by use of the gestalt principle of common region and thus, served as objects. Each display contained 6 blue-colored discs and 2 red-colored discs with the latter ones always presented at neighboring positions. In separate conditions, the two red-colored discs either usually (p=0.9 belonged to the same object (standard: red-in-same-object or to two different objects (standard: red-in-different-objects. Occasionally (p=0.1, the assignment of the two red-colored discs to objects was exchanged. That is, deviances were exclusively defined on the basis of object-irregularities, since the features and their distribution were identical between standard and deviant displays. Each test-display was shown for 120 ms and was followed by an inter stimulus interval of 300 ms. Participants were instructed to detect slight changes of the continuously presented fixation cross. Thus, the display items included in the object stimuli were fully task irrelevant. We found no differences between the ERPs elicited by the physically identical deviant and standard red-in-different objects displays. However, comparison of the ERPs elicited by deviant and standard red-in-same object displays yielded an occipitally maximal negative deflection peaking in the 200-260 ms latency range, which was identified as vMMN. The elicitation of vMMN shows that visual object formation can precede pre-attentive deviance-detection. Therefore, the results support theories of pre attentive visual object formation. The asymmetry between the change from red in-different objects to red in same object (eliciting vMMN and the reversed configuration (resulting in no vMMN elicitation parallels similar MMN findings in the auditory modality: When the deviant was a part of the standard no or only a small MMN was elicited. In our design, red-in-different-objects deviants may be seen as being part of the red-in-same-object standards and thus, elicit no vMMN.

  11. Improved Brain Tumor Detection Using Object Based Segmentation

    OpenAIRE

    Harneet Kaur; Sukhwinder Kaur

    2014-01-01

    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...

  12. Context-based classification of objects in cartographic data

    OpenAIRE

    Mulhare, Leo; O'Donoghue, Diarmuid; Winstanley, Adam C.

    2002-01-01

    The Ordnance Survey has traditionally recorded the large-scale topography of Britain as Cartesian co-ordinate-based point, line and text label features within the tile-based Land-Line® Database. Under their Digital National Framework™ (DNF™) project, this data has been re-engineered into a topologically structured format known as OS MasterMap™ [Ordnance Survey]. This required the modelling of the area features enclosed by the line data as polygon objects. This new polygon-enriched...

  13. Progressive coding of 3D objects based on overcomplete decompositions

    OpenAIRE

    Tosic, I.; Frossard, P; Vandergheynst, P.

    2005-01-01

    This paper presents a progressive coding scheme for 3D objects, based on an overcomplete decomposition of the 3D model on a sphere. Due to increased freedom in the bases construction, redundant expansions have shown interesting approximation properties in the decomposition of signals with multidimensional singularities organized along embedded submanifolds. We propose to map simple 3D models on 2D spheres and then to decompose the signal over a redundant dictionary of oriented and anisotropic...

  14. 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

  15. Matching interpolation of CT faulted images based on corresponding object

    International Nuclear Information System (INIS)

    For CT faulted images interpolation this paper presents a corresponding pint matching interpolation algorithm, which is based on object feature. Compared with the traditional interpolation algorithms, the new algorithm improves visual effect and its interpolation error. The computer experiments show that the algorithm can effectively improve the interpolation quality, especially more clear scene at the boundary. (authors)

  16. 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...

  17. Assessing Dimensionality by Maximizing "H" Coefficient-Based Objective Functions

    Science.gov (United States)

    van Abswoude, Alexandra A. H.; Vermunt, Jeroen K.; Hemker, Bas T.

    2007-01-01

    Mokken scale analysis can be used for scaling under nonparametric item response theory models. The results may, however, not reflect the underlying dimensionality of data. Various features of Mokken scale analysis--the H coefficient, Mokken scale conditions, and algorithms--may explain this result. In this article, three new H-based objective…

  18. Object-oriented vision for a behavior-based robot

    Science.gov (United States)

    Bischoff, Rainer; Graefe, Volker; Wershofen, Klaus P.

    1996-10-01

    As one realization out of the class of behavior-based robot architectures a specific concept of situation-oriented behavior-based navigation has been proposed. Its main characteristic is that the selection of the behaviors to be executed in each moment is based on a continuous recognition and evaluation of the dynamically changing situation in which the robot is finding itself. An important prerequisite for such as approach is a timely and comprehensive perception of the robot's dynamically changing environment. Object-oriented vision as proposed and successfully applied, e.g., in freeway traffic scenes is a particularly well suited sensing modality for robot control. Our work concentrated on modeling the physical objects which are relevant for indoor navigation, i.e. walls, intersections of corridors, and landmarks. In the interest of efficiency these models include only those necessary features for allowing the robot to reliably recognize different situations in real time. According to the concept of object- oriented vision recognizing such objects is largely reduced to a knowledge-based verification of objects or features that may be expected to be visible in the current situation. The following results have been achieved: 1) By using its vision system and a knowledge base in the form of an attributed topological map the robot could orient itself and navigate autonomously in a known environment. 2) In an unknown environment the robot was able to build, by means of supervised learning, an attributed topological map as a basis for subsequent autonomous navigation. 3) The experiments could be performed both under unmodified artificial light and under natural light shining through the glass walls of the building.

  19. 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.

  20. Robust Object Tracking Based on Adaptive Feature Selection

    Directory of Open Access Journals (Sweden)

    Chen Dong-Yue

    2013-01-01

    Full Text Available In order to solve the video-based object tracking problem in complex dynamic scenes, a robust tracking algorithm based on adaptive feature selection was proposed in this paper. To address the poor robustness of candidates in the feature pool in the online Adaboost algorithm and the drift problem caused by the template updating, a new feature pool was built based on both color features and histogram of pyramidal gradient features. An occlusion detector is added after the tracking in the current frame to improve the reliability of the realtime updated template. Experimental results showed that the proposed algorithm has better performance against object deformation, pose transformation, illumination variance and occlusion.

  1. Multi Objective AODV Based On a Realistic Mobility Model

    Directory of Open Access Journals (Sweden)

    Hamideh Babaei

    2010-05-01

    Full Text Available Routing is one of the most important challenges in ad hoc network. Numerous algorithms have been presented and one of the most important of them is AODV. This algorithm like many other algorithm calculate optimum path while pays no attention to environment situations, mobility pattern and mobile nodes status. However several presented algorithm have considered this situation and presented algorithm which named environment aware or mobility based. But in them have not considered realistic movement and environment such as obstacles, pathways and realistic movement pattern of the mobile nodes. This article present new algorithm based on AODV which find optimum path based on multi objectives. These objectives have been mined from a realistic mobility model, internal status of the mobile nodes and its status in routing. In this method the objectives are optional and each node can consider a couple of them in routing. Therefore this method supports GPS less mobile nodes. Evaluation of the new method shows that considering multi objectives influence routing metrics and can improve some of them.

  2. Symmetry axis based object recognition under translation, rotation and scaling.

    Science.gov (United States)

    Hyder, Mashud; Islam, Md Monirul; Akhand, M A H; Murase, Kazuyuki

    2009-02-01

    This paper presents a new approach, known as symmetry axis based feature extraction and recognition (SAFER), for recognizing objects under translation, rotation and scaling. Unlike most previous invariant object recognition (IOR) systems, SAFER puts emphasis on both simplicity and accuracy of the recognition system. To achieve simplicity, it uses simple formulae for extracting invariant features from an object. The scheme used in feature extraction is based on the axis of symmetry and angles of concentric circles drawn around the object. SAFER divides the extracted features into a number of groups based on their similarity. To improve the recognition performance, SAFER uses a number of neural networks (NNs) instead of single NN are used for training and recognition of extracted features. The new approach, SAFER, has been tested on two of real world problems i.e., English characters with two different fonts and images of different shapes. The experimental results show that SAFER can produce good recognition performance in comparison with other algorithms. PMID:19263501

  3. 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.

  4. 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.

  5. 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.

  6. Generative Learning Objects Instantiated with Random Numbers Based Expressions

    Directory of Open Access Journals (Sweden)

    Ciprian Bogdan Chirila

    2015-12-01

    Full Text Available The development of interactive e-learning content requires special skills like programming techniques, web integration, graphic design etc. Generally, online educators do not possess such skills and their e-learning products tend to be static like presentation slides and textbooks. In this paper we propose a new interactive model of generative learning objects as a compromise betweenstatic, dull materials and dynamic, complex software e-learning materials developed by specialized teams. We find that random numbers based automatic initialization learning objects increases content diversity, interactivity thus enabling learners’ engagement. The resulted learning object model is at a limited level of complexity related to special e-learning software, intuitive and capable of increasing learners’ interactivity, engagement and motivation through dynamic content. The approach was applied successfully on several computer programing disciplines.

  7. Teaching object concepts for XML-based representations.

    Energy Technology Data Exchange (ETDEWEB)

    Kelsey, R. L. (Robert L.)

    2002-01-01

    Students learned about object-oriented design concepts and knowledge representation through the use of a set of toy blocks. The blocks represented a limited and focused domain of knowledge and one that was physical and tangible. The blocks helped the students to better visualize, communicate, and understand the domain of knowledge as well as how to perform object decomposition. The blocks were further abstracted to an engineering design kit for water park design. This helped the students to work on techniques for abstraction and conceptualization. It also led the project from tangible exercises into software and programming exercises. Students employed XML to create object-based knowledge representations and Java to use the represented knowledge. The students developed and implemented software allowing a lay user to design and create their own water slide and then to take a simulated ride on their slide.

  8. 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.

  9. 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.

  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. Data Warehouse Requirements Analysis Framework: Business-Object Based Approach

    Directory of Open Access Journals (Sweden)

    Anirban Sarkar

    2012-01-01

    Full Text Available Detailed requirements analysis plays a key role towards the design of successful Data Warehouse (DW system. The requirements analysis specifications are used as the prime input for the construction of conceptual level multidimensional data model. This paper has proposed a Business Object based requirements analysis framework for DW system which is supported with abstraction mechanism and reuse capability. It also facilitate the stepwise mapping of requirements descriptions into high level design components of graph semantic based conceptual level object oriented multidimensional data model. The proposed framework starts with the identification of the analytical requirements using business process driven approach and finally refine the requirements in further detail to map into the conceptual level DW design model using either Demand-driven of Mixed-driven approach for DW requirements analysi

  12. Invariant object recognition based on the generalized discrete radon transform

    Science.gov (United States)

    Easley, Glenn R.; Colonna, Flavia

    2004-04-01

    We introduce a method for classifying objects based on special cases of the generalized discrete Radon transform. We adjust the transform and the corresponding ridgelet transform by means of circular shifting and a singular value decomposition (SVD) to obtain a translation, rotation and scaling invariant set of feature vectors. We then use a back-propagation neural network to classify the input feature vectors. We conclude with experimental results and compare these with other invariant recognition methods.

  13. 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...

  14. Efficient Model-Based 3D Tracking of Deformable Objects

    OpenAIRE

    Muñoz, Enrique; Buenaposada Biencinto, José Miguel; Baumela Molina, Luis

    2005-01-01

    Efficient incremental image alignment is a topic of renewed interest in the computer vision community because of its applications in model fitting and model-based object tracking. Successful compositional procedures for aligning 2D and 3D models under weak-perspective imaging conditions have already been proposed. Here we present a mixed compositional and additive algorithm which is applicable to the full projective camera case.

  15. Objective Stereo Image Quality Assessment Model based on Matrix Decomposition

    OpenAIRE

    Gangyi Jiang; Xiangying Mao; Mei Yu; Feng Shao; Zongju Peng; Jiangying Zhu

    2014-01-01

    Stereo image quality assessment (SIQA) is a key issue of stereo image processing. Image pixels have strong correlation and highly structured features, according to that an image quality mainly depends on the structure information distortion of the image, an objective stereo image quality assessment (OSIQA) model based on matrix decomposition is proposed. Firstly, the concavity and convexity maps of image are extracted through Hessian matrix decomposition, which reflects complexity of image, a...

  16. 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.

  17. DMD-based multi-object spectrograph on Galileo telescope

    Science.gov (United States)

    Zamkotsian, Frederic; Spano, Paolo; Lanzoni, Patrick; Bon, William; Riva, Marco; Nicastro, Luciano; Molinari, Emilio; Di Marcantonio, Paolo; Zerbi, Filippo; Valenziano, Luca

    2013-03-01

    Next-generation infrared astronomical instrumentation for ground-based and space telescopes could be based on MOEMS programmable slit masks for multi-object spectroscopy (MOS). This astronomical technique is used extensively to investigate the formation and evolution of galaxies. We propose to develop a 2048x1080 DMD-based MOS instrument to be mounted on the Galileo telescope and called BATMAN. A two-arm instrument has been designed for providing in parallel imaging and spectroscopic capabilities. The two arms with F/4 on the DMD are mounted on a common bench, and an upper bench supports the detectors thanks to two independent hexapods. Very good optical quality on the DMD and the detectors will be reached. ROBIN, a BATMAN demonstrator, has been designed, realized and integrated. It permits to determine the instrument integration procedure, including optics and mechanics integration, alignment procedure and optical quality. First images have been obtained and measured. A DMD pattern manager has been developed in order to generate any slit mask according to the list of objects to be observed; spectra have been generated and measured. Observation strategies will be studied and demonstrated for the scientific optimization strategy over the whole FOV. BATMAN on the sky is of prime importance for characterizing the actual performance of this new family of MOS instruments, as well as investigating the operational procedures on astronomical objects. This instrument will be placed on the Telescopio Nazionale Galileo at the beginning of next year, in 2014.

  18. New developments in HgCdTe APDs and LADAR receivers

    Science.gov (United States)

    McKeag, William; Veeder, Tricia; Wang, Jinxue; Jack, Michael; Roberts, Tom; Robinson, Tom; Neisz, James; Andressen, Cliff; Rinker, Robert; Cook, T. Dean; Amzajerdian, Farzin

    2011-06-01

    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 MMSS) program and (2) staring 256 × 256 configuration for the Autonomous Landing and Hazard Avoidance Technology (ALHAT) lunar landing mission.

  19. WOMBAT: sWift Objects for Mhd BAsed on Tvd

    Science.gov (United States)

    Mendygral, Peter; Porter, David; Edmon, Paul; Delgado, Jennifer

    2012-04-01

    WOMBAT (sWift Objects for Mhd BAsed on Tvd) is an astrophysical fluid code that is an implementation of a non-relativistic MHD TVD scheme; an extension for relativistic MHD has been added. The code operates on 1, 2, and 3D Eulerian meshes (cartesian and cylindrical coordinates) with magnetic field divergence restriction controlled by a constrained transport (CT) scheme. The user can tune code performance to a given processor based on chip cache sizes. Proper settings yield significant speed-ups due to efficient cache reuse.

  20. 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.

  1. Multi-objective community detection based on memetic algorithm.

    Science.gov (United States)

    Wu, Peng; Pan, Li

    2015-01-01

    Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646

  2. Multispectral photoacoustic microscopy based on an optical–acoustic objective

    Directory of Open Access Journals (Sweden)

    Rui Cao

    2015-06-01

    Full Text Available We have developed reflection-mode multispectral photoacoustic microscopy (PAM based on a novel optical–acoustic objective that integrates a customized ultrasonic transducer and a commercial reflective microscope objective into one solid piece. This technical innovation provides zero chromatic aberration and convenient confocal alignment of the optical excitation and acoustic detection. With a wavelength-tunable optical-parametric-oscillator laser, we have demonstrated multispectral PAM over an ultrabroad spectral range of 270–1300 nm. A near-constant lateral resolution of ?2.8 ?m is achieved experimentally. Capitalizing on the consistent performance over the ultraviolet, visible, and near-infrared range, multispectral PAM enables label-free concurrent imaging of cell nucleus (DNA/RNA contrast at 270 nm, blood vessel (hemoglobin contrast at 532 nm, and sebaceous gland (lipid contrast at 1260 nm at the same spatial scale in a living mouse ear.

  3. 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.

  4. 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.

  5. STARSAT: a joint NASA/AF project for laser calibration of small objects in space

    Science.gov (United States)

    Campbell, Jonathan W.

    2002-09-01

    The Air Force Research Laboratory/Directed Energy Directorate (AFRL/DE) and NASA/Marshall Space Flight Center (MSFC) are looking at a series of joint laser space calibration experiments using the 12J 15Hz CO2 HIgh Performance CO2 Ladar Surveillance Sensor (HI-CLASS) system on the 3.67 meter aperture Advanced Electro-Optics System (AEOS). The objectives of these experiments are to provide accurate range and signature measurements of calibration spheres, demonstrate high resolution tracking capability of small objects, and precision dray determination for LEO. Ancillary benefits include calibrating radar and optical sites, completing satellite conjunction analyses, supporting orbital perturbations analyses, and comparing radar and optical signatures. In the first experiment, a Global Positioning System (GPS)/laser beacon instrumented micro-satellite about 25 cm in diameter will be deployed from a Space Shuttle Hitchhiker canister or other suitable launch means. Orbiting in low earth orbit, the micro-satellite will pass over AEOS on the average of two times per 24-hour period. An onboard orbit propagator will activate the GPS unit and a visible laser beacon at the appropriate times. The HI-CLASS/AEOS system will detect the micro-satellite as it rises above the horizon, using GPS-generated acquisition vectors. The visible laser beacon will be used to fine-tune the tracking parameters for continuous ladar data measurements throughout the pass. This operational approach should maximize visibility to the ground-based laser while allowing battery life to be conserved, thus extending the lifetime of the satellite. GPS data will be transmitted to the ground providing independent location information for the micro-satellite down to sub-meter accuracies.

  6. Adaptive color correction based on object color classification

    Science.gov (United States)

    Kotera, Hiroaki; Morimoto, Tetsuro; Yasue, Nobuyuki; Saito, Ryoichi

    1998-09-01

    An adaptive color management strategy depending on the image contents is proposed. Pictorial color image is classified into different object areas with clustered color distribution. Euclidian or Mahalanobis color distance measures, and maximum likelihood method based on Bayesian decision rule, are introduced to the classification. After the classification process, each clustered pixels are projected onto principal component space by Hotelling transform and the color corrections are performed for the principal components to be matched each other in between the individual clustered color areas of original and printed images.

  7. 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.

  8. 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.

  9. State-based modeling and object extraction from echocardiogram video.

    Science.gov (United States)

    Roy, Aditi; Sural, Shamik; Mukherjee, Jayanta; Majumdar, Arun K

    2008-05-01

    In this paper, we propose a hierarchical state-based model for representing an echocardiogram video. It captures the semantics of video segments from dynamic characteristics of objects present in each segment. Our objective is to provide an effective method for segmenting an echo video into view, state, and substate levels. This is motivated by the need for building efficient indexing tools to support better content management. The modeling is done using four different views, namely, short axis, long axis, apical four chamber, and apical two chamber. For view classification, an artificial neural network is trained with the histogram of a region of interest of each video frame. Object states are detected with the help of synthetic M-mode images. In contrast to traditional single M-mode, we present a novel approach named sweep M-mode for state detection. We also introduce radial M-mode for substate identification from color flow Doppler 2-D imaging. The video model described here represents the semantics of video segments using first-order predicates. Suitable operators have been defined for querying the segments. We have carried out experiments on 20 echo videos and compared the results with manual annotation done by two experts. View classification accuracy is 97.19%. Misclassification error of the state detection stage is less than 13%, which is within acceptable range since only frames at the state boundaries are found to be misclassified. PMID:18693504

  10. 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.

  11. Object-based landslide detection in different geographic regions

    Science.gov (United States)

    Friedl, Barbara; Hölbling, Daniel; Eisank, Clemens; Blaschke, Thomas

    2015-04-01

    Landslides occur in almost all mountainous regions of the world and rank among the most severe natural hazards. In the last decade - according to the world disaster report 2014 published by the International Federation of Red Cross and Red Crescent Societies (IRFC) - more than 9.000 people were killed by mass movements, more than 3.2 million people were affected and the total amount of disaster estimated damage accounts to more than 1.700 million US dollars. The application of remote sensing data for mapping landslides can contribute to post-disaster reconstruction or hazard mitigation, either by providing rapid information about the spatial distribution and location of landslides in the aftermath of triggering events or by creating and updating landslide inventories. This is especially valid for remote and inaccessible areas, where information on landslides is often lacking. However, reliable methods are needed for extracting timely and relevant information about landslides from remote sensing data. In recent years, novel methods such as object-based image analysis (OBIA) have been successfully employed for semi-automated landslide mapping. Several studies revealed that OBIA frequently outperforms pixel-based approaches, as a range of image object properties (spectral, spatial, morphometric, contextual) can be exploited during the analysis. However, object-based methods are often tailored to specific study areas, and thus, the transferability to regions with different geological settings, is often limited. The present case study evaluates the transferability and applicability of an OBIA approach for landslide detection in two distinct regions, i.e. the island of Taiwan and Austria. In Taiwan, sub-areas in the Baichi catchment in the North and in the Huaguoshan catchment in the southern-central part of the island are selected; in Austria, landslide-affected sites in the Upper Salzach catchment in the federal state of Salzburg are investigated. For both regions, SPOT-5 images are combined with digital elevation models (DEM) for developing a consistent semi-automated landslide detection approach using eCognition (Trimble) software. Suitable image objects are generated by means of multiresolution segmentation. Expert knowledge, i.e. reported facts on features (e.g. mean object slope, mean NDVI) and thresholds that are commonly chosen by professionals for digital landslide mapping, is considered during classification. The applicability of a range of features is tested and the most promising parameters, i.e. features that produce appropriate results for both regions, are selected for landslide detection. However, minor adaptations of particular thresholds are necessary due to the distinct environmental conditions of the test sites. In order to reduce the number of required adjustments to a minimum, relational features and spectral indices are primarily used for classification. The obtained results are finally compared to manually digitized reference polygons and existing landslide inventories in order to quantify the applicability of the developed object-based landslide detection approach in different geographic regions.

  12. Objective Mixed and Manually Controlled Data Base OMG

    Science.gov (United States)

    Kratzsch, T.; Rohn, M.

    2009-09-01

    Many customers of Deutscher Wetterdienst get forecast products (different deterministic meteorological parameters) as so-called Point-Time-Prognoses (PTPs). There's the need for data of high resolution in space (several kilometers, cities) and time (hourly up to forecast-day 7, updated each hour). Those interpretations of the numerical models have been designed by different methods, called DMO, Model Output Statistics (MOS), Kalman filtering. Because of different model results and different methods there are between five and ten different PTPs for the same location. While a forecaster, based on his experience, can choose between that different interpretations, an automatic customers supply can't do so. Because updates of those interpretations are only available for each new model run, there's also the need for more actual forecast data, using nowcasting methods as well as controlling and modifying mechanisms for the forecasters. A process "Objective Optimization” has been implemented which automatically combines the available PTP data, nowcasting products and observations at all required locations. A frequent update of this optimization process every 30 minutes ensures that the OOG is based on the latest available model, nowcasting, and observational information. The resulting so-called "Objectively Optimized Guidance” (OOG) passes an interactive quality control step to produce a "Man Modified output” (MMO). The corresponding tool "MMO-Editor” provides point editing functions together with automatic quality checks and corrections. The combination of automatic data merging (OOG) and quality check with optional manual corrections (MMO) aims at providing a single quality ensured data base for subsequent automatic customer supply. The presentation describes the methods, the "status quo” and the plans of implementation a data base called OMG.

  13. A mobile agent-based moving objects indexing algorithm in location based service

    Science.gov (United States)

    Fang, Zhixiang; Li, Qingquan; Xu, Hong

    2006-10-01

    This paper will extends the advantages of location based service, specifically using their ability to management and indexing the positions of moving object, Moreover with this objective in mind, a mobile agent-based moving objects indexing algorithm is proposed in this paper to efficiently process indexing request and acclimatize itself to limitation of location based service environment. The prominent feature of this structure is viewing moving object's behavior as the mobile agent's span, the unique mapping between the geographical position of moving objects and span point of mobile agent is built to maintain the close relationship of them, and is significant clue for mobile agent-based moving objects indexing to tracking moving objects.

  14. 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.

  15. 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...

  16. Multi-Object Optimization Based RV Selection Algorithm for VCN

    Directory of Open Access Journals (Sweden)

    Rong Chai

    2014-04-01

    Full Text Available Vehicular communication network (VCN has recently received considerable attention both from academia and industry. In VCN, vehicles are expected to be capable of communicating with other vehicles as well as stationary infrastructures, i.e., the access points (APs of wireless access networks. In the case that the direct connection between a source vehicle (SV and APs is inaccessible, relay vehicles (RVs can be applied for supporting multi-hop connection between SVs and APs. In this paper, a multi-object based RV selection algorithm for VCN is proposed, which jointly considers the characteristics of physical channel, link status between SVs and RVs, the bandwidth and delay characteristics of RVs and user service requirements. The utility functions of both SVs and RVs are modeled and a multi-object optimization problem is formulated. Applying ideal point method, the problem can be solved and the optimal SV-RV pairs can be obtained. Simulation results demonstrate that compared to previous algorithms, the proposed algorithm offers better performance in terms of user throughput, successful transmission rate and average transmission delay

  17. The roles of structure-based and function-based action knowledge in object recognition.

    Science.gov (United States)

    Liu, Ye; Ni, Long; Fu, Xiaolan

    2015-09-01

    In recent years, a growing body of research has shown that action knowledge is an important part in the representation of object concepts and plays a role in the recognition of manipulable objects (Lin, Guo, Han, & Bi, 2011; Matheson, White, & McMullen, 2014). Action knowledge of manipulable objects regards how an object could be grasped, moved, and used. Further evidence from neuropsychological and brain imaging research has suggested that there are two kinds of action knowledge: function-based and structure-based action knowledge (Bub & Masson, 2013). Structure-based action refers to grasping an object and moving it, and function-based action refers to functionally using an object. Both types of action knowledge could be activated automatically during object processing, and they are independent of each other functionally and neuroanatomically (Bub & Masson, 2013; Jax & Buxbaum, 2010). However, their respective roles in object recognition is still unclear. In the present two experiments, static action pictures (Experiment 1) and dynamic action videos (Experiment 2) of structural versus functional hand gestures were used as primes to examine their respective roles in the recognition of manipulable target objects. Experiment 1 found that structural and functional hand gestures could facilitate the naming of manipulable objects to the same extent. However, Experiment 2 found that the prime effect of functional hand gestures on the naming of manipulable objects was much stronger than the effect of structural hand gestures. The findings indicated that both function-based action and structure-based action knowledge did play important roles in object recognition, but the facilitation effect of dynamic function-based action was more significant. The present research provided further evidence for the role of the dorsal pathway in object recognition that previously considered subserved only by the ventral pathway, and the distinction between the two action systems: "Grasp" and "Use" systems. Meeting abstract presented at VSS 2015. PMID:26325923

  18. 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...

  19. Poka Yoke system based on image analysis and object recognition

    Science.gov (United States)

    Belu, N.; Ionescu, L. M.; Misztal, A.; Mazăre, A.

    2015-11-01

    Poka Yoke is a method of quality management which is related to prevent faults from arising during production processes. It deals with “fail-sating” or “mistake-proofing”. The Poka-yoke concept was generated and developed by Shigeo Shingo for the Toyota Production System. Poka Yoke is used in many fields, especially in monitoring production processes. In many cases, identifying faults in a production process involves a higher cost than necessary cost of disposal. Usually, poke yoke solutions are based on multiple sensors that identify some nonconformities. This means the presence of different equipment (mechanical, electronic) on production line. As a consequence, coupled with the fact that the method itself is an invasive, affecting the production process, would increase its price diagnostics. The bulky machines are the means by which a Poka Yoke system can be implemented become more sophisticated. In this paper we propose a solution for the Poka Yoke system based on image analysis and identification of faults. The solution consists of a module for image acquisition, mid-level processing and an object recognition module using associative memory (Hopfield network type). All are integrated into an embedded system with AD (Analog to Digital) converter and Zync 7000 (22 nm technology).

  20. Orbital correlation of space objects based on orbital elements

    Science.gov (United States)

    Wang, Xiu-Hong; Li, Jun-Feng; Du, Xin-Peng; Zhang, Xuan

    2016-03-01

    Orbital correlation of space objects is one of the most important elements in space object identification. Using the orbital elements, we provide correlation criteria to determine if objects are coplanar, co-orbital or the same. We analyze the prediction error of the correlation parameters for different orbital types and propose an orbital correlation method for space objects. The method is validated using two line elements and multisatellite launching data. The experimental results show that the proposed method is effective, especially for space objects in near-circular orbits.

  1. Object-based classification of semi-arid wetlands

    Science.gov (United States)

    Halabisky, Meghan; Moskal, L. Monika; Hall, Sonia A.

    2011-01-01

    Wetlands are valuable ecosystems that benefit society. However, throughout history wetlands have been converted to other land uses. For this reason, timely wetland maps are necessary for developing strategies to protect wetland habitat. The goal of this research was to develop a time-efficient, automated, low-cost method to map wetlands in a semi-arid landscape that could be scaled up for use at a county or state level, and could lay the groundwork for expanding to forested areas. Therefore, it was critical that the research project contain two components: accurate automated feature extraction and the use of low-cost imagery. For that reason, we tested the effectiveness of geographic object-based image analysis (GEOBIA) to delineate and classify wetlands using freely available true color aerial photographs provided through the National Agriculture Inventory Program. The GEOBIA method produced an overall accuracy of 89% (khat = 0.81), despite the absence of infrared spectral data. GEOBIA provides the automation that can save significant resources when scaled up while still providing sufficient spatial resolution and accuracy to be useful to state and local resource managers and policymakers.

  2. 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

  3. Fragment-Based Learning of Visual Object Categories

    OpenAIRE

    Hegdé, Jay; Bart, Evgeniy; Kersten, Daniel

    2008-01-01

    When we perceive a visual object, we implicitly or explicitly associate it with a category we know [1-3]. It is known that the visual system can use local, informative image fragments of a given object, rather than the whole object, to classify it into a familiar category [4-8]. How we acquire informative fragments has remained unclear. Here, we show that human observers acquire informative fragments during the initial learning of categories. We created new, but naturalistic, classes of visua...

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

    DEFF Research Database (Denmark)

    Schultz, Ulrik Pagh

    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....

  5. Gait-based carried object detection using persistent homology

    OpenAIRE

    Lamar León, Javier; Alonso Baryolo, Raúl; García Reyes, Edel; González Díaz, Rocío

    2014-01-01

    There are surveillance scenarios where it is important to emit an alarm when a person carrying an object is detected. In order to detect when a person is carrying an object, we build models of naturally-walking and object-carrying persons using topological features. First, a stack of human silhouettes, extracted by background subtraction and thresholding, are glued through their gravity centers, forming a 3D digital image I. Second, different filters (i.e. orderings of the cells) are applied ...

  6. Resampling technique in the orthogonal direction for down-looking Synthetic Aperture Imaging Ladar

    Science.gov (United States)

    Li, Guangyuan; Sun, Jianfeng; Lu, Zhiyong; Zhang, Ning; Cai, Guangyu; Sun, Zhiwei; Liu, Liren

    2015-09-01

    The implementation of down-looking Synthetic Aperture Imaging Ladar(SAIL) uses quadratic phase history reconstruction in the travel direction and linear phase modulation reconstruction in the orthogonal direction. And the linear phase modulation in the orthogonal direction is generated by the shift of two cylindrical lenses in the two polarization-orthogonal beams. Therefore, the fast-moving of two cylindrical lenses is necessary for airborne down-looking SAIL to match the aircraft flight speed and to realize the compression of the orthogonal direction, but the quick start and the quick stop of the cylindrical lenses must greatly damage the motor and make the motion trail non-uniform. To reduce the damage and get relatively well trajectory, we make the motor move like a sinusoidal curve to make it more realistic movement, and through a resampling interpolation imaging algorithm, we can transform the nonlinear phase to linear phase, and get good reconstruction results of point target and area target in laboratory. The influences on imaging quality in different sampling positions when the motor make a sinusoidal motion and the necessity of the algorithm are analyzed. At last, we perform a comparison of the results of two cases in resolution.

  7. Robust B+ -Tree-Based Indexing of Moving Objects

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Tiesyte, Dalia; Tradisauskas, Nerius

    2006-01-01

    With the emergence of an infrastructure that enables the geo-positioning of on-line, mobile users, the management of so-called moving objects has emerged as an active area of research. Among the indexing techniques for efficiently answering predictive queries on moving-object positions, the recen...

  8. Interrater Objectivity for Field-Based Fundamental Motor Skill Assessment

    Science.gov (United States)

    Barnett, Lisa; van Beurden, Eric; Morgan, Philip J.; Lincoln, Doug; Zask, Avigdor; Beard, John

    2009-01-01

    An important aspect in studies concerning fundamental motor skills (FMS) proficiency is interrater objectivity (or interrater reliability), defined as the consistency or agreement in scores obtained from two or more raters. In a training setting, interrater objectivity is commonly determined as the relative number of times raters agree with an…

  9. Objective Based Flexible Business Process Management Using the Map Model

    Directory of Open Access Journals (Sweden)

    A. Bentellis

    2009-01-01

    Full Text Available In the proposal, a flexible business process management axed on the objective concept and for the process lifecycle is presented. The main feature of this approach is that the map model is used as the key element to drive the construction and execution of flexible business processes. An analysis phase starts with a model which fully considers the objective and sub-objectives of the business process, when defining it. A design phase uses the map model for specifying and representing the possible plans that are capable of achieving the predefined objective and this will be done in a modular manner. Examples are presented from a case study in the travel agency Numédia. The architecture of the execution engine for, so defined, business process map modeling is presented for its interpretation and its execution. Finally, an evaluation of the degree of flexibility brought by proposed management is given.

  10. Vision-based grasp tracking for planar objects

    OpenAIRE

    Recatalá Ballester, Gabriel; Carloni, Raffaella; Melchiorri, Claudio; Sanz Valero, Pedro José; Cervera Mateu, Enric; Pobil, Àngel Pasqual del

    2008-01-01

    In robotics, the manipulation of a priori unknown objects involves several steps and problems that must be carefully considered and solved by proper planning and control algorithms. For example, once suitable contact points have been computed, the control system should be able to track them in the approach phase, i.e., while the relative position/ orientation of the object and the gripper of the robotic system change due to the approaching movement of the robot toward the ob...

  11. Segmentation-based multi-class semantic object detection

    OpenAIRE

    Vieux, Remi; Benois-Pineau, Jenny; Domenger, Jean-Philippe; Braquelaire, Achille

    2011-01-01

    In this paper we study the problem of the detection of semantic objects from known categories in images. Unlike existing techniques which operate at the pixel or at a patch level for recognition, we propose to rely on the categorization of image segments. Recent work has highlighted that image segments provide a sound support for visual object class recognition. In this work, we use image segments as primitives to extract robust features and train detection models for a predefined set of cate...

  12. Robotic grasping of unknown objects: A knowledge-based approach

    Energy Technology Data Exchange (ETDEWEB)

    Stansfield, S.A. [Sandia National Labs., Albuquerque, NM (United States)

    1990-11-01

    In this paper, the authors demonstrate a general-purpose robotic grasping system for use in unstructured environments. Using computer vision and a compact set of heuristics, the system automatically generates the robot arm and hand motions required for grasping an unmodeled object. The utility of such a system is most evident in environments where the robot will have to grasp and manipulate a variety of unknown objects, but where many of the manipulation tasks may be relatively simple. Examples of such domains are planetary exploration and astronaut assistance, undersea salvage and rescue, and nuclear waste site clean-up. This work implements a two-stage model of grasping: stage one is an orientation of the hand and wrist and a ballistic reach toward the object; stage two is hand preshaping and adjustment. Visual features are first extracted from the unmodeled object. These features and their relations are used by an expert system to generate a set of valid reach/grasps for the object. These grasps are then used in driving the robot hand and arm to bring the fingers into contact with the object in the desired configuration. Experimental results are presented to illustrate the functioning of the system.

  13. Multiple Object Based RFID System Using Security Level

    Science.gov (United States)

    Kim, Jiyeon; Jung, Jongjin; Ryu, Ukjae; Ko, Hoon; Joe, Susan; Lee, Yongjun; Kim, Boyeon; Chang, Yunseok; Lee, Kyoonha

    2007-12-01

    RFID systems are increasingly applied for operational convenience in wide range of industries and individual life. However, it is uneasy for a person to control many tags because common RFID systems have the restriction that a tag used to identify just a single object. In addition, RFID systems can make some serious problems in violation of privacy and security because of their radio frequency communication. In this paper, we propose a multiple object RFID tag which can keep multiple object identifiers for different applications in a same tag. The proposed tag allows simultaneous access for their pair applications. We also propose an authentication protocol for multiple object tag to prevent serious problems of security and privacy in RFID applications. Especially, we focus on efficiency of the authentication protocol by considering security levels of applications. In the proposed protocol, the applications go through different authentication procedures according to security level of the object identifier stored in the tag. We implemented the proposed RFID scheme and made experimental results about efficiency and stability for the scheme.

  14. 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.

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

    DEFF Research Database (Denmark)

    Wang, Qi; Zhang, Chunyu; Ding, Yi; Østergaard, Jacob

    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...

  16. Object Tracking Based on Camshift with Multi-feature Fusion

    Directory of Open Access Journals (Sweden)

    Zhiyu Zhou

    2014-01-01

    Full Text Available It is very hard for traditional Camshift to survive of drastic interferences and occlusions of similar objects. This paper puts forward an innovative tracking method using Camshift with multi-feature fusion. Firstly, SIFT features and edge features of the Camshift in RGB space are counted to reduce the probability of disruption by occlusion and clutter. Then, the texture features are collected to resolve the problems of analogue interference, the texture similarity between current frame and previous frames are calculated to determine the object area. The paper also describes the GM(1,1 prediction model, which could solve the occlusion problems in a novel way. Finally, through the motion trajectory, it can anticipate the exact position of the object. The results of several tracking tasks prove that our method has solved problems of occlusions, interferences and shadows. And it performs well in both tracking robustness and computational efficiency.

  17. Aircraft Simulator Designing based on Object Oriented Methodologies

    Directory of Open Access Journals (Sweden)

    Rahul Kosarwal

    2012-03-01

    Full Text Available Object plays a very important role in comparing softwareentities. But the role of object when it comes to simulationfield is still undefined. Several standards have been createdwith the purpose to provide a design solution for the projectof Simulators. The design solution reported in this paperaggregates the principles of both software and simulatorarchitectures. The objective is to invert the top-downstrategy of model-driven development with the SimulationModel Portability (SMP standard into a bottom-updevelopment process of a SMP framework. The paper alsoprovides solution for two development lines of two differentframeworks: the first is the SMP framework that changesaccording to the design models, and the second is aframework designed to support the development ofreusable behavior implementations

  18. 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…

  19. CONTENT BASED INDEXING OF MUSIC OBJECTS USING APPROXIMATE SEQUENTIAL PATTERNS

    Directory of Open Access Journals (Sweden)

    D.Vikram

    2015-03-01

    Full Text Available The music objects are classified into Monophonic and Polyphonic. In Monophonic there is only one track which is the main melody that leads the song. In Polyphonic objects, there are several tracks that accompany the main melody. Each track is a sequence of notes played simultaneously with other tracks. But, the main melody captures the essence of the music and plays vital role in MIR. The MIR involves representation of main melody as a sequence of notes played, extraction of repeating patterns from it and matching of query sequence with frequent repeating sequential patterns constituting the music object. Repeating patterns are subsequences of notes played time and again in a main melody with possible variations in the notes to a tolerable extent. Similarly, the query sequence meant for retrieving a music object may not contain the repeating patterns of the main melody in its exact form. Hence, extraction of approximate patterns is essential for a MIR system. This paper proposes a novel method of finding approximate repeating patterns for the purpose of MIR. The effectiveness of methodology is tested and found satisfactory on real world data namely ‘Raga Surabhi’ an Indian Carnatic Music portal.

  20. 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…

  1. 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…

  2. 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.

  3. Generative Learning Objects Instantiated with Random Numbers Based Expressions

    OpenAIRE

    Ciprian Bogdan Chirila; Horia Ciocârlie; Lăcrămioara Stoicu-Tivadar

    2015-01-01

    The development of interactive e-learning content requires special skills like programming techniques, web integration, graphic design etc. Generally, online educators do not possess such skills and their e-learning products tend to be static like presentation slides and textbooks. In this paper we propose a new interactive model of generative learning objects as a compromise betweenstatic, dull materials and dynamic, complex software e-learning materials developed by specialized teams. We fi...

  4. Software-Based Extraction of Objective Parameters from Music Performances

    OpenAIRE

    Lerch, Alexander

    2008-01-01

    Different music performances of the same score may significantly differ from each other. It is obvious that not only the composer’s work, the score, defines the listener’s music experience, but that the music performance itself is an integral part of this experience. Music performers use the information contained in the score, but interpret, transform or add to this information. Four parameter classes can be used to describe a performance objectively: tempo and timing, loudness, timbre and pi...

  5. Effective RFID-based Object Tracking for Manufacturing

    OpenAIRE

    Brusey, James; McFarlane, Duncan C

    2009-01-01

    Abstract Abstract Automated Identification and in particular, Radio Frequency Identification (RFID) promises to assist with the automation of mass customised production processes by simplifying the retrieval, tracking and usage of highly specialised components. RFID has long been used to gather a history or trace of object movements, but its use as an integral part of the automated control process is yet to be fully exploited. Such (automated) use places stringent demands on the qu...

  6. 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.

  7. 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.

  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. 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...

  10. 0.18 ?m CMOS fully differential CTIA for a 32x16 ROIC for 3D ladar imaging systems

    Science.gov (United States)

    Helou, Jirar N.; Garcia, Jorge; Sarmiento, Mayra; Kiamilev, Fouad; Lawler, William

    2006-08-01

    We describe a 2-D fully differential Readout Integrated Circuit (ROIC) designed to convert the photocurrents from an array of differential metal-semiconductor-metal (MSM) detectors into voltage signals suitable for digitization and post processing. The 2-D MSM array and CMOS ROIC are designed to function as a front-end module for an amplitude modulated/continuous time AM/CW 3-D Ladar imager under development at the Army Research Laboratory. One important aspect of our ROIC design is scalability. Within reasonable power consumption and photodetector size constraints, the ROIC architecture presented here scales up linearly without compromising complexity. The other key feature of our ROIC design is the mitigation of local oscillator coupling. In our ladar imaging application, the signal demodulation process that takes place in the MSM detectors introduces parasitic radio frequency (rf) currents that can be 4 to 5 orders of magnitude greater than the signal of interest. We present a fully-differential photodetector architecture and a circuit level solution to reduce the parasitic effect. As a proof of principle we have fabricated a 0.18 ?m CMOS 32x16 fully differential ROIC with an array of 32 correlated double sampling (cds) capacitive transimpedance amplifiers (CTIAs), and a custom printed circuit board equipped to verify the test chip functionality. In this paper we discuss the fully differential IC design architecture and implementation and present the future testing strategy.

  11. Finger Readjustment Algorithm for Object Manipulation Based on Tactile Information

    Directory of Open Access Journals (Sweden)

    Juan Antonio Corrales Ramo?n

    2013-01-01

    Full Text Available This paper presents a novel algorithm which registers pressure information from tactile sensors installed over the fingers of a robotic hand in order to perform manipulation tasks with objects. This algorithm receives as an input the joint trajectories of the fingers which have to be executed and adapts it to the real contact pressure of each finger in order to guarantee that undesired slippage or contact?breaking is avoided during the execution of the manipulation task. This algorithm has been applied not only for the manipulation of normal rigid bodies but also for bodies whose centre of mass can be changed during the execution of the manipulation task.

  12. Object based manipulation with 3D scenes in mobile environment

    OpenAIRE

    Slavik, Pavel; Cmolik, Ladislav; Mikovec, Zdenek

    2005-01-01

    The increasing power and display resolution of mobile devices allow the user nowadays to work with 3D information in mobile environment. The use of this new technology brings some new problems that need an urgent solution. One of them has its roots in the fact that common users are not trained to work in 3D graphical environment in general. The main obstacle for a common user is the fact that 3D environment offers too much freedom for object manipulation in comparison with situation in 2D env...

  13. Sustainable System Management with Fisher Information based Objectives

    Science.gov (United States)

    Sustainable ecosystem management that integrates ecological, economic and social perspectives is a complex task where simultaneous persistence of human and natural components of the system must be ensured. Given the complexity of this task, systems theory approaches based on soun...

  14. An object oriented computer-based patient record reference model.

    OpenAIRE

    Doré, L.; Lavril, M.; Jean, F. C.; Degoulet, P

    1995-01-01

    In the context of health care information systems based on client/server architecture, we address the problem of a common Computer-based Patient Record (CPR). We define it as a collection of faithful observations about patients care, with respect to the free expression of physicians. This CPR model supports several views of the medical data, in order to provide applications with a comprehensive and standardized access to distributed patient data. Finally, we validated our CPR approach as a pr...

  15. 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

  16. Digital Microdroplet Ejection Technology-Based Heterogeneous Objects Prototyping

    Science.gov (United States)

    Yang, Jiquan; Feng, Chunmei; Yang, Jianfei; Zhu, Liya; Guo, Aiqing

    2016-01-01

    An integrate fabrication framework is presented to build heterogeneous objects (HEO) using digital microdroplets injecting technology and rapid prototyping. The heterogeneous materials part design and manufacturing method in structure and material was used to change the traditional process. The net node method was used for digital modeling that can configure multimaterials in time. The relationship of material, color, and jetting nozzle was built. The main important contributions are to combine the structure, material, and visualization in one process and give the digital model for manufacture. From the given model, it is concluded that the method is effective for HEO. Using microdroplet rapid prototyping and the model given in the paper HEO could be gotten basically. The model could be used in 3D biomanufacturing.

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

    Science.gov (United States)

    Soliman, M.; Wu, Z.

    2008-06-01

    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.

  18. 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.

  19. An object oriented computer-based patient record reference model.

    Science.gov (United States)

    Doré, L; Lavril, M; Jean, F C; Degoulet, P

    1995-01-01

    In the context of health care information systems based on client/server architecture, we address the problem of a common Computer-based Patient Record (CPR). We define it as a collection of faithful observations about patients care, with respect to the free expression of physicians. This CPR model supports several views of the medical data, in order to provide applications with a comprehensive and standardized access to distributed patient data. Finally, we validated our CPR approach as a primary data model server for an application for hypertensive patient management. PMID:8563306

  20. Sources of bias in the perception of heading in the presence of moving objects: Object-based and border-based discrepancies.

    Science.gov (United States)

    Layton, Oliver W; Fajen, Brett R

    2016-01-01

    The focus of expansion (FoE) specifies the heading direction of an observer during self-motion, and experiments show that humans can accurately perceive their heading from optic flow. However, when the environment contains an independently moving object, heading judgments may be biased. When objects approach the observer in depth, the heading bias may be due to discrepant optic flow within the contours of the object that radiates from a secondary FoE (object-based discrepancy) or by motion contrast at the borders of the object (border-based discrepancy). In Experiments 1 and 2, we manipulated the object's path angle and distance from the observer to test whether the heading bias induced by moving objects is entirely due to object-based discrepancies. The results showed consistent bias even at large path angles and when the object moved far in depth, which is difficult to reconcile with the influence of discrepant optic flow within the object. In Experiment 3, we found strong evidence that the misperception of heading can also result from a specific border-based discrepancy ("pseudo FoE") that emerges from the relative motion between the object and background at the trailing edge of the object. Taken together, the results from the present study support the idea that when moving objects are present, heading perception is biased in some conditions by discrepant optic flow within the contours of the object and in other conditions by motion contrast at the border (the pseudo FoE). Center-weighted spatial pooling mechanisms in MSTd may account for both effects. PMID:26762278

  1. 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.

  2. Multi Objective AODV Based On a Realistic Mobility Model

    OpenAIRE

    Hamideh Babaei; Morteza Romoozi

    2010-01-01

    Routing is one of the most important challenges in ad hoc network. Numerous algorithms have been presented and one of the most important of them is AODV. This algorithm like many other algorithm calculate optimum path while pays no attention to environment situations, mobility pattern and mobile nodes status. However several presented algorithm have considered this situation and presented algorithm which named environment aware or mobility based. But in them have not considered realistic move...

  3. Multiple Object Tracking Using Evolutionary MCMC-Based Particle Algorithms

    OpenAIRE

    Septier, François; Carmi, Avishy; Pang, Sze Kim; Godsill, Simon

    2009-01-01

    Algorithms are presented for detection and tracking of multiple clusters of coordinated targets. Based on a Markov chain Monte Carlo sampling mechanization, the new algorithms maintain a discrete approximation of the filtering density of the clusters' state. The filters' tracking efficiency is enhanced by incorporating various sampling improvement strategies into the basic Metropolis-Hastings scheme. Thus, an evolutionary stage consisting of two primary steps is introduced: 1) producing a pop...

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

    OpenAIRE

    Eirik Borgen; Henning Neerland; Strandhagen, Jan O.

    1990-01-01

    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 equipme...

  5. Adaptability Evaluation of Enterprise Information Systems Based on Object-based Knowledge Mesh

    Directory of Open Access Journals (Sweden)

    Chaogai Xue

    2013-05-01

    Full Text Available To apply enterprise information systems more widely, it is necessary to evaluate their adaptability. In this paper, firstly, an index set of adaptability evaluation system based on object-based knowledge mesh (OKM is proposed and then, according to goal-question-metrics (GQM for enterprise information systems, and the quantitative measurement is given. Second, based on similarity to ideal solution (TOPSIS, the evaluation model is built and the adaptability evaluation (AE algorithm is proposed to evaluate enterprise information systems’ adaptability. Finally, the application of the evaluation system and AE algorithm is verified through an example, which provides quantitative references for evaluating and optimizing enterprise information systems’ adaptability.

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

    OpenAIRE

    Pham The Bao; Bui Ngoc Nam

    2012-01-01

    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 normali...

  7. Object-based wavelet compression using coefficient selection

    Science.gov (United States)

    Zhao, Lifeng; Kassim, Ashraf A.

    1998-12-01

    In this paper, we present a novel approach to code image regions of arbitrary shapes. The proposed algorithm combines a coefficient selection scheme with traditional wavelet compression for coding arbitrary regions and uses a shape adaptive embedded zerotree wavelet coding (SA-EZW) to quantize the selected coefficients. Since the shape information is implicitly encoded by the SA-EZW, our decoder can reconstruct the arbitrary region without separate shape coding. This makes the algorithm simple to implement and avoids the problem of contour coding. Our algorithm also provides a sufficient framework to address content-based scalability and improved coding efficiency as described by MPEG-4.

  8. Mass Measurements of Isolated Objects from Space-based Microlensing

    CERN Document Server

    Zhu, Wei; Gould, A; Udalski, A; Han, C; Shvartzvald, Y; Ranc, C; Jorgensen, U G; Poleski, R; Bozza, V; Beichman, C; Bryden, G; Carey, S; Gaudi, B S; Henderson, C B; Pogge, R W; Porritt, I; Wibking, B; Yee, J C; Pawlak, M; Szymanski, M K; Skowron, J; Mroz, P; Kozlowski, S; Wyrzykowski, L; Pietrukowicz, P; Pietrzynski, G; Soszynski, I; Ulaczyk, K; Choi, J Y; Park, H; Jung, Y K; Shin, I -G; Albrow, M D; Park, B -G; Kim, S -L; Lee, C -U; Kim, D -J; Lee, Y; Friedmann, M; Kaspi, S; Maoz, D; Hundertmark, M; Street, R A; Tsapras, Y; Bramich, D M; Cassan, A; Dominik, M; Bachelet, E; Dong, Subo; Jaimes, R Figuera; Horne, K; Mao, S; Menzies, J; Schmidt, R; Snodgrass, C; Steele, I A; Wambsganss, J; Skottfelt, J; Andersen, M I; Burgdorf, M J; Ciceri, S; D'Ago, G; Evans, D F; Gu, S -H; Hinse, T C; Kerins, E; Korhonen, H; Kuffmeier, M; Mancini, L; Peixinho, N; popovas, A; Rabus, M; Rahvar, S; Rasmussen, R T; Scarpetta, G; Southworth, J; Surdej, J; von Essen, C; Wang, Y -B; Wertz, O

    2015-01-01

    We report on the mass and distance measurements of two single-lens events from the 2015 \\emph{Spitzer} microlensing campaign. With both finite-source effect and microlens parallax measurements, we find that the lens of OGLE-2015-BLG-1268 is a $47\\pm7$ $M_{\\rm J}$ brown dwarf at $5.4\\pm1.0$ kpc, and that the lens of OGLE-2015-BLG-0763 is a $0.50\\pm0.04$ $M_\\odot$ star at $6.9\\pm1.0$ kpc. We show that the probability to definitively measure the mass of isolated microlenses, including isolated stellar mass black holes and free floating planets, is dramatically increased once simultaneous ground- and space-based observations are conducted.

  9. 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...

  10. 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.

  11. Shift-based density estimation for pareto-based algorithms in many-objective optimization

    OpenAIRE

    Li, M.; Yang, S.; X. LIU

    2014-01-01

    It is commonly accepted that Pareto-based evolutionary multiobjective optimization (EMO) algorithms encounter difficulties in dealing with many-objective problems. In these algorithms, the ineffectiveness of the Pareto dominance relation for a high-dimensional space leads diversity maintenance mechanisms to play the leading role during the evolutionary process, while the preference of diversity maintenance mechanisms for individuals in sparse regions results in the final solutions distributed...

  12. Ontological representation based on semantic descriptors applied to geographic objects

    Directory of Open Access Journals (Sweden)

    Miguel Jesús Torres-Ruiz

    2009-01-01

    Full Text Available En esta tesis se presenta la metodología GEONTO - MET, orientada a formalizar la conceptualización del dominio geográfico, considerando las especificaciones del Instituto Nacional de Estadística, Geografía e Informática (INEGI. El espíritu de esta metodología es proporcionar un conjunto de descripciones semánticas que reflejen las propiedades y relaciones que describen entre sí el comportamiento de los objetos geográficos, tomando estos elementos directamente de la ontología de dominio geográfico diseñada para este fin. Esta tesis sienta las bases para una futura interpretación automática de regiones geográficas, orientado al soporte de toma de decisiones, haciendo uso de la conceptualización del dominio geográfico; con el objeto de generar nuevo conocimiento en forma automática y realizar un análisis más profundo del entorno geoespacial. El hecho de contar con una descripción semántica de un entorno geográfico, permite establecer los requerimientos necesarios hacia un razonamiento espacial; es decir, el hecho de conocer el comportamiento que presentan los objetos geográficos inmersos en una partición geográfica es de suma importancia para entender e interpretar la semántica que representan y explotar la inferencia implícita que posee la conceptualización. En consecuencia, este trabajo aporta la metodología que permite integrar y compartir información geoespacial. GEONTO - MET proporciona soluciones viables hacia estos tópicos y otros, como el hecho de compactar datos mediante estructuras alternas a modelos tradicionales y evitar la ambigüedad de términos al utilizar una conceptualización del dominio.

  13. A NEW MASK-BASED OBJECTIVE MEASURE FOR PREDICTING THE INTELLIGIBILITY OF BINARY MASKED SPEECH

    OpenAIRE

    Yu, Chengzhu; Wójcicki, Kamil K.; Loizou, P. C.; John H. L. Hansen

    2013-01-01

    Mask-based objective speech-intelligibility measures have been successfully proposed for evaluating the performance of binary masking algorithms. These objective measures were computed directly by comparing the estimated binary mask against the ground truth ideal binary mask (IdBM). Most of these objective measures, however, assign equal weight to all time-frequency (T-F) units. In this study, we propose to improve the existing mask-based objective measures by weighting each T-F unit accordin...

  14. A Generic Object-Calculus Based on Addressed Term Rewriting Systems

    OpenAIRE

    Dougherty, Daniel J.; Lang, Frederic; Lescanne, Pierre; Liquori, Luigi; Rose, Kristoffer

    2002-01-01

    We describe the foundations of Obj^+a, a framework, or generic calculus, for modeling object-oriented programming languages. This framework provides a setting for a formal operational semantics of object based languages, in the style of the Lambda Calculus of Objects of Fisher, Honsell, and Mitchell. As a formalism for specification, is arranged in modules, permitting a natural classification of many object-based calculi according to their features. In particular, there are modules for calcul...

  15. 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.

  16. 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.

  17. Attribute and topology based change detection in a constellation of previously detected objects

    Energy Technology Data Exchange (ETDEWEB)

    Paglieroni, David W.; Beer, Reginald N.

    2016-01-19

    A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

  18. Novel 3-D Object Recognition Methodology Employing a Curvature-Based Histogram

    OpenAIRE

    Liang-Chia Chen; Hoang Hong Hai; Xuan-Loc Nguyen; Hsiao-Wen Wu

    2013-01-01

    In this paper, a new object recognition algorithm employing a curvature-based histogram is presented. Recognition of three-dimensional (3-D) objects using range images remains one of the most challenging problems in 3-D computer vision due to its noisy and cluttered scene characteristics. The key breakthroughs for this problem mainly lie in defining unique features that distinguish the similarity among various 3-D objects. In our approach, an object detection scheme is developed to identify t...

  19. 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...

  20. Suspicious Object Recognition Method in Video Stream Based on Visual Attention

    OpenAIRE

    Wang, Panqu; Zhang, Yan

    2013-01-01

    We propose a state of the art method for intelligent object recognition and video surveillance based on human visual attention. Bottom up and top down attention are applied respectively in the process of acquiring interested object(saliency map) and object recognition. The revision of 4 channel PFT method is proposed for bottom up attention and enhances the speed and accuracy. Inhibit of return (IOR) is applied in judging the sequence of saliency object pop out. Euclidean distance of color di...

  1. Object Tracking in Rotational-based and Regular Deployment Visual Sensor Networks

    OpenAIRE

    Hua-Wen Tsai; Xiao-Feng Zhao

    2013-01-01

    Visual sensor networks offer surveillance applications, particularly object tracking. This study uses a rotational-based and regular deployment visual sensor network to track an object. The proposed method is applied to detect the object tracking in security monitoring. This study provides two types of network architecture to deploy the sensor nodes and utilizes the lines of sight between cameras to form a defense face to surround the mobile object. Each sensor ...

  2. Self-Localization and Stream Field Based Partially Observable Moving Object Tracking

    OpenAIRE

    Kuo-Shih Tseng; Angela Chih-Wei Tang

    2009-01-01

    Self-localization and object tracking are key technologies for human-robot interactions. Most previous tracking algorithms focus on how to correctly estimate the position, velocity, and acceleration of a moving object based on the prior state and sensor information. What has been rarely studied so far is how a robot can successfully track the partially observable moving object with laser range finders if there is no preanalysis of object trajectories. In this case, traditional tracking algori...

  3. Robobarista: Object Part based Transfer of Manipulation Trajectories from Crowd-sourcing in 3D Pointclouds

    OpenAIRE

    Sung, Jaeyong; Jin, Seok Hyun; Saxena, Ashutosh

    2015-01-01

    There is a large variety of objects and appliances in human environments, such as stoves, coffee dispensers, juice extractors, and so on. It is challenging for a roboticist to program a robot for each of these object types and for each of their instantiations. In this work, we present a novel approach to manipulation planning based on the idea that many household objects share similarly-operated object parts. We formulate the manipulation planning as a structured prediction ...

  4. Coordination and control in project-based work: digital objects and infrastructures for delivery

    OpenAIRE

    Whyte, Jennifer; Lobo, Sunila

    2010-01-01

    A major infrastructure project is used to investigate the role of digital objects in the coordination of engineering design work. From a practice-based perspective, research emphasizes objects as important in enabling cooperative knowledge work and knowledge sharing. The term ‘boundary object’ has become used in the analysis of mutual and reciprocal knowledge sharing around physical and digital objects. The aim is to extend this work by analysing the introduction of an extranet in...

  5. 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...

  6. Semi-automatic classification of glaciovolcanic landforms: An object-based mapping approach based on geomorphometry

    Science.gov (United States)

    Pedersen, G. B. M.

    2016-02-01

    A new object-oriented approach is developed to classify glaciovolcanic landforms (Procedure A) and their landform elements boundaries (Procedure B). It utilizes the principle that glaciovolcanic edifices are geomorphometrically distinct from lava shields and plains (Pedersen and Grosse, 2014), and the approach is tested on data from Reykjanes Peninsula, Iceland. The outlined procedures utilize slope and profile curvature attribute maps (20 m/pixel) and the classified results are evaluated quantitatively through error matrix maps (Procedure A) and visual inspection (Procedure B). In procedure A, the highest obtained accuracy is 94.1%, but even simple mapping procedures provide good results (> 90% accuracy). Successful classification of glaciovolcanic landform element boundaries (Procedure B) is also achieved and this technique has the potential to delineate the transition from intraglacial to subaerial volcanic activity in orthographic view. This object-oriented approach based on geomorphometry overcomes issues with vegetation cover, which has been typically problematic for classification schemes utilizing spectral data. Furthermore, it handles complex edifice outlines well and is easily incorporated into a GIS environment, where results can be edited or fused with other mapping results. The approach outlined here is designed to map glaciovolcanic edifices within the Icelandic neovolcanic zone but may also be applied to similar subaerial or submarine volcanic settings, where steep volcanic edifices are surrounded by flat plains.

  7. 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.

    2015-06-01

    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.

  8. 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.

  9. 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.

  10. Reduced object-based perception in the near-hand space.

    Science.gov (United States)

    Suh, Jihyun; Abrams, Richard A

    2015-12-01

    Previous studies have shown that hand proximity changes visual perception (Abrams et al. in Cognition 107(3):1035-1047, 2008). The present study examined the effects of hand proximity on object-based perception. In three experiments, participants viewed stimuli that were either near to or far from their hands. The target stimulus appeared, after a cue, in one of two rectangular objects: either at the location that had been previously cued, at the uncued end of the cued object, or in the uncued object. We found a significantly reduced same-object benefit in reaction time for stimuli near the hands in one experiment. Interestingly, we observed a same-object cost in sensitivity for stimuli near the hands in another experiment. The results reveal that object-based perception is disrupted in the near-hand space. This is consistent with previous findings revealing altered visual processing near the hands. PMID:26289483

  11. Self-Localization and Stream Field Based Partially Observable Moving Object Tracking

    Directory of Open Access Journals (Sweden)

    Kuo-Shih Tseng

    2009-01-01

    Full Text Available Self-localization and object tracking are key technologies for human-robot interactions. Most previous tracking algorithms focus on how to correctly estimate the position, velocity, and acceleration of a moving object based on the prior state and sensor information. What has been rarely studied so far is how a robot can successfully track the partially observable moving object with laser range finders if there is no preanalysis of object trajectories. In this case, traditional tracking algorithms may lead to the divergent estimation. Therefore, this paper presents a novel laser range finder based partially observable moving object tracking and self-localization algorithm for interactive robot applications. Dissimilar to the previous work, we adopt a stream field-based motion model and combine it with the Rao-Blackwellised particle filter (RBPF to predict the object goal directly. This algorithm can keep predicting the object position by inferring the interactive force between the object goal and environmental features when the moving object is unobservable. Our experimental results show that the robot with the proposed algorithm can localize itself and track the frequently occluded object. Compared with the traditional Kalman filter and particle filter-based algorithms, the proposed one significantly improves the tracking accuracy.

  12. Multi-feature object identification of remote sensing image based on vague soft sets

    Science.gov (United States)

    Wei, Bo; Wang, Zhichao; Xie, Qingqing; Zhang, Kailin

    2015-12-01

    Multi-feature classification and image segmentation are two cores in object-oriented classification method of high resolution remote sensing images. Multi-feature object identification is an important part of multi-feature classification, which is identification for the image regions or the segmentation objects segmented by image segmentation under the guidance of a corresponding relationship between objects and features or combination. A method of multi-feature object identification was proposed based on vague soft sets. Firstly, the vague soft sets were formed by building the parameter sets according to spectral characteristics and object-oriented features of the segmentation objects. Secondly, according to general TOPSIS (the Technique for Order Preference by Similarity to Ideal Solution), a TOPSIS based on Vague soft sets for multi-feature object identification was proposed, which obtained a object identification result of the segmentation objects by using similarity measure of vague soft sets to sort attribution of the cover types for the segmentation objects. The experimental results show that the proposed method obtains a correct result of object identification and is feasible and effective.

  13. Object recognition based on Google's reverse image search and image similarity

    Science.gov (United States)

    Horváth, András.

    2015-12-01

    Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.

  14. Unsupervised Spectral-Spatial Feature Selection-Based Camouflaged Object Detection Using VNIR Hyperspectral Camera

    Science.gov (United States)

    2015-01-01

    The detection of camouflaged objects is important for industrial inspection, medical diagnoses, and military applications. Conventional supervised learning methods for hyperspectral images can be a feasible solution. Such approaches, however, require a priori information of a camouflaged object and background. This letter proposes a fully autonomous feature selection and camouflaged object detection method based on the online analysis of spectral and spatial features. The statistical distance metric can generate candidate feature bands and further analysis of the entropy-based spatial grouping property can trim the useless feature bands. Camouflaged objects can be detected better with less computational complexity by optical spectral-spatial feature analysis. PMID:25879073

  15. Vision-based grasping of unknown objects to improve disabled people autonomy.

    OpenAIRE

    Dune, C.; Remazeilles, A.; Marchand, E.; C. Leroux

    2008-01-01

    This paper presents our contribution to vision based robotic assistance for people with disabilities. The rehabilitative robotic arms currently available on the market are directly controlled by adaptive devices, which lead to increasing strain on the user's disability. To reduce the need for user's actions, we propose here several vision-based solutions to automatize the grasping of unknown objects. Neither appearance data bases nor object models are considered. All the needed information is...

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

    DEFF Research Database (Denmark)

    Gerlach, Christian; Law, Ian; Paulson, Olaf B

    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...

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

    Directory of Open Access Journals (Sweden)

    Yunna Wu

    2013-08-01

    Full Text Available 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 reliability control theory of new energy power projects, then combined the known reliability control standards to assess project reliability, finally established objective integrated control model of new energy power projects based on reliability theory. Finally an simple example proves that the proposed objective integrated control model is simple and practical.  

  18. Real-Time Occlusion Handling in Augmented Reality Based on an Object Tracking Approach

    Directory of Open Access Journals (Sweden)

    Yuan Tian

    2010-03-01

    Full Text Available To produce a realistic augmentation in Augmented Reality, the correct relative positions of real objects and virtual objects are very important. In this paper, we propose a novel real-time occlusion handling method based on an object tracking approach. Our method is divided into three steps: selection of the occluding object, object tracking and occlusion handling. The user selects the occluding object using an interactive segmentation method. The contour of the selected object is then tracked in the subsequent frames in real-time. In the occlusion handling step, all the pixels on the tracked object are redrawn on the unprocessed augmented image to produce a new synthesized image in which the relative position between the real and virtual object is correct. The proposed method has several advantages. First, it is robust and stable, since it remains effective when the camera is moved through large changes of viewing angles and volumes or when the object and the background have similar colors. Second, it is fast, since the real object can be tracked in real-time. Last, a smoothing technique provides seamless merging between the augmented and virtual object. Several experiments are provided to validate the performance of the proposed method.

  19. Real-time occlusion handling in augmented reality based on an object tracking approach.

    Science.gov (United States)

    Tian, Yuan; Guan, Tao; Wang, Cheng

    2010-01-01

    To produce a realistic augmentation in Augmented Reality, the correct relative positions of real objects and virtual objects are very important. In this paper, we propose a novel real-time occlusion handling method based on an object tracking approach. Our method is divided into three steps: selection of the occluding object, object tracking and occlusion handling. The user selects the occluding object using an interactive segmentation method. The contour of the selected object is then tracked in the subsequent frames in real-time. In the occlusion handling step, all the pixels on the tracked object are redrawn on the unprocessed augmented image to produce a new synthesized image in which the relative position between the real and virtual object is correct. The proposed method has several advantages. First, it is robust and stable, since it remains effective when the camera is moved through large changes of viewing angles and volumes or when the object and the background have similar colors. Second, it is fast, since the real object can be tracked in real-time. Last, a smoothing technique provides seamless merging between the augmented and virtual object. Several experiments are provided to validate the performance of the proposed method. PMID:22319278

  20. 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.

  1. Laser-based detection and tracking moving objects using data-driven Markov chain Monte Carlo

    OpenAIRE

    Vu, Trung-Dung; Aycard, Olivier

    2009-01-01

    We present a method of simultaneous detection and tracking moving objects from a moving vehicle equipped with a single layer laser scanner. A model-based approach is introduced to interpret the laser measurement sequence by hypotheses of moving object trajectories over a sliding window of time. Knowledge of various aspects including object model, measurement model, motion model are integrated in one theoretically sound Bayesian framework. The data-driven Markov chain Monte Carlo (DDMCMC) tech...

  2. 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...

  3. Building Viewpoints in an Object-Based Representation System for Knowledge Discovery in Databases

    OpenAIRE

    Simon, Arnaud; Napoli, Amedeo

    1999-01-01

    In this paper, we present an approach to knowledge discovery in databases in the context of object-based representation systems. The goal of this approach is to extract viewpoints and association rules from data represented by objects. A viewpoint is a hierarchy of classes (a kind of partial lattice) and an association rule can be defined within a viewpoint or between two classes lying in different viewpoints. The viewpoints construction algorithm allows to manipulate objects which are indiff...

  4. 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)

  5. Moving Object Classification Method Based on SOM and K-means

    OpenAIRE

    Jian Wu; Jie Xia; Jian-ming Chen; Zhi-ming Cui

    2011-01-01

    We do research on moving object classification in traffic video. Our aim is to classify the moving objects into pedestrians, bicycles and vehicles. Due to the advantage of self-organizing feature map (SOM), an unsupervised learning algorithm, which is simple and self organization, and the common usage of K-means clustering method, this paper combines SOM with K-means to do classification of moving objects in traffic video, constructs a system including four parts, and proposes a method based ...

  6. Multiple Moving Object Recognitions in video based on Log Gabor-PCA Approach

    OpenAIRE

    Gopalakrishna, M. T.; M. Ravishankar; Rameshbabu, D. R

    2014-01-01

    Object recognition in the video sequence or images is one of the sub-field of computer vision. Moving object recognition from a video sequence is an appealing topic with applications in various areas such as airport safety, intrusion surveillance, video monitoring, intelligent highway, etc. Moving object recognition is the most challenging task in intelligent video surveillance system. In this regard, many techniques have been proposed based on different methods. Despite of ...

  7. Object-Based Classification of Abandoned Logging Roads under Heavy Canopy Using LiDAR

    OpenAIRE

    Jason Sherba; Leonhard Blesius; Jerry Davis

    2014-01-01

    LiDAR-derived slope models may be used to detect abandoned logging roads in steep forested terrain. An object-based classification approach of abandoned logging road detection was employed in this study. First, a slope model of the study site in Marin County, California was created from a LiDAR derived DEM. Multiresolution segmentation was applied to the slope model and road seed objects were iteratively grown into candidate objects. A road classification accuracy of 86% was achieved using th...

  8. Content-based fused off-axis object illumination direct-to-digital holography

    Science.gov (United States)

    Price, Jeffery R.

    2006-05-02

    Systems and methods are described for content-based fused off-axis illumination direct-to-digital holography. A method includes calculating an illumination angle with respect to an optical axis defined by a focusing lens as a function of data representing a Fourier analyzed spatially heterodyne hologram; reflecting a reference beam from a reference mirror at a non-normal angle; reflecting an object beam from an object the object beam incident upon the object at the illumination angle; focusing the reference beam and the object beam at a focal plane of a digital recorder to from the content-based off-axis illuminated spatially heterodyne hologram including spatially heterodyne fringes for Fourier analysis; and digitally recording the content based off-axis illuminated spatially heterodyne hologram including spatially heterodyne fringes for Fourier analysis.

  9. Optoelectronic System for Roll Angles Measuring of Maneuvering Objects Based on Anamorphosis Effect

    International Nuclear Information System (INIS)

    The objects mutual displacement measurement is an important task, particularly, the measuring of roll angles. New method for roll angles measuring of maneuvering objects based on anamorphosis effect is developed. Optical scheme for whole measurement system and for anamorphosis element is proposed. Equation for the static characteristic of the system and its graphical representation are showed

  10. Visual Statistical Learning Based on the Perceptual and Semantic Information of Objects

    Science.gov (United States)

    Otsuka, Sachio; Nishiyama, Megumi; Nakahara, Fumitaka; Kawaguchi, Jun

    2013-01-01

    Five experiments examined what is learned based on the perceptual and semantic information of objects in visual statistical learning (VSL). In the familiarization phase, participants viewed a sequence of line drawings and detected repetitions of various objects. In a subsequent test phase, they watched 2 test sequences (statistically related…

  11. 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…

  12. A knowledge-based object recognition system for applications in the space station

    Science.gov (United States)

    Dhawan, Atam P.

    1988-01-01

    A knowledge-based three-dimensional (3D) object recognition system is being developed. The system uses primitive-based hierarchical relational and structural matching for the recognition of 3D objects in the two-dimensional (2D) image for interpretation of the 3D scene. At present, the pre-processing, low-level preliminary segmentation, rule-based segmentation, and the feature extraction are completed. The data structure of the primitive viewing knowledge-base (PVKB) is also completed. Algorithms and programs based on attribute-trees matching for decomposing the segmented data into valid primitives were developed. The frame-based structural and relational descriptions of some objects were created and stored in a knowledge-base. This knowledge-base of the frame-based descriptions were developed on the MICROVAX-AI microcomputer in LISP environment. The simulated 3D scene of simple non-overlapping objects as well as real camera data of images of 3D objects of low-complexity have been successfully interpreted.

  13. A simple and efficient object detection method based on saliency measure for infrared radiation image

    Science.gov (United States)

    Sun, Zhaolei; Hui, Bin

    2014-11-01

    Detection of visually salient objects plays an important role in applications such as object segmentation, adaptive compression, object recognition, etc. A simple and computationally efficient method is presented in this paper for detecting visually salient objects in Infrared Radiation images. The proposed method can be divided into three steps. Firstly, the infrared image is pre-processed to increase the contrast between objects and background. Secondly, the spectral residual of the pre-processed image is extracted in the log spectrum, then via corresponding inverse transform and threshold segmentation we can get the rough regions of the salient objects. Finally, we apply a sliding window to acquire the explicit position of the salient objects using the probabilistic interpretation of the semi-local feature contrast which is estimated by comparing the gray level distribution of the object and the surrounding area in the original image. And as we change the size of the sliding window, different size of objects can be found out. In our proposed method, the first two steps combined together to play a role in narrowing the searching region and thus accelerating computation. The third procedure is applied to extract the salient objects. We test our method on abundant amount of Infrared Radiation images, and the results show that our saliency detection based object detection method is effective and robust.

  14. 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)

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

    DEFF Research Database (Denmark)

    Gu, Tao; Chen, Shaxun; Tao, Xianping; Lu, Jian

    2010-01-01

    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 fingerprints to recognize activities without human labeling. We show how to build our activity models...... based on object-use fingerprints, which are sets of contrast patterns describing significant differences of object use between any two activity classes. We then propose a fingerprint-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...

  16. 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.

  17. An Index Structure for Fast Query Retrieval in Object Oriented Data Bases Using Signature Weight Declustering

    OpenAIRE

    I. Elizabeth Shanthi; R. Nadarajan

    2009-01-01

    An important question in information retrieval is how to create a database index which can be searched efficiently for the data one seeks. One such technique called signature file based access method is preferred for its easy handling of insertion and update operations. Most of the proposed methods use either efficient search method or tree based intermediate data structure to filter data objects matching the query. Use of search techniques retrieves the objects by sequentially compari...

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

    OpenAIRE

    Wies?aw PAMU?A

    2009-01-01

    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 assesse...

  19. 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.

  20. A repository based tool for re-engineering towards an object oriented environment

    OpenAIRE

    Signore, Oreste; Loffredo, Mario

    1993-01-01

    Software re-engineering and object orientation are two areas of growing interest in the last years. However, while many researchers have focused their interest in the object-oriented design methodologies, a little attention has been paid to the re-engineering towards an object-oriented environment. In this paper we examine the motivations towards object-oriented re-engineering (extendibility, robustness and reusability of the code) and the problems found in moving from a process-based to an o...

  1. 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 ...

  2. An Automatic Algorithm for Object Recognition and Detection Based on Asift Keypoints

    Directory of Open Access Journals (Sweden)

    Reza Oji

    2012-10-01

    Full Text Available Object recognition is an important task in image processing and computer vision. This paper presents a perfect method for object recognition with full boundary detection by combining affine scale invariant feature transform (ASIFT and a region merging algorithm. ASIFT is a fully affine invariant algorithm that means features are invariant to six affine parameters namely translation (2 parameters, zoom, rotation and two camera axis orientations. The features are very reliable and give us strong keypoints that can be used for matching between different images of an object. We trained an object in several images with different aspects for finding best keypoints of it. Then, a robust region merging algorithm is used to recognize and detect the object with full boundary in the other images based on ASIFT keypoints and a similarity measure for merging regions in the image. Experimental results show that the presented method is very efficient and powerful to recognize the object and detect it with high accuracy.

  3. Multi-view space object recognition and pose estimation based on kernel regression

    Directory of Open Access Journals (Sweden)

    Zhang Haopeng

    2014-10-01

    Full Text Available The application of high-performance imaging sensors in space-based space surveillance systems makes it possible to recognize space objects and estimate their poses using vision-based methods. In this paper, we proposed a kernel regression-based method for joint multi-view space object recognition and pose estimation. We built a new simulated satellite image dataset named BUAA-SID 1.5 to test our method using different image representations. We evaluated our method for recognition-only tasks, pose estimation-only tasks, and joint recognition and pose estimation tasks. Experimental results show that our method outperforms the state-of-the-arts in space object recognition, and can recognize space objects and estimate their poses effectively and robustly against noise and lighting conditions.

  4. 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.

  5. A 3-Step Algorithm Using Region-Based Active Contours for Video Objects Detection

    OpenAIRE

    Aubert Gilles; Jehan-Besson Stéphanie; Barlaud Michel

    2002-01-01

    We propose a 3-step algorithm for the automatic detection of moving objects in video sequences using region-based active contours. First, we introduce a very full general framework for region-based active contours with a new Eulerian method to compute the evolution equation of the active contour from a criterion including both region-based and boundary-based terms. This framework can be easily adapted to various applications, thanks to the introduction of functions named descriptors of the d...

  6. 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.

  7. 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.

  8. 3D object following based on visual information for Unmanned Aerial Vehicles

    OpenAIRE

    Mondragon Bernal, Ivan Fernando; Campoy Cervera, Pascual; Olivares Méndez, Miguel Ángel; Martínez 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...

  9. Object-based change detection on multiscale fusion for VHR remote sensing images

    Science.gov (United States)

    Zhang, Hansong; Chen, Jianyu; Liu, Xin

    2015-12-01

    This paper presents a novel Object-based context sensitive technique for unsupervised change detection in very high spatial resolution(VHR) remote sensing images. The proposed technique models the scene at different segment levels defining multiscale-level image objects. Multiscale-level image object change features is helpful for improving the discriminability between the changed class and unchanged class. Firstly according to the best classification principle as "homogeneity in class, heterogeneity between class", A set of optimal scales are determined. Then a multiscale level change vector analysis to each pixel of the considered images helps improve the accuracy and the degree of automation, which is implemented on multiscale features fusion. The technique properly analyzes the multiscale-level image objects' context information of the considered spatial position. The adaptive nature of optimal multiscale image objects and their multilevel representation allow one a proper modeling of complex scene in the investigated region. Experimental results confirm the effectiveness of the proposed approach.

  10. Digital holographic microscope for measurement of high gradient deep topography object based on superresolution concept.

    Science.gov (United States)

    Liżewski, Kamil; Kozacki, Tomasz; Kostencka, Julianna

    2013-06-01

    In this Letter, a novel concept based on superresolution technique that enables the measurement of high gradient and deep topography objects using digital holographic (DH) microscopy is introduced. The major problem of DH systems is limited NA that prohibits the metrological characterization of object features of high frequencies. The proposed technique has the ability to extend spatial frequency spectrum of the measured topography by applying multidirectional plane wave illumination, which is experimentally realized with a grating. The technique recovers sample topography from the set of object waves with different object spectra that are converted into a set of topographies by using an algorithm which takes into account refraction. Application of this novel approach is experimentally validated by characterization of high gradient topography objects with maximum angle of tangent 65°. PMID:23722775

  11. Key Object Discovery and Tracking Based on Context-Aware Saliency

    Directory of Open Access Journals (Sweden)

    Geng Zhang

    2013-01-01

    Full Text Available In this paper, we propose an online key object discovery and tracking system based on visual saliency. We formulate the problem as a temporally consistent binary labelling task on a conditional random field and solve it by using a particle filter. We also propose a context‐aware saliency measurement, which can be used to improve the accuracy of any static or dynamic saliency maps. Our refined saliency maps provide clearer indications as to where the key object lies. Based on good saliency cues, we can further segment the key object inside the resulting bounding box, considering the spatial and temporal context. We tested our system extensively on different video clips. The results show that our method has significantly improved the saliency maps and tracks the key object accurately.

  12. An Efficient Lagrangean Relaxation-based Object Tracking Algorithm in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Frank Yeong-Sung Lin

    2010-08-01

    Full Text Available In this paper we propose an energy-efficient object tracking algorithm in wireless sensor networks (WSNs. Such sensor networks have to be designed to achieve energy-efficient object tracking for any given arbitrary topology. We consider in particular the bi-directional moving objects with given frequencies for each pair of sensor nodes and link transmission cost. This problem is formulated as a 0/1 integer-programming problem. A Lagrangean relaxation-based (LR-based heuristic algorithm is proposed for solving the optimization problem. Experimental results showed that the proposed algorithm achieves near optimization in energy-efficient object tracking. Furthermore, the algorithm is very efficient and scalable in terms of the solution time.

  13. Image Fusion Quality Assessment of High Resolution Satellite Imagery based on an Object Level Strategy

    Directory of Open Access Journals (Sweden)

    Farhad Samadzadegan

    2013-04-01

    Full Text Available Considering the importance of fusion accuracy on the quality of fused images, it seems necessary to evaluate the quality of fused images before using them in further applications. Current quality evaluation metrics are mainly developed on the basis of applying quality metrics in pixel level and to evaluate the final quality by average computation. In this paper, an object level strategy for quality assessment of fused images is proposed. Based on the proposed strategy, image fusion quality metrics are applied on image objects and quality assessment of fusion are conducted based on inspecting fusion quality in those image objects. Results clearly show the inconsistency of fusion behavior in different image objects and the weakness of traditional pixel level strategies in handling these heterogeneities.

  14. Nonredundant representation of images allowing object-based and multiresolution scalable coding

    Science.gov (United States)

    Amonou, Isabelle; Duhamel, Pierre

    2000-05-01

    In this work, we investigate a new class of scalable image coders. We target at the same time multiresolution (for spatial scalability), critical (for compression efficiency) and (hierarchical) segmentation based decompositions (for object based scalability). Hierarchical segmentation allows to access the description of a scene in terms of regions or objects at several resolution levels, and thus encode and transmit the objects selectively. From a coding viewpoint, it is obviously interesting to couple the multi-level segmentation with a critically decimated decomposition of the image (to avoid redundancy of representation). However, the association of object representation combined with critically sampled multiresolution decomposition has not been studied to our knowledge. In this paper, we propose new methods to perform hierarchical segmentation of an image using critically decimated non linear filter banks; the resulting decomposition embeds a hierarchical segmentation map and is therefore particularly well suited for region based coding and progressive transmission. As the segmentation map is embedded by reconstruction inside the decomposition, we do not really need to transmit it separately, thus attempting to reduce the bitrate. Simulations show that a prototype coder of this type has a degradation in terms of rate/distortion tradeoff compared to a conventional wavelet based image coder, but offers in addition new perspectives for object based manipulations, coding and transmission.

  15. Scalable Object-Based Indexing of HD Videos: A JPEG2000- Oriented solution

    OpenAIRE

    Morand, Claire; Benois-Pineau, Jenny; Domenger, Jean-Philippe

    2008-01-01

    Video indexing technique is crucial in multimedia applications. In the case of HD (High Definition) Video, the principle of scalability is of great importance. The wavelet decomposition used in the JPEG2000 standard provides this property. In this paper, we propose a scalable descriptor based on objects. First, a scalable moving object extraction method is constructed. Using the wavelet data, it relies on the combination of a robust global motion estimation with a morphological color segmenta...

  16. 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...

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

    OpenAIRE

    Levi?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...

  18. A cluster-based method for marine sensitive object extraction and representation

    Science.gov (United States)

    Xue, Cunjin; Dong, Qing; Qin, Lijuan

    2015-08-01

    Within the context of global change, marine sensitive factors or Marine Essential Climate Variables have been defined by many projects, and their sensitive spatial regions and time phases play significant roles in regional sea-air interactions and better understanding of their dynamic process. In this paper, we propose a cluster-based method for marine sensitive region extraction and representation. This method includes a kernel expansion algorithm for extracting marine sensitive regions, and a field-object triple form, integration of object-oriented and field-based model, for representing marine sensitive objects. Firstly, this method recognizes ENSO-related spatial patterns using empirical orthogonal decomposition of long term marine sensitive factors and correlation analysis with multiple ENSO index. The cluster kernel, defined by statistics of spatial patterns, is initialized to carry out spatial expansion and cluster mergence with spatial neighborhoods recursively, then all the related lattices with similar behavior are merged into marine sensitive regions. After this, the Field-object triple form of is used to represent the marine sensitive objects, both with the discrete object with a precise extend and boundary, and the continuous field with variations dependent on spatial locations. Finally, the marine sensitive objects about sea surface temperature are extracted, represented and analyzed as a case of study, which proves the effectiveness and the efficiency of the proposed method.

  19. 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.

  20. Real-time underwater object detection based on an electrically scanned high-resolution sonar

    DEFF Research Database (Denmark)

    Henriksen, Lars

    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...... 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...

  1. Neural-network-based object recognition scheme directly from the boundary information

    Science.gov (United States)

    Venugopal, Kootala P.; Mandalia, Anil D.; Abusalah, S.

    1992-07-01

    We describe a neural network based recognition scheme for 2-D objects directly from the boundary information. The encoded boundary of the object is directly fed as input to the neural network cutting short the feature extraction stage and hence making the scheme computationally simpler. Also, the described scheme is invariant to translation, rotation, and scale changes to the objects. Using isolated hand-written digits, we show that the proposed scheme provides recognition accuracy of up to 87%. The error backpropagation method is used as the learning algorithm for the neural network.

  2. 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.

  3. Metallurgical characterization of three archaeological objects of copper base materials proceeding from low Aragon (Spain)

    International Nuclear Information System (INIS)

    Three archaeological metallic objects corresponding to three different cultural times are studied. The objects are: a point of arrow Palmela type, a fragment of adze (possibly of the First Iron Agen) and a ring or small ring of the Roman Period. The analysis show concordant results similar finds of the same chronology and contribute new data about the metallurgical technology of the copper base material for each of the cultural times of oaring. At the same time how has affected the environment in which the objects have been found has been determine. (Author) 18 refs

  4. The use of enzymes for construction of DNA-based objects and assemblies

    OpenAIRE

    Keller, Sascha; Marx, Andreas

    2011-01-01

    DNA has found wide applications in DNA-based nanotechnology due to its simplicity and predictability of its secondary structure. Selecting DNA for the nanoconstruction of objectsand assemblies bears the inherent potential for manipulations and control by DNA modifying enzymes. In this tutorial review, we present an overview of the enzyme-catalysed constructionof DNA-based objects and assemblies. It is illustrated how a diversity of enzyme-based biochemical reactions are transferred in nanotec...

  5. 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...

  6. An object-based method for Rician noise estimation in MR images.

    OpenAIRE

    Coupé, Pierrick; Manjon, Jose Vicente; Gedamu, Elias; Arnold, Douglas,; Robles, Montserrat; Collins, Louis

    2009-01-01

    The estimation of the noise level in MR images is used to assess the consistency of statistical analysis or as an input parameter in some image processing techniques. Most of the existing Rician noise estimation methods are based on background statistics, and as such are sensitive to ghosting artifacts. In this paper, a new object-based method is proposed. This method is based on the adaptation of the Median Absolute Deviation (MAD) estimator in the wavelet domain for Rician noise. The adapta...

  7. Fast physical object identification based on unclonable features and soft fingerprinting

    OpenAIRE

    Holotyak, Taras; Voloshynovskyy, Svyatoslav; Koval, Oleksiy; Beekhof, Fokko Pieter

    2011-01-01

    In this paper we advocate a new technique for the fast identification of physical objects based on their physical unclonable features (surface microstructures). The proposed identification method is based on soft fingerprinting and consists of two stages: at the first stage the list of possible candidates is estimated based on the most reliable bits of a soft fingerprint and the traditional maximum likelihood decoding is applied to the obtained list to find a single best match at the second s...

  8. 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%.

  9. Learning-Based Object Identification and Segmentation Using Dual-Energy CT Images for Security.

    Science.gov (United States)

    Martin, Limor; Tuysuzoglu, Ahmet; Karl, W Clem; Ishwar, Prakash

    2015-11-01

    In recent years, baggage screening at airports has included the use of dual-energy X-ray computed tomography (DECT), an advanced technology for nondestructive evaluation. The main challenge remains to reliably find and identify threat objects in the bag from DECT data. This task is particularly hard due to the wide variety of objects, the high clutter, and the presence of metal, which causes streaks and shading in the scanner images. Image noise and artifacts are generally much more severe than in medical CT and can lead to splitting of objects and inaccurate object labeling. The conventional approach performs object segmentation and material identification in two decoupled processes. Dual-energy information is typically not used for the segmentation, and object localization is not explicitly used to stabilize the material parameter estimates. We propose a novel learning-based framework for joint segmentation and identification of objects directly from volumetric DECT images, which is robust to streaks, noise and variability due to clutter. We focus on segmenting and identifying a small set of objects of interest with characteristics that are learned from training images, and consider everything else as background. We include data weighting to mitigate metal artifacts and incorporate an object boundary field to reduce object splitting. The overall formulation is posed as a multilabel discrete optimization problem and solved using an efficient graph-cut algorithm. We test the method on real data and show its potential for producing accurate labels of the objects of interest without splits in the presence of metal and clutter. PMID:26186788

  10. 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

    2015-08-01

    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

  11. 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.

  12. JTpack90: A parallel, object-based, Fortran 90 linear algebra package

    Energy Technology Data Exchange (ETDEWEB)

    Turner, J.A.; Kothe, D.B. [Los Alamos National Lab., NM (United States); Ferrell, R.C. [Cambridge Power Computing Associates, Ltd., Brookline, MA (United States)

    1997-03-01

    The authors have developed an object-based linear algebra package, currently with emphasis on sparse Krylov methods, driven primarily by needs of the Los Alamos National Laboratory parallel unstructured-mesh casting simulation tool Telluride. Support for a number of sparse storage formats, methods, and preconditioners have been implemented, driven primarily by application needs. They describe the object-based Fortran 90 approach, which enhances maintainability, performance, and extensibility, the parallelization approach using a new portable gather/scatter library (PGSLib), current capabilities and future plans, and present preliminary performance results on a variety of platforms.

  13. Multi-class remote sensing object recognition based on discriminative sparse representation.

    Science.gov (United States)

    Wang, Xin; Shen, Siqiu; Ning, Chen; Huang, Fengchen; Gao, Hongmin

    2016-02-20

    The automatic recognition of multi-class objects with various backgrounds is a big challenge in the field of remote sensing (RS) image analysis. In this paper, we propose a novel recognition framework for multi-class RS objects based on the discriminative sparse representation. In this framework, the recognition problem is implemented in two stages. In the first, or discriminative dictionary learning stage, considering the characterization of remote sensing objects, the scale-invariant feature transform descriptor is first combined with an improved bag-of-words model for multi-class objects feature extraction and representation. Then, information about each class of training samples is fused into the dictionary learning process; by using the K-singular value decomposition algorithm, a discriminative dictionary can be learned for sparse coding. In the second, or recognition, stage, to improve the computational efficiency, the phase spectrum of a quaternion Fourier transform model is applied to the test image to predict a small set of object candidate locations. Then, a multi-scale sliding window mechanism is utilized to scan the image over those candidate locations to obtain the object candidates (or objects of interest). Subsequently, the sparse coding coefficients of these candidates under the discriminative dictionary are mapped to the discriminative vectors that have a good ability to distinguish different classes of objects. Finally, multi-class object recognition can be accomplished by analyzing these vectors. The experimental results show that the proposed work outperforms a number of state-of-the-art methods for multi-class remote sensing object recognition. PMID:26906591

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

    Directory of Open Access Journals (Sweden)

    Kompatsiaris Ioannis

    2004-01-01

    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.

  15. An approach for autonomous space object identification based on normalized AMI and illumination invariant MSA

    Science.gov (United States)

    Ding, Hao; Li, Xudong; Zhao, Huijie

    2013-03-01

    The space environment is becoming more and more severe and crowded because of the rapid growth of space objects, which reveals an urgent demand to protect active satellites and other space assets. To accomplish such missions, e.g. the collision warning, the identification of space objects is important. In this paper, a three-stage approach for autonomous space object identification based on optical images is proposed. Firstly, on the basis of the approximate perspective imaging model, a scale and illumination invariant descriptor, composed of the normalized affine moment invariants (AMI) and the illumination invariant multiscale autoconvolution (MSA) transform, is developed to characterize the space object. Secondly, a multi-view modeling method is applied to construct multi-view databases of space objects for handling the viewpoint change. Finally, considering the extensibility of the databases, a K-nearest neighbor classifier is employed, and a K-means clustering is adopted to boost the search speed. Furthermore, to test the performance, a novel system based on the proposed approach is built and evaluated. The experimental evidence suggests that the system is stable and works well when the scale of a space object, the phase angle and the viewpoint change.

  16. Thickness and clearance visualization based on distance field of 3D objects

    Directory of Open Access Journals (Sweden)

    Masatomo Inui

    2015-07-01

    Full Text Available This paper proposes a novel method for visualizing the thickness and clearance of 3D objects in a polyhedral representation. The proposed method uses the distance field of the objects in the visualization. A parallel algorithm is developed for constructing the distance field of polyhedral objects using the GPU. The distance between a voxel and the surface polygons of the model is computed many times in the distance field construction. Similar sets of polygons are usually selected as close polygons for close voxels. By using this spatial coherence, a parallel algorithm is designed to compute the distances between a cluster of close voxels and the polygons selected by the culling operation so that the fast shared memory mechanism of the GPU can be fully utilized. The thickness/clearance of the objects is visualized by distributing points on the visible surfaces of the objects and painting them with a unique color corresponding to the thickness/clearance values at those points. A modified ray casting method is developed for computing the thickness/clearance using the distance field of the objects. A system based on these algorithms can compute the distance field of complex objects within a few minutes for most cases. After the distance field construction, thickness/clearance visualization at a near interactive rate is achieved.

  17. 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.

  18. 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

  19. 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; Nymann, Ole

    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...... 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-shaped objects...

  20. SQL-Based Compound Object Comparators: A Case Study of Images Stored in ICE

    Science.gov (United States)

    ?l?zak, Dominik; Sosnowski, ?ukasz

    We introduce the framework for storing and comparing compound objects. The implemented system is based on the RDBMS model, which - unlike other approaches in this area - enables to access the most detailed data about considered objects. It also contains ROLAP cubes designed for specific object classes and appropriately abstracted modules that compute object similarities, referred as comparators. In this paper, we focus on the case study related to images. We show specific examples of fuzzy logic comparators, together with their corresponding SQL statements executed at the level of pixels. We examine several open source database engines by means of their capabilities of storing and querying large amounts of such represented image data. We conclude that the performance of some of them is comparable to standard techniques of image storage and processing, with far better flexibility in defining new similarity criteria and analyzing larger image collections.

  1. Visualization of partially occluded 3D object using wedge prism-based axially distributed sensing

    Science.gov (United States)

    Zhang, Miao; Piao, Yongri; Lee, Joon-Jae; Shin, Donghak; Lee, Byung-Gook

    2014-02-01

    Recently, an axially distributed sensing system (ADS) was proposed for three-dimensional imaging and visualization. In ADS system, the 3D information cannot be collected when the coordinates of the object are close to the optical axis. In this paper, we present a wedge-prism based axially distributed sensing for improving the visual quality of 3D reconstructed images. In the proposed method, a wedge prism is placed in front of a camera and the parallax information is collected through the wedge prism by translating the wedge prism and the image sensor together along the optical axis. Accordingly, the 3D object is recorded as the improved multiple 2D perspective images within the full area of the image sensor. The volumetric images are generated from the recorded elemental images using a computational reconstruction algorithm based on ray back-projection. The proposed method is applied to partially occluded 3D object visualization. Preliminary experiments are performed to verify the approach.

  2. Phase object power mapping and cosmetic defects enhancement by Fourier-based deflectometry

    Science.gov (United States)

    Beghuin, D.; Dubois, X.; Joannes, L.

    2009-06-01

    Optical deflectometry, likewise many other optical methods, permits to reconstruct the wavefront deformations induced by a refractive or a phase object. In this paper, a Fourier based deflectometry method is presented. A telecentric imaging system acquires pictures of a grating being the superposition of two crossed Ronchi rulings of the same spatial frequency. The object under test is inserted in the optical path between the grating and the telecentric imaging system. The presented Fourier based image analysis permits to extract the wavefront derivatives, and therefore permits to reconstruct the wavefront or the local power of the object. In this paper, the method is illustrated on several free form thermoplasic elements, the sensitivity is determined experimentally, the precision is analyzed and the ability to characterize cosmetic defects is evaluated.

  3. Vision based Object Recognition of E-Puck Mobile Robot for Warehouse Application

    Directory of Open Access Journals (Sweden)

    Mehmet S. Guzel

    2015-02-01

    Full Text Available At present, most warehouses still require human services for unloading of goods. Unloading of goods requires a continuous system to ensure the quality of work productivity. Therefore the need of autonomous robot system in warehouse is needed to improve the quality of work. Thus, a localization and recognition algorithm is developed and implemented on the E-puck robot. The task involves the recognition of desired object based on their colour (red and blue and locating the desired object to the target location (marked by green marker. In addition, the collision avoidance algorithm is also developed and integrated to allow the robot manoeuvre safely in its working environment. The colour histogram technique is used to recognize the desired object and the target location. Based on the experimental results, the developed algorithm is successfully fulfilling the pick and place requirement with success rate of approximately 70% in simulation study and 50% in real implementation.

  4. aDORe: a modular, standards-based Digital Object Repository

    CERN Document Server

    Van de Sompel, Herbert; Liu, X; Balakireva, L; Schwander, T; Sompel, Herbert Van de; Bekaert, Jeroen; Liu, Xiaoming; Balakireva, Luda; Schwander, Thorsten

    2005-01-01

    This paper describes the aDORe repository architecture, designed and implemented for ingesting, storing, and accessing a vast collection of Digital Objects at the Research Library of the Los Alamos National Laboratory. The aDORe architecture is highly modular and standards-based. In the architecture, the MPEG-21 Digital Item Declaration Language is used as the XML-based format to represent Digital Objects that can consist of multiple datastreams as Open Archival Information System Archival Information Packages (OAIS AIPs).Through an ingestion process, these OAIS AIPs are stored in a multitude of autonomous repositories. A Repository Index keeps track of the creation and location of all the autonomous repositories, whereas an Identifier Locator registers in which autonomous repository a given Digital Object or OAIS AIP resides. A front-end to the complete environment, the OAI-PMH Federator, is introduced for requesting OAIS Dissemination Information Packages (OAIS DIPs). These OAIS DIPs can be the stored OAIS ...

  5. 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.

  6. Three-dimensional shape measurement of small object based on tri-frequency heterodyne method

    Science.gov (United States)

    Liu, Shouqi; Feng, Wei; Zhang, Qican; Liu, Yuankun

    2015-08-01

    Among temporal phase unwrapping methods based on structured light projection, tri-frequency heterodyne method, with the merits of less projected fringe, high precision and high reliability, has become a practical method in objects three-dimensional (3D) shape measurement. In this paper, a 3D shape measuring system was developed with a digital micromirror device (DMD) and synchronously trigged CCD camera. The 3D shape of a measured object was reconstructed from the deformed fringe patterns based on tri-frequency heterodyne method. The practical experiments were carried on some coins, and the results show that the system can restore their 3D shape on the tested partition with an accuracy of microns. This measurement system is prominent in 3D shape measurement of small or tiny objects, sample testing, and many other application fields.

  7. 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.

  8. Costs and Advantages of Object-Based Image Coding with Shape-Adaptive Wavelet Transform

    Directory of Open Access Journals (Sweden)

    Cagnazzo Marco

    2007-01-01

    Full Text Available Object-based image coding is drawing a great attention for the many opportunities it offers to high-level applications. In terms of rate-distortion performance, however, its value is still uncertain, because the gains provided by an accurate image segmentation are balanced by the inefficiency of coding objects of arbitrary shape, with losses that depend on both the coding scheme and the object geometry. This work aims at measuring rate-distortion costs and gains for a wavelet-based shape-adaptive encoder similar to the shape-adaptive texture coder adopted in MPEG-4. The analysis of the rate-distortion curves obtained in several experiments provides insight about what performance gains and losses can be expected in various operative conditions and shows the potential of such an approach for image coding.

  9. 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.

  10. User-specific interfaces for clinical data-management systems: an object-based approach.

    OpenAIRE

    Wilton, R.

    1992-01-01

    Multiple user-specific visual interfaces are desirable in any computer-based clinical data-management system that is used by different people with different jobs to perform. The programming and maintenance problems of supporting multiple user interfaces to a single information system can be addressed by separating user-interface functionality from data-management subsystems, and by building user interfaces from object-based software components whose functionality is bound to an underlying ser...

  11. 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 ...

  12. ARTIFICIAL NEURAL NETWORK BASED DISCRIMINATION OF MINELIKE OBJECTS IN INFRARED IMAGES

    OpenAIRE

    G.Suganthi; Reeba Korah; N.Seetharaman

    2014-01-01

    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 dif...

  13. 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...

  14. Object-based analysis of hyperspectral and thermal infrared satellite imagery

    International Nuclear Information System (INIS)

    The given paper proposes an object-based procedure for the combined analysis of high-resolution optical, thermal infrared and hyperspectral satellite imagery for different nuclear safeguards-related tasks. Some case studies using Hyperion, Landsat, QuickBird and Ikonos data will demonstrate the advantages of this approach. (author)

  15. Competency-Based Training: Objective Structured Clinical Exercises (OSCE) in Marriage and Family Therapy

    Science.gov (United States)

    Miller, John K.

    2010-01-01

    The field of marriage and family therapy (MFT) has recently engaged in the process of defining core competencies for the profession. Many MFT training programs are adapting their curriculum to develop more competency-based training strategies. The Objective Structured Clinical "Examination" (OSCE) is widely used in the medical profession to assess…

  16. Dynamic Multi-objective Optimization Algorithm Based On GEP and Virus Evolution

    Directory of Open Access Journals (Sweden)

    Weihong Wang

    2012-01-01

    Full Text Available Dynamic Multi-objective Optimization (DMO is very popular nowadays. A new algorithm for DMO called Virus-GEP Dynamic based on Gene Expression Programming (GEP and virus evolution is proposed. Experiments on two test problems have shown that the algorithm has better performance on convergence, diversity and the breadth of the distribution.

  17. Learning Mathematics by Designing, Programming, and Investigating with Interactive, Dynamic Computer-Based Objects

    Science.gov (United States)

    Marshall, Neil; Buteau, Chantal

    2014-01-01

    As part of their undergraduate mathematics curriculum, students at Brock University learn to create and use computer-based tools with dynamic, visual interfaces, called Exploratory Objects, developed for the purpose of conducting pure or applied mathematical investigations. A student's Development Process Model of creating and using an Exploratory…

  18. A Distance-Based Variety of Nonlinear Multivariate Data Analysis Including Weights for Objects and Variables.

    Science.gov (United States)

    Commandeur, Jacques J. F.; Groenen, Patrick J. F.; Meulman, Jacqueline J.

    1999-01-01

    Presents two methods for including weights in distance-based nonlinear multivariate data analysis. One method assigns weights to the objects, while the other is concerned with differential weighing of groups of variables. Discusses applications of these weighting schemes and proposed an algorithm to minimize the corresponding loss function. (SLD)

  19. 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.

  20. Mapping Urban Tree Species Using Very High Resolution Satellite Imagery: Comparing Pixel-Based and Object-Based Approaches

    Directory of Open Access Journals (Sweden)

    Harini Nagendra

    2013-03-01

    Full Text Available We assessed the potential of multi-spectral GeoEye imagery for biodiversity assessment in an urban context in Bangalore, India. Twenty one grids of 150 by 150 m were randomly located in the city center and all tree species within these grids mapped in the field. The six most common species, collectively representing 43% of the total trees sampled, were selected for mapping using pixel-based and object-based approaches. All pairs of species were separable based on spectral reflectance values in at least one band, with Peltophorum pterocarpum being most distinct from other species. Object-based approaches were consistently superior to pixel-based methods, which were particularly low in accuracy for tree species with small canopy sizes, such as Cocos nucifera and Roystonea regia. There was a strong and significant correlation between the number of trees determined on the ground and from object-based classification. Overall, object-based approaches appear capable of discriminating the six most common species in a challenging urban environment, with substantial heterogeneity of tree canopy sizes.

  1. 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.

  2. 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.

  3. Autonomic Management of Object Replication for FT-CORBA Based Intelligent Transportation Systems

    Science.gov (United States)

    Suh, Woonsuk; Lee, Eunseok

    Intelligent Transportation Systems (ITS) comprises the electronics, communications or information processing used singly or integrated to improve the efficiency or safety of surface transportation. Accordingly, the ITS has to perform collection, management, and provision of real time transport information reliably. It can be deployed based on the Common Object Request Broker Architecture (CORBA) of the Object Management Group (OMG) because it consists of many interconnected heterogeneous systems deployed by independent organizations. Fault Tolerant CORBA (FT-CORBA) supports real time requirement of transport information stably through redundancy by replication of server objects. However, object replication, management, and related protocols of FT-CORBA require extra system resources of CPU and memory, and can degrade the system performance both locally and as a whole. This paper proposes an architecture to enhance performance of FT-CORBA based ITS in terms of CPU and memory by managing object replication adaptively during system operation with an agent. The application of the agent is expected to support fault tolerance of real ITS efficiently.

  4. High-quality slab-based intermixing method for fusion rendering of multiple medical objects.

    Science.gov (United States)

    Kim, Dong-Joon; Kim, Bohyoung; Lee, Jeongjin; Shin, Juneseuk; Kim, Kyoung Won; Shin, Yeong-Gil

    2016-01-01

    The visualization of multiple 3D objects has been increasingly required for recent applications in medical fields. Due to the heterogeneity in data representation or data configuration, it is difficult to efficiently render multiple medical objects in high quality. In this paper, we present a novel intermixing scheme for fusion rendering of multiple medical objects while preserving the real-time performance. First, we present an in-slab visibility interpolation method for the representation of subdivided slabs. Second, we introduce virtual zSlab, which extends an infinitely thin boundary (such as polygonal objects) into a slab with a finite thickness. Finally, based on virtual zSlab and in-slab visibility interpolation, we propose a slab-based visibility intermixing method with the newly proposed rendering pipeline. Experimental results demonstrate that the proposed method delivers more effective multiple-object renderings in terms of rendering quality, compared to conventional approaches. And proposed intermixing scheme provides high-quality intermixing results for the visualization of intersecting and overlapping surfaces by resolving aliasing and z-fighting problems. Moreover, two case studies are presented that apply the proposed method to the real clinical applications. These case studies manifest that the proposed method has the outstanding advantages of the rendering independency and reusability. PMID:26403436

  5. Comprehensive Analysis with KVM Techniques and Implementation of Object Pool Based on J2ME RMS

    Directory of Open Access Journals (Sweden)

    Nandika Sood

    2011-11-01

    Full Text Available J2ME services play an important role in the field of Communication industry. In this paper, we discuss and analyze the consumptive behaviour based on object pool with RMS capabilities. We discuss and analyze different aspects of RMS mining techniques and their behaviour in mobile devices. We also analyze the better method or rule of implementing services which is more suitable for mobile devices. The method this paper mentioned has benefit to analyze large numbers of data in consumptive behaviours and provides some instructions to improve better marketing in concerned fields. In this paper we use J2ME components like CLDC (Connected Limited Device Configuration and MIDP (Mobile Information Device Profile with data mining services (DMS that provide local storage, a user interface, and networking capabilities that runs on mobile computing devices. We also discuss the need of Object Pool in mobile devices to enhance the capability of mobile devices. Object pool model based on RMS is proposed. Aimed to solve the Memory peak problem in J2ME, on the basis of object pool design pattern, an object pool model used RMS is designed and implemented.

  6. Comprehensive Analysis with KVM Techniques and Implementation Of Object Pool Based On J2ME RMS

    Directory of Open Access Journals (Sweden)

    Ms. Nandika Sood

    2011-09-01

    Full Text Available J2ME services play an important role in the field of Communication industry. In this paper, we discuss and analyze the consumptive behaviour based on object pool with RMS capabilities. We discuss and analyze different aspects of RMS mining techniques and their behaviour in mobile devices. We also analyze the better method or rule of implementing services which is more suitable for mobile devices. The method this paper mentioned has benefit to analyze large numbers of data in consumptive behaviours and provides some instructions to improve better marketing in concerned fields. In this paper we use J2ME components like CLDC (Connected Limited Device Configuration and MIDP (Mobile Information Device Profile with data mining services (DMS that provide local storage, a user interface, and networking capabilities that runs on mobile computing devices. We also discuss the need of Object Pool in mobile devices to enhance the capability of mobile devices. Object pool model based on RMS is proposed. Aimed to solve the Memory peak problem in J2ME, on the basis of object pool design pattern, an object pool model used RMS is designed and implemented.

  7. 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.

  8. IR-videostream rendering based on high-level object information

    Science.gov (United States)

    Becker, Stefan; Hübner, Wolfgang; Arens, Michael

    2012-10-01

    IR-sensors are mainly utilized in video surveillance systems in order to provide vision during nighttime and in diffuse lighting conditions. The dynamic range of IR-sensors usually exceeds that of conventional display devices. Hence, range compression associated with loss of information is always required. Range compression methods can be divided into global methods, which are based on the intensity distribution, and local methods focused on smaller regions of interest. In contrast to local methods, global methods are computationally efficient. Nevertheless, global methods have the drawback that fine details can be suppressed by intensity changes at image locations which are unrelated to the object of interest. In order to overcome these restrictions, we propose a method to render IR images based on high level object information. The overall processing pipeline consists of a contrast enhancement method, followed by object detection, and a range compression method that takes the location of objects into account. Here we use pedestrians as an exemplary object category. The output of the detector is a rectangular bounding box, centered at the person location. Restricting range compression to a person location, allows to display details on the person surface that most probably would remain undetected using global range compression methods. The proposed combination of rendering with high level information is intended to be integrated in a surveillance system to assist human operators. Towards this end, this paper provides some insights into the design of visualization tools.

  9. MCMC-Particle-based group tracking of space objects within Bayesian framework

    Science.gov (United States)

    Huang, Jian; Hu, Weidong

    2014-01-01

    With the intense increase in space objects, especially space debris, it is necessary to efficiently track and catalog the extensive dense clusters of space objects. As the main instrument for low earth orbit (LEO) space surveillance, ground-based radar system is usually limited by its resolution while tracking small space debris with high density. Thus, the obtained measurement information could have been seriously missed, which makes the traditional tracking method inefficient. To address this issue, we conceived the concept of group tracking. For group tracking, the overall tendency of the group objects is expected to be revealed, and the trajectories of individual objects are simultaneously reconstructed explicitly. According to model the interaction between the group center and individual trajectories using the Markov random field (MRF) within Bayesian framework, the objects' number and individual trajectory can be estimated more accurately in the condition of high miss alarm probability. The Markov chain Monte Carlo (MCMC)-Particle algorithm was utilized for solving the Bayesian integral problem. Furthermore, we introduced the mechanism for describing the behaviors of groups merging and splitting, which can expand the single group tracking algorithm to track variable multiple groups. Finally, simulation of the group tracking of space objects was carried out to validate the efficiency of the proposed method.

  10. Generalization Improvement of Radial Basis Function Network Based on Multi-Objective Particle Swarm Optimization

    Directory of Open Access Journals (Sweden)

    S.N. Qasem

    2010-01-01

    Full Text Available The problem of unsupervised and supervised learning of RBF networks is discussed with Multi-Objective Particle Swarm Optimization (MOPSO. This study presents an evolutionary multi-objective selection method of RBF networks structure. The candidates of RBF networks structures are encoded into particles in PSO. These particles evolve toward Pareto-optimal front defined by several objective functions with model accuracy and complexity. This study suggests an approach of RBF network training through simultaneous optimization of architectures and connections with PSO-based multi-objective algorithm. Present goal is to determine whether MOPSO can train RBF networks and the performance is validated on accuracy and complexity. The experiments are conducted on two benchmark datasets obtained from the machine learning repository. The results show that; the best results are obtained for our proposed method that has obtained 100 and 80.21% classification accuracy from the experiments made on the data taken from breast cancer and diabetes diseases database, respectively. The results also show that our approach provides an effective means to solve multi-objective RBF networks and outperforms multi-objective genetic algorithm.

  11. 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.

  12. 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

  13. 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

  14. 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 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.

  15. Artificial Bee Colony Algorithm based Multi-Objective Node Placement for Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    R K Jena

    2014-05-01

    Full Text Available The recent popularity of applications based on wireless sensor networks (WSN provides a strong motivation for pursuing research in different dimensions of WSN. Node placement is an essential task in wireless sensor network and is a multi-objective combinatorial problem in nature. The positions of sensor nodes are very important and must be able to provide maximum coverage with longer lifetimes. So, for efficient node placement, a novel multi-objective Artificial Bee Colony (ABC algorithm based framework is proposed in this paper. The framework optimizes the operational modes of the sensor nodes along with clustering schemes and transmission signal strengths. The results show that the proposed algorithm outperformed the contemporary methodology based on TPSMA, PSO and ACO.

  16. Smart learning objects for smart education in computer science theory, methodology and robot-based implementation

    CERN Document Server

    Stuikys, Vytautas

    2015-01-01

    This monograph presents the challenges, vision and context to design smart learning objects (SLOs) through Computer Science (CS) education modelling and feature model transformations. It presents the latest research on the meta-programming-based generative learning objects (the latter with advanced features are treated as SLOs) and the use of educational robots in teaching CS topics. The introduced methodology includes the overall processes to develop SLO and smart educational environment (SEE) and integrates both into the real education setting to provide teaching in CS using constructivist a

  17. 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.

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

    Directory of Open Access Journals (Sweden)

    Da Rugna Jérôme

    2008-01-01

    Full Text Available Abstract 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.

  19. Real-Time Traffic Flow Statistical Analysis Based on Network-Constrained Moving Object Trajectories

    Science.gov (United States)

    Ding, Zhiming; Huang, Guangyan

    In this paper, we propose a novel traffic flow analysis method, Network-constrained Moving Objects Database based Traffic Flow Statistical Analysis (NMOD-TFSA) model. By sampling and analyzing the spatial-temporal trajectories of network constrained moving objects, NMOD-TFSA can get the real-time traffic conditions of the transportation network. The experimental results show that, compared with the floating-car methods which are widely used in current traffic flow analyzing systems, NMOD-TFSA provides an improved performance in terms of communication costs and statistical accuracy.

  20. Empirical analysis of web-based user-object bipartite networks

    OpenAIRE

    Shang, Ming-Sheng; Lü, Linyuan; Zhang, Yi-Cheng; Zhou, Tao

    2009-01-01

    Understanding the structure and evolution of web-based user-object networks is a significant task since they play a crucial role in e-commerce nowadays. This letter reports the empirical analysis on two large-scale web sites, audioscrobbler.com (http://audioscrobbler.com/) and del.icio.us (http://del.icio.us/), where users are connected with music groups and bookmarks, respectively. The degree distributions and degree-degree correlations for both users and objects are reported. We propose a n...

  1. On Decomposing Object Appearance using PCA and Wavelet bases with Applications to Image Segmentation

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille; Forchhammer, SØren

    2002-01-01

    Generative models capable of synthesising complete object images have over the past few years proven their worth when interpreting images. Due to the recent development of computational machinery it has become feasible to model the variation of image intensities and landmark positions over the complete object surface using principal component analysis. This typically involves matrices with a few thousands and up to 100.000+ rows. This paper demonstrates applications of such models applied on colour images of human faces and cardiac magnetic resonance images. Further, we devise methods for alleviating the obvious computational and storage requirements of these large models by means of truncated wavelet bases.

  2. Interactive 2D and 3D object definition in medical images based on multiresolution image descriptions

    International Nuclear Information System (INIS)

    The authors present means of interactive definition of anatomic objects in medical images via a description of the image in terms of visually sensible regions. The description is produced by computing structures capturing image geometry and following them through the image simplification of Gaussian blurring. In particular, the authors suggest that the structure made from intensity ''ridge'' and ''course'' curves defined by the locus of intensity level curve vertices, augmented by the pile of internal and external symmetric axes of these level curves, satisfies desirable criteria for a structure on which to base such object definition

  3. Radar and Optical Data Fusion for Object Based Urban Land Cover Mapping

    OpenAIRE

    Jacob, Alexander

    2011-01-01

    The creation and classification of segments for object based urban land cover mapping is the key goal of this master thesis. An algorithm based on region growing and merging was developed, implemented and tested. The synergy effects of a fused data set of SAR and optical imagery were evaluated based on the classification results. The testing was mainly performed with data of the city of Beijing China. The dataset consists of SAR and optical data and the classified land cover/use maps were eva...

  4. 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

  5. Model-based system engineering in support of the eGY data lifecycle objectives

    Science.gov (United States)

    Hartman, Leo; Melanson, Philip; Piggott, Stephen

    The objectives of the Electronic Geophysical Year (eGY) address the challenges and opportunities associated with modern digital technology for the creation and delivery of earth science data. In particular, eGY focuses on issues of access, sharing, archiving and interoperability of this science data and their associated enabling tools. System engineering supported by modelbased tools and techniques has a pivotal role to play in this endeavor since for most space missions the first formal representation of eGY related data results from system engineering activities and the extent to which these activities and the resulting representations (or models) make data life cycle issues prominent is the extent to which eGY objectives are satisfied or supported by the particular missions. The paper will review ongoing system engineering standardization efforts addressing the data life cycle and in particular will review how relatively new model-based system engineering methodologies contribute to eGY objectives.

  6. Man-made Object Detection Based on Texture Clustering and Geometric Structure Feature Extracting

    Directory of Open Access Journals (Sweden)

    Fei Cai

    2011-03-01

    Full Text Available Automatic aerial image interpretation is one of new rising high-tech application fields, and it’s proverbially applied in the military domain. Based on human visual attention mechanism and texture visual perception, this paper proposes a new approach for man-made object detection and marking by extracting texture and geometry structure features. After clustering the texture feature to realize effective image segmentation, geometry structure feature is obtained to achieve final detection and marking. Thus a man-made object detection methodology is designed, by which typical man-made objects in complex natural background, including airplanes, tanks and vehicles can be detected. The experiments sustain that the proposed method is effective and rational.

  7. An object boundary detection system based on a 3D stereo monitor

    Science.gov (United States)

    Zhang, Shuqun; Furia, Bryan

    2014-09-01

    In this paper we present an object boundary detection system using an off-the-shelf available 3D stereo monitor. Instead of implementing algorithms, the system's image processing is based on utilizing the polarization feature of liquid-crystal display and the way the image is displayed on the 3D monitor to enhance object boundary. The users can view the enhanced object contour through a polarization glasses in real-time, which can be also recorded using a camera for further processing. A software is developed for user interaction and providing feedback to obtain the best detection results. The effectiveness of the proposed system is demonstrated using some medical and biological images. The proposed system has the advantages of real-time high speed processing, almost no numerical computation, and robustness to noise over the traditional methods using image processing algorithms.

  8. 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.

  9. An Index Structure for Fast Query Retrieval in Object Oriented Data Bases Using Signature Weight Declustering

    Directory of Open Access Journals (Sweden)

    I. Elizabeth Shanthi

    2009-01-01

    Full Text Available An important question in information retrieval is how to create a database index which can be searched efficiently for the data one seeks. One such technique called signature file based access method is preferred for its easy handling of insertion and update operations. Most of the proposed methods use either efficient search method or tree based intermediate data structure to filter data objects matching the query. Use of search techniques retrieves the objects by sequentially comparing the positions of 1s in it. Such methods take longer retrieval time. On the other hand tree based structures traverse multiple paths making comparison process tedious. This study describes a new indexing technique for object-oriented data bases using the dynamic balancing of B+ tree called SD (Signature Declustering tree. The SD-tree represents all 1s in signatures in a compact manner that results in saving of insertion and searching time. Analytical experiments have been conducted by varying the signature length and the distribution of signature weight. The study clearly indicates the advantage of fast retrieval time in a way quite different from the other methods suggested in the past.

  10. 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

  11. A NEW FRAMEWORK FOR OBJECT-BASED IMAGE ANALYSIS BASED ON SEGMENTATION SCALE SPACE AND RANDOM FOREST CLASSIFIER

    Directory of Open Access Journals (Sweden)

    A. Hadavand

    2015-12-01

    Full Text Available In this paper a new object-based framework is developed for automate scale selection in image segmentation. The quality of image objects have an important impact on further analyses. Due to the strong dependency of segmentation results to the scale parameter, choosing the best value for this parameter, for each class, becomes a main challenge in object-based image analysis. We propose a new framework which employs pixel-based land cover map to estimate the initial scale dedicated to each class. These scales are used to build segmentation scale space (SSS, a hierarchy of image objects. Optimization of SSS, respect to NDVI and DSM values in each super object is used to get the best scale in local regions of image scene. Optimized SSS segmentations are finally classified to produce the final land cover map. Very high resolution aerial image and digital surface model provided by ISPRS 2D semantic labelling dataset is used in our experiments. The result of our proposed method is comparable to those of ESP tool, a well-known method to estimate the scale of segmentation, and marginally improved the overall accuracy of classification from 79% to 80%.

  12. 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.

  13. An Adaptive Motion Model and Multi-feature Cues Based on Particle Filter for Object Tracking

    Directory of Open Access Journals (Sweden)

    Ming Li

    2012-10-01

    Full Text Available If there is an occlusion, the target state model would not match motion model anymore and measurement model also would get worse. To solve these problems, an improved particle filtering algorithm based on adaptive motion model and multiple-cue fusion is presented. Under the theory framework of particle filters, the weighted color histogram and LBP texture feature entropy are used to describe features. And the algorithm adjusts features distribution coefficient  automatically by calculating the Bhattacharyya distance between the object reference distribution and object sample distribution, thus the color and texture features can intelligently be fused to develop the observation model. The simple second order auto regressive model is chosen as the state transition model, and the system noise variance is adaptively determined by the minimum noise variance of every feature in object tracking. For the occlusion problem, the system maximum noise variance can be selected, along with particle random motion intensified and disseminating coverage amplified. The posterior distribution of the object is approximated by a set of weighted samples, while object tracking is implemented by the Bayesian propagation of the sample set. The analyses and experiments show that the performance of the proposed method is more effective and robust to target maneuver and occlusion and has good performances under complex background.

  14. Identification of the lateral position of a virtual object based on echoes by humans.

    Science.gov (United States)

    Rowan, Daniel; Papadopoulos, Timos; Edwards, David; Holmes, Hannah; Hollingdale, Anna; Evans, Leah; Allen, Robert

    2013-06-01

    Echolocation offers a promising approach to improve the quality of life of people with blindness although little is known about the factors influencing object localisation using a 'searching' strategy. In this paper, we describe a series of experiments using sighted and blind human listeners and a 'virtual auditory space' technique to investigate the effects of the distance and orientation of a reflective object and the effect of stimulus bandwidth on ability to identify the right-versus-left position of the object, with bands of noise and durations from 10-400 ms. We found that performance reduced with increasing object distance. This was more rapid for object orientations where mirror-like reflection paths do not exist to both ears (i.e., most possible orientations); performance with these orientations was indistinguishable from chance at 1.8 m for even the best performing listeners in other conditions. Above-chance performance extended to larger distances when the echo was artificially presented in isolation, as might be achieved in practice by an assistive device. We also found that performance was primarily based on information above 2 kHz. Further research should extend these investigations to include other factors that are relevant to real-life echolocation. PMID:23538130

  15. Object-based Encoding in Visual Working Memory: Evidence from Memory-driven Attentional Capture.

    Science.gov (United States)

    Gao, Zaifeng; Yu, Shixian; Zhu, Chengfeng; Shui, Rende; Weng, Xuchu; Li, Peng; Shen, Mowei

    2016-01-01

    Visual working memory (VWM) adopts a specific manner of object-based encoding (OBE) to extract perceptual information: Whenever one feature-dimension is selected for entry into VWM, the others are also extracted. Currently most studies revealing OBE probed an 'irrelevant-change distracting effect', where changes of irrelevant-features dramatically affected the performance of the target feature. However, the existence of irrelevant-feature change may affect participants' processing manner, leading to a false-positive result. The current study conducted a strict examination of OBE in VWM, by probing whether irrelevant-features guided the deployment of attention in visual search. The participants memorized an object's colour yet ignored shape and concurrently performed a visual-search task. They searched for a target line among distractor lines, each embedded within a different object. One object in the search display could match the shape, colour, or both dimensions of the memory item, but this object never contained the target line. Relative to a neutral baseline, where there was no match between the memory and search displays, search time was significantly prolonged in all match conditions, regardless of whether the memory item was displayed for 100 or 1000 ms. These results suggest that task-irrelevant shape was extracted into VWM, supporting OBE in VWM. PMID:26956084

  16. 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.)

  17. 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.

  18. 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

  19. Bi-objective optimization for multi-modal transportation routing planning problem based on Pareto optimality

    Directory of Open Access Journals (Sweden)

    Yan Sun

    2015-09-01

    Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.

  20. Strategic flight assignment approach based on multi-objective parallel evolution algorithm with dynamic migration interval

    Directory of Open Access Journals (Sweden)

    Zhang Xuejun

    2015-04-01

    Full Text Available The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by reasonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimization problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm (MPEA framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is proposed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution (CC algorithm combined with non-dominated sorting genetic algorithm II (NSGA-II is introduced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multi-objective genetic algorithm (MOGA, multi-objective evolutionary algorithm based on decomposition (MOEA/D, CC-based multi-objective algorithm (CCMA as well as other two MPEAs with different migration interval strategies.

  1. Evaluation of ALOS PALSAR Imagery for Burned Area Mapping in Greece Using Object-Based Classification

    Directory of Open Access Journals (Sweden)

    Anastasia Polychronaki

    2013-11-01

    Full Text Available In this work, the potential of Advanced Land Observing Satellite (ALOS Phased Array type L-band Synthetic Aperture Radar (PALSAR imagery to map burned areas was evaluated in two study areas in Greece. For this purpose, we developed an object-based classification scheme to map the fire-disturbed areas using the PALSAR imagery acquired before and shortly after fire events. The advantage of employing an object-based approach was not only the use of the temporal variation of the backscatter coefficient, but also the incorporation in the classification of topological features, such as neighbor objects, and class related features, such as objects classified as burned. The classification scheme resulted in mapping the burned areas with satisfactory results: 0.71 and 0.82 probabilities of detection for the two study areas. Our investigation revealed that the pre-fire vegetation conditions and fire severity should be taken in consideration when mapping burned areas using PALSAR in Mediterranean regions. Overall, findings suggest that the developed scheme could be applied for rapid burned area assessment, especially to areas where cloud cover and fire smoke inhibit accurate mapping of burned areas when optical data are used.

  2. Personalised Learning Object System Based on Self-Regulated Learning Theories

    Directory of Open Access Journals (Sweden)

    Ali Alharbi

    2014-06-01

    Full Text Available Self-regulated learning has become an important construct in education research in the last few years. Selfregulated learning in its simple form is the learner’s ability to monitor and control the learning process. There is increasing research in the literature on how to support students become more self-regulated learners. However, the advancement in the information technology has led to paradigm changes in the design and development of educational content. The concept of learning object instructional technology has emerged as a result of this shift in educational technology paradigms. This paper presents the results of a study that investigated the potential educational effectiveness of a pedagogical framework based on the self-regulated learning theories to support the design of learning object systems to help computer science students. A prototype learning object system was developed based on the contemporary research on self-regulated learning. The system was educationally evaluated in a quasi-experimental study over two semesters in a core programming languages concepts course. The evaluation revealed that a learning object system that takes into consideration contemporary research on self-regulated learning can be an effective learning environment to support computer science education.

  3. 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

  4. 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 technical frameworks 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 levels linked 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 Language contracts 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.

  5. 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...

  6. A 3-Step Algorithm Using Region-Based Active Contours for Video Objects Detection

    Directory of Open Access Journals (Sweden)

    Stéphanie Jehan-Besson

    2002-06-01

    Full Text Available We propose a 3-step algorithm for the automatic detection of moving objects in video sequences using region-based active contours. First, we introduce a very full general framework for region-based active contours with a new Eulerian method to compute the evolution equation of the active contour from a criterion including both region-based and boundary-based terms. This framework can be easily adapted to various applications, thanks to the introduction of functions named descriptors of the different regions. With this new Eulerian method based on shape optimization principles, we can easily take into account the case of descriptors depending upon features globally attached to the regions. Second, we propose a 3-step algorithm for detection of moving objects, with a static or a mobile camera, using region-based active contours. The basic idea is to hierarchically associate temporal and spatial information. The active contour evolves with successively three sets of descriptors: a temporal one, and then two spatial ones. The third spatial descriptor takes advantage of the segmentation of the image in intensity homogeneous regions. User interaction is reduced to the choice of a few parameters at the beginning of the process. Some experimental results are supplied.

  7. Empirical analysis of web-based user-object bipartite networks

    Science.gov (United States)

    Shang, Ming-Sheng; Lü, Linyuan; Zhang, Yi-Cheng; Zhou, Tao

    2010-05-01

    Understanding the structure and evolution of web-based user-object networks is a significant task since they play a crucial role in e-commerce nowadays. This letter reports the empirical analysis on two large-scale web sites, audioscrobbler.com and del.icio.us, where users are connected with music groups and bookmarks, respectively. The degree distributions and degree-degree correlations for both users and objects are reported. We propose a new index, named collaborative similarity, to quantify the diversity of tastes based on the collaborative selection. Accordingly, the correlation between degree and selection diversity is investigated. We report some novel phenomena well characterizing the selection mechanism of web users and outline the relevance of these phenomena to the information recommendation problem.

  8. A 3D City Model with Dynamic Behaviour Based on Geospatial Managed Objects

    DEFF Research Database (Denmark)

    Kjems, Erik; Kolá?, Jan

    . 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......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...

  9. Empirical analysis of web-based user-object bipartite networks

    CERN Document Server

    Shang, Mingsheng; Zhang, Yi-Cheng; Zhou, Tao

    2009-01-01

    Understanding the structure and evolution of web-based user-object networks is a significant task since they play a crucial role in e-commerce nowadays. This Letter reports the empirical analysis on two large-scale web sites, audioscrobbler.com and del.icio.us, where users are connected with music groups and bookmarks, respectively. The degree distributions and degree-degree correlations for both users and objects are reported. We propose a new index, named collaborative clustering coefficient, to quantify the clustering behavior based on the collaborative selection. Accordingly, the clustering properties and clustering-degree correlations are investigated. We report some novel phenomena well characterizing the selection mechanism of web users and outline the relevance of these phenomena to the information recommendation problem.

  10. Retrospective cues based on object features improve visual working memory performance in older adults.

    Science.gov (United States)

    Gilchrist, Amanda L; Duarte, Audrey; Verhaeghen, Paul

    2016-03-01

    Research with younger adults has shown that retrospective cues can be used to orient top-down attention toward relevant items in working memory. We examined whether older adults could take advantage of these cues to improve memory performance. Younger and older adults were presented with visual arrays of five colored shapes; during maintenance, participants were presented either with an informative cue based on an object feature (here, object shape or color) that would be probed, or with an uninformative, neutral cue. Although older adults were less accurate overall, both age groups benefited from the presentation of an informative, feature-based cue relative to a neutral cue. Surprisingly, we also observed differences in the effectiveness of shape versus color cues and their effects upon post-cue memory load. These results suggest that older adults can use top-down attention to remove irrelevant items from visual working memory, provided that task-relevant features function as cues. PMID:26208404

  11. Real-Time Object Recognition Based on Cortical Multi-scale Keypoints

    OpenAIRE

    Tersic, K.; Rodrigues, J. M. F.; du Buf, J. M. H.

    2013-01-01

    In recent years, a large number of impressive object categorisation algorithms have surfaced, both computational and biologically motivated. While results on standardised benchmarks are impressive, very few of the best-performing algorithms took run-time performance into account, rendering most of them useless for real-time active vision scenarios such as cognitive robots. In this paper, we combine cortical keypoints based on primate area V1 with a state-of-the-art nearest neighbour classifie...

  12. A Tool for Creating Exams Automatically from an Object-Oriented Knowledge Base Question Bank

    OpenAIRE

    Khaled N. Elsayed

    2013-01-01

    The way of creating exams can enhance education. Also, the exam should cover majority of course material and should include various levels of difficulties. This paper presents a tool designed for automatically creating exams by selecting questions from a bank of questions for several courses. This bank of question is designed as an object-oriented knowledge base. Its questions should emphasize on the structuring categories of all course domains. An intelligent agent will help in selecting que...

  13. Validating an objective video-based dyskinesia severity score in Parkinson’s disease patients

    OpenAIRE

    Rao, Anusha Sathyanarayanan; Dawant, Benoit M; Bodenheimer, Robert E.; Li, Rui; Fang, John; Phibbs, Fenna; Hedera, Peter; Davis, Thomas

    2012-01-01

    Dyskinesia is a common side effect of prolonged dopaminergic therapy in Parkinson’s disease patients. Assessing the severity of dyskinesia can help develop better pharmacological and surgical interventions. We have developed a semi-automatic video-based objective dyskinesia quantifying measure called the severity score (SVS) that was evaluated on 35 patient videos. We present a study to evaluate the utility of our severity score and compare its performance to clinical ratings of neurologists....

  14. Parallel Code Generation in MathModelica / An Object Oriented Component Based Simulation Environment

    OpenAIRE

    Aronsson, Peter; Fritzson, Peter

    2001-01-01

    Modelica is an a-causal, equation based, object oriented modeling lan- guage for modeling and efficient simulation of large and complex multi domain systems. The Modelica language, with its strong software component model, makes it possible to use visual component programming, where large complex physical systems can be modeled and composed in a graphical way. One tool with support for both graphical modeling, textual programming and simulation is MathModelica. To deal with growing complexity...

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

    DEFF Research Database (Denmark)

    Civilis, A.; Jensen, Christian Søndergaard; Pakalnis, Stardas

    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 m...

  16. Integrated Model-Driven Development Environments for Equation-Based Object-Oriented Languages

    OpenAIRE

    Pop, Adrian

    2008-01-01

    Integrated development environments are essential for efficient realization of complex industrial products, typically consisting of both software and hardware components. Powerful equation-based object-oriented (EOO) languages such as Modelica are successfully used for modeling and virtual prototyping increasingly complex physical systems and components, whereas software modeling approaches like UML, especially in the form of domain specific language subsets, are increasingly used for softwar...

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

    OpenAIRE

    Martin Sjölund; Peter Fritzson; Adrian Pop

    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...

  18. An Anthropo-based Standpoint on Mediating Objects: Evolution and Extension of Industrial Design Practices.

    OpenAIRE

    Elsen, Catherine; Darses, Françoise; Leclercq, Pierre

    2010-01-01

    This paper questions the new uses of design tools and representations in the industrial field. A two months in situ observation of real industrial practices shows (i) how strongly CAD (Computer-Aided Design) tools are integrated in work practices, in preliminary design phases as well, and (ii) how design actors sometimes deviate this tool from its initial objectives to use it in complement of sketches’ contributions. A multi-layered study built on an anthropo-based approach hel...

  19. Comprehensive Analysis with KVM Techniques and Implementation Of Object Pool Based On J2ME RMS

    OpenAIRE

    Ms. Nandika Sood; Mr. Amit Sinhal

    2011-01-01

    J2ME services play an important role in the field of Communication industry. In this paper, we discuss and analyze the consumptive behaviour based on object pool with RMS capabilities. We discuss and analyze different aspects of RMS mining techniques and their behaviour in mobile devices. We also analyze the better method or rule of implementing services which is more suitable for mobile devices. The method this paper mentioned has benefit to analyze large numbers of data in consumptive behav...

  20. Fourier-transform Ghost Imaging for pure phase object based on Compressive Sampling algorithm

    OpenAIRE

    Wang, Hui; Han, Shensheng

    2009-01-01

    A special algorithm for the Fourier-transform Ghost Imaging (GI) scheme is discussed based on the Compressive Sampling (CS) theory. Though developed mostly in real space, CS algorithm could also be used for the Fourier spectrum reconstruction of pure phase object by setting a proper sensing matrix. This could find its application in diffraction imaging of X-ray, neutron and electron with higher efficiency and resolution. Simulation and experiment results are also presented t...

  1. 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 ...

  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 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. Image Processing Strategies Based on a Visual Saliency Model for Object Recognition Under Simulated Prosthetic Vision.

    Science.gov (United States)

    Wang, Jing; Li, Heng; Fu, Weizhen; Chen, Yao; Li, Liming; Lyu, Qing; Han, Tingting; Chai, Xinyu

    2016-01-01

    Retinal prostheses have the potential to restore partial vision. Object recognition in scenes of daily life is one of the essential tasks for implant wearers. Still limited by the low-resolution visual percepts provided by retinal prostheses, it is important to investigate and apply image processing methods to convey more useful visual information to the wearers. We proposed two image processing strategies based on Itti's visual saliency map, region of interest (ROI) extraction, and image segmentation. Itti's saliency model generated a saliency map from the original image, in which salient regions were grouped into ROI by the fuzzy c-means clustering. Then Grabcut generated a proto-object from the ROI labeled image which was recombined with background and enhanced in two ways-8-4 separated pixelization (8-4 SP) and background edge extraction (BEE). Results showed that both 8-4 SP and BEE had significantly higher recognition accuracy in comparison with direct pixelization (DP). Each saliency-based image processing strategy was subject to the performance of image segmentation. Under good and perfect segmentation conditions, BEE and 8-4 SP obtained noticeably higher recognition accuracy than DP, and under bad segmentation condition, only BEE boosted the performance. The application of saliency-based image processing strategies was verified to be beneficial to object recognition in daily scenes under simulated prosthetic vision. They are hoped to help the development of the image processing module for future retinal prostheses, and thus provide more benefit for the patients. PMID:25981202

  4. Moment feature based fast feature extraction algorithm for moving object detection using aerial images.

    Science.gov (United States)

    Saif, A F M Saifuddin; Prabuwono, Anton Satria; Mahayuddin, Zainal Rasyid

    2015-01-01

    Fast and computationally less complex feature extraction for moving object detection using aerial images from unmanned aerial vehicles (UAVs) remains as an elusive goal in the field of computer vision research. The types of features used in current studies concerning moving object detection are typically chosen based on improving detection rate rather than on providing fast and computationally less complex feature extraction methods. Because moving object detection using aerial images from UAVs involves motion as seen from a certain altitude, effective and fast feature extraction is a vital issue for optimum detection performance. This research proposes a two-layer bucket approach based on a new feature extraction algorithm referred to as the moment-based feature extraction algorithm (MFEA). Because a moment represents the coherent intensity of pixels and motion estimation is a motion pixel intensity measurement, this research used this relation to develop the proposed algorithm. The experimental results reveal the successful performance of the proposed MFEA algorithm and the proposed methodology. PMID:26030818

  5. An advanced object-based software framework for complex ecosystem modeling and simulation

    Energy Technology Data Exchange (ETDEWEB)

    Sydelko, P. J.; Dolph, J. E.; Majerus, K. A.; Taxon, T. N.

    2000-06-29

    Military land managers and decision makers face an ever increasing challenge to balance maximum flexibility for the mission with a diverse set of multiple land use, social, political, and economic goals. In addition, these goals encompass environmental requirements for maintaining ecosystem health and sustainability over the long term. Spatiotemporal modeling and simulation in support of adaptive ecosystem management can be best accomplished through a dynamic, integrated, and flexible approach that incorporates scientific and technological components into a comprehensive ecosystem modeling framework. The Integrated Dynamic Landscape Analysis and Modeling System (IDLAMS) integrates ecological models and decision support techniques through a geographic information system (GIS)-based backbone. Recently, an object-oriented (OO) architectural framework was developed for IDLAMS (OO-IDLAMS). This OO-IDLAMS Prototype was built upon and leverages from the Dynamic Information Architecture System (DIAS) developed by Argonne National Laboratory. DIAS is an object-based architectural framework that affords a more integrated, dynamic, and flexible approach to comprehensive ecosystem modeling than was possible with the GIS-based integration approach of the original IDLAMS. The flexibility, dynamics, and interoperability demonstrated through this case study of an object-oriented approach have the potential to provide key technology solutions for many of the military's multiple-use goals and needs for integrated natural resource planning and ecosystem management.

  6. 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.

  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. 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)

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

    Directory of Open Access Journals (Sweden)

    Rongjun Qin

    2014-08-01

    Full Text Available 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 (Scale-Invariant Feature Transform feature points, via the general bundle adjustment framework. Thus, the Digital Surface Models (DSMs and orthophotos can be generated for raster-based change analysis. In the next step, a multi-primitive segmentation method combining the spectral and geometric information is proposed for object-based analysis. In the final step, a multi-criteria decision analysis is carried out concerning the height, spectral and geometric coherence, and shape regularity for change determination. Experiments based on UAV images with five-centimeter ground resolution demonstrate the effectiveness of the proposed method, leading to the conclusion that this method is practically applicable for frequent monitoring.

  10. Feature-based fuzzy connectedness segmentation of ultrasound images with an object completion step.

    Science.gov (United States)

    Rueda, Sylvia; Knight, Caroline L; Papageorghiou, Aris T; Alison Noble, J

    2015-12-01

    Medical ultrasound (US) image segmentation and quantification can be challenging due to signal dropouts, missing boundaries, and presence of speckle, which gives images of similar objects quite different appearance. Typically, purely intensity-based methods do not lead to a good segmentation of the structures of interest. Prior work has shown that local phase and feature asymmetry, derived from the monogenic signal, extract structural information from US images. This paper proposes a new US segmentation approach based on the fuzzy connectedness framework. The approach uses local phase and feature asymmetry to define a novel affinity function, which drives the segmentation algorithm, incorporates a shape-based object completion step, and regularises the result by mean curvature flow. To appreciate the accuracy and robustness of the methodology across clinical data of varying appearance and quality, a novel entropy-based quantitative image quality assessment of the different regions of interest is introduced. The new method is applied to 81 US images of the fetal arm acquired at multiple gestational ages, as a means to define a new automated image-based biomarker of fetal nutrition. Quantitative and qualitative evaluation shows that the segmentation method is comparable to manual delineations and robust across image qualities that are typical of clinical practice. PMID:26319973

  11. Simulation-based study of wind loads on semi-submersed object in ocean wave field

    Science.gov (United States)

    Xie, Shengbai; Yang, Di; Liu, Yi; Shen, Lian

    2016-01-01

    Wind forcing makes a vital contribution to the hydrodynamic loads on structures at sea. The flow physics is complex, involving interactions among surface water waves, turbulent wind, and semi-submersed object. We perform a simulation-based study on a canonical problem of wind past a semi-submersed rectangular prism with the focus on the wave effect, which is an essential factor in wind loads at sea but has been elusive. To tackle this problem, we develop a hybrid simulation method consisting of two parts: a precursor simulation of coupled wind and wave motions in the far field upstream to provide physical inflow condition, and a near-field simulation of the air and water motions around the object. The simulation method is validated through numerical tests and comparisons with data from the literature for different aspects of the code. This hybrid simulation method is then applied to study the effect of surface wave motions on the wind load on the object. Various wave conditions are considered, including pure wind-sea satisfying the Joint North Sea Wave Project spectrum as well as wind-sea mixed with long-wavelength ocean swells. The simulation results exhibit significant oscillations in the wind load on the object. The oscillations are found to correlate well with the incident wave motions and are particularly strong in the presence of swells. The underlying mechanism is explained through analyses on variations of wind speed with different wave phases and wave-correlated flow patterns of the wind when it impinges on the object. Our simulations also indicate that waves have an appreciable effect on the wake behind the object.

  12. 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.

  13. Mapping Urban Tree Species Using Very High Resolution Satellite Imagery: Comparing Pixel-Based and Object-Based Approaches

    OpenAIRE

    Harini Nagendra; Shivani Agarwal; Madhumitha Jaganmohan; Lionel Sujay Vailshery

    2013-01-01

    We assessed the potential of multi-spectral GeoEye imagery for biodiversity assessment in an urban context in Bangalore, India. Twenty one grids of 150 by 150 m were randomly located in the city center and all tree species within these grids mapped in the field. The six most common species, collectively representing 43% of the total trees sampled, were selected for mapping using pixel-based and object-based approaches. All pairs of species were separable based on spectral reflectance values i...

  14. An effective docking strategy for virtual screening based on multi-objective optimization algorithm

    Directory of Open Access Journals (Sweden)

    Kang Ling

    2009-02-01

    Full Text Available Abstract Background Development of a fast and accurate scoring function in virtual screening remains a hot issue in current computer-aided drug research. Different scoring functions focus on diverse aspects of ligand binding, and no single scoring can satisfy the peculiarities of each target system. Therefore, the idea of a consensus score strategy was put forward. Integrating several scoring functions, consensus score re-assesses the docked conformations using a primary scoring function. However, it is not really robust and efficient from the perspective of optimization. Furthermore, to date, the majority of available methods are still based on single objective optimization design. Results In this paper, two multi-objective optimization methods, called MOSFOM, were developed for virtual screening, which simultaneously consider both the energy score and the contact score. Results suggest that MOSFOM can effectively enhance enrichment and performance compared with a single score. For three different kinds of binding sites, MOSFOM displays an excellent ability to differentiate active compounds through energy and shape complementarity. EFMOGA performed particularly well in the top 2% of database for all three cases, whereas MOEA_Nrg and MOEA_Cnt performed better than the corresponding individual scoring functions if the appropriate type of binding site was selected. Conclusion The multi-objective optimization method was successfully applied in virtual screening with two different scoring functions that can yield reasonable binding poses and can furthermore, be ranked with the potentially compromised conformations of each compound, abandoning those conformations that can not satisfy overall objective functions.

  15. Digital Image Watermarking for Arbitrarily Shaped Objects Based On SA-DWT

    Directory of Open Access Journals (Sweden)

    F. Regragui

    2009-10-01

    Full Text Available Many image watermarking schemes have been proposed in recent years, but they usually involve embedding a watermark to the entire image without considering only a particular object in the image, which the image owner may be interested in. This paper proposes a watermarking scheme that can embed a watermark to an arbitrarily shaped object in an image. Before embedding, the image owner specifies an object of arbitrary shape that is of a concern to him. Then the object is transformed into the wavelet domain using in place lifting shape adaptive DWT(SADWT and a watermark is embedded by modifying the wavelet coefficients. 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. JPEG, JPEG2000, scaling, adding noise, filtering, etc.

  16. Digital Image Watermarking for Arbitrarily Shaped Objects Based On SA-DWT

    CERN Document Server

    Essaouabi, A; Fegragui, F

    2009-01-01

    Many image watermarking schemes have been proposed in recent years, but they usually involve embedding a watermark to the entire image without considering only a particular object in the image, which the image owner may be interested in. This paper proposes a watermarking scheme that can embed a watermark to an arbitrarily shaped object in an image. Before embedding, the image owner specifies an object of arbitrary shape that is of a concern to him. Then the object is transformed into the wavelet domain using in place lifting shape adaptive DWT(SADWT) and a watermark is embedded by modifying the wavelet coefficients. 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 loss...

  17. 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.

  18. Confidence-Level-Based New Adaptive Particle Filter for Nonlinear Object Tracking

    Directory of Open Access Journals (Sweden)

    Xiaoyong Zhang

    2012-11-01

    Full Text Available Nonlinear object tracking from noisy measurements is a basic skill and a challenging task of mobile robotics, especially under dynamic environments. The particle filter is a useful tool for nonlinear object tracking with non?Gaussian noise. Nonlinear object tracking needs the real?time processing capability of the particle filter. While the number in a traditional particle filter is fixed, that can lead to a lot of unnecessary computation. To address this issue, a confidence?level? based new adaptive particle filter (NAPF algorithm is proposed in this paper. In this algorithm the idea of confidence interval is utilized. The least number of particles for the next time instant is estimated according to the confidence level and the variance of the estimated state. Accordingly, an improved systematic re?sampling algorithm is utilized for the new improved particle filter. NAPF can effectively reduce the computation while ensuring the accuracy of nonlinear object tracking. The simulation results and the ball tracking results of the robot verify the effectiveness of the algorithm.

  19. 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

  20. 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 matching

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

    Energy Technology Data Exchange (ETDEWEB)

    Guerra, C; Pascucci, V

    2004-12-13

    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 matching.

  2. A new strategy for object-identification based on its inherent geometrical characteristic

    Science.gov (United States)

    Lin, Yuchi; Xie, Yuchan; Cui, Yanping; Huang, Yinguo

    2008-03-01

    Object-identification using edge extraction techniques from background function in uncontrolled lighting environments containing more object pose information and have many applications. In order to depressing noise, identify aim body robustly and rapidly, in this paper, We take cuboid as model and present a new strategy for edge extraction and object-identification based on object inherent features. This strategy includes the following steps. Firstly, pre-processing is applied to the raw image, in which Canny operator was used to extract edges pixels, then, image was divided into a grid of overlapping windows and noise was suppressed by regression grid windows in which the number of pixels is less than a threshold. Secondly, as model contour's geometry characters known already, the cuboids upright edges was used as their existence evidence to estimate model's existence area and so the lines failed spatial constraints are eliminated, then, object edges was extracted within the finite ranges of orientation in Hough transform space. Thirdly, the intersections of the component extracted edges are taken, the candidate edges extraction and matches was assessed based on the intersections, rather than the component extracted edges. After a series of matching tests the aim body is extracted. The proposed method makes three major contributions. Firstly, on the base of study the correspondence between model's boundary edges parameters in image space and Hough space we extract edges in finite area in Hough transform space, the aimless computations and searching is reduced greatly, its efficiency improved. Secondly, as Canny operator can extract aim lines with single pixel width, the edges extraction strategy of combining Canny operator with Hough transform extractor could avoid error impact of edges pixels numbers to Hough extractor. Thirdly, after fusion model's knowledge in image space, Hough space, global space, learning from others strong points to offset one's weakness, we extract model's edges from complex noise background without regarding to regression caused by the errors due to spurious or missing pixels because edge extraction is imperfect for real images. The results of experiments demonstrated that the proposed method could suppress noise effectively, identified and extracted target from complex backgrounds robustly. This new strategy may have potential application in visual servo, object tracking, port AGV and robots fields etc.

  3. 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

  4. 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.

  5. 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.

  6. 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.

  7. Moving Object Tracking and Avoidance Algorithm for Differential Driving AGV Based on Laser Measurement Technology

    Directory of Open Access Journals (Sweden)

    Pandu Sandi Pratama

    2012-12-01

    Full Text Available This paper proposed an algorithm to track the obstacle position and avoid the moving objects for differential driving Automatic Guided Vehicles (AGV system in industrial environment. This algorithm has several abilities such as: to detect the moving objects, to predict the velocity and direction of moving objects, to predict the collision possibility and to plan the avoidance maneuver. For sensing the local environment and positioning, the laser measurement system LMS-151 and laser navigation system NAV-200 are applied. Based on the measurement results of the sensors, the stationary and moving obstacles are detected and the collision possibility is calculated. The velocity and direction of the obstacle are predicted using Kalman filter algorithm. Collision possibility, time, and position can be calculated by comparing the AGV movement and obstacle prediction result obtained by Kalman filter. Finally the avoidance maneuver using the well known tangent Bug algorithm is decided based on the calculation data. The effectiveness of proposed algorithm is verified using simulation and experiment. Several examples of experiment conditions are presented using stationary obstacle, and moving obstacles. The simulation and experiment results show that the AGV can detect and avoid the obstacles successfully in all experimental condition. [Keywords— Obstacle avoidance, AGV, differential drive, laser measurement system, laser navigation system].

  8. Genetic algorithm-based multi-objective optimal absorber system for three-dimensional seismic structures

    Science.gov (United States)

    Ren, Wenjie; Li, Hongnan; Song, Gangbing; Huo, Linsheng

    2009-03-01

    The problem of optimizing an absorber system for three-dimensional seismic structures is addressed. The objective is to determine the number and position of absorbers to minimize the coupling effects of translation-torsion of structures at minimum cost. A procedure for a multi-objective optimization problem is developed by integrating a dominance-based selection operator and a dominance-based penalty function method. Based on the two-branch tournament genetic algorithm, the selection operator is constructed by evaluating individuals according to their dominance in one run. The technique guarantees the better performing individual winning its competition, provides a slight selection pressure toward individuals and maintains diversity in the population. Moreover, due to the evaluation for individuals in each generation being finished in one run, less computational effort is taken. Penalty function methods are generally used to transform a constrained optimization problem into an unconstrained one. The dominance-based penalty function contains necessary information on non-dominated character and infeasible position of an individual, essential for success in seeking a Pareto optimal set. The proposed approach is used to obtain a set of non-dominated designs for a six-storey three-dimensional building with shape memory alloy dampers subjected to earthquake.

  9. Global stability-based design optimization of truss structures using multiple objectives

    Indian Academy of Sciences (India)

    Tugrul Talaslioglu

    2013-02-01

    This paper discusses the effect of global stability on the optimal size and shape of truss structures taking into account of a nonlinear critical load, truss weight and serviceability at the same time. The nonlinear critical load is computed by arc-length method. In order to increase the accuracy of the estimation of critical load (ignoring material nonlinearity), an eigenvalue analysis is implemented into the arc-length method. Furthermore, a pure pareto-ranking based multi-objective optimization model is employed for the design optimization of the truss structure with multiple objectives. The computational performance of the optimization model is increased by implementing an island model into its evolutionary search mechanism. The proposed design optimization approach is applied for both size and shape optimization of real world trusses including 101, 224 and 444 bars and successful in generating feasible designations in a large and complex design space. It is observed that the computational performance of pareto-ranking based island model is better than the pure pareto-ranking based model. Therefore, pareto-ranking based island model is recommended to optimize the design of truss structure possessing geometric nonlinearity

  10. 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

  11. An Object Oriented Knowledge based System for Basic Problem solving in Science and Engineering .

    Directory of Open Access Journals (Sweden)

    M. V. Krishnamurthy

    1993-04-01

    Full Text Available The databases systems and knowledge-based systems are inadequate to handle the knowledge required to solve computational problems in science and engineering. The conventional handbooks and textbooks of science and engineering contain data on scientific quantities in the form of tables and a large number of formulae relating these quantities in the form of algebraic equations. This paper describes a knowledge-based system, developed using object-oriented approach, to store and manipulate this kind of knowledge. The formulae are input in the same form as they are written, in terms of the well known symbols used by an engineer or a scientist, The system interprets the symbols as representing scientific quantities and links them with the underlying data and methods in the knowledge base. By linking data on scientific quantities with one or more appropriate formulae, it is shown that the knowledge base can be used for basic problem solving in science and engineering. The system has been developed on a Sun Sparc Station using object-oriented environment, objectworks C++.

  12. Discriminative boosted forest with convolutional neural network-based patch descriptor for object detection

    Science.gov (United States)

    Xiang, Tao; Li, Tao; Ye, Mao; Li, Xudong

    2016-01-01

    Object detection with intraclass variations is challenging. The existing methods have not achieved the optimal combinations of classifiers and features, especially features learned by convolutional neural networks (CNNs). To solve this problem, we propose an object-detection method based on improved random forest and local image patches represented by CNN features. First, we compute CNN-based patch descriptors for each sample by modified CNNs. Then, the random forest is built whose split functions are defined by patch selector and linear projection learned by linear support vector machine. To improve the classification accuracy, the split functions in each depth of the forest make up a local classifier, and all local classifiers are assembled in a layer-wise manner by a boosting algorithm. The main contributions of our approach are summarized as follows: (1) We propose a new local patch descriptor based on CNN features. (2) We define a patch-based split function which is optimized with maximum class-label purity and minimum classification error over the samples of the node. (3) Each local classifier is assembled by minimizing the global classification error. We evaluate the method on three well-known challenging datasets: TUD pedestrians, INRIA pedestrians, and UIUC cars. The experiments demonstrate that our method achieves state-of-the-art or competitive performance.

  13. Parts and Relations in Young Children's Shape-Based Object Recognition

    Science.gov (United States)

    Augustine, Elaine; Smith, Linda B.; Jones, Susan S.

    2011-01-01

    The ability to recognize common objects from sparse information about geometric shape emerges during the same period in which children learn object names and object categories. Hummel and Biederman's (1992) theory of object recognition proposes that the geometric shapes of objects have two components--geometric volumes representing major object…

  14. 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.

  15. 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.

  16. Simple Ontology of Manipulation Actions based on Hand-Object Relations

    DEFF Research Database (Denmark)

    Wörgötter, Florentin; Aksoy, E. E.; Krüger, Norbert; Piater, Justus; Ude, Ales; Tamosiunaite, M.

    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...... and encoded. Examples of manipulations recognition and execution by a robot based on this representation are given at the end of this study....

  17. Context based Coding of Binary Shapes by Object Boundary Straightness Analysis

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Søren

    A new lossless compression scheme for bilevel images targeted at binary shapes of image and video objects is presented. The scheme is based on a local analysis of the digital straightness of the causal part of the object boundary, which is used in the context definition for arithmetic encoding....... Tested on individual images of binary shapes and binary layers of digital maps the algorithm outperforms PWC, JBIG and MPEG-4 CAE. On the binary shapes the code lengths are reduced by 21%, 25%, and 42%, respectively. On the maps the reductions are 34%, 32%, and 59%, respectively. The algorithm is also...... more efficient than the state-of-the-art and more complex free tree coder for most of the binary shape and map test images....

  18. Objective Assessment of Anesthesiology Resident Skills Using an Innovative Competition-Based Simulation Approach.

    Science.gov (United States)

    Rebel, Annette; DiLorenzo, Amy; Fragneto, Regina Y; Dority, Jeremy S; Rose, Greg L; Nguyen, Dung; Hassan, Zaki-Udin; Schell, Randall M

    2015-09-01

    Residency programs are charged with teaching, assessing, and documenting resident competency for a multitude of skills. Documentation of competency requires demonstrating specific milestones mandated by the Accreditation Council for Graduate Medical Education. Our department designed an innovative, competition-based approach to objectively assess the skill level of postgraduate year 1 residents in performing basic anesthesia-related tasks after 1 month of anesthesiology training. We launched an "Olympic" event to assess requisite skills in an environment of friendly competition. A simulation format was chosen to allow standardized objective assessment of the resident's skill level at an early stage of training, with possible identification of and intervention for skills needing improvement. Our experience may serve as a template for other programs and specialties developing processes for assessing and documenting improvement in skill and competency over the course of residency training. PMID:26323035

  19. 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%.

  20. Comparison of Planar Parallel Manipulator Architectures based on a Multi-objective Design Optimization Approach

    CERN Document Server

    Chablat, Damien; Ur-Rehman, Raza; Wenger, Philippe

    2010-01-01

    This paper deals with the comparison of planar parallel manipulator architectures based on a multi-objective design optimization approach. The manipulator architectures are compared with regard to their mass in motion and their regular workspace size, i.e., the objective functions. The optimization problem is subject to constraints on the manipulator dexterity and stiffness. For a given external wrench, the displacements of the moving platform have to be smaller than given values throughout the obtained maximum regular dexterous workspace. The contributions of the paper are highlighted with the study of 3-RPR, 3-RPR and 3-RPR planar parallel manipulator architectures, which are compared by means of their Pareto frontiers obtained with a genetic algorithm.

  1. 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.

  2. [An object-oriented remote sensing image segmentation approach based on edge detection].

    Science.gov (United States)

    Tan, Yu-Min; Huai, Jian-Zhu; Tang, Zhong-Shi

    2010-06-01

    Satellite sensor technology endorsed better discrimination of various landscape objects. Image segmentation approaches to extracting conceptual objects and patterns hence have been explored and a wide variety of such algorithms abound. To this end, in order to effectively utilize edge and topological information in high resolution remote sensing imagery, an object-oriented algorithm combining edge detection and region merging is proposed. Susan edge filter is firstly applied to the panchromatic band of Quickbird imagery with spatial resolution of 0.61 m to obtain the edge map. Thanks to the resulting edge map, a two-phrase region-based segmentation method operates on the fusion image from panchromatic and multispectral Quickbird images to get the final partition result. In the first phase, a quad tree grid consisting of squares with sides parallel to the image left and top borders agglomerates the square subsets recursively where the uniform measure is satisfied to derive image object primitives. Before the merger of the second phrase, the contextual and spatial information, (e. g., neighbor relationship, boundary coding) of the resulting squares are retrieved efficiently by means of the quad tree structure. Then a region merging operation is performed with those primitives, during which the criterion for region merging integrates edge map and region-based features. This approach has been tested on the QuickBird images of some site in Sanxia area and the result is compared with those of ENVI Zoom Definiens. In addition, quantitative evaluation of the quality of segmentation results is also presented. Experiment results demonstrate stable convergence and efficiency. PMID:20707163

  3. 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.

  4. 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.

  5. Multi-objective Decision Based Available Transfer Capability in Deregulated Power System Using Heuristic Approaches

    Science.gov (United States)

    Pasam, Gopi Krishna; Manohar, T. Gowri

    2015-07-01

    Determination of available transfer capability (ATC) requires the use of experience, intuition and exact judgment in order to meet several significant aspects in the deregulated environment. Based on these points, this paper proposes two heuristic approaches to compute ATC. The first proposed heuristic algorithm integrates the five methods known as continuation repeated power flow, repeated optimal power flow, radial basis function neural network, back propagation neural network and adaptive neuro fuzzy inference system to obtain ATC. The second proposed heuristic model is used to obtain multiple ATC values. Out of these, a specific ATC value will be selected based on a number of social, economic, deregulated environmental constraints and related to specific applications like optimization, on-line monitoring, and ATC forecasting known as multi-objective decision based optimal ATC. The validity of results obtained through these proposed methods are scrupulously verified on various buses of the IEEE 24-bus reliable test system. The results presented and derived conclusions in this paper are very useful for planning, operation, maintaining of reliable power in any power system and its monitoring in an on-line environment of deregulated power system. In this way, the proposed heuristic methods would contribute the best possible approach to assess multiple objective ATC using integrated methods.

  6. Robust object tracking based on weighted subspace reconstruction error with forward: backward tracking criterion

    Science.gov (United States)

    Zhou, Tao; Xie, Kai; Zhang, Junhao; Yang, Jie; He, Xiangjian

    2015-05-01

    It is a challenging task to develop an effective and robust object tracking method due to factors such as severe occlusion, background clutters, abrupt motion, illumination variation, and so on. A tracking algorithm based on weighted subspace reconstruction error is proposed. The discriminative weights are defined based on minimizing reconstruction error with a positive dictionary while maximizing reconstruction error with a negative dictionary. Then a confidence map for candidates is computed through the subspace reconstruction error. Finally, the location of the target object is estimated by maximizing the decision map which combines the discriminative weights and subspace reconstruction error. Furthermore, the new evaluation method based on a forward-backward tracking criterion is used to verify the proposed method and demonstrates its robustness in the updating stage and its effectiveness in the reduction of accumulated errors. Experimental results on 12 challenging video sequences show that the proposed algorithm performs favorably against 12 state-of-the-art methods in terms of accuracy and robustness.

  7. 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

  8. 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...

  9. Browse evaluation of tall shrubs based on direct measurement of a management objective

    Science.gov (United States)

    Keigley, R.B.; Frisina, M.R.

    2008-01-01

    The monitoring of Geyer willow was based on the following management objective: Browsing will prevent fewer than 50 percent of Geyer willow shrubs from growing taller than 3 m . Three questions were addressed: (1) Is browsing a potential factor? (2) If so, can young plants grow taller than 3 meters? (3) If not, is browsing the dominant factor? All shrubs were intensely browsed. With a post-browsing growth rate of 5.0 cm per yr, no shrub could grow 3 m tall. Analyses of stem growth rate excluded dominant roles for climate and plant vigor. Browsing and stem age were the dominant factors that limited growth to 3 m tall.

  10. A high energy physics run control system based on an object oriented approach

    International Nuclear Information System (INIS)

    This paper reports describes the Run Control system developed for the Obelix experiment at the Low Energy Antiproton Ring of CERN. The adopted approach is based on a State Manager developed as a part of the MODEL project. The State Manager incorporates a model of the different activities and of the way they must be organized. An object-oriented decomposition of the on-line system is performed. A clean separation of the control. logic and operating tasks is achieved. Remote Procedure Call techniques are employed to cope with the problems of a distributed system architecture

  11. An energy planning approach based on mixed 0-1 Multiple Objective Linear Programming

    International Nuclear Information System (INIS)

    Multiple Objective Linear Programming (MOLP) models have been widely used in the energy sector for taking into account several conflicting objectives pursued in energy planning. However, continuous variables are not sufficient to accurately represent discrete phenomena encountered in many practical decision situations, such as the power generation expansion problem. This paper presents a new approach based on a mixed 0-1 MOLP model and applied to the Greek electricity generation sector for identifying the number and output of each type of power units needed to satisfy the expected electricity demand in the future. The core of the model is a branch and bound algorithm, which has been properly modified for the multi-objective case and is capable of generating the whole set of efficient solutions. The results provided by this method is the extraction of the efficient combinations of the power generation units, and for each combination the efficient solutions determining electricity production from each unit. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

  12. 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

  13. An interactive system for creating object models from range data based on simulated annealing

    Energy Technology Data Exchange (ETDEWEB)

    Hoff, W.A.; Hood, F.W.; King, R.H. [Colorado School of Mines, Golden, CO (United States). Center for Robotics and Intelligent Systems

    1997-05-01

    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.

  14. 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.

  15. 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.

  16. 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 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.

  17. 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)

  18. A novel objective sour taste evaluation method based on near-infrared spectroscopy.

    Science.gov (United States)

    Hoshi, Ayaka; Aoki, Soichiro; Kouno, Emi; Ogasawara, Masashi; Onaka, Takashi; Miura, Yutaka; Mamiya, Kanji

    2014-05-01

    One of the most important themes in the development of foods and drinks is the accurate evaluation of taste properties. In general, a sensory evaluation system is frequently used for evaluating food and drink. This method, which is dependent on human senses, is highly sensitive but is influenced by the eating experience and food palatability of individuals, leading to subjective results. Therefore, a more effective method for objectively estimating taste properties is required. Here we show that salivary hemodynamic signals, as measured by near-infrared spectroscopy, are a useful objective indicator for evaluating sour taste stimulus. In addition, the hemodynamic responses of the parotid gland are closely correlated to the salivary secretion volume of the parotid gland in response to basic taste stimuli and respond to stimuli independently of the hedonic aspect. Moreover, we examined the hemodynamic responses to complex taste stimuli in food-based solutions and demonstrated for the first time that the complicated phenomenon of the "masking effect," which decreases taste intensity despite the additional taste components, can be successfully detected by near-infrared spectroscopy. In summary, this study is the first to demonstrate near-infrared spectroscopy as a novel tool for objectively evaluating complex sour taste properties in foods and drinks. PMID:24474216

  19. 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.

  20. An objective assessment method of digital image mosaic artifacts visibility based on visual perception

    Science.gov (United States)

    Yu, Hongsheng; Jin, Weiqi; Liu, Xiusheng

    2010-10-01

    The difference of illumination between to-be-mosaicked images will cause mosaic artifacts when digital images are mosaicked. An objective assessment method of digital images mosaic artifacts visibility based on human visual perception has been studied in this paper. The process of the method are as follows; 1) the gradient errors image is obtained according to the to-be-mosaicked images, 2) the just noticeable difference (JND) of reference image is derived by considering the human visual frequency sensitivity, the brightness mask effects and texture mask effects on visual resolution comprehensively; 3) the mosaic artifacts image which is perceptible visually can be acquired by subtracting the JND threshold values from the wavelet coefficients of gradient errors image in wavelet domain. The mosaic artifacts visibility (MAV) of digital image is constructed to use as an objective assessment index of image stitching seam visibility by considering the average value and information entropy of the mosaic artifacts image comprehensively. The experiment indicates that the objective assessment results of digital image mosaic artifacts visibility by MAV index are consistent with those of the subjective perceptual method basically.

  1. Optimization of Enterprise Information System based on Object-based Knowledge Mesh and Binary Tree with Maximum User Satisfaction

    Directory of Open Access Journals (Sweden)

    Haiwang Cao

    2012-04-01

    Full Text Available This paper deals with an approach to the optimization of enterprise information system (EIS based on the object-based knowledge mesh (OKM and binary tree. Firstly, to explore the optimization of EIS by the user’s function requirements, an OKM expression representation based on the user’s satisfaction and binary tree is proposed. Secondly, based on the definitions of the fuzzy function-satisfaction degree relationships on the OKM functions, the optimization model is constructed. Thirdly, the OKM multiple set operation expression is optimized by the immune genetic algorithm and binary tree, with the steps of the OKM optimization presented in detail as well. Finally, the optimization of EIS is illustrated by an example to verify the proposed approaches.

  2. 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.

  3. Region segmentation techniques for object-based image compression: a review

    Science.gov (United States)

    Schmalz, Mark S.; Ritter, Gerhard X.

    2004-10-01

    Image compression based on transform coding appears to be approaching an asymptotic bit rate limit for application-specific distortion levels. However, a new compression technology, called object-based compression (OBC) promises improved rate-distortion performance at higher compression ratios. OBC involves segmentation of image regions, followed by efficient encoding of each region"s content and boundary. Advantages of OBC include efficient representation of commonly occurring textures and shapes in terms of pointers into a compact codebook of region contents and boundary primitives. This facilitates fast decompression via substitution, at the cost of codebook search in the compression step. Segmentation cose and error are significant disadvantages in current OBC implementations. Several innovative techniques have been developed for region segmentation, including (a) moment-based analysis, (b) texture representation in terms of a syntactic grammar, and (c) transform coding approaches such as wavelet based compression used in MPEG-7 or JPEG-2000. Region-based characterization with variance templates is better understood, but lacks the locality of wavelet representations. In practice, tradeoffs are made between representational fidelity, computational cost, and storage requirement. This paper overviews current techniques for automatic region segmentation and representation, especially those that employ wavelet classification and region growing techniques. Implementational discussion focuses on complexity measures and performance metrics such as segmentation error and computational cost.

  4. Combining TerraSAR-X and SPOT-5 data for object-based landslide detection

    Science.gov (United States)

    Friedl, B.; Hölbling, D.; Füreder, P.

    2012-04-01

    Landslide detection and classification is an essential requirement in pre- and post-disaster hazard analysis. In earlier studies landslide detection often was achieved through time-consuming and cost-intensive field surveys and visual orthophoto interpretation. Recent studies show that Earth Observation (EO) data offer new opportunities for fast, reliable and accurate landslide detection and classification, which may conduce to an effective landslide monitoring and landslide hazard management. To ensure the fast recognition and classification of landslides at a regional scale, a (semi-)automated object-based landslide detection approach is established for a study site situated in the Huaguoshan catchment, Southern Taiwan. The study site exhibits a high vulnerability to landslides and debris flows, which are predominantly typhoon-induced. Through the integration of optical satellite data (SPOT-5 with 2.5 m GSD), SAR (Synthetic Aperture Radar) data (TerraSAR-X Spotlight with 2.95 m GSD) and digital elevation information (DEM with 5 m GSD) including its derived products (e.g. slope, curvature, flow accumulation) landslides may be examined in a more efficient way as if relying on single data sources only. The combination of optical and SAR data in an object-based image analysis (OBIA) domain for landslide detection and classification has not been investigated so far, even if SAR imagery show valuable properties for landslide detection, which differ from optical data (e.g. high sensitivity to surface roughness and soil moisture). The main purpose of this study is to recognize and analyze existing landslides by applying object-based image analysis making use of eCognition software. OBIA provides a framework for examining features defined by spectral, spatial, textural, contextual as well as hierarchical properties. Objects are derived through image segmentation and serve as input for the classification process, which relies on transparent rulesets, representing knowledge. Through class modeling, an iterative process of segmentation and classification, objects can be addressed individually in a region-specific manner. The presented approach is marked by the comprehensive use of available data sets from various sources. This full integration of optical, SAR and DEM data conduces to the development of a robust method, which makes use of the most appropriate characteristics (e.g. spectral, textural, contextual) of each data set. The proposed method contributes to a more rapid and accurate landslide mapping in order to assist disaster and crisis management. Especially SAR data proves to be useful in the aftermath of an event, as radar sensors are mostly independent of illumination and weather conditions and therefore data is more likely to be available. The full data integration allows coming up with a robust approach for the detection and classification of landslides. However, more research is needed to make the best of the integration of SAR data in an object-based environment and for making the approach easier adaptable to different study sites and data.

  5. Approach to proliferation risk assessment based on multiple objective analysis framework

    International Nuclear Information System (INIS)

    The approach to the assessment of proliferation risk using the methods of multi-criteria decision making and multi-objective optimization is presented. The approach allows the taking into account of the specifics features of the national nuclear infrastructure, and possible proliferation strategies (motivations, intentions, and capabilities). 3 examples of applying the approach are shown. First, the approach has been used to evaluate the attractiveness of HEU (high enriched uranium)production scenarios at a clandestine enrichment facility using centrifuge enrichment technology. Secondly, the approach has been applied to assess the attractiveness of scenarios for undeclared production of plutonium or HEU by theft of materials circulating in nuclear fuel cycle facilities and thermal reactors. Thirdly, the approach has been used to perform a comparative analysis of the structures of developing nuclear power systems based on different types of nuclear fuel cycles, the analysis being based on indicators of proliferation risk

  6. Approach to proliferation risk assessment based on multiple objective analysis framework

    Energy Technology Data Exchange (ETDEWEB)

    Andrianov, A.; Kuptsov, I. [Obninsk Institute for Nuclear Power Engineering of NNRU MEPhI (Russian Federation); Studgorodok 1, Obninsk, Kaluga region, 249030 (Russian Federation)

    2013-07-01

    The approach to the assessment of proliferation risk using the methods of multi-criteria decision making and multi-objective optimization is presented. The approach allows the taking into account of the specifics features of the national nuclear infrastructure, and possible proliferation strategies (motivations, intentions, and capabilities). 3 examples of applying the approach are shown. First, the approach has been used to evaluate the attractiveness of HEU (high enriched uranium)production scenarios at a clandestine enrichment facility using centrifuge enrichment technology. Secondly, the approach has been applied to assess the attractiveness of scenarios for undeclared production of plutonium or HEU by theft of materials circulating in nuclear fuel cycle facilities and thermal reactors. Thirdly, the approach has been used to perform a comparative analysis of the structures of developing nuclear power systems based on different types of nuclear fuel cycles, the analysis being based on indicators of proliferation risk.

  7. 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.

  8. A Kalman Filter-Based Algorithm for Measuring the Parameters of Moving Objects

    Science.gov (United States)

    Dichev, Dimitar; Koev, Hristofor; Bakalova, Totka; Louda, Petr

    2015-02-01

    One of the most complex problems in measuring equipment is related to the provision of the required dynamic accuracy of measuring systems determining the parameters of moving objects. The present paper views an algorithm for improving the dynamic accuracy of such measuring systems. It is based on the Kalman method. The algorithm aims to eliminate the influence of a number of interference sources, each of which is of secondary significance. However, their total effect can cause considerable distortion of the measurement signal. The algorithm model is designed for gyro-free measuring systems. It is based on one of the most widely used elements in the dynamic systems, namely the physical pendulum, due to which measuring systems of high dynamic accuracy and low cost can be developed. The presented experimental results confirm the effectiveness of the proposed algorithm with respect to the dynamic accuracy of measuring systems of this type.

  9. A Color-Texture Based Segmentation Method To Extract Object From Background

    Directory of Open Access Journals (Sweden)

    Saka Kezia

    2013-03-01

    Full Text Available Extraction of flower regions from complex background is a difficult task, it is an important part of flower image retrieval, and recognition .Image segmentation denotes a process of partitioning an image into distinct regions. A large variety of different segmentation approaches for images have been developed. Image segmentation plays an important role in image analysis. According to several authors, segmentation terminates when the observer’s goal is satisfied. For this reason, a unique method that can be applied to all possible cases does not yet exist. This paper studies the flower image segmentation in complex background. Based on the visual characteristics differences of the flower and the surrounding objects, the flower from different backgrounds are separated into a single set of flower image pixels. The segmentation methodology on flower images consists of five steps. Firstly, the original image of RGB space is transformed into Lab color space. In the second step ‘a’ component of Lab color space is extracted. Then segmentation by two-dimension OTSU of automatic threshold in ‘a-channel’ is performed. Based on the color segmentation result, and the texture differences between the background image and the required object, we extract the object by the gray level co-occurrence matrix for texture segmentation. The GLCMs essentially represent the joint probability of occurrence of grey-levels for pixels with a given spatial relationship in a defined region. Finally, the segmentation result is corrected by mathematical morphology methods. The algorithm was tested on plague image database and the results prove to be satisfactory. The algorithm was also tested on medical images for nucleus segmentation.

  10. 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.

  11. Object-based image analysis and data mining for building ontology of informal urban settlements

    Science.gov (United States)

    Khelifa, Dejrriri; Mimoun, Malki

    2012-11-01

    During recent decades, unplanned settlements have been appeared around the big cities in most developing countries and as consequence, numerous problems have emerged. Thus the identification of different kinds of settlements is a major concern and challenge for authorities of many countries. Very High Resolution (VHR) Remotely Sensed imagery has proved to be a very promising way to detect different kinds of settlements, especially through the using of new objectbased image analysis (OBIA). The most important key is in understanding what characteristics make unplanned settlements differ from planned ones, where most experts characterize unplanned urban areas by small building sizes at high densities, no orderly road arrangement and Lack of green spaces. Knowledge about different kinds of settlements can be captured as a domain ontology that has the potential to organize knowledge in a formal, understandable and sharable way. In this work we focus on extracting knowledge from VHR images and expert's knowledge. We used an object based strategy by segmenting a VHR image taken over urban area into regions of homogenous pixels at adequate scale level and then computing spectral, spatial and textural attributes for each region to create objects. A genetic-based data mining was applied to generate high predictive and comprehensible classification rules based on selected samples from the OBIA result. Optimized intervals of relevant attributes are found, linked with land use types for forming classification rules. The unplanned areas were separated from the planned ones, through analyzing of the line segments detected from the input image. Finally a simple ontology was built based on the previous processing steps. The approach has been tested to VHR images of one of the biggest Algerian cities, that has grown considerably in recent decades.

  12. 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.

  13. 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.

  14. 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.

  15. Genetic Algorithm Based Objective Functions Comparative Study for Damage Detection and Localization in Beam Structures

    Science.gov (United States)

    Samir, K.; Idir, B.; Serra, R.; Brahim, B.; Aicha, A.

    2015-07-01

    The detection techniques based on non-destructive testing (NDT) defects are preferable because of their low cost and operational aspects related to the use of the analyzed structure. In this study, we used the genetic algorithm (GA) for detecting and locating damage. The finite element was used for diagnostic beams. Different structures considered may incur damage to be modelled by a loss of rigidity supposed to represent a defect in the structure element. Identification of damage is formulated as an optimization problem using three objective functions (change of natural frequencies, Modal Assurance Criterion MAC and MAC natural frequency). The results show that the best objective function is based on the natural frequency and MAC while the method of the genetic algorithm present its efficiencies in indicating and quantifying multiple damage with great accuracy. Three defects have been created to enhance damage depending on the elements 2, 5 and 8 with a percentage allocation of 50% in the beam structure which has been discretized into 10 elements. Finally the defect with noise was introduced to test the stability of the method against uncertainty.

  16. 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...

  17. 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.

  18. 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%.

  19. Rule-Driven Object Tracking in Clutter and Partial Occlusion with Model-Based Snakes

    Directory of Open Access Journals (Sweden)

    Rapantzikos Konstantinos

    2004-01-01

    Full Text Available In the last few years it has been made clear to the research community that further improvements in classic approaches for solving low-level computer vision and image/video understanding tasks are difficult to obtain. New approaches started evolving, employing knowledge-based processing, though transforming a priori knowledge to low-level models and rules are far from being straightforward. In this paper, we examine one of the most popular active contour models, snakes, and propose a snake model, modifying terms and introducing a model-based one that eliminates basic problems through the usage of prior shape knowledge in the model. A probabilistic rule-driven utilization of the proposed model follows, being able to handle (or cope with objects of different shapes, contour complexities and motions; different environments, indoor and outdoor; cluttered sequences; and cases where background is complex (not smooth and when moving objects get partially occluded. The proposed method has been tested in a variety of sequences and the experimental results verify its efficiency.

  20. Visual object categorization with new keypoint-based adaBoost features

    CERN Document Server

    Bdiri, Taoufik; Steux, Bruno

    2009-01-01

    We present promising results for visual object categorization, obtained with adaBoost using new original ?keypoints-based features?. These weak-classifiers produce a boolean response based on presence or absence in the tested image of a ?keypoint? (a kind of SURF interest point) with a descriptor sufficiently similar (i.e. within a given distance) to a reference descriptor characterizing the feature. A first experiment was conducted on a public image dataset containing lateral-viewed cars, yielding 95% recall with 95% precision on test set. Preliminary tests on a small subset of a pedestrians database also gives promising 97% recall with 92 % precision, which shows the generality of our new family of features. Moreover, analysis of the positions of adaBoost-selected keypoints show that they correspond to a specific part of the object category (such as ?wheel? or ?side skirt? in the case of lateral-cars) and thus have a ?semantic? meaning. We also made a first test on video for detecting vehicles from adaBoost...

  1. 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.

  2. A Novel Java Based Computation and Comparison Method (JBCCM for Differentiating Object Oriented Paradigm Using Coupling Measures

    Directory of Open Access Journals (Sweden)

    Sandeep Singh

    2011-12-01

    Full Text Available In this paper we propose a novel java based computation and comparison method (JBCCM. In this method we taking three type of object oriented files for showing the computation. Those three files belong to C++, Java and C#. We first compute class, Inheritance, Interface, object and Line of Codes (LOC. Then we assume three databases based on several properties of C++, java, C#. Then we compare three files Based on class (BOC, Based on Inheritance (BOI, Based on Interfaces (BOIN, Based on Object (BOO and Based on LOC (BOL. Then we deduce a comparative result for that particular object oriented file. The result approximate that the file is best suited on which platform. So we can deduce best platform and coupling measures for Object Oriented Paradigm.

  3. Object-based landslide mapping on satellite images from different sensors

    Science.gov (United States)

    Hölbling, Daniel; Friedl, Barbara; Eisank, Clemens; Blaschke, Thomas

    2015-04-01

    Several studies have proven that object-based image analysis (OBIA) is a suitable approach for landslide mapping using remote sensing data. Mostly, optical satellite images are utilized in combination with digital elevation models (DEMs) for semi-automated mapping. The ability of considering spectral, spatial, morphometric and contextual features in OBIA constitutes a significant advantage over pixel-based methods, especially when analysing non-uniform natural phenomena such as landslides. However, many of the existing knowledge-based OBIA approaches for landslide mapping are rather complex and are tailored to specific data sets. These restraints lead to a lack of transferability of OBIA mapping routines. The objective of this study is to develop an object-based approach for landslide mapping that is robust against changing input data with different resolutions, i.e. optical satellite imagery from various sensors. Two study sites in Taiwan were selected for developing and testing the landslide mapping approach. One site is located around the Baolai village in the Huaguoshan catchment in the southern-central part of the island, the other one is a sub-area of the Taimali watershed in Taitung County near the south-eastern Pacific coast. Both areas are regularly affected by severe landslides and debris flows. A range of very high resolution (VHR) optical satellite images was used for the object-based mapping of landslides and for testing the transferability across different sensors and resolutions: (I) SPOT-5, (II) Formosat-2, (III) QuickBird, and (IV) WorldView-2. Additionally, a digital elevation model (DEM) with 5 m spatial resolution and its derived products (e.g. slope, plan curvature) were used for supporting the semi-automated mapping, particularly for differentiating source areas and accumulation areas according to their morphometric characteristics. A focus was put on the identification of comparatively stable parameters (e.g. relative indices), which could be transferred to the different satellite images. The presence of bare ground was assumed to be an evidence for the occurrence of landslides. For separating vegetated from non-vegetated areas the Normalized Difference Vegetation Index (NDVI) was primarily used. Each image was divided into two respective parts based on an automatically calculated NDVI threshold value in eCognition (Trimble) software by combining the homogeneity criterion of multiresolution segmentation and histogram-based methods, so that heterogeneity is increased to a maximum. Expert knowledge models, which depict features and thresholds that are usually used by experts for digital landslide mapping, were considered for refining the classification. The results were compared to the respective results from visual image interpretation (i.e. manually digitized reference polygons for each image), which were produced by an independent local expert. By that, the spatial overlaps as well as under- and over-estimated areas were identified and the performance of the approach in relation to each sensor was evaluated. The presented method can complement traditional manual mapping efforts. Moreover, it contributes to current developments for increasing the transferability of semi-automated OBIA approaches and for improving the efficiency of change detection approaches across multi-sensor imagery.

  4. View Independent Object Classification Based on Automated Ground Plane Rectification for Traffic Scene Surveillance

    OpenAIRE

    Zhang, Zhaoxiang; Li, Min; Huang, Kaiqi; Tan, Tieniu

    2008-01-01

    We address the problem of view independent object classification. Our aim is to classify moving objects of traffic scene surveillance videos into pedestrians, bicycles and vehicles. However, this problem is very challenging due to large object appearance variance, low resolution videos and limited object size. Especially, perspective distortion of surveillance cameras makes most 2D object features like size and speed related to view angles and not suitable for object classification. In this p...

  5. Increasing the range accuracy of three-dimensional ghost imaging ladar using optimum slicing number method

    Science.gov (United States)

    Yang, Xu; Zhang, Yong; Xu, Lu; Yang, Cheng-Hua; Wang, Qiang; Liu, Yue-Hao; Zhao, Yuan

    2015-12-01

    The range accuracy of three-dimensional (3D) ghost imaging is derived. Based on the derived range accuracy equation, the relationship between the slicing number and the range accuracy is analyzed and an optimum slicing number (OSN) is determined. According to the OSN, an improved 3D ghost imaging algorithm is proposed to increase the range accuracy. Experimental results indicate that the slicing number can affect the range accuracy significantly and the highest range accuracy can be achieved if the 3D ghost imaging system works with OSN. Project supported by the Young Scientist Fund of the National Natural Science Foundation of China (Grant No. 61108072).

  6. Object-based image analysis for the impact of sewage pollution in Malad Creek, Mumbai, India.

    Science.gov (United States)

    Shirke, Shivani; Pinto, Shannon M; Kushwaha, Vikash K; Mardikar, Trupti; Vijay, Ritesh

    2016-02-01

    Today, object-based image analysis provides an option for integrating spatial information beyond conventional pixel-based classifications for high-resolution imagery. Due to its rare applicability in pollution assessment, an attempt has been made to assess the spatial extent of sewage pollution in Malad Creek, Mumbai, India. Based on multiresolution segmentation of an IRS P6 (LISS IV) image and the Normalized Difference Turbidity Index (NDTI), the various water quality regions in the creek were classified. The existing literature implies that the reflectance of turbid water is similar to that of bare soil which gives positive NDTI values. In contrast to this, negative values of NDTI are observed in the present study due to the presence of organic matter which absorbs light and imparts turbidity, which is supported by the significant correlation between NDTI and turbidity. A strong relationship is observed between turbidity and water quality parameters, implying the impact of organic matter through discharges of sewage in the creek. Based on the classified regions and the water quality parameters, the extent of pollution was ranked as high, moderate, low and least. The methodology developed in the present study was successfully applied on an IKONOS image for the same study area but a different time frame. The approach will help in impact assessment of sewage pollution and its spatial extent in other water bodies. PMID:26780414

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

    Directory of Open Access Journals (Sweden)

    Taylor Sawyer

    2011-03-01

    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.

  8. A Model-Based System For Object Recognition In Aerial Scenes

    Science.gov (United States)

    Cullen, M. F.; Hord, R. M.; Miller, S. F.

    1987-03-01

    Preliminary results of a system that uses model descriptions of objects to predict and match features derived from aerial images are presented. The system is organized into several phases: 1) processing of image scenes to obtain image primitives, 2) goal-oriented sorting of primitives into classes of related features, 3) prediction of the location of object model features in the image, and 4) matching image features to the model predicted features. The matching approach is centered upon a compatibility figure of merit between a set of image features and model features chosen to direct the search. The search process utilizes an iterative hypothesis generation and verication cycle. A "search matrix" is con-structed from image features and model features according to a first approximation of compatibility based upon orientation. Currently, linear features are used as primitives. Input to the matching algorithm is in the form of line segments extracted from an image scene via edge operatiors and a Hough transform technique for grouping. Additional processing is utilized to derive closed boundaries and complete edge descriptions. Line segments are then sorted into specific classes such that, on a higher level, a priori knowledge about a particular scene can be used to control the priority of line segments in the search process. Additional knowledge about the object model under consideration is utilized to construct the search matrix with the classes of line segments most likely containing the model description. It is shown that these techniques result in a, reduction in the size of the object recognition search space and hence in the time to locate the object in the image. The current system is implemented on a Symbolics LispTM machine. While experimentation continues, we have rewritten and tested the search process and several image processing functions for parallel implementation on a Connection Machine TM computer. It is shown that several orders of magnitude faster processing rates are achieved, as well as the possibility of entirely new processing schemes which take advantage of the unique Connection Machine architecture.

  9. 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.

  10. A Probabilistic Framework Based on KDE-GMM Hybrid Model for Moving Object Segmentation in Dynamic Scenes

    OpenAIRE

    Liu, Zhou; Chen, Wei; Huang, Kaiqi; Tan, Tieniu

    2008-01-01

    In real scenes, dynamic background and moving cast shadow always make accurate moving object detection difficult. In this paper, a probabilistic framework for moving object segmentation in dynamic scenes is proposed. Under this framework, we deal with foreground detection and shadow removal simultaneously by constructing probability density functions (PDFs) of moving objects and non-moving objects. Here, these PDFs are constructed based on KDEGMMhybrid model (KGHM) which has advantages of KDE...

  11. 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.

  12. 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.

  13. Textured digital elevation model formation from low-cost UAV LADAR/digital image data

    Science.gov (United States)

    Bybee, Taylor C.; Budge, Scott E.

    2015-05-01

    Textured digital elevation models (TDEMs) have valuable use in precision agriculture, situational awareness, and disaster response. However, scientific-quality models are expensive to obtain using conventional aircraft-based methods. The cost of creating an accurate textured terrain model can be reduced by using a low-cost (simulated data from a small UAV gathering swaths of texel images of the terrain below. Being a low-cost UAV, only a coarse knowledge of position and attitude is known, and thus both 2D- and 3D-image registration techniques must be used to register adjacent swaths of texel imagery to create a TDEM. The process of creating an aggregate texel image (a TDEM) from many smaller texel image swaths is described. The algorithm is seeded with the rough estimate of position and attitude of each capture. Details such as the required amount of texel image overlap, registration models, simulated flight patterns (level and turbulent), and texture image formation are presented. In addition, examples of such TDEMs are shown and analyzed for accuracy.

  14. 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.

  15. 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.

  16. 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.

  17. Combining structured light and ladar for pose tracking in THz sensor management

    Science.gov (United States)

    Engström, Philip; Axelsson, Maria; Karlsson, Mikael

    2013-05-01

    Stand-off 3D THz imaging to detect concealed treats is currently under development. The technology can provide high resolution 3D range data of a passing subject showing layers of clothes and if there are concealed items. However, because it is a scanning sensor technology with a narrow field of view, the subjects pose and position need to be accurately tracked in real time to focus the system and map the imaged THz data to specific body parts. Structured light is a technique to obtain 3D range information. It is, for example, used in the Microsoft Kinect for pose tracking of game players in real time. We demonstrate how structured light can contribute to a THz sensor management system and track subjects in real time. The main advantage of structured light is its simplicity, the disadvantages are the sensitivity to lighting conditions and material properties as well as a relatively low accuracy. Time of flight laser scanning is a technique that complements structured light well, the accuracy is usually much higher and it is less sensitive to lighting conditions. We show that by combining the techniques it is possible to create a robust real time pose tracking system for THz sensor management. We present a concept system based on the Microsoft Kinect and a SICK LMS-511 laser scanner. The laser scanner is used for 2D tracking of the subjects, this tracking is then used to initialize and validate the Microsoft Kinect pose tracking. We have evaluated the sensors individually in both static and dynamic scenes and present their advantages and drawbacks.

  18. A multi-objective improved teaching-learning based optimization algorithm for unconstrained and constrained optimization problems

    OpenAIRE

    R. Venkata Rao; Vivek Patel

    2014-01-01

    The present work proposes a multi-objective improved teaching-learning based optimization (MO-ITLBO) algorithm for unconstrained and constrained multi-objective function optimization. The MO-ITLBO algorithm is the improved version of basic teaching-learning based optimization (TLBO) algorithm adapted for multi-objective problems. The basic TLBO algorithm is improved to enhance its exploration and exploitation capacities by introducing the concept of number of teachers, adaptive teaching facto...

  19. A fast model-free morphology-based object tracking algorithm

    OpenAIRE

    Owens, Jonathan; Hunter, Andrew; Fletcher, Eric

    2002-01-01

    This paper describes the multiple object tracking component of an automated CCTV surveillance system. The system tracks objects, and alerts the operator if unusual trajectories are discovered. Objects are detected by background differencing. Low contrast levels can present problems, leading to poor object segmentation and fragmentation, particularly on older analogue surveillance networks. The model-free tracking algorithm described in this paper addresses object fragmentation, and the obj...

  20. The new ALICE DQM client: a web access to ROOT-based objects

    Science.gov (United States)

    von Haller, B.; Carena, F.; Carena, W.; Chapeland, S.; Chibante Barroso, V.; Costa, F.; Delort, C.; Dénes, E.; Diviá, R.; Fuchs, U.; Niedziela, J.; Simonetti, G.; Soós, C.; Telesca, A.; Vande Vyvre, P.; Wegrzynek, A.

    2015-12-01

    A Large Ion Collider Experiment (ALICE) is the heavy-ion detector designed to study the physics of strongly interacting matter and the quark-gluon plasma at the CERN Large Hadron Collider (LHC). The online Data Quality Monitoring (DQM) plays an essential role in the experiment operation by providing shifters with immediate feedback on the data being recorded in order to quickly identify and overcome problems. An immediate access to the DQM results is needed not only by shifters in the control room but also by detector experts worldwide. As a consequence, a new web application has been developed to dynamically display and manipulate the ROOT-based objects produced by the DQM system in a flexible and user friendly interface. The architecture and design of the tool, its main features and the technologies that were used, both on the server and the client side, are described. In particular, we detail how we took advantage of the most recent ROOT JavaScript I/O and web server library to give interactive access to ROOT objects stored in a database. We describe as well the use of modern web techniques and packages such as AJAX, DHTMLX and jQuery, which has been instrumental in the successful implementation of a reactive and efficient application. We finally present the resulting application and how code quality was ensured. We conclude with a roadmap for future technical and functional developments.

  1. Region-Based Convolutional Networks for Accurate Object Detection and Segmentation.

    Science.gov (United States)

    Girshick, Ross; Donahue, Jeff; Darrell, Trevor; Malik, Jitendra

    2016-01-01

    Object detection performance, as measured on the canonical PASCAL VOC Challenge datasets, plateaued in the final years of the competition. The best-performing methods were complex ensemble systems that typically combined multiple low-level image features with high-level context. In this paper, we propose a simple and scalable detection algorithm that improves mean average precision (mAP) by more than 50 percent relative to the previous best result on VOC 2012-achieving a mAP of 62.4 percent. Our approach combines two ideas: (1) one can apply high-capacity convolutional networks (CNNs) to bottom-up region proposals in order to localize and segment objects and (2) when labeled training data are scarce, supervised pre-training for an auxiliary task, followed by domain-specific fine-tuning, boosts performance significantly. Since we combine region proposals with CNNs, we call the resulting model an R-CNN or Region-based Convolutional Network. Source code for the complete system is available at http://www.cs.berkeley.edu/~rbg/rcnn. PMID:26656583

  2. Environmental flow assessments in estuaries based on an integrated multi-objective method

    Science.gov (United States)

    Sun, T.; Xu, J.; Yang, Z. F.

    2013-02-01

    An integrated multi-objective method for environmental flow assessments was developed that considered variability of potential habitats as a critical factor in determining how ecosystems respond to hydrological alterations. Responses of habitat area, and the magnitude of those responses as influenced by salinity and water depth, were established and assessed according to fluctuations in river discharge and tidal currents. The requirements of typical migratory species during pivotal life-stage seasons (e.g., reproduction and juvenile growth) and natural flow variations were integrated into the flow-needs assessment. Critical environmental flows for a typical species were defined based on two primary objectives: (1) high level of habitat area and (2) low variability of habitat area. After integrating the water requirements for various species with the maximum acceptable discharge boundary, appropriate temporal limits of environmental flows for ecosystems were recommended. The method was applied in the Yellow River estuary in eastern Shandong province, China. Our results show that, while recommended environmental flows established with variability of potential habitats in mind may not necessarily benefit short-term survival of a typical resident organism on a limited temporal or spatial scale, they may encourage long-term, stable biodiversity and ecosystem health. Thus, short-term ecosystem losses may be compensated by significant long-term gains.

  3. Portfolio optimization using fundamental indicators based on multi-objective EA

    CERN Document Server

    Silva, Antonio Daniel; Horta, Nuno

    2016-01-01

    This work presents a new approach to portfolio composition in the stock market. It incorporates a fundamental approach using financial ratios and technical indicators with a Multi-Objective Evolutionary Algorithms to choose the portfolio composition with two objectives the return and the risk. Two different chromosomes are used for representing different investment models with real constraints equivalents to the ones faced by managers of mutual funds, hedge funds, and pension funds. To validate the present solution two case studies are presented for the SP&500 for the period June 2010 until end of 2012. The simulations demonstrates that stock selection based on financial ratios is a combination that can be used to choose the best companies in operational terms, obtaining returns above the market average with low variances in their returns. In this case the optimizer found stocks with high return on investment in a conjunction with high rate of growth of the net income and a high profit margin. To obtain s...

  4. Environmental flow assessments in estuaries based on an integrated multi-objective method

    Directory of Open Access Journals (Sweden)

    T. Sun

    2013-02-01

    Full Text Available An integrated multi-objective method for environmental flow assessments was developed that considered variability of potential habitats as a critical factor in determining how ecosystems respond to hydrological alterations. Responses of habitat area, and the magnitude of those responses as influenced by salinity and water depth, were established and assessed according to fluctuations in river discharge and tidal currents. The requirements of typical migratory species during pivotal life-stage seasons (e.g., reproduction and juvenile growth and natural flow variations were integrated into the flow-needs assessment. Critical environmental flows for a typical species were defined based on two primary objectives: (1 high level of habitat area and (2 low variability of habitat area. After integrating the water requirements for various species with the maximum acceptable discharge boundary, appropriate temporal limits of environmental flows for ecosystems were recommended. The method was applied in the Yellow River estuary in eastern Shandong province, China. Our results show that, while recommended environmental flows established with variability of potential habitats in mind may not necessarily benefit short-term survival of a typical resident organism on a limited temporal or spatial scale, they may encourage long-term, stable biodiversity and ecosystem health. Thus, short-term ecosystem losses may be compensated by significant long-term gains.

  5. 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

  6. Objective Error Criterion for Evaluation of Mapping Accuracy Based on Sensor Time-of-Flight Measurements

    Directory of Open Access Journals (Sweden)

    Billur Barshan

    2008-12-01

    Full Text Available An objective error criterion is proposed for evaluating the accuracy of maps of unknown environments acquired by making range measurements with different sensing modalities and processing them with different techniques. The criterion can also be used for the assessment of goodness of fit of curves or shapes fitted to map points. A demonstrative example from ultrasonic mapping is given based on experimentally acquired time-of-flight measurements and compared with a very accurate laser map, considered as absolute reference. The results of the proposed criterion are compared with the Hausdorff metric and the median error criterion results. The error criterion is sufficiently general and flexible that it can be applied to discrete point maps acquired with other mapping techniques and sensing modalities as well.

  7. Objective Error Criterion for Evaluation of Mapping Accuracy Based on Sensor Time-of-Flight Measurements

    Science.gov (United States)

    Barshan, Billur

    2008-01-01

    An objective error criterion is proposed for evaluating the accuracy of maps of unknown environments acquired by making range measurements with different sensing modalities and processing them with different techniques. The criterion can also be used for the assessment of goodness of fit of curves or shapes fitted to map points. A demonstrative example from ultrasonic mapping is given based on experimentally acquired time-of-flight measurements and compared with a very accurate laser map, considered as absolute reference. The results of the proposed criterion are compared with the Hausdorff metric and the median error criterion results. The error criterion is sufficiently general and flexible that it can be applied to discrete point maps acquired with other mapping techniques and sensing modalities as well.

  8. Ecosystem-based management objectives for the North Sea: riding the forage fish rollercoaster

    DEFF Research Database (Denmark)

    Dickey-Collas, Mark; Engelhard, Georg H.; Rindorf, Anna; Raab, Kristina; Smout, Sophie; Aarts, Geert; Deurs, Mikael van; Brunel, Thomas; Hoff, Ayoe; Lauerburg, Rebecca A.M.; Garthe, Stefan; Andersen, Ken Haste; Scott, F.; Kooten, Tobias van; Beare, D.; Peck, Myron A.

    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...

  9. A multi-resolution technique based on shape optimization for the reconstruction of homogeneous dielectric objects

    International Nuclear Information System (INIS)

    In the framework of inverse scattering techniques, this paper presents the integration of a multi-resolution technique and the level-set method for qualitative microwave imaging. On the one hand, in order to effectively exploit the limited amount of information collectable from scattering measurements, the iterative multi-scaling approach (IMSA) is employed for enabling a detailed reconstruction only where needed without increasing the number of unknowns. On the other hand, the a priori information on the homogeneity of the unknown object is exploited by adopting a shape-based optimization and representing the support of the scatterer via a level-set function. Reliability and effectiveness of the proposed strategy are also assessed by processing both synthetic and experimental scattering data for simple and complex geometries

  10. Object oriented design of anthropomorphic phantoms and Geant4-based implementations

    International Nuclear Information System (INIS)

    Various models of anthropomorphic phantoms have been developed in the past decades for usage in Monte Carlo simulation for radiation protection and other medical physics applications; they adopt two alternative approaches, either modelling the body components through analytical geometrical representations or through voxelized geometries. An original system has been developed associated with the use of the Geant4 simulation tool kit. It exploits Geant4 advanced capabilities to model geometrical components, and the object oriented technology to provide a variety of models of the human body usable in a simulation application. The flexible software design allows the creation of both analytical and voxel phantoms. The system allows the creation of phantoms of different sex and age; phantoms based on established models are provided, as well as the option for the user to assemble customized phantoms. (authors)

  11. Memetic Multi-Objective Particle Swarm Optimization-Based Energy-Aware Virtual Network Embedding

    Directory of Open Access Journals (Sweden)

    Ashraf A. Shahin

    2015-04-01

    Full Text Available In cloud infrastructure, accommodating multiple virtual networks on a single physical network reduces power consumed by physical resources and minimizes cost of operating cloud data centers. However, mapping multiple virtual network resources to physical network components, called virtual network embedding (VNE, is known to be NP-hard. With considering energy efficiency, the problem becomes more complicated. In this paper, we model energy-aware virtual network embedding, devise metrics for evaluating performance of energy aware virtual network-embedding algorithms, and propose an energy aware virtual network-embedding algorithm based on multi-objective particle swarm optimization augmented with local search to speed up convergence of the proposed algorithm and improve solutions quality. Performance of the proposed algorithm is evaluated and compared with existing algorithms using extensive simulations, which show that the proposed algorithm improves virtual network embedding by increasing revenue and decreasing energy consumption.

  12. Identifying Objective True/False from Subjective Yes/No Semantic based on OWA and CWA

    Directory of Open Access Journals (Sweden)

    Yucong Duan

    2013-07-01

    Full Text Available Distinguishing objective(OBJ semantic from subjective(SUBJ semantic is essential to information processing of either explicit design formalization or implicit natural language(NL communication of projects’ implementation. We summarized our past experience of solutions for semantic knowledge management projects. An adopted hypothesis is that among the tremendous and rapid increasing information, there is a relative stable core which can map/relate to every specific piece of information uniformly starting from the discussion on existence and conceptualization. The mapping will result in an expansion formalization based on open world assumption (OWA and closed world assumption (CWA. This formalization can be widely applied for guiding semantic formalization and validation. We show initial applications on transformations from SUBJ to OBJ, etc.

  13. 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).

  14. Question Answering in a Natural Language Understanding System Based on Object-Oriented Semantics

    CERN Document Server

    Ostapov, Yuriy

    2011-01-01

    Algorithms of question answering in a computer system oriented on input and logical processing of text information are presented. A knowledge domain under consideration is social behavior of a person. A database of the system includes an internal representation of natural language sentences and supplemental information. The answer {\\it Yes} or {\\it No} is formed for a general question. A special question containing an interrogative word or group of interrogative words permits to find a subject, object, place, time, cause, purpose and way of action or event. Answer generation is based on identification algorithms of persons, organizations, machines, things, places, and times. Proposed algorithms of question answering can be realized in information systems closely connected with text processing (criminology, operation of business, medicine, document systems).

  15. A Multi-Objective Genetic Algorithm for determining efficient Risk-Based Inspection programs

    International Nuclear Information System (INIS)

    This paper proposes a coupling between Risk-Based Inspection (RBI) methodology and Multi-Objective Genetic Algorithm (MOGA) for defining efficient inspection programs in terms of inspection costs and risk level, which also comply with restrictions imposed by international standards and/or local government regulations. The proposed RBI+MOGA approach has the following advantages: (i) a user-defined risk target is not required; (ii) it is not necessary to estimate the consequences of failures; (iii) the inspection expenditures become more manageable, which allows assessing the impact of prevention investments on the risk level; (iv) the proposed framework directly provides, as part of the solution, the information on how the inspection budget should be efficiently spent. Then, genetic operators are tailored for solving this problem given the huge size of the search space. The ability of the proposed RBI+MOGA in providing efficient solutions is evaluated by means of two examples, one of them involving an oil and gas separator vessel subject to internal and external corrosion that cause thinning. The obtained results indicate that the proposed genetic operators significantly reduce the search space to be explored and RBI+MOGA is a valuable method to support decisions concerning the mechanical integrity of plant equipment. - Highlights: • This paper proposes an original RBI multi-objective-based framework. • The exhaustive evaluation of these feasible programs is impossible in practice. • Thus, the effort to accomplish the analysis is fairly reduced. • Tool to support efficient decisions related to mechanical integrity of equipment

  16. Object-based Image Classification of Arctic Sea Ice and Melt Ponds through Aerial Photos

    Science.gov (United States)

    Miao, X.; Xie, H.; Li, Z.; Lei, R.

    2013-12-01

    The last six years have marked the lowest Arctic summer sea ice extents in the modern era, with a new record summer minimum (3.4 million km2) set on 13 September 2012. It has been predicted that the Arctic could be free of summer ice within the next 25-30. The loss of Arctic summer ice could have serious consequences, such as higher water temperature due to the positive feedback of albedo, more powerful and frequent storms, rising sea levels, diminished habitats for polar animals, and more pollution due to fossil fuel exploitation and/ or increased traffic through the Northwest/ Northeast Passage. In these processes, melt ponds play an important role in Earth's radiation balance since they strongly absorb solar radiation rather than reflecting it as snow and ice do. Therefore, it is necessary to develop the ability of predicting the sea ice/ melt pond extents and space-time evolution, which is pivotal to prepare for the variation and uncertainty of the future environment, political, economic, and military needs. A lot of efforts have been put into Arctic sea ice modeling to simulate sea ice processes. However, these sea ice models were initiated and developed based on limited field surveys, aircraft or satellite image data. Therefore, it is necessary to collect high resolution sea ice aerial photo in a systematic way to tune up, validate, and improve models. Currently there are many sea ice aerial photos available, such as Chinese Arctic Exploration (CHINARE 2008, 2010, 2012), SHEBA 1998 and HOTRAX 2005. However, manually delineating of sea ice and melt pond from these images is time-consuming and labor-intensive. In this study, we use the object-based remote sensing classification scheme to extract sea ice and melt ponds efficiently from 1,727 aerial photos taken during the CHINARE 2010. The algorithm includes three major steps as follows. (1) Image segmentation groups the neighboring pixels into objects according to the similarity of spectral and texture information; (2) random forest ensemble classifier can distinguish the following objects: water, submerged ice, shadow, and ice/snow; and (3) polygon neighbor analysis can further separate melt ponds from submerged ice according to the spatial neighboring relationship. Our results illustrate the spatial distribution and morphological characters of melt ponds in different latitudes of the Arctic Pacific sector. This method can be applied to massive photos and images taken in past years and future years, in deriving the detailed sea ice and melt pond distribution and changes through years.

  17. The research of edge extraction and target recognition based on inherent feature of objects

    Science.gov (United States)

    Xie, Yu-chan; Lin, Yu-chi; Huang, Yin-guo

    2008-03-01

    Current research on computer vision often needs specific techniques for particular problems. Little use has been made of high-level aspects of computer vision, such as three-dimensional (3D) object recognition, that are appropriate for large classes of problems and situations. In particular, high-level vision often focuses mainly on the extraction of symbolic descriptions, and pays little attention to the speed of processing. In order to extract and recognize target intelligently and rapidly, in this paper we developed a new 3D target recognition method based on inherent feature of objects in which cuboid was taken as model. On the basis of analysis cuboid nature contour and greyhound distributing characteristics, overall fuzzy evaluating technique was utilized to recognize and segment the target. Then Hough transform was used to extract and match model's main edges, we reconstruct aim edges by stereo technology in the end. There are three major contributions in this paper. Firstly, the corresponding relations between the parameters of cuboid model's straight edges lines in an image field and in the transform field were summed up. By those, the aimless computations and searches in Hough transform processing can be reduced greatly and the efficiency is improved. Secondly, as the priori knowledge about cuboids contour's geometry character known already, the intersections of the component extracted edges are taken, and assess the geometry of candidate edges matches based on the intersections, rather than the extracted edges. Therefore the outlines are enhanced and the noise is depressed. Finally, a 3-D target recognition method is proposed. Compared with other recognition methods, this new method has a quick response time and can be achieved with high-level computer vision. The method present here can be used widely in vision-guide techniques to strengthen its intelligence and generalization, which can also play an important role in object tracking, port AGV, robots fields. The results of simulation experiments and theory analyzing demonstrate that the proposed method could suppress noise effectively, extracted target edges robustly, and achieve the real time need. Theory analysis and experiment shows the method is reasonable and efficient.

  18. Multi-Objective Ant Colony Optimization Based on the Physarum-Inspired Mathematical Model for Bi-Objective Traveling Salesman Problems

    Science.gov (United States)

    Zhang, Zili; Gao, Chao; Lu, Yuxiao; Liu, Yuxin; Liang, Mingxin

    2016-01-01

    Bi-objective Traveling Salesman Problem (bTSP) is an important field in the operations research, its solutions can be widely applied in the real world. Many researches of Multi-objective Ant Colony Optimization (MOACOs) have been proposed to solve bTSPs. However, most of MOACOs suffer premature convergence. This paper proposes an optimization strategy for MOACOs by optimizing the initialization of pheromone matrix with the prior knowledge of Physarum-inspired Mathematical Model (PMM). PMM can find the shortest route between two nodes based on the positive feedback mechanism. The optimized algorithms, named as iPM-MOACOs, can enhance the pheromone in the short paths and promote the search ability of ants. A series of experiments are conducted and experimental results show that the proposed strategy can achieve a better compromise solution than the original MOACOs for solving bTSPs. PMID:26751562

  19. 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.

  20. 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.

  1. EXTRACTION OF BENTHIC COVER INFORMATION FROM VIDEO TOWS AND PHOTOGRAPHS USING OBJECT-BASED IMAGE ANALYSIS

    Directory of Open Access Journals (Sweden)

    M. T. L. Estomata

    2012-07-01

    Full Text Available Mapping benthic cover in deep waters comprises a very small proportion of studies in the field of research. Majority of benthic cover mapping makes use of satellite images and usually, classification is carried out only for shallow waters. To map the seafloor in optically deep waters, underwater videos and photos are needed. Some researchers have applied this method on underwater photos, but made use of different classification methods such as: Neural Networks, and rapid classification via down sampling. In this study, accurate bathymetric data obtained using a multi-beam echo sounder (MBES was attempted to be used as complementary data with the underwater photographs. Due to the absence of a motion reference unit (MRU, which applies correction to the data gathered by the MBES, accuracy of the said depth data was compromised. Nevertheless, even with the absence of accurate bathymetric data, object-based image analysis (OBIA, which used rule sets based on information such as shape, size, area, relative distance, and spectral information, was still applied. Compared to pixel-based classifications, OBIA was able to classify more specific benthic cover types other than coral and sand, such as rubble and fish. Through the use of rule sets on area, less than or equal to 700 pixels for fish and between 700 to 10,000 pixels for rubble, as well as standard deviation values to distinguish texture, fish and rubble were identified. OBIA produced benthic cover maps that had higher overall accuracy, 93.78±0.85%, as compared to pixel-based methods that had an average accuracy of only 87.30±6.11% (p-value = 0.0001, ? = 0.05.

  2. 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

  3. A new method for multi-objective in core fuel management optimization using biogeography based algorithm

    International Nuclear Information System (INIS)

    Highlights: • BBO algorithm is capable of finding suitably optimized loading pattern. • It seems BBO reaches to better final parameter value in comparison with the PSO. • PSO exhibits faster convergence characteristics in comparison with BBO. • Even with same initial random patterns the BBO is found to outperform PSO. - Abstract: In this investigation, we developed a new optimization method, i.e., biogeography based optimization (BBO), for loading pattern optimization problem of pressurized water reactors. BBO is a novel stochastic force based on the science of biogeography. Biogeography is the schoolwork of geographical allotment of biological organisms. BBO make use of migration operator to share information between the problem solutions. The problem solutions are called as habitats and sharing of features is called migration. For the evaluation of the proposed method, we applied a multi-objective fitness function i.e., the maximization of reactivity at BOC and the flattening of power distribution are achieved efficiently and simultaneously. The neutronic calculation is done by CITATION and WIMS codes

  4. Correspondence of feature points on moving object in tracking system based on stabilization

    Science.gov (United States)

    Wang, Bin; Zhao, Yue-jin

    2008-12-01

    Camera systems are often unsteady on platform of airborne, car borne and ship borne. Stabilization algorithm can be used to eliminate impact of vibration. But image sequence after processing is different from original sequence. If there is a moving target in camera field, feature points on the target must be indentified and made sure corresponding relationship in processed sequence. To solve the problem that moving target features position and correspondence are difficult to identify in image sequence after image stabilization processing, background updating difference moving target detection algorithm based on motion analysis is proposed. It uses subsample mean and subsample variance and introduces the concept of background gray probability to identify feature points of moving target in the steady image sequence. In addition, to solve the problem of incomplete motion track of feature points caused by obstruction or weak target detection algorithm, partial limit incomplete smooth track algorithm is proposed. It is used to identify correspondence of feature points on the moving target, and to solve temporary occlusion of moving object. Experimental results show that moving target features position and correspondence can be identified quickly through the two algorithms. Single-frame processing speed can reach an average of 27 ms with DSP6416 processor. Image stabilization algorithm and the two algorithms can be combined to realize real-time tracking based on image stabilization.

  5. Wheel Torque Distribution of Four-Wheel-Drive Electric Vehicles Based on Multi-Objective Optimization

    Directory of Open Access Journals (Sweden)

    Cheng Lin

    2015-04-01

    Full Text Available The wheel driving torque on four-wheel-drive electric vehicles (4WDEVs can be modulated precisely and continuously, therefore maneuverability and energy-saving control can be carried out at the same time. In this paper, a wheel torque distribution strategy is developed based on multi-objective optimization to improve vehicle maneuverability and reduce energy consumption. In the high-layer of the presented method, sliding mode control is used to calculate the desired yaw moment due to the model inaccuracy and parameter error. In the low-layer, mathematical programming with the penalty function consisting of the yaw moment control offset, the drive system energy loss and the slip ratio constraint is used for wheel torque control allocation. The programming is solved with the combination of off-line and on-line optimization to reduce the calculation cost, and the optimization results are sent to motor controllers as torque commands. Co-simulation based on MATLAB® and Carsim® proves that the developed strategy can both improve the vehicle maneuverability and reduce energy consumption.

  6. Sensor explication: knowledge-based robotic plan execution through logical objects.

    Science.gov (United States)

    Budenske, J; Gini, M

    1997-01-01

    Complex robot tasks are usually described as high level goals, with no details on how to achieve them. However, details must be provided to generate primitive commands to control a real robot. A sensor explication concept that makes details explicit from general commands is presented. We show how the transformation from high-level goals to primitive commands can be performed at execution time and we propose an architecture based on reconfigurable objects that contain domain knowledge and knowledge about the sensors and actuators available. Our approach is based on two premises: 1) plan execution is an information gathering process where determining what information is relevant is a great part of the process; and 2) plan execution requires that many details are made explicit. We show how our approach is used in solving the task of moving a robot to and through an unknown, and possibly narrow, doorway; where sonic range data is used to find the doorway, walls, and obstacles. We illustrate the difficulty of such a task using data from a large number of experiments we conducted with a real mobile robot. The laboratory results illustrate how the proper application of knowledge in the integration and utilization of sensors and actuators increases the robustness of plan execution. PMID:18255901

  7. 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.

  8. 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.

  9. Multi-Objective Optimization Design for Cooling Unit of Automotive Exhaust-Based Thermoelectric Generators

    Science.gov (United States)

    Qiang, J. W.; Yu, C. G.; Deng, Y. D.; Su, C. Q.; Wang, Y. P.; Yuan, X. H.

    2015-10-01

    In order to improve the performance of cooling units for automotive thermoelectric generators, a study is carried out to optimize the cold side and the fin distributions arranged on its inner faces. Based on the experimental measurements and numerical simulations, a response surface model of different internal structures is built to analyze the heat transfer and pressure drop characteristics of fluid flow in the cooling unit. For the fin distributions, five independent variables including height, length, thickness, space and distance from walls are considered. An experimental study design incorporating the central composite design method is used to assess the influence of fin distributions on the temperature field and the pressure drop in the cooling units. The archive-based micro genetic algorithm (AMGA) is used for multi-objective optimization to analyze the sensitivity of the design variables and to build a database from which to construct the surrogate model. Finally, improvement measures are proposed for optimization of the cooling system and guidelines are provided for future research.

  10. Object-based analysis of hyperspectral and thermal infrared satellite imagery

    International Nuclear Information System (INIS)

    Full text: The use of satellite imagery for nuclear safeguards applications today is very much limited to visible and short-wave infrared data, due to at least two reasons: First, from a technical point of view, these data provide the best spatial resolution in the sub-meter range for the analysis of small-scale nuclear-related activities. Second, from the user's point, the (visual) interpretation of visible and near-infrared data is more obvious rather than the analysis of thermal infrared, hyperspectral or radar image data requiring extensive pre-processing and knowledge on the sensor. However, also satellite data from thermal infrared, hyperspectral and microwave sensors involve information being relevant for nuclear monitoring. The given paper proposes an object-bases procedure for the combined analysis of high-resolution optical, thermal infrared and hyperspectral satellite imagery for different nuclear safeguards-related tasks. Some case studies using ASTER, HYPERION and QUICKBIRD data will demonstrate the advantages of this approach. 1. MONITORING OF URANIUM MINES AND MILLING. Under Integrated Safeguards all States having signed the additional protocol are obliged to declare the whole states production of uranium. Information on the production of individual mines and concentration plants have to be provided on request to the IAEA. In order to be able to verify the States declaration and to guarantee the absence of undeclared mining and/or milling activities, satellite imagery data are also taken into consideration Safeguards-related information identifiable by satellite imagery are signs of water, power and chemical usage, level of mining respectively milling activities, geographic extent of mining activities and the presence of other industrial activities associated with mining or milling respectively. The question whether hyperspectral data may be used to determine the surface mineralogy of exposed uranium tailings, has been controversially discussed recently. According to those results, analysing solely hyperspectral image data will not be lead to the identification of uranium activities or to the differentiation of uranium mining activities from other types of mining respectively. Nevertheless, hyperspectral data provide relevant information and thus the context within other remotely acquired data, such as high resolution imagery, can be interpreted. An object-based procedure is developed in order to use both the hyperspectral information and the shape and topology features from the high-resolution imagery. By this means, the classification accuracy and the interpretation of the site could be enhanced. 2. MONITORING THE OPERATIONAL STATUS OF NUCLEAR FACILITIES. Since different materials (soils, plants, water, man-made materials) selectively absorb shortwave solar energy and radiate the long-wave (thermal) energy in a specific way, it is possible to determine the type of material based on the thermal emission characteristics of the material - in case the atmospheric conditions and other influencing factors are known. Moreover, thermal data could be used to evaluate whether significant changes have taken place in the thermal characteristics of these materials over time. Thus, the use of thermal infrared imagery for the monitoring of (heat generating) nuclear facilities seems to be reasonable, even though the spatial resolution of satellite-based thermal infrared sensor bands is still limited to 60m (LANDSAT 7) and 90m (ASTER) respectively. The image data given by the thermal infrared system enables the user to analyse thermal differences between the area of interest and its neighbourhood and thus to derive information on the operational status of the facility. The description of an object as 'cold' or 'warm' compared to its neighbourhood has to be given in connection with the material and environmental parameters. Environmental influences may overlay or modify the natural or artificial thermal radiation or even result in thermal anomalies. The thermal behaviour of two different materials during the course o f th

  11. Object Search for the Internet of Things Using Tag-based Location Signatures

    OpenAIRE

    Jung-Sing Jwo; Ting-Chia Chen; Mengru Tu

    2012-01-01

    In this paper, an object search solution for the Internet of Things (IoT) is proposed. This study first differentiates localization and searching. Localization is to calculate an object’s current location. Searching is to return a set of locations where a target object could be. It is possible that the locations of the returned set are not contiguous. Searching accuracy can be improved if the number of the returned locations is small. Even though localization technique is applicable to ...

  12. Ladar signature simulation

    Science.gov (United States)

    Estep, Jeffrey A.; Gu, Zu-Han

    1992-09-01

    The design of laser radars and the determination of laser radar signatures of various vehicles require accurate data on the monostatic reflectivity of many target materials to far-field laser illumination at many different wavelengths. Modelling software is required that will take the monostatic reflectance data as an input, and combine this data with geometrical models to develop a laser radar signature. Recently a program has been started at Surface Optics Corporation to design and develop a laboratory system for the monostatic measurement of the bidirectional reflectance properties of target samples and generation of laser radar signatures from this data. This system, the Monostatic Bidirectional Reflectometer (MBR), will be flexible enough to accommodate various laser sources and detectors. The MBR will be capable of accurate measurement of the BRDF of target samples and combining this data with geometrical target models for signature predictions which will be further used for development of hardware in the loop simulations at a reduction in the cost of live-fire evaluation of various weapon systems.

  13. Understanding Developmental Changes in the Stability and Flexibility of Spatial Categories Based on Object Relatedness

    Science.gov (United States)

    Hund, Alycia M.; Foster, Emily K.

    2008-01-01

    Two experiments examined the flexibility and stability with which children and adults organize locations into categories on the basis of object relatedness. Seven-, 9-, and 11-year-olds and adults learned the locations of 20 objects belonging to 4 categories. Displacement patterns revealed that children and adults used object cues to organize the…

  14. 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

  15. Complementary Hemispheric Asymmetries in Object Naming and Recognition: A Voxel-Based Correlational Study

    Science.gov (United States)

    Acres, K.; Taylor, K. I.; Moss, H. E.; Stamatakis, E. A.; Tyler, L. K.

    2009-01-01

    Cognitive neuroscientific research proposes complementary hemispheric asymmetries in naming and recognising visual objects, with a left temporal lobe advantage for object naming and a right temporal lobe advantage for object recognition. Specifically, it has been proposed that the left inferior temporal lobe plays a mediational role linking…

  16. 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.

  17. Modelling of cooperating robotized systems with the use of object-based approach

    Science.gov (United States)

    Foit, K.; Gwiazda, A.; Banas, W.; Sekala, A.; Hryniewicz, P.

    2015-11-01

    Today's robotized manufacturing systems are characterized by high efficiency. The emphasis is placed mainly on the simultaneous work of machines. It could manifest in many ways, where the most spectacular one is the cooperation of several robots, during work on the same detail. What's more, recently a dual-arm robots are used that could mimic the manipulative skills of human hands. As a result, it is often hard to deal with the situation, when it is necessary not only to maintain sufficient precision, but also the coordination and proper sequence of movements of individual robots’ arms. The successful completion of this task depends on the individual robot control systems and their respective programmed, but also on the well-functioning communication between robot controllers. A major problem in case of cooperating robots is the possibility of collision between particular links of robots’ kinematic chains. This is not a simple case, because the manufacturers of robotic systems do not disclose the details of the control algorithms, then it is hard to determine such situation. Another problem with cooperation of robots is how to inform the other units about start or completion of part of the task, so that other robots can take further actions. This paper focuses on communication between cooperating robotic units, assuming that every robot is represented by object-based model. This problem requires developing a form of communication protocol that the objects can use for collecting the information about its environment. The approach presented in the paper is not limited to the robots and could be used in a wider range, for example during modelling of the complete workcell or production line.

  18. 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 ABSTRACT: 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. ABSTRAK: Pembangunan lestari bermatlamat memperbaiki dan mengekalkan kesejahteraan rakyat serta ekologi. Walau bagaimanapun, kertas kajian ini hanya memberi tumpuan kepada aspek-aspek ekologi. Pemilihan penentu perlindungan serta keselamatan bagi aspek ekologi memainkan peranan yang amat penting dalam meningkatkan kualiti alam sekitar di Malaysia. Kertas kajian ini telah menggunakan kaedah Wang dan Lee (2009 dan Yong (2006 yang mengaplikasikan kaedah TOPSIS kabur berdasarkan pemberat subjektif dan objektif. Terdapat empat alternatif yang akan diuji iaitu: pencegahan pencemaran (A1, pemuliharaan (A2, pengurusan yang baik (A3, kesedaran orang awam (A4. Selain itu, terdapat empat kriteria yang perlu dipertimbangkan: faktor kualiti air (C1, faktor kualiti tanah (C2, faktor kualiti udara (C3, faktor kepelbagaian biologi (C4. Kesimpulannya, contoh pengiraan untuk memperoleh penentu pemilihan perlindungan ekologi telah digunakan bagi menunjukkan kaedah yang dicadangkan.KEYWORDS: sustainable development; ecological factors; subjective and objective weight; fuzzy TOPSIS

  19. 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.

  20. 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.