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. Ladar-based terrain cover classification

    Science.gov (United States)

    Macedo, Jose; Manduchi, Roberto; Matthies, Larry H.

    2001-09-01

    An autonomous vehicle driving in a densely vegetated environment needs to be able to discriminate between obstacles (such as rocks) and penetrable vegetation (such as tall grass). We propose a technique for terrain cover classification based on the statistical analysis of the range data produced by a single-axis laser rangefinder (ladar). We first present theoretical models for the range distribution in the presence of homogeneously distributed grass and of obstacles partially occluded by grass. We then validate our results with real-world cases, and propose a simple algorithm to robustly discriminate between vegetation and obstacles based on the local statistical analysis of the range data.

  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. Photographic-based target models for LADAR applications

    Science.gov (United States)

    Jack, James T.; Delashmit, Walter H.

    2009-05-01

    A long standing need for the application of laser radar (LADAR) to a wider range of targets is a technique for creating a "target model" from target photographs. This is feasible since LADAR images are 3D and photographs at selected azimuth/elevation angles will allow the required models to be created. Preferred photographic images of a wide range of selected targets were specified and collected. These photographs were processed using code developed in house and some commercial software packages. These "models" were used in model-based automatic target recognition (ATR) algorithms. The ATR performance was excellent. This technique differs significantly from other techniques for creating target models. Those techniques require CAD models which are much harder to manipulate and contain extraneous detail. The technique in this paper develops the photographic-based target models in component form so that any component (e.g., turret of a tank) can be independently manipulated, such as rotating the turret. This new technique also allows models to be generated for targets for which no actual LADAR data has ever been collected. A summary of the steps used in the modeling process is as follows: start with a set of input photographs, calibrate the imagery into a 3D world space to generate points corresponding to target features, create target geometry by connecting points with surfaces, mark all co-located points in each image view and verify alignment of points, place in a 3D space, create models by creating surfaces (i.e., connect points with planar curves) and scale target into real-world coordinates.

  5. 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...

  6. 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.

  7. 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

  8. Simulation of laser detection and ranging (LADAR) and forward-looking infrared (FLIR) data for autonomous tracking of airborne objects

    Science.gov (United States)

    Powell, Gavin; Markham, Keith C.; Marshall, David

    2000-06-01

    This paper presents the results of an investigation leading into an implementation of FLIR and LADAR data simulation for use in a multi sensor data fusion automated target recognition system. At present the main areas of application are in military environments but systems can easily be adapted to other areas such as security applications, robotics and autonomous cars. Recent developments have been away from traditional sensor modeling and toward modeling of features that are external to the system, such as atmosphere and part occlusion, to create a more realistic and rounded system. We have implemented such techniques and introduced a means of inserting these models into a highly detailed scene model to provide a rich data set for later processing. From our study and implementation we are able to embed sensor model components into a commercial graphics and animation package, along with object and terrain models, which can be easily used to create a more realistic sequence of images.

  9. LADAR Proximity Fuze - System Study -

    OpenAIRE

    Blanquer, Eric

    2007-01-01

    LADAR (Laser Detection and Ranging) systems constitue a direct extension of the conventional radar techniques. Because they operate at much shorter wavelengths, LADARs have the unique capability to generate 3D images of objects. These laser systems have many applications in both the civilian and the defence fields concerning target detection and identification. The extraction of these features depends on the processing algorithms, target properties and 3D images quality. In order to support f...

  10. 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.

  11. Ground vehicle based ladar for standoff detection of road-side hazards

    Science.gov (United States)

    Hollinger, Jim; Close, Ryan

    2015-05-01

    In recent years, the number of commercially available LADAR (also referred to as LIDAR) systems have grown with the increased interest in ground vehicle robotics and aided navigation/collision avoidance in various industries. With this increased demand the cost of these systems has dropped and their capabilities have increased. As a result of this trend, LADAR systems are becoming a cost effective sensor to use in a number of applications of interest to the US Army. One such application is the standoff detection of road-side hazards from ground vehicles. This paper will discuss detection of road-side hazards partially concealed by light to medium vegetation. Current algorithms using commercially available LADAR systems for detecting these targets will be presented, along with results from relevant data sets. Additionally, optimization of commercial LADAR sensors and/or fusion with Radar will be discussed as ways of increasing detection ability.

  12. MBE based HgCdTe APDs and 3D LADAR sensors

    Science.gov (United States)

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

    2007-04-01

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

  13. Extracting intelligence from ladar sensing modalities

    Science.gov (United States)

    Burwinkel, Allan M.; Shelley, Stuart J.; Ajose, Cinque M.

    2011-06-01

    Modern LADAR sensors have the potential to utilize a number of sensing modalities that provide a rich array of information in addition to traditional 3D geometry. Imaging polarization, multi-spectral reflectance/absorption and vibration spectral signature characteristics can all be sensed, potentially in a single LADAR sensor. This paper will examine how these rich sensing capabilities enhance the utility of LADAR signature exploitation. This research utilizes a strong understanding of underlying physical phenomena, enabling the development of data exploitation capabilities that are not brittle to small variations from assumed targets and environmental conditions, and minimizing the need for experimentally obtained training data. Physics-based signal processing research has demonstrated a promising ability to extract useful and actionable intelligence from the various sensing modalities of modern LADAR systems. A summary of the intelligence provided by the LADAR sensing modalities is presented as well as a demonstration of how the individual modes and combinations of LADAR sensing modes can be leveraged to add unique and valuable information to intelligence gathering missions. Particular utility is demonstrated for detection of adversary presence in cluttered, obstructed, hidden or underground environments. Furthermore, research has shown 3D geometry, polarization, multi-spectral and vibrometry LADAR sensing modalities can provide valuable intelligence for identifying and/or classifying the adversary and analyzing threat.

  14. 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

  15. 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...

  16. 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),...

  17. 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.

  18. Design and validation of the eyesafe ladar testbed (ELT) using the LadarSIM system simulator

    Science.gov (United States)

    Neilsen, Kevin D.; Budge, Scott E.; Pack, Robert T.; Fullmer, R. Rees; Cook, T. Dean

    2009-05-01

    The development of an experimental full-waveform LADAR system has been enhanced with the assistance of the LadarSIM system simulation software. The Eyesafe LADAR Test-bed (ELT) was designed as a raster scanning, single-beam, energy-detection LADAR with the capability of digitizing and recording the return pulse waveform at up to 2 GHz for 3D off-line image formation research in the laboratory. To assist in the design phase, the full-waveform LADAR simulation in LadarSIM was used to simulate the expected return waveforms for various system design parameters, target characteristics, and target ranges. Once the design was finalized and the ELT constructed, the measured specifications of the system and experimental data captured from the operational sensor were used to validate the behavior of the system as predicted during the design phase. This paper presents the methodology used, and lessons learned from this "design, build, validate" process. Simulated results from the design phase are presented, and these are compared to simulated results using measured system parameters and operational sensor data. The advantages of this simulation-based process are also presented.

  19. 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).

  20. 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...

  1. 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 ...

  2. Foliage discrimination using a rotating ladar

    Science.gov (United States)

    Castano, A.; Matthies, L.

    2003-01-01

    We present a real time algorithm that detects foliage using range from a rotating laser. Objects not classified as foliage are conservatively labeled as non-driving obstacles. In contrast to related work that uses range statistics to classify objects, we exploit the expected localities and continuities of an obstacle, in both space and time. Also, instead of attempting to find a single accurate discriminating factor for every ladar return, we hypothesize the class of some few returns and then spread the confidence (and classification) to other returns using the locality constraints. The Urbie robot is presently using this algorithm to descriminate drivable grass from obstacles during outdoor autonomous navigation tasks.

  3. 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 <10 cm range accuracy through foliage in real-time. The 3D imaging flash ladar is designed for a STUAS with a complete system SWAP estimate of <9 kg, <0.2 m3 and <350 W power. The system is modeled using LadarSIM, a MATLAB® 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.

  4. 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...

  5. 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.

  6. ATA algorithm suite for co-boresighted pmmw and ladar imagery

    Science.gov (United States)

    Stevens, Mark R.; Snorrason, Magnus; Ablavsky, Vitaly; Amphay, Sengvieng A.

    2001-08-01

    The need for air-to-ground missiles with day/night, adverse weather and pinpoint accuracy Autonomous Target Acquisition (ATA) seekers is essential for today's modern warfare scenarios. Passive millimeter wave (PMMW) sensors have the ability to see through clouds; in fact they tend to show metallic objects in high contrast regardless of weather conditions. However, their resolution is very low when compared with other ATA sensor such as laser radar (LADAR). We present an ATA algorithm suite that combines the superior target detection potential of PMMW with the high-quality segmentation and recognition abilities of LADAR. Preliminary detection and segmentation results are presented for a set of image-pairs of military vehicles that were collected for this project using an 89 Ghz, 18 inch aperture PMMW sensor from TRW and a 1.06 (mu) high-resolution LADAR.

  7. 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 μm 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

  8. Object-Based Benefits without Object-Based Representations

    OpenAIRE

    Alvarez, George Angelo; Fougnie, Daryl; Cormiea, Sarah M

    2012-01-01

    The organization of visual information into objects strongly influences visual memory: Displays with objects defined by two features (e.g. color, orientation) are easier to remember than displays with twice as many objects defined by one feature (Olson & Jiang, 2002). Existing theories suggest that this ‘object-benefit’ is based on object-based limitations in working memory: because a limited number of objects can be stored, packaging features together so that fewer objects have to be remembe...

  9. 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.

  10. An Object -Based VRML Interface

    Science.gov (United States)

    Araya, Shinji; Suzaki, Kenichi; Miyake, Yoshihiro

    This paper proposes an object-based VRML interface that can reduce the burden of both users and developers. In order to automatically generate the object menu, a new VRML node type that defines the names of objects in a scene graph is introduced together with the methods for real-time control of an active viewpoint node.

  11. Sparsity based Single Object Tracking

    OpenAIRE

    Glincy Abraham; K. A Narayanankutty; Soman, K. P.

    2013-01-01

    Object tracking has importance in various video processing applications like video surveillance, perceptual user interface driver assistance, tracking etc. This paper deals with a new tracking technique that combines the dictionary based background subtraction along with sparsity based tracking. The speed and performance challenges faced during the sparsity based tracking alone are addressed, as it is based on a background subtraction preprocessing and local compressive tracking. It also over...

  12. 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...

  13. 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...

  14. 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…

  15. 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)

  16. Infrared-based object tracking

    Science.gov (United States)

    Gervais, Jon; Youngblood, Austin; Delashmit, Walter H.

    2009-05-01

    Often it is necessary to track moving objects on horizontal paths. Human error and the associated cost and dangers of using humans lead to a requirement to automate this task. The system presented here was designed, built and tested. The system uses an IR beacon and a microcontroller receiver/controller module. The design consists of a field programmable gate array (FPGA) based IR transmitter and a microcontroller based IR receiver/controller. The design consisted of two main parts, the transmitter (beacon) and the receiver/controller module. The receiver was implemented with a FPGA so that the characteristics of the beacon signal could be adjusted more quickly and with greater precision. The controller module was integrated with the receivers and detailed system integration tests were performed. Measurements were collected, recorded and analyzed.

  17. 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.

  18. 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...

  19. 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.

  20. 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.

  1. 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 (<$20k) UAV system fitted with ladar and electro-optical (EO) sensors. A texel camera fuses calibrated ladar and EO data upon simultaneous capture, creating a texel image. This eliminates the problem of fusing the data in a post-processing step and enables both 2D- and 3D-image registration techniques to be used. This paper describes formation of TDEMs using 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.

  2. Speedy Object Detection Based on Shape

    Directory of Open Access Journals (Sweden)

    Y. Jayanta Singh

    2013-07-01

    Full Text Available This study is a part of design of an audio system for in-house object detection system for visually impaired,low vision personnel by birth or by an accident ordue to old age. The input of the system will be scene andoutput as audio. Alert facility is provided based on severity levels of the objects (snake, broke glass etc andalso during difficulties. The study proposed techniques to provide speedy detection of objects based onshapes and its scale. Features are extraction to have minimum spaces using dynamic scaling. From ascene, clusters of objects are formed based on thescale and shape. Searching is performed among theclusters initially based on the shape, scale, meancluster value and index of object(s. The minimumoperation to detect the possible shape of the object is performed. In case the object does not have alikelymatching shape, scale etc, then the several operations required for an object detection will not perform;instead, it will declared as a new object. In suchway, this study finds a speedy way of detecting objects.

  3. SPEEDY OBJECT DETECTION BASED ON SHAPE

    Directory of Open Access Journals (Sweden)

    Y. Jayanta Singh

    2013-06-01

    Full Text Available This study is a part of design of an audio system for in-house object detection system for visually impaired, low vision personnel by birth or by an accident or due to old age. The input of the system will be scene and output as audio. Alert facility is provided based on severity levels of the objects (snake, broke glass etc and also during difficulties. The study proposed techniques to provide speedy detection of objects based on shapes and its scale. Features are extraction to have minimum spaces using dynamic scaling. From a scene, clusters of objects are formed based on the scale and shape. Searching is performed among the clusters initially based on the shape, scale, mean cluster value and index of object(s. The minimum operation to detect the possible shape of the object is performed. In case the object does not have a likely matching shape, scale etc, then the several operations required for an object detection will not perform; instead, it will declared as a new object. In such way, this study finds a speedy way of detecting objects.

  4. 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

  5. Building a Knowledge Base from Learning Objects

    OpenAIRE

    Fredlund, Per Kristen

    2005-01-01

    The goal of this thesis has been to investigate if it is possible to develop a knowledge structure,knowledge base, based on learning objects. In this connection a learning object is a digital unitwhich should, as a minimum, contain a picture and some text. Most likely a learning objectwould function as a container with anchors for video, animations and links to html-pages.For every learning object there exists a textual description. If we consider the learning object asan overhead presented i...

  6. 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.

  7. Retratamento de LASIK com fotoablao personalizada versus fotoablao 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 primrio convencional. MTODOS: Estudo retrospectivo de reviso de pronturios consecutivos, de 38 olhos em 38 pacientes, submetidos a retratamento [...] de LASIK para correo 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 variveis foram comparadas: acuidade visual de alto contraste e refrao manifesta. A qualidade visual foi estimada e comparada atravs de inqurito subjetivo proposto aos pacientes. RESULTADOS: No houve diferena estatstica entre os grupos comparando-se as variveis estudadas. O equivalente esfrico ps-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 aberraes pr-operatrio foi maior do que o ps-operatrio 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

  8. Coding Transparency in Object-Based Video

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Sren

    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...

  9. 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.

  10. 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.

  11. 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.

  12. Time reversed photonic beamforming of arbitrary waveform ladar arrays

    Science.gov (United States)

    Cox, Joseph L.; Zmuda, Henry; Bussjaeger, Rebecca J.; Erdmann, Reinhard K.; Fanto, Michael L.; Hayduk, Michael J.; Malowicki, John E.

    2007-04-01

    Herein is described a novel approach of performing adaptive photonic beam forming of an array of optical fibers with the expressed purpose of performing laser ranging. The beam forming technique leverages the concepts of time reversal, previously implemented in the sonar community, and wherein photonic implementation has recently been described for use by beamforming of ultra-wideband radar arrays. Photonic beam forming is also capable of combining the optical output of several fiber lasers into a coherent source, exactly phase matched on a pre-determined target. By implementing electro-optically modulated pulses from frequency chirped femtosecond-scale laser pulses, ladar waveforms can be generated with arbitrary spectral and temporal characteristics within the limitations of the wide-band system. Also described is a means of generating angle/angle/range measurements of illuminated targets.

  13. 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.

  14. 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.

  15. Top-down facilitation of visual object recognition: object-based and context-based contributions.

    Science.gov (United States)

    Fenske, Mark J; Aminoff, Elissa; Gronau, Nurit; Bar, Moshe

    2006-01-01

    The neural mechanisms subserving visual recognition are traditionally described in terms of bottom-up analysis, whereby increasingly complex aspects of the visual input are processed along a hierarchical progression of cortical regions. However, the importance of top-down facilitation in successful recognition has been emphasized in recent models and research findings. Here we consider evidence for top-down facilitation of recognition that is triggered by early information about an object, as well as by contextual associations between an object and other objects with which it typically appears. The object-based mechanism is proposed to trigger top-down facilitation of visual recognition rapidly, using a partially analyzed version of the input image (i.e., a blurred image) that is projected from early visual areas directly to the prefrontal cortex (PFC). This coarse representation activates in the PFC information that is back-projected as "initial guesses" to the temporal cortex where it presensitizes the most likely interpretations of the input object. In addition to this object-based facilitation, a context-based mechanism is proposed to trigger top-down facilitation through contextual associations between objects in scenes. These contextual associations activate predictive information about which objects are likely to appear together, and can influence the "initial guesses" about an object's identity. We have shown that contextual associations are analyzed by a network that includes the parahippocampal cortex and the retrosplenial complex. The integrated proposal described here is that object- and context-based top-down influences operate together, promoting efficient recognition by framing early information about an object within the constraints provided by a lifetime of experience with contextual associations. PMID:17027376

  16. 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.

  17. Imaging signal-to-noise ratio of synthetic aperture ladar

    Science.gov (United States)

    Liu, Liren

    2015-09-01

    On the basis of the Poisson photocurrent statistics in the photon-limited heterodyne detection, in this paper, the signal-to-noise ratios in the receiver in the time domain and on the focused 1-D image and 2-D image in the space domain are derived for both the down-looking and side-looking synthetic aperture imaging ladars using PIN or APD photodiodes. The major shot noises in the down-looking SAIL and the side-looking SAIL are, respectively, from the dark current of photodiode and the local beam current. It is found that the ratio of 1-D image SNR to receiver SNR is proportional to the number of resolution elements in the cross direction of travel and the ratio of 2-D image SNR to 1-D image SNR is proportional to the number of resolution elements in the travel direction. And the sensitivity, the effect of Fourier transform of sampled signal, and the influence of time response of detection circuit are discussed, too. The study will help to correctly design a SAIL system.

  18. 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...

  19. 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.

  20. Ontology Based Object Learning and Recognition

    OpenAIRE

    Maillot, Nicolas

    2005-01-01

    This thesis deals with the problem of complex object recognition. The proposed approach takes place in the conceptual framework of cognitive vision. This thesis shows how an object categorization system is set up in three phases.The knowledge acquisition phase consists of acquiring domain knowledge as a taxonomy/partonomy of domain classes. It also consists of acquiring the visual description of these domain classes. This description is driven by a visual concept ontology composed of several ...

  1. ROIC for gated 3D imaging LADAR receiver

    Science.gov (United States)

    Chen, Guoqiang; Zhang, Junling; Wang, Pan; Zhou, Jie; Gao, Lei; Ding, Ruijun

    2013-09-01

    Time of flight laser range finding, deep space communications and scanning video imaging are three applications requiring very low noise optical receivers to achieve detection of fast and weak optical signal. HgCdTe electrons initiated avalanche photodiodes (e-APDs) in linear multiplication mode is the detector of choice thanks to its high quantum efficiency, high gain at low bias, high bandwidth and low noise factor. In this project, a readout integrated circuit of hybrid e-APD focal plane array (FPA) with 100um pitch for 3D-LADAR was designed for gated optical receiver. The ROIC works at 77K, including unit cell circuit, column-level circuit, timing control, bias circuit and output driver. The unit cell circuit is a key component, which consists of preamplifier, correlated double Sampling (CDS), bias circuit and timing control module. Specially, the preamplifier used the capacitor feedback transimpedance amplifier (CTIA) structure which has two capacitors to offer switchable capacitance for passive/active dual mode imaging. The main circuit of column-level circuit is a precision Multiply-by-Two circuit which is implemented by switched-capacitor circuit. Switched-capacitor circuit is quite suitable for the signal processing of readout integrated circuit (ROIC) due to the working characteristics. The output driver uses a simply unity-gain buffer. Because the signal is amplified in column-level circuit, the amplifier in unity-gain buffer uses a rail-rail amplifier. In active imaging mode, the integration time is 80ns. Integrating current from 200nA to 4uA, this circuit shows the nonlinearity is less than 1%. In passive imaging mode, the integration time is 150ns. Integrating current from 1nA to 20nA shows the nonlinearity less than 1%.

  2. 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

  3. Interval-based Specification of Concurrent Objects

    DEFF Research Database (Denmark)

    Lvengreen, Hans Henrik; Srensen, 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...

  4. Monitoring objects orbiting earth using satellite-based telescopes

    Science.gov (United States)

    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.

  5. 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 objects physical extension, gradually becomes inappropriate. Extended object tracking (EOT) technology is able to obtain more information about the object through jointly estimating both centroids 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...

  6. Content based image retrieval through object features

    OpenAIRE

    R Meenakshi

    2014-01-01

    Digital images are an increasingly important class of data, especially as computers become more usable with greater memory and communication capacities. As the demand for digital images increases, the need to store and retrieve images in an intuitive and efficient manner arises. These approaches can roughly be classified into three categories such as text-based, content-based and semantic based. ARC-BC or convexity measures. The aim of this thesis to show that the rate of retrieval can be ...

  7. 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...

  8. 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

  9. Content-Based Object Movie Retrieval and Relevance Feedbacks

    OpenAIRE

    Lee, Greg C.; 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...

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

    Science.gov (United States)

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

    2014-10-14

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

  11. Attending to Motion: an object-based approach

    OpenAIRE

    Belardinelli, Anna

    2010-01-01

    Visual attention is the biological mechanism allowing to turn mere sensing into conscious perception. In this process, object-based modulation of attention provides a further layer between low-level space/feature-based region selection and full object recognition. In this context, motion is a very powerful feature, naturally attracting our gaze and yielding rapid and effective shape distinction. Moving from a pixel-based account of attention to the definition of proto-objects as perc...

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

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Sren

    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...

  13. Propagation of geotags based on object duplicate detection

    OpenAIRE

    Vajda, Péter; Ivanov, Ivan; Lee, Jong-Seok; Goldmann, Lutz; Ebrahimi, Touradj

    2010-01-01

    In this paper, we consider the use of object duplicate detection for the propagation of geotags from a small set of images with location names (IPTC) to a large set of non-tagged images. The motivation behind this idea is that images of individual locations usually contain specific objects such as monuments, buildings or signs. Therefore, object duplicate detection can be used to establish the correspondence between tagged and non-tagged images. Our recent graph based object duplicate detecti...

  14. 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.

  15. Object-based attentional facilitation and inhibition are neuropsychologically dissociated.

    Science.gov (United States)

    Smith, Daniel T; Ball, Keira; Swalwell, Robert; Schenk, Thomas

    2016-01-01

    Salient peripheral cues produce a transient shift of attention which is superseded by a sustained inhibitory effect. Cueing part of an object produces an inhibitory cueing effect (ICE) that spreads throughout the object. In dynamic scenes the ICE stays with objects as they move. We examined object-centred attentional facilitation and inhibition in a patient with visual form agnosia. There was no evidence of object-centred attentional facilitation. In contrast, object-centred ICE was observed in 3 out of 4 tasks. These inhibitory effects were strongest where cues to objecthood were highly salient. These data are evidence of a neuropsychological dissociation between the facilitatory and inhibitory effects of attentional cueing. From a theoretical perspective the findings suggest that 'grouped arrays' are sufficient for object-based inhibition, but insufficient to generate object-centred attentional facilitation. PMID:26551577

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

    Science.gov (United States)

    Moussa, A.; El-Sheimy, N.

    2012-07-01

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

  17. Model-based detection, segmentation, and classification of compact objects

    Science.gov (United States)

    Carlotto, Mark J.

    2015-05-01

    A unified model-based approach to ATR that uses 3D models to control detection, segmentation, and classification is described. Objects are modeled by rectangular boxes whose dimensions are Gaussian random variables. A fast predictor estimates the size and shape of expected objects in the image, which controls detection and segmentation algorithms. Segmentation fits oriented rectangles (length x width @ pose) to object-like regions detected using a multi-level thresholding/region tracking approach. Detections are classified by comparing measured to predicted region length and width in the pose direction. The method is fast and requires only a coarse characterization of objects/object classes.

  18. Automatic fuzzy object-based analysis of VHSR images for urban objects extraction

    Science.gov (United States)

    Sebari, Imane; He, Dong-Chen

    2013-05-01

    We present an automatic approach for object extraction from very high spatial resolution (VHSR) satellite images based on Object-Based Image Analysis (OBIA). The proposed solution requires no input data other than the studied image. Not input parameters are required. First, an automatic non-parametric cooperative segmentation technique is applied to create object primitives. A fuzzy rule base is developed based on the human knowledge used for image interpretation. The rules integrate spectral, textural, geometric and contextual object proprieties. The classes of interest are: tree, lawn, bare soil and water for natural classes; building, road, parking lot for man made classes. The fuzzy logic is integrated in our approach in order to manage the complexity of the studied subject, to reason with imprecise knowledge and to give information on the precision and certainty of the extracted objects. The proposed approach was applied to extracts of Ikonos images of Sherbrooke city (Canada). An overall total extraction accuracy of 80% was observed. The correctness rates obtained for building, road and parking lot classes are of 81%, 75% and 60%, respectively.

  19. Road environment perception algorithm based on object semantic probabilistic model

    Science.gov (United States)

    Liu, Wei; Wang, XinMei; Tian, Jinwen; Wang, Yong

    2015-12-01

    This article seeks to discover the object categories' semantic probabilistic model (OSPM) based on statistical test analysis method. We applied this model on road forward environment perception algorithm, including on-road object recognition and detection. First, the image was represented by a set composed of words (local feature regions). Then, found the probability distribution among image, local regions and object semantic category based on the new model. In training, the parameters of the object model are estimated. This is done by using expectation-maximization in a maximum likelihood setting. In recognition, this model is used to classify images by using a Bayesian manner. In detection, the posterios is calculated to detect the typical on-road objects. Experiments release the good performance on object recognition and detection in urban street background.

  20. 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.

  1. RFID and IP Based Object Identification in Ubiquitous Networking

    Directory of Open Access Journals (Sweden)

    Nisha Vaghela

    2012-10-01

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

  2. 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.

  3. 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.

  4. Distributed Shared Memory Consistency Object-based Model

    OpenAIRE

    Abdelfatah A. Yahya; Rana M.I. Bader

    2007-01-01

    A novel model that describes consistency in shared memory was developed, presented and discussed. The new object-based model handles errors of inaccuracy and misrepresentation in distributed shared memory process. The issue of misalignment was also covered.

  5. Efficient, dense, object-based segmentation from RGBD video

    OpenAIRE

    Ghafarianzadeh, Mahsa; Blaschko, Matthew; Sibley, Gabe

    2016-01-01

    Ghafarianzadeh M., Blaschko M., Sibley G., ''Efficient, dense, object-based segmentation from RGBD video'', IEEE international conference on robotics and automation - ICRA 2016, May 16-21, 2016, Stockholm, Sweden (accepted).

  6. 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...

  7. Autocorrelation based reconstruction of two-dimensional binary objects

    International Nuclear Information System (INIS)

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

  8. 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

  9. Inheritance in Actor Based Concurrent Object-Oriented Languages

    OpenAIRE

    Kafura, Dennis G.; Lee, Keung Hae

    1988-01-01

    Inheritance is a valuable mechanism which enhances reusability and maintainability of software. A language design based on the actor model of concurrent computation faces a serious problem arising from the interference between concurrency and inheritance. A similar problem also occurs in other concurrent object-oriented languages. In this paper, we describe problems found in existing concurrent object-oriented languages. We present a solution which is based on a concept called behavior abstra...

  10. 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.

  11. 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.

  12. Object-based mapping of drumlins from DTMs

    Science.gov (United States)

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

    2012-04-01

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

  13. 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.

  14. Vector ordinal optimization based multi-objective transmission planning

    International Nuclear Information System (INIS)

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

  15. Research on moving object detection based on frog's eyes

    Science.gov (United States)

    Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

    2008-12-01

    On the basis of object's information processing mechanism with frog's eyes, this paper discussed a bionic detection technology which suitable for object's information processing based on frog's vision. First, the bionics detection theory by imitating frog vision is established, it is an parallel processing mechanism which including pick-up and pretreatment of object's information, parallel separating of digital image, parallel processing, and information synthesis. The computer vision detection system is described to detect moving objects which has special color, special shape, the experiment indicates that it can scheme out the detecting result in the certain interfered background can be detected. A moving objects detection electro-model by imitating biologic vision based on frog's eyes is established, the video simulative signal is digital firstly in this system, then the digital signal is parallel separated by FPGA. IN the parallel processing, the video information can be caught, processed and displayed in the same time, the information fusion is taken by DSP HPI ports, in order to transmit the data which processed by DSP. This system can watch the bigger visual field and get higher image resolution than ordinary monitor systems. In summary, simulative experiments for edge detection of moving object with canny algorithm based on this system indicate that this system can detect the edge of moving objects in real time, the feasibility of bionic model was fully demonstrated in the engineering system, and it laid a solid foundation for the future study of detection technology by imitating biologic vision.

  16. 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

  17. 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.

  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. 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.

  20. 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,...

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

    Science.gov (United States)

    Daily, Michael R.; Rohde, Steven B.; Novak, James L.

    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.

  2. 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...

  3. 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.

  4. 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...

  5. 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....

  6. 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 dont 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.

  7. Novel Scheme for Object-based Embedded Image Coding

    Directory of Open Access Journals (Sweden)

    Yuer Wang

    2012-11-01

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

  8. 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.

  9. 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.

  10. Inverse treatment planning using volume-based objective functions

    International Nuclear Information System (INIS)

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

  11. Rule-Based Orientation Recognition Of A Moving Object

    Science.gov (United States)

    Gove, Robert J.

    1989-03-01

    This paper presents a detailed description and a comparative analysis of the algorithms used to determine the position and orientation of an object in real-time. The exemplary object, a freely moving gold-fish in an aquarium, provides "real-world" motion, with definable characteristics of motion (the fish never swims upside-down) and the complexities of a non-rigid body. For simplicity of implementation, and since a restricted and stationary viewing domain exists (fish-tank), we reduced the problem of obtaining 3D correspondence information to trivial alignment calculations by using two cameras orthogonally viewing the object. We applied symbolic processing techniques to recognize the 3-D orientation of a moving object of known identity in real-time. Assuming motion, each new frame (sensed by the two cameras) provides images of the object's profile which has most likely undergone translation, rotation, scaling and/or bending of the non-rigid object since the previous frame. We developed an expert system which uses heuristics of the object's motion behavior in the form of rules and information obtained via low-level image processing (like numerical inertial axis calculations) to dynamically estimate the object's orientation. An inference engine provides these estimates at frame rates of up to 10 per second (which is essentially real-time). The advantages of the rule-based approach to orientation recognition will be compared other pattern recognition techniques. Our results of an investigation of statistical pattern recognition, neural networks, and procedural techniques for orientation recognition will be included. We implemented the algorithms in a rapid-prototyping environment, the TI-Ezplorer, equipped with an Odyssey and custom imaging hardware. A brief overview of the workstation is included to clarify one motivation for our choice of algorithms. These algorithms exploit two facets of the prototype image processing and understanding workstation - both low-level (segmentation) and high-level (rule-based recognition) vision capabilities.

  12. 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 participants 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.

  13. Model-based objects recognition in man-made environments

    OpenAIRE

    Martí Bonmatí, Joan; Casals, Alícia

    1996-01-01

    We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some ...

  14. 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...

  15. A Learning Object Approach To Evidence based learning

    OpenAIRE

    Zabin Visram; Bruce Elson; Patricia Reynolds

    2005-01-01

    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 mea...

  16. 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)

  17. Distributed Shared Memory Consistency Object-based Model

    Directory of Open Access Journals (Sweden)

    Abdelfatah A. Yahya

    2007-01-01

    Full Text Available A novel model that describes consistency in shared memory was developed, presented and discussed. The new object-based model handles errors of inaccuracy and misrepresentation in distributed shared memory process. The issue of misalignment was also covered.

  18. 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...

  19. 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

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

    Science.gov (United States)

    Yao, Jie; Cao, Qiang; Huang, Jianzhong

    2009-08-01

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

  1. Object based data access at the D0 experiment

    International Nuclear Information System (INIS)

    The D OE Experiment at Fermilab is currently participating in the FNAL Computing Division's ''Computing for Analysis Project'' (CAP) to investigate object based data storage and access. Following a short description of the CAP system architecture, the D OE data model is explored. A brief discussion of the method of operation of the CAP system leads into a concluding section

  2. 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

  3. 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.

  4. 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.

  5. A Primitive-Based 3D Object Recognition System

    Science.gov (United States)

    Dhawan, Atam P.

    1988-08-01

    A knowledge-based 3D object recognition system has been developed. The system uses the hierarchical structural, geometrical and relational knowledge in matching the 3D object models to the image data through pre-defined primitives. The primitives, we have selected, to begin with, are 3D boxes, cylinders, and spheres. These primitives as viewed from different angles covering complete 3D rotation range are stored in a "Primitive-Viewing Knowledge-Base" in form of hierarchical structural and relational graphs. The knowledge-based system then hypothesizes about the viewing angle and decomposes the segmented image data into valid primitives. A rough 3D structural and relational description is made on the basis of recognized 3D primitives. This description is now used in the detailed high-level frame-based structural and relational matching. The system has several expert and knowledge-based systems working in both stand-alone and cooperative modes to provide multi-level processing. This multi-level processing utilizes both bottom-up (data-driven) and top-down (model-driven) approaches in order to acquire sufficient knowledge to accept or reject any hypothesis for matching or recognizing the objects in the given image.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Fission-track dating using object-based image analysis

    International Nuclear Information System (INIS)

    Full text: Geological dating with the help of fission track analysis is based on a time-consuming counting of the spontaneous and induced tracks in the minerals. Fission tracks are damage trails in minerals caused by fast charged particles, released in nuclear fission. In this study the 950;-method is used for fission-track dating. In order to determine the age, spontaneous tracks in the apatite and induced tracks in the muscovite external detector have to be counted. The automatic extraction and identification would not only improve the speed of track counting and eliminate the personal factor. Pixel values alone are not enough to distinguish between tracks and background. Traditional pixel based approaches are therefore inefficient for fission track counting. Image analysis based on objects, which include shape, texture and contextual information is a more promising method. A procedure for automatic object - based classification is used to extract the track objects. Resolving the individual tracks in a multi-track object is based on morphological operations. The individual track objects are skeletonized and the number of individual tracks in the object is counted by processing the skeletons. To give the right fission track age, there has to be a calibration of every single user manually counting the tracks. We calibrate the automatic approach for counting in the same way. Durango apatite standard samples are used to determine the 950;- and Z-calibration factor. The automatic approach is useful for counting tracks in apatite standards and induced tracks in muscovite external detectors where the quality and quantities of the etched tracks is high. Muscovite detectors irradiated against glasses can also be used to determine the thermal neutron fluence, which is necessary to determine an absolute age. These images are of high quality and free of disturbing background irregularities. Here the automatic approach is a practical alternative. However for natural samples of small grain size, low track-numbers and background irregularities, the implementation is questionable. The algorithm for the automatic extraction and counting of fission tracks in standard samples of Durango Apatite and muscovite external detectors is shown to be self-consistent. (author)

  14. 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.

  15. 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

  16. Extended object wavefront sensing based on the correlation spectrum phase

    Science.gov (United States)

    Knutsson, Per A.; Owner-Petersen, Mette; Dainty, Chris

    2005-11-01

    In this paper we investigate the performance of a Fourier based algorithm for fast subpixel shift determination of two mutually shifted images subjected to noise. The algorithm will be used for Shack-Hartmann based adaptive optics correction of images of an extended object subjected to dynamical atmospheric fluctuations. The performance of the algorithm is investigated both analytically and by Monte Carlo simulations. Good agreement is achieved in relation to how the precision of the shift estimate depends on image parameters such as contrast, photon counts and readout noise, as well as the dependence on sampling format, zero-padding and field of view. Compared to the conventional method for extended object wavefront sensing, a reduction of the computational cost is gained at a marginal expense of precision.

  17. 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.

  18. Migrating relational databases into object-based and XML databases

    OpenAIRE

    Maatuk, Abdelsalam

    2009-01-01

    Rapid changes in information technology, the emergence of object-based and WWW applications, and the interest of organisations in securing benefits from new technologies have made information systems re-engineering in general and database migration in particular an active research area. In order to improve the functionality and performance of existing systems, the re-engineering process requires identifying and understanding all of the components of such systems. An underlying database is one...

  19. 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...

  20. 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.

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

    Science.gov (United States)

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

    2014-01-01

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

  2. 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.

  3. 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.

  4. 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

  5. Object-Based Image Analysis in Wetland Research: A Review

    Directory of Open Access Journals (Sweden)

    Iryna Dronova

    2015-05-01

    Full Text Available The applications of object-based image analysis (OBIA in remote sensing studies of wetlands have been growing over recent decades, addressing tasks from detection and delineation of wetland bodies to comprehensive analyses of within-wetland cover types and their change. Compared to pixel-based approaches, OBIA offers several important benefits to wetland analyses related to smoothing of the local noise, incorporating meaningful non-spectral features for class separation and accounting for landscape hierarchy of wetland ecosystem organization and structure. However, there has been little discussion on whether unique challenges of wetland environments can be uniformly addressed by OBIA across different types of data, spatial scales and research objectives, and to what extent technical and conceptual aspects of this framework may themselves present challenges in a complex wetland setting. This review presents a synthesis of 73 studies that applied OBIA to different types of remote sensing data, spatial scale and research objectives. It summarizes the progress and scope of OBIA uses in wetlands, key benefits of this approach, factors related to accuracy and uncertainty in its applications and the main research needs and directions to expand the OBIA capacity in the future wetland studies. Growing demands for higher-accuracy wetland characterization at both regional and local scales together with advances in very high resolution remote sensing and novel tasks in wetland restoration monitoring will likely continue active exploration of the OBIA potential in these diverse and complex environments.

  6. Multispectral photoacoustic microscopy based on an opticalacoustic 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 opticalacoustic 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 2701300nm. 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 270nm, blood vessel (hemoglobin contrast at 532nm, and sebaceous gland (lipid contrast at 1260nm at the same spatial scale in a living mouse ear.

  7. 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.

  8. 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.

  9. Cloud Aggregation and Bursting for Object Based Sharable Environment

    Directory of Open Access Journals (Sweden)

    Mr. Pradeep Kumar Tripathi

    2011-09-01

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

  10. 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. 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

  12. Detecting Algorithm for Moving Objects Based on Bayesian Judging Criterion

    Directory of Open Access Journals (Sweden)

    Yingxia Liu

    2011-05-01

    Full Text Available This paper considers the problem of accuracy for judging threshold under the complicated circumstance. In the detecting system, threshold is one of the most important factor, it decides the accuracy of the detecting result. Because the circumstance is changing, the threshold is asked to adapt the change. The traditional algorithm can hardly satisfy the need of the system. Bayesian model is an efficient system based on statistics rule, and it can give a better detecting result. In order to adapt the change of the light in a same video sequence, Bayesian judging criterion is used to detect object, void warm price and falling report price is considered comprehensively, combined with likelihood function and Bayesian risk assessment, an adaptive threshold is obtained. The threshold is determined by mean and variance of the image, so it is an optimal threshold changed with every image. The optimal threshold is used to separate object from background. Compared with the traditional threshold, it can suit different circumstance. The experimental result shows that the background noise can be removed with the dynamic threshold and the moving object can be detected accurately.

  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. Object-based landslide detection in different geographic regions

    Science.gov (United States)

    Friedl, Barbara; Hlbling, 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.

  15. 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.

  16. Noise-based Detection and Segmentation of Nebulous Objects

    Science.gov (United States)

    Akhlaghi, Mohammad; Ichikawa, Takashi

    2015-09-01

    A noise-based non-parametric technique for detecting nebulous objects, for example, irregular or clumpy galaxies, and their structure in noise is introduced. “Noise-based” and “non-parametric” imply that this technique 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 independently 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 0.88 for the final detections as compared to 0.29 for SExtractor when a completeness of 1 is desired for a sample of extremely faint and diffuse mock galaxy profiles. The difference in the mean of the undetected pixels with the known background of mock images is decreased by 4.6 times depending on the diffuseness of the test profiles, quantifying the success in their detection. A non-parametric approach to defining substructure over a detected region is also introduced. NoiseChisel is our software implementation of this new technique. Contrary to the existing signal-based approach to detection, in its various implementations, signal-related parameters such as the image point-spread function or known object shapes and models are irrelevant here. Such features make this technique very useful in astrophysical applications such as detection, photometry, or morphological analysis of nebulous objects buried in noise, for example, galaxies that do not generically have a known shape when imaged.

  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. 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...

  19. Mobile object retrieval in server-based image databases

    Science.gov (United States)

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

    2013-05-01

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

  20. 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).

  1. 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...

  2. 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.

  3. Coherent ladar imaging of the SEASAT satellite retro-reflector array using linear-FM chirp waveforms and pulse-compression

    Science.gov (United States)

    Youmans, Douglas G.

    2007-04-01

    Coherent ladar imaging of satellite retro-reflector arrays is analyzed to determine some of the potential capabilities of coherent ladar systems for long range imaging. The satellites are at mega-meters of slant range and are basically angularly unresolved assuming a nominal one meter telescope used at a laser wavelength of 1.064 μm corresponding to a 281,625 GHz center-frequency. A coherent ladar may have a selectable waveform ranging from single nanosecond pulses through tone-pulses, but the imaging waveform considered here is the linear-FM chirp pulse-compression ladar waveform, which consists of a series of frequency chirps over a long period of time. The linear-FM chirp return is pulse compressed digitally using several possible approaches. Image reconstruction follows basic ISAR algorithms in forming a "range-resolved Doppler and intensity" (RRDI) image. A retro-reflector ring on the SEASAT satellite is used to illustrate the ladar's capability, although we spin the satellite faster than the true rotation rate to demonstrate waveform resolution. Several other useful algorithms as (multi-chirp) range-time-intensity (RTI matrix) range-bin summation and segmented-spectrum frequency-bin summation are also discussed. A covariance matrix calculation is applied to the RTI matrix and also to the segmented-spectrum matrix for the extraction of additional target information.

  4. 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

  5. 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.

  6. 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...

  7. 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 des...... description of a simple partial evaluator for a minimal object-oriented language, and give directions for extending this partial evaluator to handle realistic programs....

  8. Gait-based carried object detection using persistent homology

    OpenAIRE

    Lamar Len, Javier; Alonso Baryolo, Ral; Garca Reyes, Edel; Gonzlez Daz, Roco

    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 ...

  9. Model Based Fault Isolation for Object-Oriented Control Systems

    OpenAIRE

    Larsson, Magnus; Klein, Inger; Lawesson, Dan; Nilsson, Ulf

    1999-01-01

    This report addresses the problem of fault propagation between software modules in a large industrial control system with anobject oriented architecture. There exists a conflict between object-oriented design goals such as encapsulation and modularity, and the possibility to suppress propagating error conditions. When an object detects an error condition, it is not desirable toperform the extensive querying of other objects that would be necessary to decide how close to the real fault the obj...

  10. Object Tracking Approach based on Mean Shift Algorithm

    OpenAIRE

    Xiaojing Zhang; Yajie Yue; Chenming Sha

    2013-01-01

    Object tracking has always been a hotspot in the field of computer vision, which has a range of applications in real world. The object tracking is a critical task in many vision applications. The main steps in video analysis are: detection of interesting moving objects and tracking of such objects from frame to frame. Most of tracking algorithms use pre-defined methods to process. In this paper, we introduce the Mean shift tracking algorithm, which is a kind of important no parameters estimat...

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

    DEFF Research Database (Denmark)

    Jensen, Christian Sndergaard; 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...

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

    DEFF Research Database (Denmark)

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

    2014-01-01

    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...

  13. 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

  14. Multimedia Learning Systems Based on IEEE Learning Object Metadata (LOM).

    Science.gov (United States)

    Holzinger, Andreas; Kleinberger, Thomas; Muller, Paul

    One of the "hottest" topics in recent information systems and computer science is metadata. Learning Object Metadata (LOM) appears to be a very powerful mechanism for representing metadata, because of the great variety of LOM Objects. This is on of the reasons why the LOM standard is repeatedly cited in projects in the field of eLearning Systems.…

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

    CERN Document Server

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

    2010-01-01

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

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

    Science.gov (United States)

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

    2014-01-01

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

  17. Exploiting database technology for object based event storage and retrieval

    International Nuclear Information System (INIS)

    This paper discusses the storage and retrieval of experimental data on relational databases. Physics experiments carried out using reactors and particle accelerators, generate huge amount of data. Also, most of the data analysis and simulation programs are developed using object oriented programming concepts. Hence, one of the most important design features of an experiment related software framework is the way object persistency is handled. We intend to discuss these issues in the light of the module developed by us for storing C++ objects in relational databases like Oracle. This module was developed under the POOL persistency framework being developed for LHC, CERN grid. (author)

  18. Gateway-based call admission in distributed object oriented systems

    OpenAIRE

    Widell, Niklas; Nyberg, Christian

    2000-01-01

    Many applications in telecommunications will depend on distributed systems to provide enough capacity. In a distributed system a service is split up into a number of modules (often called objects) that can be placed at different nodes or processors in a network. A service can be seen as a number of invocations of the objects in a certain order. There are a number of performance problems which have to be solved. How shall objects be distributed on the nodes? How shall the load b...

  19. 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.

  20. Tailoring Green Infrastructure Implementation Scenarios based on Stormwater Management Objectives

    Science.gov (United States)

    Green infrastructure (GI) refers to stormwater management practices that mimic nature by soaking up, storing, and controlling onsite. GI practices can contribute reckonable benefits towards meeting stormwater management objectives, such as runoff peak shaving, volume reduction, f...

  1. 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 Numdia. 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.

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

    OpenAIRE

    Abhijeet S. Tayde*

    2015-01-01

    In object recognition, there are two sets of edge-texture features and discriminative Robust Local Binary Pattern (DRLBP) and Ternary Pattern (DRLTP). By knowing the limitations of Local Binary Pattern (LBP), Local Ternary Pattern (LTP) and Robust LBP (RLBP). DRLBP and DRLTP are proposed with new features to solve the problem of discrimination between a bright object against a dark background and vice-versa inherent in LBP and LTP. DRLBP also solves the problem of RLBP whereby LBP...

  3. Real-time Object Detection Based on ARM9

    OpenAIRE

    M.Vijay babu

    2013-01-01

    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 ...

  4. A Biological Hierarchical Model Based Underwater Moving Object Detection

    OpenAIRE

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

    2014-01-01

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

  5. JBOOM: Java Based Object Oriented Model of Software Configuration Management

    OpenAIRE

    Bhavya Mehta; S.K. Muttoo

    2006-01-01

    Most of the present Software Configuration Management systems deal with version and configurations in the form of files and directories, the need today is to have a Software Configuration Management system that handles versions and configurations directly in terms of functions (program module). A major objective of this research is the use of Java in the Software Configuration Management systems. An object-oriented language provides both design and implementation in an integrated manner. We h...

  6. 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.

  7. 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.

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

    Science.gov (United States)

    Barak, Miri; Ziv, Shani

    2013-01-01

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

  9. LBP-based edge-texture features for object recognition.

    Science.gov (United States)

    Satpathy, Amit; Jiang, Xudong; Eng, How-Lung

    2014-05-01

    This paper proposes two sets of novel edge-texture features, Discriminative Robust Local Binary Pattern (DRLBP) and Ternary Pattern (DRLTP), for object recognition. By investigating the limitations of Local Binary Pattern (LBP), Local Ternary Pattern (LTP) and Robust LBP (RLBP), DRLBP and DRLTP are proposed as new features. They solve the problem of discrimination between a bright object against a dark background and vice-versa inherent in LBP and LTP. DRLBP also resolves the problem of RLBP whereby LBP codes and their complements in the same block are mapped to the same code. Furthermore, the proposed features retain contrast information necessary for proper representation of object contours that LBP, LTP, and RLBP discard. Our proposed features are tested on seven challenging data sets: INRIA Human, Caltech Pedestrian, UIUC Car, Caltech 101, Caltech 256, Brodatz, and KTH-TIPS2-a. Results demonstrate that the proposed features outperform the compared approaches on most data sets. PMID:24690574

  10. 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

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

    Directory of Open Access Journals (Sweden)

    Dr.M.Shashi

    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.

  12. 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…

  13. 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…

  14. Flattop beam illumination for 3D imaging ladar with simple optical devices in the wide distance range

    Science.gov (United States)

    Tsuji, Hidenobu; Nakano, Takayuki; Matsumoto, Yoshihiro; Kameyama, Shumpei

    2016-04-01

    We have developed an illumination optical system for 3D imaging ladar (laser detection and ranging) which forms flattop beam shape by transformation of the Gaussian beam in the wide distance range. The illumination is achieved by beam division and recombination using a prism and a negative powered lens. The optimum condition of the transformation by the optical system is derived. It is confirmed that the flattop distribution can be formed in the wide range of the propagation distance from 1 to 1000 m. The experimental result with the prototype is in good agreement with the calculation result.

  15. 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.

  16. 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.

  17. 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 composers work, the score, defines the listeners 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...

  18. 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...

  19. Structural similarity-based object tracking in video sequences

    OpenAIRE

    Mihaylova, L.; Loza, Artur T; Canagarajah, CN; Bull, David

    2006-01-01

    This paper addresses the problem of object tracking in video sequences. The use of a structural similarity measure for tracking is proposed. The measure reflects the distance between two images by comparing their structural and spatial characteristics and has shown to be robust to illumination and contrast changes. As a result it guarantees robustness of the tracking process under changes in the environment. The previously used Bhattacharyya distance is not robust to such changes. Additionall...

  20. 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.

  1. 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.

  2. 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...

  3. 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.

  4. Model-based beam control for illumination of remote objects

    Science.gov (United States)

    Chandler, Susan M.; Lukesh, Gordon W.; Voelz, David; Basu, Santasri; Sjogren, Jon A.

    2004-11-01

    On September 1, 2003, Nukove Scientific Consulting, together with partner New Mexico State University, began work on a Phase 1 Small Business Technology TRansfer (STTR) grant from the United States Air Force Office of Scientific Research (AFOSR). The purpose of the grant was to show the feasibility of taking Nukove's pointing estimation technique from a post-processing tool for estimation of laser system characteristics to a real-time tool usable in the field. Nukove's techniques for pointing, shape, and OCS estimation do not require an imaging sensor nor a target board, thus estimates may be made very quickly. To prove feasibility, Nukove developed an analysis tool RHINO (Real-time Histogram Interpretation of Numerical Observations) and successfully demonstrated the emulation of real-time, frame-by-frame estimation of laser system characteristics, with data streamed into the tool and the estimates displayed as they are made. The eventual objective will be to use the frame-by-frame estimates to allow for feedback to a fielded system. Closely associated with this, NMSU developed a laboratory testbed to illuminate test objects, collect the received photons, and stream the data into RHINO. The two coupled efforts clearly demonstrate the feasibility of real-time pointing control of a laser system.

  5. A modified PSO based particle filter algorithm for object tracking

    Science.gov (United States)

    Tang, Yufei; Fu, Siyao; Tang, Bo; He, Haibo

    2013-05-01

    In this paper, a modified particle swarm optimization (PSO) approach, particle swarm optimization with ɛ- greedy exploration ɛPSO), is used to tackle the object tracking. In the modified ɛPSO algorithm, the cooperative learning mechanism among individuals has been introduced, namely, particles not only adjust its own flying speed according to itself and the best individual of the swarm but also learn from other best individuals according to certain probability. This kind of biologically-inspired mutual-learning behavior can help to find the global optimum solution with better convergence speed and accuracy. The ɛPSO algorithm has been tested on benchmark function and demonstrated its effectiveness in high-dimension multi-modal optimization. In addition to the standard benchmark study, we also combined our new ɛPSO approach with the traditional particle filter (PF) algorithm on the object tracking task, such as car tracking in complex environment. Comparative studies between our ɛPSO combined PF algorithm with those of existing techniques, such as the particle filter (PF) and classic PSO combined PF will be used to verify and validate the performance of our approach.

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

    OpenAIRE

    Dor, 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...

  7. 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

  8. 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.

  9. 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.

  10. 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

  11. Digital Microdroplet Ejection Technology-Based Heterogeneous Objects Prototyping.

    Science.gov (United States)

    Li, Na; 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. PMID:26981110

  12. 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. PMID:26981110

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

    Science.gov (United States)

    Dor, 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

  14. The Neural Fate of Task-Irrelevant Features in Object-Based Processing

    OpenAIRE

    Xu, Yaoda

    2010-01-01

    Objects are one of the most fundamental units in visual attentional selection and information processing. Studies have shown that, during object-based processing, all features of an attended object may be encoded together, even when these features are task irrelevant. Some recent studies, however, have failed to find this effect. What determines when object-based processing may or may not occur? In three experiments, observers were asked to encode object colors and the processing of task-irre...

  15. 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...

  16. Line fitting based feature extraction for object recognition

    Science.gov (United States)

    Li, Bing

    2014-06-01

    Image feature extraction plays a significant role in image based pattern applications. In this paper, we propose a new approach to generate hierarchical features. This new approach applies line fitting to adaptively divide regions based upon the amount of information and creates line fitting features for each subsequent region. It overcomes the feature wasting drawback of the wavelet based approach and demonstrates high performance in real applications. For gray scale images, we propose a diffusion equation approach to map information-rich pixels (pixels near edges and ridge pixels) into high values, and pixels in homogeneous regions into small values near zero that form energy map images. After the energy map images are generated, we propose a line fitting approach to divide regions recursively and create features for each region simultaneously. This new feature extraction approach is similar to wavelet based hierarchical feature extraction in which high layer features represent global characteristics and low layer features represent local characteristics. However, the new approach uses line fitting to adaptively focus on information-rich regions so that we avoid the feature waste problems of the wavelet approach in homogeneous regions. Finally, the experiments for handwriting word recognition show that the new method provides higher performance than the regular handwriting word recognition approach.

  17. 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.

  18. 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...

  19. Research on the Project Portfolio Technology Based on Functional Objective

    OpenAIRE

    Haiyang Li; Jingchun Feng; Zhanjun Liu; Xin Zhang

    2011-01-01

    The portfolio technology is used to solve project portfolio problems from strategic-level and tactical-level, namely, project portfolios based on goals and similarities, respectively. On the basis of analyzing and proposing the type of portfolio of project, we analyzed the relation between the project functional goals and the project, introduced the project portfolio technology of functional goals. On this basis, we studied the principle and process of the project portfolio technology which i...

  20. Detecting Algorithm for Moving Objects Based on Bayesian Judging Criterion

    OpenAIRE

    Yingxia Liu; Faliang Chang

    2011-01-01

    This paper considers the problem of accuracy for judging threshold under the complicated circumstance. In the detecting system, threshold is one of the most important factor, it decides the accuracy of the detecting result. Because the circumstance is changing, the threshold is asked to adapt the change. The traditional algorithm can hardly satisfy the need of the system. Bayesian model is an efficient system based on statistics rule, and it can give a better detecting result. In order to ada...

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

    OpenAIRE

    Eirik Borgen; Henning Neerland; Jan O. Strandhagen

    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...

  2. 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.

  3. 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.

  4. Actin-based propulsion of spatially extended objects

    International Nuclear Information System (INIS)

    We propose a mathematical model of the actin-based propulsion of spatially extended obstacles. It starts from the properties of individual actin filaments and includes transient attachment to the obstacle, polymerization as well as cross-linking. Two particular geometries are discussed, which apply to the motion of protein-coated beads in a cell-like medium and the leading edge of a cell protrusion, respectively. The model gives rise to both steady and saltatory movement of beads and can explain the experimentally observed transitions of the dynamic regime with changing bead radius and protein surface density. Several spatiotemporal patterns are obtained with a soft obstacle under tension, including the experimentally observed spontaneous emergence of lateral traveling waves in crawling cells. Thus, we suggest a unifying mechanism for systems that are currently described by differential concepts.

  5. 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...

  6. 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...

  7. 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.

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

    Science.gov (United States)

    Hölbling, Daniel; Friedl, Barbara; Eisank, Clemens

    2014-05-01

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

  9. Memory-Based Multiagent Coevolution Modeling for Robust Moving Object Tracking

    OpenAIRE

    Yanjiang Wang; Yujuan Qi; Yongping Li

    2013-01-01

    The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper. Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experience. A number of such memory-based agents are randomly distributed nearby the located object region...

  10. Guided Creation and Update of Objects in RDF(S) Bases

    OpenAIRE

    Hermann, Alice; Ferré, Sébastien; Ducassé, Mireille

    2011-01-01

    Updating existing knowledge bases is crucial to take into account the information that are regularly discovered. However, this is quite tedious and in practice Semantic Web data are rarely updated by users. This paper presents UTILIS, an approach to help users create and update objects in RDF(S) bases. While creating a new object, o, UTILIS searches for similar objects, found by applying relaxation rules to the description of o, taken as a query. The resulting objects and their properties ser...

  11. 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...

  12. Blackboard- and Object-Based Systems via Multi-Head Clauses

    OpenAIRE

    A. Ciampolini; El Lamma; C. Stefanelli; Mello, P.

    2012-01-01

    This paper presents a distributed architecture supporting and integrating both blackboard- and object-based multi-agent models. The architecture is based on a concurrent logic language with multi-head clauses, committed/choice behaviour and restricted AND parallelism. A blackboard/based application is mapped into a set of multi-head clauses representing logic agents which communicate via a common (possibly distributed) working memory. Objects are clusters of processes, objects' state is repre...

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

    Directory of Open Access Journals (Sweden)

    Shahnawaz Talpur

    2013-07-01

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

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

    International Nuclear Information System (INIS)

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

  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. Proposal of a Framework for Internet Based Licensing of Learning Objects

    Science.gov (United States)

    Santos, Osvaldo A.; Ramos, Fernando M. S.

    2004-01-01

    This paper presents a proposal of a framework whose main objective is to manage the delivery and rendering of learning objects in a digital rights controlled environment. The framework is based on a digital licensing scheme that requires each learning object to have the proper license in order to be rendered by a trusted player. A conceptual model…

  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. Memory-based multiagent coevolution modeling for robust moving object tracking.

    Science.gov (United States)

    Wang, Yanjiang; Qi, Yujuan; Li, Yongping

    2013-01-01

    The three-stage human brain memory model is incorporated into a multiagent coevolutionary process for finding the best match of the appearance of an object, and a memory-based multiagent coevolution algorithm for robust tracking the moving objects is presented in this paper. Each agent can remember, retrieve, or forget the appearance of the object through its own memory system by its own experience. A number of such memory-based agents are randomly distributed nearby the located object region and then mapped onto a 2D lattice-like environment for predicting the new location of the object by their coevolutionary behaviors, such as competition, recombination, and migration. Experimental results show that the proposed method can deal with large appearance changes and heavy occlusions when tracking a moving object. It can locate the correct object after the appearance changed or the occlusion recovered and outperforms the traditional particle filter-based tracking methods. PMID:23843739

  19. 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...

  20. 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...

  1. Robust video object tracking using particle filter with likelihood based feature fusion and adaptive template updating

    OpenAIRE

    Dai, Yi; Liu, Bin

    2015-01-01

    A robust algorithm solution is proposed for tracking an object in complex video scenes. In this solution, the bootstrap particle filter (PF) is initialized by an object detector, which models the time-evolving background of the video signal by an adaptive Gaussian mixture. The motion of the object is expressed by a Markov model, which defines the state transition prior. The color and texture features are used to represent the object, and a marginal likelihood based feature fusion approach is ...

  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. Particle Filter Algorithm for Object Tracking Based on Color Local Entropy

    OpenAIRE

    Huan Wang; Qinglin Wang; Yuan Li; Yaping Dai

    2013-01-01

    To achieve accurate visual object tracking and overcome the difficulties brought by the object deformation, occlusion, and illumination variations, a particle filter for object tracking algorithm based on color local entropy (CLE) is proposed. First we improved the traditional histogram weighted function by using a scale factor. Then, for the shortcoming that the color feature is sensitive to illumination and environmental interference, a color local entropy object observation model is constr...

  4. 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...

  5. 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 ...

  6. 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...

  7. A simple software environment based on objects and relations / [by] Bruce J. MacLennan.

    OpenAIRE

    MacLennan, Bruce J.

    1985-01-01

    Author(s) key words: Object-oriented programming, programming environments, software engineering environments, production rules, production systems, entity-relationship approach, software prototyping, knowledge representation, logic programming, simulation languages, rule-based systems, knowledge base fifth generation languages, classification

  8. 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...

  9. 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.

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

    Science.gov (United States)

    Tseng, Kuo-Shih; Tang, Angela Chih-Wei

    2009-12-01

    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 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.

  11. 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.

  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. 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.

  14. 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.

  15. File-based storage of Digital Objects and constituent datastreams: XMLtapes and Internet Archive ARC files

    OpenAIRE

    Liu, XM; BALAKIREVA, L; Hochstenbach, Patrick; H. Van de Sompel

    2005-01-01

    This paper introduces the write-once/read-many XMLtape/ARC storage approach for Digital Objects and their constituent datastreams. The approach combines two interconnected file-based storage mechanisms that are made accessible in a protocol-based manner. First, XML-based representations of multiple Digital Objects are concatenated into a single file named an XMLtape. An XMLtape is a valid XML file; its format definition is independent of the choice of the XML-based complex object format by wh...

  16. Model-based recognition of 3-D objects by geometric hashing technique

    International Nuclear Information System (INIS)

    A model-based object recognition system is developed for recognition of polyhedral objects. The system consists of feature extraction, modelling and matching stages. Linear features are used for object descriptions. Lines are obtained from edges using rotation transform. For modelling and recognition process, geometric hashing method is utilized. Each object is modelled using 2-D views taken from the viewpoints on the viewing sphere. A hidden line elimination algorithm is used to find these views from the wire frame model of the objects. The recognition experiments yielded satisfactory results. (author). 8 refs, 5 figs

  17. Model of Recommendation System for for Indexing and Retrieving the Learning Object based on Multiagent System

    Directory of Open Access Journals (Sweden)

    Ronaldo Lima Rocha Campos

    2012-07-01

    Full Text Available This paper proposes a multiagent system application model for indexing, retrieving and recommendation learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the signification of the results we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.

  18. 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

  19. 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.

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

    International Nuclear Information System (INIS)

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

  1. A computer graphics based model for scattering from objects of arbitrary shapes in the optical region

    Science.gov (United States)

    Goel, Narendra S.; Rozehnal, Ivan; Thompson, Richard L.

    1991-01-01

    A computer-graphics-based model, named DIANA, is presented for generation of objects of arbitrary shape and for calculating bidirectional reflectances and scattering from them, in the visible and infrared region. The computer generation is based on a modified Lindenmayer system approach which makes it possible to generate objects of arbitrary shapes and to simulate their growth, dynamics, and movement. Rendering techniques are used to display an object on a computer screen with appropriate shading and shadowing and to calculate the scattering and reflectance from the object. The technique is illustrated with scattering from canopies of simulated corn plants.

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

    OpenAIRE

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

    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...

  3. 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.

  4. 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.

  5. 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

  6. 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.

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

    OpenAIRE

    Xiaoyong Zhang; Jun Peng; Wentao Yu; Kuo-chi Lin

    2012-01-01

    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 ...

  8. 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)

  9. A model-based evolutionary algorithm for Bi-objective optimization

    OpenAIRE

    A. Zhou; Zhang, Q.; Jin, Y.; Tsang, E; Okabe, T.

    2005-01-01

    The Pareto optimal solutions to a multi-objective optimization problem often distribute very regularly in both the decision space and the objective space. Most existing evolutionary algorithms do not explicitly take advantage of such a regularity. This paper proposed a model-based evolutionary algorithm (M-MOEA) for bi-objective optimization problems. Inspired by the ideas from estimation of distribution algorithms, M-MOEA uses a probability model to capture the regularity of the distribution...

  10. 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...

  11. The modulation of spatial congruency by object-based attention: analysing the "locus" of the modulation.

    Science.gov (United States)

    Luo, Chunming; Lupiáñez, Juan; Funes, María Jesús; Fu, Xiaolan

    2011-12-01

    Earlier studies have demonstrated that spatial cueing differentially reduces stimulus-stimulus congruency (e.g., spatial Stroop) interference but not stimulus-response congruency (e.g., Simon; e.g., Lupiáñez & Funes, 2005). This spatial cueing modulation over spatial Stroop seems to be entirely attributable to object-based attention (e.g., Luo, Lupiáñez, Funes, & Fu, 2010). In the present study, two experiments were conducted to further explore whether the cueing modulation of spatial Stroop is object based and/or space based and to analyse the "locus" of this modulation. In Experiment 1, we found that the cueing modulation over spatial Stroop is entirely object based, independent of stimulus-response congruency. In Experiment 2, we observed that the modulation of object-based attention over the spatial Stroop only occurred at a short cue-target interval (i.e., stimulus onset asynchrony; SOA), whereas the stimulus-response congruency effect was not modulated either by object-based or by location-based attentional cueing. The overall pattern of results suggests that the spatial cueing modulation over spatial Stroop arises from object-based attention and occurs at the perceptual stage of processing. PMID:21923623

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

    Science.gov (United States)

    Shen, Mowei; Huang, Xiang; Gao, Zaifeng

    2015-04-01

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

  13. 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

    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...

  14. 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…

  15. 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.

  16. 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.

  17. 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.

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

    OpenAIRE

    Liubai Li

    2012-01-01

    In the process of object tracking, the major problem is how to mark the tracking box of the object. Moreover, multi-objects tracking is also difficult. This paper proposed and efficient fast object-tracking scheme based on motion-vector-located pattern match, which adopts motion vector of Mpeg2 to mark the moving targets in static video in order to mark and locate the targets automatically and quickly. Then, extract multi-dimensional characteristics from the initial targets taken by motion ve...

  19. A Novel Multi-objective Formulation for Hydrothermal Power Scheduling Based on Reservoir End Volume Relaxation

    Science.gov (United States)

    Basak, Aniruddha; Pal, Siddharth; Pandi, V. Ravikumar; Panigrahi, B. K.; Mallick, M. K.; Mohapatra, Ankita

    The paper presents a new multi-objective approach to determine the optimal power generation for short term hydrothermal scheduling. Generation cost is considered as one objective. Novelty of the paper lies in choosing the second objective. Instead of introducing a hard constraint on the reservoir end volume we have reasoned that allowing it to relax makes better solutions feasible. The degree of relaxation is kept as the second objective. We have tested our approach on a multi-reservoir cascaded hydrothermal system with four hydro and one thermal plant. We have solved the optimization problem using a decomposition based MOEA called MOEA/D-DE.

  20. Concept of development of integrated computer - based control system for 'Ukryttia' object

    International Nuclear Information System (INIS)

    The structural concept of Chernobyl NPP 'Ukryttia' Object's integrated computer - based control system development is presented on the basis of general concept of integrated Computer - based Control System (CCS) design process for organizing and technical management subjects.The concept is aimed at state-of-the-art architectural design technique application and allows using modern computer-aided facilities for functional model,information (logical and physical) models development,as well as for system object model under design

  1. 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...

  2. Object-oriented Modelling for Module-based Production Logistics Inventory System

    OpenAIRE

    Khabbazi, Mahmood Reza; Hasan, M K; SHAPI’I, A; Sulaiman, R.; Keshavarz, Y; Mousavi, A.

    2013-01-01

    This paper proposes module-based object-oriented data models for inventory systemfocusing on the production logistics business processes. It expounds the methodology and modellingprocedure to provide the inventory system requirements. Through warehousing business processanalysis for production logistics and based on the object-oriented technique in a modular basis, thedomain and entity class diagrams are modelled. Through identifying all the required and realizingsystem interfaces, the system...

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

    OpenAIRE

    Stow, D; A. Lopez; LIPPITT, C.; HINTON, S.; Weeks, J

    2007-01-01

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

  4. Retrospective radon progeny measurements for dwellings based on implanted {sup 210}Po activities in glass objects

    Energy Technology Data Exchange (ETDEWEB)

    Yip, C.W.Y.; Nikezic, D. [Department of Physics and Materials Science, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong); Yu, K.N. [Department of Physics and Materials Science, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong (Hong Kong)], E-mail: peter.yu@cityu.edu.hk

    2008-08-15

    In the present work, we used the (CR-LR) difference technique for retrospective radon progeny measurements in 17 dwellings based on implanted {sup 210}Po activities in glass objects. A total of 48 glass objects were examined, but only 19 objects gave results which were sufficiently reliable due to the sensitivity of the method. From these 19 data, an increase in the surface {sup 210}Po activities in the glass objects with the age of the glass objects was noticeable as expected. The surface activities of {sup 210}Po in the glass objects were then converted to the potential alpha energy concentration (PAEC) through a calibration curve. It was found that the PAEC for dwelling sites did not change significantly with the building age.

  5. MODEL OF STORAGE XML DATABASE BASED ON THE RELATIONAL-OBJECT MODEL

    OpenAIRE

    Laila Alami Kasri; Imran A. Tasadduq

    2010-01-01

    The objective of this work is to define a model of storage represented strictly in XML, this model is based on the structure of the relational model using the types of the model object. We suggest then creating our database according to this model by requests SQL3. We thus realize a framework of management and administration ofdatabases XML based on requests object relational SQL3. We analyze at first the mapping since a request SQL towards a structure of a document XML. We shall describe the...

  6. Multi-Objective Design Optimization of an Over-Constrained Flexure-Based Amplifier

    Directory of Open Access Journals (Sweden)

    Yuan Ni

    2015-07-01

    Full Text Available The optimizing design for enhancement of the micro performance of manipulator based on analytical models is investigated in this paper. By utilizing the established uncanonical linear homogeneous equations, the quasi-static analytical model of the micro-manipulator is built, and the theoretical calculation results are tested by FEA simulations. To provide a theoretical basis for a micro-manipulator being used in high-precision engineering applications, this paper investigates the modal property based on the analytical model. Based on the finite element method, with multipoint constraint equations, the model is built and the results have a good match with the simulation. The following parametric influences studied show that the influences of other objectives on one objective are complicated.  Consequently, the multi-objective optimization by the derived analytical models is carried out to find out the optimal solutions of the manipulator. Besides the inner relationships among these design objectives during the optimization process are discussed.

  7. 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.

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

    Directory of Open Access Journals (Sweden)

    L. DJEROU,

    2012-01-01

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

  9. 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.

  10. 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.

  11. An object-oriented classification method of high resolution imagery based on improved AdaTree

    International Nuclear Information System (INIS)

    With the popularity of the application using high spatial resolution remote sensing image, more and more studies paid attention to object-oriented classification on image segmentation as well as automatic classification after image segmentation. This paper proposed a fast method of object-oriented automatic classification. First, edge-based or FNEA-based segmentation was used to identify image objects and the values of most suitable attributes of image objects for classification were calculated. Then a certain number of samples from the image objects were selected as training data for improved AdaTree algorithm to get classification rules. Finally, the image objects could be classified easily using these rules. In the AdaTree, we mainly modified the final hypothesis to get classification rules. In the experiment with WorldView2 image, the result of the method based on AdaTree showed obvious accuracy and efficient improvement compared with the method based on SVM with the kappa coefficient achieving 0.9242

  12. The pixel rectangle index used in object based building extraction from high resolution images

    International Nuclear Information System (INIS)

    An improved high resolution object-based building extraction method based on Pixel Rectangle Index is presented in this paper. We use Minimum Span Tree optimal theory to realize object-based high resolution image segmentation. First, we proposed a rotation invariant Pixel Rectangle Index by introducing the principal direction of homogeneous area. Second, we improved the calculation of edge-weight by introducing the band-weight and Pixel Rectangle Index. The QuickBird high resolution images were used to do the building extraction experiment. The experiment result proved that this method can obtain high extraction accuracy and this algorithm can be efficiently used in remote sensing images

  13. Recognition of low-contrast FLIR tank object based on multiscale fractal character vector

    Science.gov (United States)

    Xue, Donghui; Zhu, Yaoting; Zhu, Guang-Xi; Xiong, Yan

    1996-05-01

    Low-contrast FLIR tank object detection is a difficulty. This paper presents a new method based on fractal geometry and multiscale analysis for the target detection. A new metric called multiscale fractal character vector which can distinguish man-made objects and natural scenes is defined. And then a segmentation algorithm based on this new metric is given. Finally, experimental results have shown our method can give better segmentation results than the usual segmentation method which is based on H parameter of only one scale image.

  14. 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.

  15. Action-Based Learning of Multistate Objects in the Medial Temporal Lobe.

    Science.gov (United States)

    Hindy, Nicholas C; Turk-Browne, Nicholas B

    2016-05-01

    Actions constrain perception by changing the appearance of objects in the environment. As such, they provide an interactive basis for learning the structure of visual input. If an action systematically transforms one stimulus into another, then these stimuli are more likely to reflect different states of the same persisting object over time. Here we show that such multistate objects are represented in the human medial temporal lobe-the result of a mechanism in which actions influence associative learning of how objects transition between states. We further demonstrate that greater recruitment of these action-based representations during object perception is accompanied by attenuated activity in stimulus-selective visual cortex. In this way, our interactions with the environment help build visual knowledge that predictively facilitates perceptual processing. PMID:25754517

  16. 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

  17. 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.

  18. 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.

  19. Query and Update Efficient B+-Tree Based Indexing of Moving Objects

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Lin, Dan; Ooi, Beng Chin

    A number of emerging applications of data management technology involve the monitoring and querying of large quantities of continuous variables, e.g., the positions of mobile service users, termed moving objects. In such applications, large quantities of state samples obtained via sensors are...... streamed to a database. Indexes for moving objects must support queries efficiently, but must also support frequent updates. Indexes based on minimum bounding regions (MBRs) such as the R-tree exhibit high concurrency overheads during node splitting, and each individual update is known to be quite costly....... This motivates the design of a solution that enables the B+-tree to manage moving objects. We represent moving-object locations as vectors that are timestamped based on their update time. By applying a novel linearization technique to these values, it is possible to index the resulting values using a...

  20. Child's objection to non-beneficial research: capacity and distress based models.

    Science.gov (United States)

    Waligora, Marcin; Różyńska, Joanna; Piasecki, Jan

    2016-03-01

    A child's objection, refusal and dissent regarding participation in non-beneficial biomedical research must be respected, even when the parents or legal representatives have given their permission. There is, however, no consensus on the definition and criteria of a meaningful and valid child's objection. The aim of this article is to clarify this issue. In the first part we describe the problems of a child's assent in research. In the second part we distinguish and analyze two models of a child's objection to research: the capacity-based model and the distress-based model. In the last part we present arguments for a broader and unified understanding of a child's objection within regulations and practices. This will strengthen children's rights and facilitate the entire process of assessment of research protocols. PMID:25916607

  1. 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.

  2. 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...

  3. A Fast Object Tracking Approach Based on the Motion Vector in a Compressed Domain

    OpenAIRE

    Hui-bin Wang; Jie Shen; Zhe Chen; Jun-lei Shen

    2013-01-01

    Particle set sampling and weighting are both at the core of particle filter‐based object tracking methods. Aiming to optimally represent the objectʹs motion state, a large amount of particles ‐ in the classical particle method ‐ is a prerequisite. The high‐cost calculation of these particles significantly slows down the convergence of the algorithm. To this problem, a prior approach which originated from the process of video compressing and uncompressing is introduced to optimize the phase of...

  4. Invariant visual object and face recognition: neural and computational bases, and a model, VisNet

    OpenAIRE

    Rolls, Edmund T.

    2012-01-01

    Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is ...

  5. Wnbac: A Weighted Network Based Adaptive Clustering Algorithm for Spatial Objects

    OpenAIRE

    Pan Xu-Wei; Jin Min

    2013-01-01

    To overcome shortcomings such as slowness of the convergence, sensitive to initial value and pre-awareness of dataset in most clustering algorithm, a Weighted Network Based Adaptive Clustering (WNBAC) algorithm is put forward. The WNBAC algorithm is to build the weighted network for spatial objects in term of the similarity among objects, then to partition nodes in the weighted network by nodes’ strength and edges’ weight. The core idea, main process, building procedure and parameter setting ...

  6. 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.

  7. 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.

  8. 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

  9. An Objects Detecting and Tracking method based on MSPF and SVM

    OpenAIRE

    Wei Sun; Xu Zhang; Yunyi Yan

    2012-01-01

    Considering that the robust real-time tracking of non-rigid objects is difficult to realize, We present an objects detecting and tracking method based on mean-shift particle filter (MSPF) and support vector machine (SVM). The proposed algorithm uses the mean-shift vector of the tracking object to update the state transition matrix of particle filter algorithm, and we define the criterion of the particle degradation,to improve the conditions of degradation,the particles will be re-distributed ...

  10. 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...

  11. Estimating Selectivity for Current Query of Moving Objects Using Index-Based Histogram

    Science.gov (United States)

    Chi, Jeong Hee; Kim, Sang Ho

    Selectivity estimation is one of the query optimization techniques. It is difficult for the previous selectivity estimation techniques for moving objects to apply the location change of moving objects to synopsis. Therefore, they result in much error when estimating selectivity for queries, because they are based on the extended spatial synopsis which does not consider the property of the moving objects. In order to reduce the estimation error, the existing techniques should often rebuild the synopsis. Consequently problem occurs, that is, the whole database should be read frequently. In this paper, we proposed a moving object histogram method based on quadtree to develop a selectivity estimation technique for moving object queries. We then analyzed the performance of the proposed method through the implementation and evaluation of the proposed method. Our method can be used in various location management systems such as vehicle location tracking systems, location based services, telematics services, emergency rescue service, etc in which the location information of moving objects changes over time.

  12. 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%.

  13. 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

  14. Vision-based object detection and recognition system for intelligent vehicles

    Science.gov (United States)

    Ran, Bin; Liu, Henry X.; Martono, Wilfung

    1999-01-01

    Recently, a proactive crash mitigation system is proposed to enhance the crash avoidance and survivability of the Intelligent Vehicles. Accurate object detection and recognition system is a prerequisite for a proactive crash mitigation system, as system component deployment algorithms rely on accurate hazard detection, recognition, and tracking information. In this paper, we present a vision-based approach to detect and recognize vehicles and traffic signs, obtain their information, and track multiple objects by using a sequence of color images taken from a moving vehicle. The entire system consist of two sub-systems, the vehicle detection and recognition sub-system and traffic sign detection and recognition sub-system. Both of the sub- systems consist of four models: object detection model, object recognition model, object information model, and object tracking model. In order to detect potential objects on the road, several features of the objects are investigated, which include symmetrical shape and aspect ratio of a vehicle and color and shape information of the signs. A two-layer neural network is trained to recognize different types of vehicles and a parameterized traffic sign model is established in the process of recognizing a sign. Tracking is accomplished by combining the analysis of single image frame with the analysis of consecutive image frames. The analysis of the single image frame is performed every ten full-size images. The information model will obtain the information related to the object, such as time to collision for the object vehicle and relative distance from the traffic sings. Experimental results demonstrated a robust and accurate system in real time object detection and recognition over thousands of image frames.

  15. A Skeleton-Based 3D Shape Reconstruction of Free-Form Objects with Stereo Vision

    Science.gov (United States)

    Saini, Deepika; Kumar, Sanjeev

    2015-12-01

    In this paper, an efficient approach is proposed for recovering the 3D shape of a free-form object from its arbitrary pair of stereo images. In particular, the reconstruction problem is treated as the reconstruction of the skeleton and the external boundary of the object. The reconstructed skeleton is termed as the line-like representation or curve-skeleton of the 3D object. The proposed solution for object reconstruction is based on this evolved curve-skeleton. It is used as a seed for recovering shape of the 3D object, and the extracted boundary is used for terminating the growing process of the object. NURBS-skeleton is used to extract the skeleton of both views. Affine invariant property of the convex hulls is used to establish the correspondence between the skeletons and boundaries in the stereo images. In the growing process, a distance field is defined for each skeleton point as the smallest distance from that point to the boundary of the object. A sphere centered at a skeleton point of radius equal to the minimum distance to the boundary is tangential to the boundary. Filling in the spheres centered at each skeleton point reconstructs the object. Several results are presented in order to check the applicability and validity of the proposed algorithm.

  16. 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...

  17. Validation of a computer based objective structured clinical examination in the assessment of undergraduate dermatology courses

    OpenAIRE

    Feroze Kaliyadan; Abdul Sattar Khan; Joel Kuruvilla; Kaberi Feroze

    2014-01-01

    Many teaching centers have now adopted objective structured clinical examination (OSCE) as an assessment method for undergraduate dermatology courses. A modification of the standard OSCE in dermatology is computer based or electronic OSCE (eOSCE). We attempted to validate the use of a computer-based OSCE in dermatology in a group of fifth year medical students. The scores of the students in the computer-based OSCE showed a strong positive correlation with the scores on the clinical presentati...

  18. Multiscale quantification of urban composition from EO-1/Hyperion data using object-based spectral unmixing

    Science.gov (United States)

    Zhang, Caiyun

    2016-05-01

    Quantification of the urban composition is important in urban planning and management. Previous research has primarily focused on unmixing medium-spatial resolution multispectral imagery using spectral mixture analysis (SMA) in order to estimate the abundance of urban components. For this study an object-based multiple endmember spectral mixture analysis (MESMA) approach was applied to unmix the 30-m Earth Observing-1 (EO-1)/Hyperion hyperspectral imagery. The abundance of two physical urban components (vegetation and impervious surface) was estimated and mapped at multiple scales and two defined geographic zones. The estimation results were validated by a reference dataset generated from fine spatial resolution aerial photography. The object-based MESMA approach was compared with its corresponding pixel-based one, and EO-1/Hyperion hyperspectral data was compared with the simulated EO-1/Advanced Land Imager (ALI) multispectral data in the unmixing modeling. The pros and cons of the object-based MESMA were evaluated. The result illustrates that the object-based MESMA is promising for unmixing the medium-spatial resolution hyperspectral imagery to quantify the urban composition, and it is an attractive alternative to the traditional pixel-based mixture analysis for various applications.

  19. a Color Features-Based Method for Object Tracking Employing a Particle Filter Algorithm

    Science.gov (United States)

    Sugandi, Budi; Kim, Hyoungseop; Tan, Joo Kooi; Ishikawa, Seiji

    2009-08-01

    We proposed a method for object tracking employing a particle filter based on color feature method. A histogram-based framework is used to describe the features. Histograms are useful because they have property that they allow changes in the object appearance while the histograms remain the same. Particle filtering is used because it is very robust for non-linear and non-Gaussian dynamic state estimation problems and performs well when clutter and occlusions are present on the image. Bhattacharyya distance is used to weight the samples in the particle filter by comparing each sample's histogram with a specified target model and it makes the measurement matching and sample's weight updating more reasonable. The method is capable to track successfully the moving object in different outdoor environment with and without initial positions information, and also, capable to track the moving object in the presence of occlusion using an appearance condition. In this paper, we propose a color features-based method for object tracking based on the particle filters. The experimental results and data show the feasibility and the effectiveness of our method.

  20. Efficient Spatiotemporal Clutter Rejection and Nonlinear Filtering-based Dim Resolved and Unresolved Object Tracking Algorithms

    Science.gov (United States)

    Tartakovsky, A.; Tong, M.; Brown, A. P.; Agh, C.

    2013-09-01

    We develop efficient spatiotemporal image processing algorithms for rejection of non-stationary clutter and tracking of multiple dim objects using non-linear track-before-detect methods. For clutter suppression, we include an innovative image alignment (registration) algorithm. The images are assumed to contain elements of the same scene, but taken at different angles, from different locations, and at different times, with substantial clutter non-stationarity. These challenges are typical for space-based and surface-based IR/EO moving sensors, e.g., highly elliptical orbit or low earth orbit scenarios. The algorithm assumes that the images are related via a planar homography, also known as the projective transformation. The parameters are estimated in an iterative manner, at each step adjusting the parameter vector so as to achieve improved alignment of the images. Operating in the parameter space rather than in the coordinate space is a new idea, which makes the algorithm more robust with respect to noise as well as to large inter-frame disturbances, while operating at real-time rates. For dim object tracking, we include new advancements to a particle non-linear filtering-based track-before-detect (TrbD) algorithm. The new TrbD algorithm includes both real-time full image search for resolved objects not yet in track and joint super-resolution and tracking of individual objects in closely spaced object (CSO) clusters. The real-time full image search provides near-optimal detection and tracking of multiple extremely dim, maneuvering objects/clusters. The super-resolution and tracking CSO TrbD algorithm provides efficient near-optimal estimation of the number of unresolved objects in a CSO cluster, as well as the locations, velocities, accelerations, and intensities of the individual objects. We demonstrate that the algorithm is able to accurately estimate the number of CSO objects and their locations when the initial uncertainty on the number of objects is large. We demonstrate performance of the TrbD algorithm both for satellite-based and surface-based EO/IR surveillance scenarios.

  1. 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.

  2. 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.

  3. 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

  4. 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.

  5. Research on optimization of imaging parameters of optical remote sensing camera based on ground objects BRDF

    Science.gov (United States)

    Li, Fangqi; He, Hongyan; Bao, Yunfei; Xing, Kun; Zhang, Zhi

    2013-10-01

    With the development of high resolution remote sensing satellite in recent years, the research of typical objects is connecting more and more closely with remote sensing applications. In the TDI CCD camera on-orbit imaging process, great changes will happen on solar angles at different time, causing a certain change of BRDF of most earth's surface objects, and finally affect the remote sensing radiances, even imaging quality. In order to solve this problem, optimization of in-orbit parameters based on the ground objects BRDF is necessary. A detailed investigation about the global imaging area of ground objects characteristics is given in this paper. We inverse BRDF of different time based on Kernel-Driven BRDF model, establish database of ground objects BRDF, make a classification of ground objects characteristics, simulate imaging effect with radiative transfer model and degradation model of remote sensor, and then optimize imaging parameters according to the imaging quality requirement. The simulation results show that the contrast, definition and dynamic range of image have improved, the proposed method in this paper can set imaging parameters reasonably of different imaging conditions, improve the imaging quality of high resolution remote sensing satellites.

  6. 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.

  7. A Fast Object Tracking Approach Based on the Motion Vector in a Compressed Domain

    Directory of Open Access Journals (Sweden)

    Hui-bin Wang

    2013-01-01

    Full Text Available Particle set sampling and weighting are both at the core of particle filter‐based object tracking methods. Aiming to optimally represent the objectʹs motion state, a large amount of particles ‐ in the classical particle method ‐ is a prerequisite. The high‐cost calculation of these particles significantly slows down the convergence of the algorithm. To this problem, a prior approach which originated from the process of video compressing and uncompressing is introduced to optimize the phase of particle sampling, making the collected particles centre on and cover the object region in the current image. This advantage dramatically reduces the number of particles required by the regularized particle sampling method, solving the problem of the high computational cost for tracking objects, while the performance of the algorithm is stable.

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

    Directory of Open Access Journals (Sweden)

    Liubai Li

    2012-05-01

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

  9. 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

  10. 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 teachers 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.

  11. Attention, segregation, and textons: bridging the gap between object-based attention and texton-based segregation.

    Science.gov (United States)

    Ben-Shahar, Ohad; Scholl, Brian J; Zucker, Steven W

    2007-03-01

    Studies of object-based attention (OBA) have suggested that attentional selection is intimately associated with discrete objects. However, the relationship of this association to the basic visual features ('textons') which guide the segregation of visual scenes into 'objects' remains largely unexplored. Here we study this hypothesized relationship for one of the most conspicuous features of early vision: orientation. To do so we examine how attention spreads through uniform (one 'object') orientation-defined textures (ODTs), and across texture-defined boundaries in discontinuous (two 'objects') ODTs. Using the divided-attention paradigm we find that visual events that are known to trigger orientation-based texture segregation, namely perceptual boundaries defined by high orientation and/or curvature gradients, also induce a significant cost on attentional selection. At the same time we show that no effect is incurred by the absolute value of the textons, i.e., by the general direction (or, the 'grain') of the texture-in conflict with previous findings in the OBA literature. Collectively these experiments begin to reveal the link between object-based attention and texton-based segregation, a link which also offers important cross-disciplinary methodological advantages. PMID:17239914

  12. Research on digital holographic interferometry based on EALCD in three dimensional deformation measurements of objects

    Science.gov (United States)

    Li, Quan-yong; Mu, Da; Guo, Jun; Sun, Jie; Wang, Wen-sheng

    2012-10-01

    In recent years, with the occurrence of photoelectric sensitive devices such as charge-coupled device (CCD) and electrical addressed liquid crystal display (EALCD), particularly with the development in the computer technology, digital holography interferometry has been developing rapidly. Digital holography was one of the important techniques in the field of three-dimensional non-contact testing. In order to realize the digitalization and real-time of the holographic interferometry, the digital holographic interferometry system based on EALCD and CCD for displacement and three dimensional deformation measurement of objects is established. The hologram and reconstructed hologram are recorded by CCD. The hologram is reconstructed by EALCD instead of holographic plate. The interference fringes which caused by micro displacement and deformation has been realized by this system. The reconstruction images of objects and holographic interference fringes are all preferable. In this paper, the holographic reconstruction and interference fringe has been enhanced and denoised by compiling program based on MATLAB and C++ in digital image processing. The single algorithm cannot meet the requirement of the experiment, so various algorithms were used in combination in order to enhance image quality and make interpretation and calculation more convenient. The straight fringes reflect the micro displacement of the object, the bending fringes represent the deformation of the object. Based many advantages of CCD and EALCD, the actual holographic interferogram with high contrast can be obtained quickly in our experiments, which the precise measurement of micro displacement and three-dimensional deformation of objects can be acquired

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

    Directory of Open Access Journals (Sweden)

    Muhammad Kamal

    2011-10-01

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

  14. Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet.

    Science.gov (United States)

    Rolls, Edmund T

    2012-01-01

    Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus. PMID:22723777

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

    Science.gov (United States)

    Sharari, T. M.

    2015-03-01

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

  16. 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.

  17. An object-based conceptual model of a nuclear physics experiments database

    Energy Technology Data Exchange (ETDEWEB)

    Ehlmann, B.K. (Dept. of Computer and Information Systems, Florida A and M Univ., Tallahassee, FL (United States)); Dennis, L.C. (Dept. of Physics, Florida State Univ., Tallahassee, FL (United States)); Riccardi, G.A. (Dept. of Computer Science, Florida State Univ., Tallahassee, FL (United States))

    1993-02-01

    Nuclear physics experiments to be conducted at future accelerators will result in the accumulation of vast quantities of data. This paper briefly discusses an object-oriented database (OODB) approach for effectively managing this data and, more importantly, presents an object-based conceptual model of a nuclear physics experiments database as an initial by-product of applying this approach. The database model is provided by an object-relationship diagram (ORD). The concepts and conventions related to an ORD are explained, and the ORDs and associated terminology of the proposed model are given. Two prototypes that are currently being developed based on the model are also briefly discussed. The nuclear physics experiments database model and prototypes result from software research and development efforts associated with the Continuous Electron Beam Accelerator Facility (CEBAF). (orig.).

  18. MODEL OF STORAGE XML DATABASE BASED ON THE RELATIONAL-OBJECT MODEL

    Directory of Open Access Journals (Sweden)

    Laila Alami Kasri

    2010-11-01

    Full Text Available The objective of this work is to define a model of storage represented strictly in XML, this model is based on the structure of the relational model using the types of the model object. We suggest then creating our database according to this model by requests SQL3. We thus realize a framework of management and administration ofdatabases XML based on requests object relational SQL3. We analyze at first the mapping since a request SQL towards a structure of a document XML. We shall describe the mapping by using the language XML SCHEMA because the data must be validated in every operation on the database. The database structure, types and tables definitions will be transformed in an equivalent XML SCHEMA which will be used to store the valid XML data.

  19. 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.

  20. 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.

  1. 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.

  2. Particle-filter-based object tracking with color and texture information fusion

    Science.gov (United States)

    Chen, RuiQing; Zhang, ZhaoHui; Lu, HanQing; Cui, HuiQing; Yan, YuKun

    2009-10-01

    In this paper, we investigate object tracking in video sequences and propose a particle filter based tracking algorithm with color and texture information fusion, in which the target model is jointly represented by spatial-weighted color histogram and LBP (Local Binary Patterns) texture histogram. The property of local grayscale or color invariance for LBP operator makes it more reliable to measure the spatial structure of local image texture. The system is less sensitive to illumination changes and partial occlusions, and can be able to track objects in diverse conditions. Experimental results demonstrate that the performance of the proposed method is more robust and accurate than the original color based method, especially when tracking objects with similar color appearance to the background and partial occlusions.

  3. 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.

  4. Dynamic Multi-objective task scheduling in Cloud Computing based on Modified particle swarm optimization

    Directory of Open Access Journals (Sweden)

    A.I.Awad

    2015-09-01

    Full Text Available Task scheduling is one of the most important research topics in Cloud Computing environment. Dynamic Multi-objective task scheduling in Cloud Computing are proposed by using modified particle swarm optimization. This paper presents efficient allocation of tasks to available virtual machine in user level base on different parameters such as reliability, time, cost and load balancing of virtual machine. Agent used to create dynamic system. We propose mathematical model multi-objective Load Balancing Mutation particle swarm optimization (MLBMPSO to schedule and allocate tasks to resource. MLBMPSO considers two objective functions to minimize round trip time and total cost. Reliability can be achieved in system by getting task failure to allocate and reschedule with available resource based on load of virtual machine. Experimental results demonstrated that MLBMPSO outperformed the other algorithms in time and cost.

  5. 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.

  6. 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 ...

  7. 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...

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

    OpenAIRE

    Ka Wai E. Cheng; Weimin Wang

    2013-01-01

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

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

    OpenAIRE

    Š. Valčuha; J. Úradníček; A.Goti; Navarro, I.

    2011-01-01

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

  10. Objective Audio Quality Assessment Based on Spectro-Temporal Modulation Analysis

    OpenAIRE

    Guo, Ziyuan

    2011-01-01

    Objective audio quality assessment is an interdisciplinary research area that incorporates audiology and machine learning. Although much work has been made on the machine learning aspect, the audiology aspect also deserves investigation. This thesis proposes a non-intrusive audio quality assessment algorithm, which is based on an auditory model that simulates human auditory system. The auditory model is based on spectro-temporal modulation analysis of spectrogram, which has been proven to be ...

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

    OpenAIRE

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

    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...

  12. 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.

  13. 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

  14. 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…

  15. 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 fishe...

  16. Frequency Affects Object Relative Clause Processing: Some Evidence in Favor of Usage-Based Accounts

    Science.gov (United States)

    Reali, Florencia

    2014-01-01

    The processing difficulty of nested grammatical structure has been explained by different psycholinguistic theories. Here I provide corpus and behavioral evidence in favor of usage-based models, focusing on the case of object relative clauses in Spanish as a first language. A corpus analysis of spoken Spanish reveals that, as in English, the…

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

    Science.gov (United States)

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

    2009-01-01

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

  18. 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

  19. 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)

  20. 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…

  1. Mapping Urban Tree Species Using Very High ResolutionSatellite 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.

  2. 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.

  3. 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

  4. 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.

  5. Objective video quality assessment method for freeze distortion based on freeze aggregation

    Science.gov (United States)

    Watanabe, Keishiro; Okamoto, Jun; Kurita, Takaaki

    2006-01-01

    With the development of the broadband network, video communications such as videophone, video distribution, and IPTV services are beginning to become common. In order to provide these services appropriately, we must manage them based on subjective video quality, in addition to designing a network system based on it. Currently, subjective quality assessment is the main method used to quantify video quality. However, it is time-consuming and expensive. Therefore, we need an objective quality assessment technology that can estimate video quality from video characteristics effectively. Video degradation can be categorized into two types: spatial and temporal. Objective quality assessment methods for spatial degradation have been studied extensively, but methods for temporal degradation have hardly been examined even though it occurs frequently due to network degradation and has a large impact on subjective quality. In this paper, we propose an objective quality assessment method for temporal degradation. Our approach is to aggregate multiple freeze distortions into an equivalent freeze distortion and then derive the objective video quality from the equivalent freeze distortion. Specifically, our method considers the total length of all freeze distortions in a video sequence as the length of the equivalent single freeze distortion. In addition, we propose a method using the perceptual characteristics of short freeze distortions. We verified that our method can estimate the objective video quality well within the deviation of subjective video quality.

  6. Object-Based Analysis of Airborne LiDAR Data for Building Change Detection

    Directory of Open Access Journals (Sweden)

    Shiyan Pang

    2014-11-01

    Full Text Available Building change detection is useful for land management, disaster assessment, illegal building identification, urban growth monitoring, and geographic information database updating. This study proposes an automatic method that applies object-based analysis to multi-temporal point cloud data to detect building changes. The aim of this building change detection method is to identify areas that have changed and to obtain from-to information. In this method, the data are first preprocessed to generate two sets of digital surface models (DSMs, digital elevation models, and normalized DSMs from registered old and new point cloud data. Thereafter, on the basis of differential DSM, candidates for changed building objects are identified from the points in the smooth areas by using a connected component analysis technique. The random sample consensus fitting algorithm is then used to distinguish the true changed buildings from trees. The changed building objects are classified as “newly built”, “taller”, “demolished” or “lower” by using rule-based analysis. Finally, a test data set consisting of many buildings of different types in an 8.5 km2 area is selected for the experiment. In the test data set, the method correctly detects 97.8% of buildings larger than 50 m2. The accuracy of the method is 91.2%. Furthermore, to decrease the workload of subsequent manual checking of the result, the confidence index for each changed object is computed on the basis of object features.

  7. 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.

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

    Science.gov (United States)

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

    2014-11-01

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

  9. 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

  10. Infrared object detection using global and local cues based on LARK

    Science.gov (United States)

    Qi, Wei; Han, Jing; Zhang, Yi; Bai, Lian-fa

    2016-05-01

    Object detection has become a challenging problem in computer vision. Locally Adaptive Regression Kernel (LARK) based detection methods are able to produce visually pleasing results without any training. We in this paper present an effective object detection method by exploring global and local cues based on LARK features. First, we encode the local context similarity by exploiting region Structural LARK (SLARK) features, which measure the likeness of a pixel to its surroundings in the query image and the test image. Second, a global constraint based on SLARK features via Heat equation is learned to detect similar features in the test image. Results from matrix cosine similarity are computed to estimate similar regions between these computed features. A compactness score is provided to refine these regions. Next, we detect the location of objects in the test image using non-maxima suppression. We show in experiments that the proposed method significantly outperforms other methods on the infrared image datasets, localizing the objects in the test images effectively.

  11. 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

  12. 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

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

    Directory of Open Access Journals (Sweden)

    Jrme 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.

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

    Directory of Open Access Journals (Sweden)

    Da Rugna Jrme

    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.

  15. Burned Area Mapping in Greece Using SPOT-4 HRVIR Images and Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    Anastasia Polychronaki

    2012-02-01

    Full Text Available The devastating series of fire events that occurred during the summers of 2007 and 2009 in Greece made evident the need for an operational mechanism to map burned areas in an accurate and timely fashion to be developed. In this work, Système pour l’Observation de la Terre (SPOT-4 HRVIR images are introduced in an object-based classification environment in order to develop a classification procedure for burned area mapping. The development of the procedure was based on two images and then tested for its transferability to other burned areas. Results from the SPOT-4 HRVIR burned area mapping showed very high classification accuracies ( 0.86 kappa coefficient, while the object-based classification procedure that was developed proved to be transferable when applied to other study areas.

  16. 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.

  17. Stereo Image Based Object Localization Framework for Visually Impaired People Using Edge Orientation Histogram and Co-occurrence Matrices

    OpenAIRE

    Supakit Fuangkaew; Karn Patanukhom

    2015-01-01

    A new framework that uses internet-based images for detecting objects and estimating real world location of the objects via stereo images is proposed. This framework provides a self-learning ability for detecting desired objects in the scene without pre-prepared classifiers by harvesting sample images of the objects from the internet. Histogram and co-occurrence matrices of edge orientation are used as features. The objects are recognized based on likelihood scores and distance in the feature...

  18. 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

  19. Fast Multi-Object Image Segmentation Algorithm Based on C-V Model

    OpenAIRE

    Zhu Lei(Lana); Yang Jing

    2011-01-01

    Multi-objective image segmentation is a frequently encountered problem. The classical C-V algorithm has the shortage about multi-iterative operations and the computational time is too long to segment the large size image. On the base of analysis upon the relationship between the image size and the number of iterations and time to get the right result, the article proposes a fast image segmentation algorithm based on local C-V active contour model which are based on threshold segmentation and ...

  20. Validation of a computer based objective structured clinical examination in the assessment of undergraduate dermatology courses.

    Science.gov (United States)

    Kaliyadan, Feroze; Khan, Abdul Sattar; Kuruvilla, Joel; Feroze, Kaberi

    2014-01-01

    Many teaching centers have now adopted objective structured clinical examination (OSCE) as an assessment method for undergraduate dermatology courses. A modification of the standard OSCE in dermatology is computer based or electronic OSCE (eOSCE). We attempted to validate the use of a computer-based OSCE in dermatology in a group of fifth year medical students. The scores of the students in the computer-based OSCE showed a strong positive correlation with the scores on the clinical presentation (Pearson's co-efficient - 0.923, P value student (Pearson's co-efficient - 0.728, P value students' feedback regarding the methods was positive. PMID:24685849

  1. 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.

  2. 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%.

  3. 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.

  4. 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.

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

    Science.gov (United States)

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

    2015-02-01

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

  6. 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

  7. 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.

  8. Object Tracking with an Evolutionary Particle Filter Based on Self-Adaptive Multi-Features Fusion

    Directory of Open Access Journals (Sweden)

    Zhang Xiaowei

    2013-01-01

    Full Text Available Particle filter algorithms are widely used for object tracking in video sequences, but the standard particle filter algorithm cannot solve the validity of particles ideally. To solve the problems of particle degeneration and sample impoverishment in a particle filter tracking algorithm, an improved object tracking algorithm is proposed, which combines a multi‐feature fusion method and a genetic evolution mechanism. The algorithm dynamically computes the feature’s fusion weight by the discriminability of each vision feature and then constructs the important density function based on selecting a feature’s fusion method adaptively. Moreover, a self‐adaptive genetic evolutionary mechanism is introduced into the particle resampling process and makes the particle become an agent with the ability of dynamic self‐adaption. With self‐adaptive crossover and mutation operators, the evolution system produces a large number of new particles, which can better approximate the true state of the tracking object. The experimental results show that the proposed object tracking algorithm surpasses the conventional particle filter on both robustness and accuracy, even though the tracking object is very challenging regarding illumination variation, structural deformation, the interference of similar targets and occlusion.

  9. 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.

  10. 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

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

    Science.gov (United States)

    Vzquez-Cervantes, Alberto; Garca-Huerta, Juan-Manuel; Hernndez-Daz, Teresa; Soto-Cajiga, J. A.; Jimnez-Hernndez, 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.

  12. 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.)

  13. Micro-object motion tracking based on the probability hypothesis density particle tracker.

    Science.gov (United States)

    Shi, Chunmei; Zhao, Lingling; Wang, Junjie; Zhang, Chiping; Su, Xiaohong; Ma, Peijun

    2016-04-01

    Tracking micro-objects in the noisy microscopy image sequences is important for the analysis of dynamic processes in biological objects. In this paper, an automated tracking framework is proposed to extract the trajectories of micro-objects. This framework uses a probability hypothesis density particle filtering (PF-PHD) tracker to implement a recursive state estimation and trajectories association. In order to increase the efficiency of this approach, an elliptical target model is presented to describe the micro-objects using shape parameters instead of point-like targets which may cause inaccurate tracking. A novel likelihood function, not only covering the spatiotemporal distance but also dealing with geometric shape function based on the Mahalanobis norm, is proposed to improve the accuracy of particle weight in the update process of the PF-PHD tracker. Using this framework, a larger number of tracks are obtained. The experiments are performed on simulated data of microtubule movements and real mouse stem cells. We compare the PF-PHD tracker with the nearest neighbor method and the multiple hypothesis tracking method. Our PF-PHD tracker can simultaneously track hundreds of micro-objects in the microscopy image sequence. PMID:26084407

  14. 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.

  15. Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics

    Directory of Open Access Journals (Sweden)

    Mirko M. Stojiljković

    2014-12-01

    Full Text Available In this paper, a methodology for multi-objective optimization of trigeneration plants is presented. It is primarily applicable to the systems for buildings’ energy supply characterized by high load variations on daily, weekly and annual bases, as well as the components applicable for flexible operation. The idea is that this approach should enable high accuracy and flexibility in mathematical modeling, while remaining efficient enough. The optimization problem is structurally decomposed into two new problems. The main problem of synthesis and design optimization is combinatorial and solved with different metaheuristic methods. For each examined combination of the synthesis and design variables, when calculating the values of the objective functions, the inner, mixed integer linear programming operation optimization problem is solved with the branch-and-cut method. The applicability of the exploited metaheuristic methods is demonstrated. This approach is compared with the alternative, superstructure-based approach. The potential for combining them is also examined. The methodology is applied for multi-objective optimization of a trigeneration plant that could be used for the energy supply of a real residential settlement in Niš, Serbia. Here, two objectives are considered: annual total costs and primary energy consumption. Results are obtained in the form of a Pareto chart using the epsilon-constraint method.

  16. 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.

  17. 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...

  18. 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.

  19. 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.

  20. Unified web-based network management based on distributed object orientated software agents

    Science.gov (United States)

    Djalalian, Amir; Mukhtar, Rami; Zukerman, Moshe

    2002-09-01

    This paper presents an architecture that provides a unified web interface to managed network devices that support CORBA, OSI or Internet-based network management protocols. A client gains access to managed devices through a web browser, which is used to issue management operations and receive event notifications. The proposed architecture is compatible with both the OSI Management reference Model and CORBA. The steps required for designing the building blocks of such architecture are identified.

  1. 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.

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

    Science.gov (United States)

    Shang, Ming-Sheng; L, 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.

  3. A fusion algorithm for joins based on collections in Odra (Object Database for Rapid Application development)

    CERN Document Server

    Satish, Laika

    2011-01-01

    In this paper we present the functionality of a currently under development database programming methodology called ODRA (Object Database for Rapid Application development) which works fully on the object oriented principles. The database programming language is called SBQL (Stack based query language). We discuss some concepts in ODRA for e.g. the working of ODRA, how ODRA runtime environment operates, the interoperability of ODRA with .net and java .A view of ODRA's working with web services and xml. Currently the stages under development in ODRA are query optimization. So we present the prior work that is done in ODRA related to Query optimization and we also present a new fusion algorithm of how ODRA can deal with joins based on collections like set, lists, and arrays for query optimization.

  4. 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

    2016-01-01

    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

  5. 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)

  6. Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics

    OpenAIRE

    Mirko M. Stojiljković; Mladen M Stojiljković; Bratislav D. Blagojević

    2014-01-01

    In this paper, a methodology for multi-objective optimization of trigeneration plants is presented. It is primarily applicable to the systems for buildings’ energy supply characterized by high load variations on daily, weekly and annual bases, as well as the components applicable for flexible operation. The idea is that this approach should enable high accuracy and flexibility in mathematical modeling, while remaining efficient enough. The optimization problem is structurally decomposed into ...

  7. 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...

  8. Sparsity-based super-resolved coherent diffraction imaging of one-dimensional objects

    OpenAIRE

    Sidorenko, Pavel; Kfir, Ofer; Shechtman, Yoav; Fleischer, Avner; Eldar, Yonina C; Segev, Mordechai; Cohen, Oren

    2015-01-01

    Phase-retrieval problems of one-dimensional (1D) signals are known to suffer from ambiguity that hampers their recovery from measurements of their Fourier magnitude, even when their support (a region that confines the signal) is known. Here we demonstrate sparsity-based coherent diffraction imaging of 1D objects using extreme-ultraviolet radiation produced from high harmonic generation. Using sparsity as prior information removes the ambiguity in many cases and enhances the resolution beyond ...

  9. Multidisciplinary conceptual design optimization of aircraft using a sound-matching-based objective function

    OpenAIRE

    Diez, Matteo; Iemma, Umberto

    2011-01-01

    Abstract The paper presents a novel approach to include community noise considerations based on sound quality in Multidisciplinary Conceptual Design Optimization (MCDO) of civil transportation aircraft. The novelty stems from the use of an unconventional objective function, defined as a measure of the distance between the noise emission of the aircraft under analysis and a reference ?weakly annoying? noise, the target sound. The minimization of such a merit factor yields an aircraf...

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

    OpenAIRE

    Tersic, K.; J.M.F. Rodrigues; 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...

  11. Extending Object-Oriented Approaches to Hydrological Modelling based on Triangular Irregular Networks

    OpenAIRE

    Stedham, RL

    2011-01-01

    This research project aims to further explore an object oriented methodology in which a hydrological system is considered to be a series of interacting hydrological elements. It will extend Slingsby’s hydrological model TINMOD (2002) whose data structure is based on a TIN with embedded methods and behaviours to build, maintain and derive its topology – as well as derive hydrological information (flow-paths, basins, flow length) about itself. Specifically, this project aims to add functional...

  12. Empirical Validation of Objective Functions in Feature Selection Based on Acceleration Motion Segmentation Data

    OpenAIRE

    Jong Gwan Lim; Mi-hye Kim; Sahngwoon Lee

    2015-01-01

    Recent change in evaluation criteria from accuracy alone to trade-off with time delay has inspired multivariate energy-based approaches in motion segmentation using acceleration. The essence of multivariate approaches lies in the construction of highly dimensional energy and requires feature subset selection in machine learning. Due to fast process, filter methods are preferred; however, their poorer estimate is of the main concerns. This paper aims at empirical validation of three objective ...

  13. A Framework for the Design and Implementation of Learning Objects: a Competence-based Approach

    OpenAIRE

    Direito, Inês; Oliveira, Miguel; Real, Paulo; Antunes, Pedro,; Santos, Arnaldo; Duarte, A. Manuel de Oliveira

    2008-01-01

    This paper presents a framework for the design and implementation of learning objects using a competence-based approach. This framework is illustrated by the development of a standalone Windows application (Trilho GOA) whose primary purpose is to create standardized pedagogical contents trough the aggregation and standardization of instructional resources in several formats that can be used later on a Learning Management System (LMS) supporting SCORM 1.2. The paper contains a brief introducti...

  14. Mental rotation performance in soccer players and gymnasts in an object-based mental rotation task

    OpenAIRE

    Jansen, Petra; Lehmann, Jennifer

    2013-01-01

    In this study, the effect of motor expertise on an object-based mental rotation task was investigated. 60 males and 60 females (40 soccer players, 40 gymnasts, and 40 non-athletes, equivalent males and females in each group) solved a psychometric mental rotation task with both cube and human figures. The results revealed that all participants had a higher mental rotation accuracy for human figures compared to cubed figures, that the gender difference was reduced with human figures, and that g...

  15. 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 ...

  16. Subsurface Scattering-Based Object Rendering Techniques for Real-Time Smartphone Games

    OpenAIRE

    Won-Sun Lee; Seung-Do Kim; Seongah Chin

    2014-01-01

    Subsurface scattering that simulates the path of a light through the material in a scene is one of the advanced rendering techniques in the field of computer graphics society. Since it takes a number of long operations, it cannot be easily implemented in real-time smartphone games. In this paper, we propose a subsurface scattering-based object rendering technique that is optimized for smartphone games. We employ our subsurface scattering method that is utilized for a real-time smartphone game...

  17. 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...

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

    OpenAIRE

    Martin Sjlund; 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...

  19. 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.

  20. Object-Based Image Analysis of Downed Logs in Disturbed Forested Landscapes Using Lidar

    Directory of Open Access Journals (Sweden)

    Maggi Kelly

    2011-11-01

    Full Text Available Downed logs on the forest floor provide habitat for species, fuel for forest fires, and function as a key component of forest nutrient cycling and carbon storage. Ground-based field surveying is a conventional method for mapping and characterizing downed logs but is limited. In addition, optical remote sensing methods have not been able to map these ground targets due to the lack of optical sensor penetrability into the forest canopy and limited sensor spectral and spatial resolutions. Lidar (light detection and ranging sensors have become a more viable and common data source in forest science for detailed mapping of forest structure. This study evaluates the utility of discrete, multiple return airborne lidar-derived data for image object segmentation and classification of downed logs in a disturbed forested landscape and the efficiency of rule-based object-based image analysis (OBIA and classification algorithms. Downed log objects were successfully delineated and classified from lidar derived metrics using an OBIA framework. 73% of digitized downed logs were completely or partially classified correctly. Over classification occurred in areas with large numbers of logs clustered in close proximity to one another and in areas with vegetation and tree canopy. The OBIA methods were found to be effective but inefficient in terms of automation and analyst’s time in the delineation and classification of downed logs in the lidar data.

  1. 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

  2. Object extraction as a basic process for content-based image retrieval (CBIR) system

    Science.gov (United States)

    Jaworska, T.

    2007-12-01

    This article describes the way in which image is prepared for content-based image retrieval system. Automated image extraction is crucial; especially, if we take into consideration the fact that the feature selection is still a task performed by human domain experts and represents a major stumbling block in the process of creating fully autonomous CBIR systems. Our CBIR system is dedicated to support estate agents. In the database, there are images of houses and bungalows. We put all our efforts into extracting elements from an image and finding their characteristic features in the unsupervised way. Hence, the paper presents segmentation algorithm based on a pixel colour in RGB colour space. Next, it presents the method of object extraction applied to obtain separate objects prepared for the process of introducing them into database and further recognition. Moreover, we present a novel method of texture identification which is based on wavelet transformation. Due to the fact that the majority of texture is geometrical (such as bricks and tiles) we have used the Haar wavelet. After a set of low-level features for all objects is computed, the database is stored with these features.

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

    Science.gov (United States)

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

    2015-01-01

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

  4. 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.

  5. 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.

  6. 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)

  7. 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.

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

    Science.gov (United States)

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

    2012-10-01

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

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

    International Nuclear Information System (INIS)

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

  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. 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.

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

    Science.gov (United States)

    Strasser, Thomas; Lang, Stefan

    2015-05-01

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

  13. ICEMAP2 (Interactive California environmental management, assessment, and planning system mark 2): A MapObjects based Internet mapping service

    OpenAIRE

    Lehmer, Eric; Lampinen, Gail S.; McCoy, Michael C.; Quinn, James F.

    1998-01-01

    ICEMAPS2 is a new Internet mapping service of the Information Center for the Environment. It is based on the new technology of MapObjects, and MapObjects Internet Map Server. ICEMAPS2 exceeds its predecessor, ICEMAPS (based on PERL and Arc/Info), in performance and functionality. The success implementation of a MapObjects based map server has cut development and maintenance time dramatically. Future versions of ICEMAPS will most probably be based on ODE Arc/Info technology.

  14. 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.

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

    Directory of Open Access Journals (Sweden)

    Jung-Sing Jwo

    2012-12-01

    Full Text Available 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 searching applications, a simpler and easier solution will attract more enterprise users. In this paper, based on a concept called location signature, defined by a set of reference tags, an object searching method named Location Signature Search (LSS is proposed. The study of LSS shows that the searching accuracy can be very high if a location signature is not shared by too many locations. Since location signatures are affected by the deployment of the reference tags, trade-off between searching accuracy and implementation cost is achievable. A real world experiment is conducted in this research. The results show that LSS indeed is a practical method for object searching applications.

  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. An Objects Detecting and Tracking method based on MSPF and SVM

    Directory of Open Access Journals (Sweden)

    Wei Sun 1

    2012-02-01

    Full Text Available Considering that the robust real-time tracking of non-rigid objects is difficult to realize, We present an objects detecting and tracking method based on mean-shift particle filter (MSPF and support vector machine (SVM. The proposed algorithm uses the mean-shift vector of the tracking object to update the state transition matrix of particle filter algorithm, and we define the criterion of the particle degradation,to improve the conditions of degradation,the particles will be re-distributed as Gaussian distribution. Because of the real-time update of the particle motion parameters, the prediction accuracy of target motion parameters is improved. Under the condition of target conflicting and partially covering, the proposed algorithm is still tracking effectively. Apply SVM to relevance feedback of object detecting and tracking, the experiments results show that the method can overcome the shortness of the traditional methods, effectively improve the tracking speed and precision. The results of the experiment indicate that the average processing time per frame of the proposed algorithm is reduces by about 21% comparing with the classical ones,while the efficiency of particle increases by about 32%.

  20. 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.

  1. Mapping Urban Tree Species Using Very High ResolutionSatellite 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...

  2. An object-based classification method for automatic detection of lunar impact craters from topographic data

    Science.gov (United States)

    Vamshi, Gasiganti T.; Martha, Tapas R.; Vinod Kumar, K.

    2016-05-01

    Identification of impact craters is a primary requirement to study past geological processes such as impact history. They are also used as proxies for measuring relative ages of various planetary or satellite bodies and help to understand the evolution of planetary surfaces. In this paper, we present a new method using object-based image analysis (OBIA) technique to detect impact craters of wide range of sizes from topographic data. Multiresolution image segmentation of digital terrain models (DTMs) available from the NASA's LRO mission was carried out to create objects. Subsequently, objects were classified into impact craters using shape and morphometric criteria resulting in 95% detection accuracy. The methodology developed in a training area in parts of Mare Imbrium in the form of a knowledge-based ruleset when applied in another area, detected impact craters with 90% accuracy. The minimum and maximum sizes (diameters) of impact craters detected in parts of Mare Imbrium by our method are 29 m and 1.5 km, respectively. Diameters of automatically detected impact craters show good correlation (R2 > 0.85) with the diameters of manually detected impact craters.

  3. 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].

  4. 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

  5. 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.

  6. A System based on Adaptive Background Subtraction Approach for Moving Object Detection and Tracking in Videos

    Directory of Open Access Journals (Sweden)

    Bahadır KARASULU

    2013-04-01

    Full Text Available Video surveillance systems are based on video and image processing research areas in the scope of computer science. Video processing covers various methods which are used to browse the changes in existing scene for specific video. Nowadays, video processing is one of the important areas of computer science. Two-dimensional videos are used to apply various segmentation and object detection and tracking processes which exists in multimedia content-based indexing, information retrieval, visual and distributed cross-camera surveillance systems, people tracking, traffic tracking and similar applications. Background subtraction (BS approach is a frequently used method for moving object detection and tracking. In the literature, there exist similar methods for this issue. In this research study, it is proposed to provide a more efficient method which is an addition to existing methods. According to model which is produced by using adaptive background subtraction (ABS, an object detection and tracking system’s software is implemented in computer environment. The performance of developed system is tested via experimental works with related video datasets. The experimental results and discussion are given in the study

  7. Object-based change detection: dimension of damage in residential areas of Abu Suruj, Sudan

    Science.gov (United States)

    Demharter, Timo; Michel, Ulrich; Ehlers, Manfred; Reinartz, Peter

    2011-11-01

    Given the importance of Change Detection, especially in the field of crisis management, this paper discusses the advantage of object-based Change Detection. This project and the used methods give an opportunity to coordinate relief actions strategically. The principal objective of this project was to develop an algorithm which allows to detect rapidly damaged and destroyed buildings in the area of Abu Suruj. This Sudanese village is located in West-Darfur and has become the victim of civil war. The software eCognition Developer was used to per-form an object-based Change Detection on two panchromatic Quickbird 2 images from two different time slots. The first image shows the area before, the second image shows the area after the massacres in this region. Seeking a classification for the huts of the Sudanese town Abu Suruj was reached by first segmenting the huts and then classifying them on the basis of geo-metrical and brightness-related values. The huts were classified as "new", "destroyed" and "preserved" with the help of a automated algorithm. Finally the results were presented in the form of a map which displays the different conditions of the huts. The accuracy of the project is validated by an accuracy assessment resulting in an Overall Classification Accuracy of 90.50 percent. These change detection results allow aid organizations to provide quick and efficient help where it is needed the most.

  8. 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 agents local objective as well as organizations global objective concurrently and are commensurable with multi agent paradigm.

  9. 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.

  10. 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

  11. 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.

  12. 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

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

    Directory of Open Access Journals (Sweden)

    L. Monika Moskal

    2013-10-01

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

  14. 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%.

  15. 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

  16. 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.

  17. 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.

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

    CERN Document Server

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

    2009-01-01

    We estimate the fraction of mass that is composed of compact objects in gravitational lens galaxies. This study is based on microlensing measurements (obtained from the literature) of a sample of 29 quasar image pairs seen through 20 lens galaxies. We determine the baseline for no microlensing magnification between two images from the ratios of emission line fluxes. Relative to this baseline, the ratio between the continua of the two images gives the difference in microlensing magnification. The histogram of observed microlensing events peaks close to no magnification and is concentrated below 0.6 magnitudes, although two events of high magnification, $\\Delta m \\sim 1.5$, are also present. We study the likelihood of the microlensing measurements using frequency distributions obtained from simulated microlensing magnification maps for different values of the fraction of mass in compact objects, $\\alpha$. The concentration of microlensing measurements close to $\\Delta m \\sim 0$ can be explained only by simulati...

  19. 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.

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

    Directory of Open Access Journals (Sweden)

    Eloisa Valenza

    2014-03-01

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

  1. Spatial and thematic assessment of object-based forest stand delineation using an OFA-matrix

    Science.gov (United States)

    Hernando, A.; Tiede, D.; Albrecht, F.; Lang, S.

    2012-10-01

    The delineation and classification of forest stands is a crucial aspect of forest management. Object-based image analysis (OBIA) can be used to produce detailed maps of forest stands from either orthophotos or very high resolution satellite imagery. However, measures are then required for evaluating and quantifying both the spatial and thematic accuracy of the OBIA output. In this paper we present an approach for delineating forest stands and a new Object Fate Analysis (OFA) matrix for accuracy assessment. A two-level object-based orthophoto analysis was first carried out to delineate stands on the Dehesa Boyal public land in central Spain (Avila Province). Two structural features were first created for use in class modelling, enabling good differentiation between stands: a relational tree cover cluster feature, and an arithmetic ratio shadow/tree feature. We then extended the OFA comparison approach with an OFA-matrix to enable concurrent validation of thematic and spatial accuracies. Its diagonal shows the proportion of spatial and thematic coincidence between a reference data and the corresponding classification. New parameters for Spatial Thematic Loyalty (STL), Spatial Thematic Loyalty Overall (STLOVERALL) and Maximal Interfering Object (MIO) are introduced to summarise the OFA-matrix accuracy assessment. A stands map generated by OBIA (classification data) was compared with a map of the same area produced from photo interpretation and field data (reference data). In our example the OFA-matrix results indicate good spatial and thematic accuracies (>65%) for all stand classes except for the shrub stands (31.8%), and a good STLOVERALL (69.8%). The OFA-matrix has therefore been shown to be a valid tool for OBIA accuracy assessment.

  2. Demonstrator of a multi-object spectrograph based on the 2048×1080 DMD

    Science.gov (United States)

    Zamkotsian, Frederic; Spano, Paolo; Bon, William; Lanzoni, Patrick

    2012-03-01

    Multi-Object Spectrographs (MOS) are the major instruments for studying primary galaxies and remote and faint objects. Current object selection systems are limited and/or difficult to implement in next generation MOS for space and ground-based telescopes. A promising solution is the use of MOEMS devices such as micromirror arrays which allow the remote control of the multi-slit configuration in real time. We are developing a Digital Micromirror Device (DMD) - based spectrograph demonstrator. We want to access the largest FOV with the highest contrast. The selected component is a DMD chip from Texas Instruments in 2048 × 1080 mirrors format, with a pitch of 13.68μm. Such component has been also studied by our team in early phase EUCLID-NIS study. Our optical design is an all-reflective spectrograph design with F/4 on the DMD component, including two arms, one spectroscopic channel and one imaging channel, thanks to the two stable positions of DMD micromirrors. This demonstrator permits the study of key parameters such as throughput, contrast and ability to remove background and spoiler sources, PSF effect. This study will be conducted in the visible with possible extension in the IR. The breadboard has been designed and is under realization before integration on a bench simulating an astronomical FOV. The demonstrator is of prime importance for characterizing the actual performance of this new family of instruments, as well as investigating the operational procedures on astronomical objects. If this demonstrator is successful, next step will be a demonstrator instrument placed on the Telescopio Nazionale Galileo.

  3. Validation of a computer based objective structured clinical examination in the assessment of undergraduate dermatology courses

    Directory of Open Access Journals (Sweden)

    Feroze Kaliyadan

    2014-01-01

    Full Text Available Many teaching centers have now adopted objective structured clinical examination (OSCE as an assessment method for undergraduate dermatology courses. A modification of the standard OSCE in dermatology is computer based or electronic OSCE (eOSCE. We attempted to validate the use of a computer-based OSCE in dermatology in a group of fifth year medical students. The scores of the students in the computer-based OSCE showed a strong positive correlation with the scores on the clinical presentation (Pearson′s co-efficient - 0.923, P value <0.000, significant at the 0.01 level and a good correlation with overall scores of the student (Pearson′s co-efficient - 0.728, P value <0.000, significant at the 0.01 level, indicating that this is a reliable method for assessment in dermatology. Generally, the students′ feedback regarding the methods was positive.

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

    Directory of Open Access Journals (Sweden)

    Š. Valčuha

    2011-04-01

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

  5. A Grid Based Cooperative Co-evolutionary Multi-Objective Algorithm

    Science.gov (United States)

    Fard, Sepehr Meshkinfam; Hamzeh, Ali; Ziarati, Koorush

    In this paper, a well performing approach in the context of Multi-Objective Evolutionary Algorithm (MOEA) is investigated due to its complexity. This approach called NSCCGA is based on previously introduced approach called NSGA-II. NSCCGA performs better than NSGA-II but with a heavy load of computational complexity. Here, a novel approach called GBCCGA is introduced based on MOCCGA with some modifications. The main difference between GBCCGA and MOCCGA is in their niching technique which instead of the traditional sharing mechanism in MOCCGA, a novel grid-based technique is used in GBCCGA. The reported results show that GBCCGA performs roughly the same as NSCCGA but with very low computational complexity with respect to the original MOCCGA.

  6. Segmentation and Classification of Remotely Sensed Images: Object-Based Image Analysis

    Science.gov (United States)

    Syed, Abdul Haleem

    Land-use-and-land-cover (LULC) mapping is crucial in precision agriculture, environmental monitoring, disaster response, and military applications. The demand for improved and more accurate LULC maps has led to the emergence of a key methodology known as Geographic Object-Based Image Analysis (GEOBIA). The core idea of the GEOBIA for an object-based classification system (OBC) is to change the unit of analysis from single-pixels to groups-of-pixels called `objects' through segmentation. While this new paradigm solved problems and improved global accuracy, it also raised new challenges such as the loss of accuracy in categories that are less abundant, but potentially important. Although this trade-off may be acceptable in some domains, the consequences of such an accuracy loss could be potentially fatal in others (for instance, landmine detection). This thesis proposes a method to improve OBC performance by eliminating such accuracy losses. Specifically, we examine the two key players of an OBC system: Hierarchical Segmentation and Supervised Classification. Further, we propose a model to understand the source of accuracy errors in minority categories and provide a method called Scale Fusion to eliminate those errors. This proposed fusion method involves two stages. First, the characteristic scale for each category is estimated through a combination of segmentation and supervised classification. Next, these estimated scales (segmentation maps) are fused into one combined-object-map. Classification performance is evaluated by comparing results of the multi-cut-and-fuse approach (proposed) to the traditional single-cut (SC) scale selection strategy. Testing on four different data sets revealed that our proposed algorithm improves accuracy on minority classes while performing just as well on abundant categories. Another active obstacle, presented by today's remotely sensed images, is the volume of information produced by our modern sensors with high spatial and temporal resolution. For instance, over this decade, it is projected that 353 earth observation satellites from 41 countries are to be launched. Timely production of geo-spatial information, from these large volumes, is a challenge. This is because in the traditional methods, the underlying representation and information processing is still primarily pixel-based, which implies that as the number of pixels increases, so does the computational complexity. To overcome this bottleneck, created by pixel-based representation, this thesis proposes a dart-based discrete topological representation (DBTR), where the DBTR differs from pixel-based methods in its use of a reduced boundary based representation. Intuitively, the efficiency gains arise from the observation that, it is lighter to represent a region by its boundary (darts) than by its area (pixels). We found that our implementation of DBTR, not only improved our computational efficiency, but also enhanced our ability to encode and extract spatial information. Overall, this thesis presents solutions to two problems of an object-based classification system: accuracy and efficiency. Our proposed Scale Fusion method demonstrated improvements in accuracy, while our dart-based topology representation (DBTR) showed improved efficiency in the extraction and encoding of spatial information.

  7. 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.

  8. High-speed three-dimensional shape measurement for isolated objects based on fringe projection

    Science.gov (United States)

    Li, Yong; Zhao, Cuifang; Wang, Hui; Jin, Hongzhen

    2011-03-01

    A method for high-speed measurement of the three-dimensional (3D) shape of spatially isolated objects is proposed. Two sinusoidal fringe patterns with phase difference π and an encoded pattern are used to measure the 3D shape. A modified Fourier transform profilometry (FTP) method is used for phase retrieval and obtaining high-quality texture. The measurable slope of the height variation is larger than for methods based on traditional FTP and the same as that for methods based on phase measurement profilometry (PMP). The number of patterns is less than for the high-speed methods based on PMP, using which isolated objects can be measured. Consequently, this approach is less sensitive to object motion. In the proposed method, the encoded pattern consists of vertical stripes with width the same as the period of the sinusoidal fringe. Three gray levels are used to form the stripes. Six symbols are encoded with these three gray levels. Then, a pseudorandom sequence is constructed with an alphabet of these six symbols. The stripes are arranged according to the sequence to form the pattern. In the procedure of phase unwrapping, the strings (subsequences) are constructed with symbols corresponding to three neighbor periods of the deformed fringe. The position of the subsequence is worked out by string matching in the pseudorandom sequence. The ranking number of the fringe is identified and then the absolute phase of the deformed fringe is obtained. The 3D shape of the objects is reconstructed with triangulation. A system consisting of a specially designed digital light processing projector and a high-speed camera is presented. The 3D capture speed of 60 frames per second (fps), with a resolution of 640 × 480 points, and that of 120 fps, with a resolution of 320 × 240 points, were achieved. Preliminary experimental results are given. If the control logic of the digital micromirror device was modified and a camera with higher speed was employed, the measurement speed would reach thousands of fps. This makes it possible to analyze dynamic objects.

  9. High-speed three-dimensional shape measurement for isolated objects based on fringe projection

    International Nuclear Information System (INIS)

    A method for high-speed measurement of the three-dimensional (3D) shape of spatially isolated objects is proposed. Two sinusoidal fringe patterns with phase difference π and an encoded pattern are used to measure the 3D shape. A modified Fourier transform profilometry (FTP) method is used for phase retrieval and obtaining high-quality texture. The measurable slope of the height variation is larger than for methods based on traditional FTP and the same as that for methods based on phase measurement profilometry (PMP). The number of patterns is less than for the high-speed methods based on PMP, using which isolated objects can be measured. Consequently, this approach is less sensitive to object motion. In the proposed method, the encoded pattern consists of vertical stripes with width the same as the period of the sinusoidal fringe. Three gray levels are used to form the stripes. Six symbols are encoded with these three gray levels. Then, a pseudorandom sequence is constructed with an alphabet of these six symbols. The stripes are arranged according to the sequence to form the pattern. In the procedure of phase unwrapping, the strings (subsequences) are constructed with symbols corresponding to three neighbor periods of the deformed fringe. The position of the subsequence is worked out by string matching in the pseudorandom sequence. The ranking number of the fringe is identified and then the absolute phase of the deformed fringe is obtained. The 3D shape of the objects is reconstructed with triangulation. A system consisting of a specially designed digital light processing projector and a high-speed camera is presented. The 3D capture speed of 60 frames per second (fps), with a resolution of 640 × 480 points, and that of 120 fps, with a resolution of 320 × 240 points, were achieved. Preliminary experimental results are given. If the control logic of the digital micromirror device was modified and a camera with higher speed was employed, the measurement speed would reach thousands of fps. This makes it possible to analyze dynamic objects

  10. 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.

  11. MEMS design synthesis: integrating case-based reasoning and multi-objective genetic algorithms

    Science.gov (United States)

    Cobb, Corie L.; Zhang, Ying; Agogino, Alice M.

    2007-01-01

    A case-based reasoning (CBR) knowledge base has been incorporated into a Micro-Electro-Mechanical Systems (MEMS) design tool that uses a multi-objective genetic algorithm (MOGA) to synthesize and optimize conceptual designs. CBR utilizes previously successful MEMS designs and sub-assemblies as building blocks stored in an indexed case library, which serves as the knowledge base for the synthesis process. Designs in the case library are represented in a parameterized object-oriented format, incorporating MEMS domain knowledge into the design synthesis loop as well as restrictions for the genetic operations of mutation and crossover for MOGA optimization. Reasoning tools locate cases in the design library with solved problems similar to the current design problem and suggest promising conceptual designs which have the potential to be starting design populations for a MOGA evolutionary optimization process, to further generate more MEMS designs concepts. Surface micro-machined resonators are used as an example to introduce this integrated MEMS design synthesis process. The results of testing on resonator case studies demonstrate how the combination of CBR and MOGA synthesis tools can help increase the number of optimal design concepts presented to MEMS designers.

  12. Multi-Objective Predictive Balancing Control of Battery Packs Based on Predictive Current

    Directory of Open Access Journals (Sweden)

    Wenbiao Li

    2016-04-01

    Full Text Available Various balancing topology and control methods have been proposed for the inconsistency problem of battery packs. However, these strategies only focus on a single objective, ignore the mutual interaction among various factors and are only based on the external performance of the battery pack inconsistency, such as voltage balancing and state of charge (SOC balancing. To solve these problems, multi-objective predictive balancing control (MOPBC based on predictive current is proposed in this paper, namely, in the driving process of an electric vehicle, using predictive control to predict the battery pack output current the next time. Based on this information, the impact of the battery pack temperature caused by the output current can be obtained. Then, the influence is added to the battery pack balancing control, which makes the present degradation, temperature, and SOC imbalance achieve balance automatically due to the change of the output current the next moment. According to MOPBC, the simulation model of the balancing circuit is built with four cells in Matlab/Simulink. The simulation results show that MOPBC is not only better than the other traditional balancing control strategies but also reduces the energy loss in the balancing process.

  13. A novel fractal monocular and stereo video codec with object-based functionality

    Science.gov (United States)

    Zhu, Shiping; Li, Liyun; Wang, Zaikuo

    2012-12-01

    Based on the classical fractal video compression method, an improved monocular fractal compression method is proposed which includes using more effective macroblock partition scheme instead of classical quadtree partition scheme; using improved fast motion estimation to increase the calculation speed; using homo-I-frame like in H.264, etc. The monocular codec uses the motion compensated prediction (MCP) structure. And stereo fractal video coding is proposed which matches the macroblock with two reference frames in left and right views, and it results in increasing compression ratio and reducing bit rate/bandwidth when transmitting compressed video data. The stereo codec combines MCP and disparity compensated prediction. And a new method of object-based fractal video coding is proposed in which each object can be encoded and decoded independently with higher compression ratio and speed and less bit rate/bandwidth when transmitting compressed stereo video data greatly. Experimental results indicate that the proposed monocular method can raise compression ratio 3.6 to 7.5 times, speed up compression time 5.3 to 22.3 times, and improve the image quality 3.81 to 9.24 dB in comparison with circular prediction mapping and non-contractive interframe mapping. The PSNR of the proposed stereo video coding is about 0.17 dB higher than that of the proposed monocular video coding, and 0.69 dB higher than that of JMVC 4.0 on average. Comparing with the bit rate resulted by the proposed monocular video coding and JMVC 4.0, the proposed stereo video coding achieves, on average, 2.53 and 21.14 Kbps bit rate saving, respectively. The proposed object-based fractal monocular and stereo video coding methods are simple and effective, and they make the applications of fractal monocular and stereo video coding more flexible and practicable.

  14. 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

  15. BATMAN: a DMD-based multi-object spectrograph on Galileo telescope

    Science.gov (United States)

    Zamkotsian, Frederic; Spano, Paolo; Lanzoni, Patrick; Ramarijaona, Harald; Moschetti, Manuele; Riva, Marco; Bon, William; Nicastro, Luciano; Molinari, Emilio; Cosentino, Rosario; Ghedina, Adriano; Gonzalez, Manuel; Di Marcantonio, Paolo; Coretti, Igor; Cirami, Roberto; Zerbi, Filippo; Valenziano, Luca

    2014-07-01

    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 are developing a 2048x1080 Digital-Micromirror-Device-based (DMD) 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 field of view (FOV) is 6.8 arcmin x 3.6 arcmin with a plate scale of 0.2 arcsec per micromirror. The wavelength range is in the visible and the spectral resolution is R=560 for 1 arcsec object (typical slit size). The two arms will have 2k x 4k CCD detectors. 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 and spectra have been obtained and measured: typical spot diameters are within 1.5 detector pixels, and spectra generated by one micro-mirror slits are displayed with this optical quality over the whole visible wavelength range. Observation strategies are 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 mid-2015.

  16. Developing a framework for monitoring coastal habitats using aerial imagery and object-based image analysis

    DEFF Research Database (Denmark)

    Juel, Anders

    Denmark contains major areas of coastal habitats, including a significant part of the European area of coastal dunes and salt marshes. The natural dynamics in coastal habitats are a prerequisite for the maintenance of their structure and biodiversity, yet very little research on the implications of...... decreased habitat dynamics exists. A valuable source of land cover changes are historical aerial imagery of which Denmark has unique datasets.This poster presents an object-based image analysis approach for mapping and monitoring af coastal habitat stucture, which integrates the high spectral resolution and...

  17. 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...

  18. The study on gear transmission multi-objective optimum design based on SQP algorithm

    Science.gov (United States)

    Li, Quancai; Qiao, Xuetao; Wu, Cuirong; Wang, Xingxing

    2011-12-01

    Gear mechanism is the most popular transmission mechanism; however, the traditional design method is complex and not accurate. Optimization design is the effective method to solve the above problems, used in gear design method. In many of the optimization software MATLAB, there are obvious advantage projects and numerical calculation. There is a single gear transmission as example, the mathematical model of gear transmission system, based on the analysis of the objective function, and on the basis of design variables and confirmation of choice restrictive conditions. The results show that the algorithm through MATLAB, the optimization designs, efficient, reliable, simple.

  19. 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.

  20. Evaluating Learning Algorithms to Support Human Rule Evaluation Based on Objective Rule Evaluation Indices

    OpenAIRE

    Abe, H.; Tsumoto, S.; Ohsaki, M; Yamaguchi, T.

    2007-01-01

    In this paper, we present an evaluation of learning algorithms of a novel rule evaluation support method for post-processing of mined results with rule evaluation models based on objective indices. Post-processing of mined results is one of the key processes in a data mining process. However, it is difficult for human experts to completely evaluate several thousands of rules from a large dataset with noise. To reduce the costs in such rule evaluation task, we have developed a rule evaluation ...

  1. 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.

  2. TOWARDS ENHANCING SOLUTION SPACE DIVERSITY IN MULTI-OBJECTIVE OPTIMIZATION: A HYPERVOLUME-BASED APPROACH

    Directory of Open Access Journals (Sweden)

    Kamyab Tahernezhadiani

    2012-02-01

    Full Text Available Diversity is an important notion in multi-objective evolutionary algorithms (MOEAs and a lot ofresearchers have investigated this issue by means of appropriate methods. However most of evolutionarymulti-objective algorithms have attempted to take control on diversity in the objective space only andmaximized diversity of solutions (population on Pareto- front. Nowadays due to importance of Multiobjectiveoptimization in industry and engineering, most of the designers want to find a diverse set ofPareto-optimal solutions which cover as much as space in its feasible regain of the solution space. Thispaper addresses this issue and attempt to introduce a method for preserving diversity of non-dominatedsolution (i.e. Pareto-set in the solution space. This paper introduces the novel diversity measure as a firsttime, and then this new diversity measure is integrated efficiently into the hypervolume based Multiobjectivemethod. At end of this paper we compare the proposed method with other state-of-the-artalgorithms on well-established test problems. Experimental results show that the proposed methodoutperforms its competitive MOEAs respect to the quality of solution space criteria and Pareto-setapproximation.

  3. 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

  4. Multi-objective exergy-based optimization of a polygeneration energy system using an evolutionary algorithm

    International Nuclear Information System (INIS)

    A comprehensive thermodynamic modeling and optimization is reported of a polygeneration energy system for the simultaneous production of heating, cooling, electricity and hot water from a common energy source. This polygeneration system is composed of four major parts: gas turbine (GT) cycle, Rankine cycle, absorption cooling cycle and domestic hot water heater. A multi-objective optimization method based on an evolutionary algorithm is applied to determine the best design parameters for the system. The two objective functions utilized in the analysis 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 by using an evolutionary algorithm. To provide a deeper insight, the Pareto frontier is shown for multi-objective optimization. In addition, a closed form equation for the relationship between exergy efficiency and total cost rate is derived. Finally, a sensitivity analysis is performed to assess the effects of several design parameters on the system total exergy destruction rate, CO2 emission and exergy efficiency.

  5. 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.

  6. Supporting dynamic pipeline changes using Class-Based Object Versioning in Astro-WISE

    Science.gov (United States)

    Mwebaze, Johnson; Boxhoorn, Danny; Rai, Idris; Valentijn, Edwin A.

    2013-01-01

    Understanding the difference between data objects is a major problem especially in a scientific collaboration which allows scientists to collectively reuse data, modify and adapt scripts developed by their peers to process data while publishing the results to a centralized data store. Although data provenance has been significantly studied to address the origins of a data item, it does not however address changes made to the source code. Systems often appear as a large number of modules each containing hundreds of lines of code. It is, in general, not obvious which parts of source code contributed to the change in data object. The paper introduces the Class-Based Object Versioning framework, which overcomes some of the shortcomings of popular versioning systems (e.g. CVS, SVN) in maintaining data and code provenance information in scientific computing environments. The framework automatically identifies and captures useful fine-grained changes in the data and code of scripts that perform scientific experiments so that important information about intermediate stages (i.e. unrecorded changes in experiment parameters and procedures) can be identified and analyzed. The benefits of such a system include querying specific methods and code attributes for data items of interest, finding missing gaps of data lineage and implicit storage of intermediate data.

  7. 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.

  8. 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.

  9. Optimal reactive power flow incorporating static voltage stability based on multi-objective adaptive immune algorithm

    International Nuclear Information System (INIS)

    People have paid more attention to enhancing voltage stability margin since voltage collapses happened in some power systems recently. This paper proposes an optimal reactive power flow (ORPF) incorporating static voltage stability based on a multi-objective adaptive immune algorithm (MOAIA). The main idea of the proposed algorithm is to add two parts to an existing immune algorithm. The first part defines both partial affinity and global affinity to evaluate the antibody affinity to the multi-objective functions. The second part uses adaptive crossover, mutation and clone rates for antibodies to maintain the antibodies diversity. Hence, the proposed algorithm can achieve a dynamic balance between individual diversity and population convergence. The paper describes ORPF's multi-objective functional mathematical model and the constraint conditions. The problems associated with the antibody are also discussed in detail. The proposed method has been tested in the IEEE-30 system and compared with IGA (immune genetic algorithm). The results show that the proposed algorithm has improved performance over the IGA

  10. System design and improvement of an emergency department using Simulation-Based Multi-Objective Optimization

    Science.gov (United States)

    Goienetxea Uriarte, A.; Ruiz Zúñiga, E.; Urenda Moris, M.; Ng, A. H. C.

    2015-05-01

    Discrete Event Simulation (DES) is nowadays widely used to support decision makers in system analysis and improvement. However, the use of simulation for improving stochastic logistic processes is not common among healthcare providers. The process of improving healthcare systems involves the necessity to deal with trade-off optimal solutions that take into consideration a multiple number of variables and objectives. Complementing DES with Multi-Objective Optimization (SMO) creates a superior base for finding these solutions and in consequence, facilitates the decision-making process. This paper presents how SMO has been applied for system improvement analysis in a Swedish Emergency Department (ED). A significant number of input variables, constraints and objectives were considered when defining the optimization problem. As a result of the project, the decision makers were provided with a range of optimal solutions which reduces considerably the length of stay and waiting times for the ED patients. SMO has proved to be an appropriate technique to support healthcare system design and improvement processes. A key factor for the success of this project has been the involvement and engagement of the stakeholders during the whole process.

  11. Intuitive Terrain Reconstruction Using Height Observation-Based Ground Segmentation and 3D Object Boundary Estimation

    Directory of Open Access Journals (Sweden)

    Sungdae Sim

    2012-12-01

    Full Text Available Mobile robot operators must make rapid decisions based on information about the robot’s surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot’s array of sensors, but some upper parts of objects are beyond the sensors’ measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances.

  12. 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.)

  13. 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

  14. 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 users function requirements, an OKM expression representation based on the users 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.