Sample records for ladar based object

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

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


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

  2. Ladar-based terrain cover classification

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


    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. Photographic-based target models for LADAR applications

    Jack, James T.; Delashmit, Walter H.


    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.

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

    Mateo, Ana Baselga


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

  5. Optical imaging process based on two-dimensional Fourier transform for synthetic aperture imaging ladar

    Sun, Zhiwei; Zhi, Ya'nan; Liu, Liren; Sun, Jianfeng; Zhou, Yu; Hou, Peipei


    The synthetic aperture imaging ladar (SAIL) systems typically generate large amounts of data difficult to compress with digital method. This paper presents an optical SAIL processor based on compensation of quadratic phase of echo in azimuth direction and two dimensional Fourier transform. The optical processor mainly consists of one phase-only liquid crystal spatial modulator(LCSLM) to load the phase data of target echo and one cylindrical lens to compensate the quadratic phase and one spherical lens to fulfill the task of two dimensional Fourier transform. We show the imaging processing result of practical target echo obtained by a synthetic aperture imaging ladar demonstrator. The optical processor is compact and lightweight and could provide inherent parallel and the speed-of-light computing capability, it has a promising application future especially in onboard and satellite borne SAIL systems.

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

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


    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.

  7. Spectral ladar: towards active 3D multispectral imaging

    Powers, Michael A.; Davis, Christopher C.


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

  8. MBE based HgCdTe APDs and 3D LADAR sensors

    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


    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 China Lake. Excellent spatial and range resolution has been achieved with 3D imagery demonstrated both at short range and long range. Ongoing development under an Air Force Sponsored MANTECH program of high performance HgCdTe MBE APDs grown on large silicon wafers promise significant FPA cost reduction both by increasing the number of arrays on a given wafer and enabling automated processing.

  9. EO Scanned Micro-LADAR Project

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

  10. EO Scanned Micro-LADAR Project

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

  11. Research on key technologies of LADAR echo signal simulator

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


    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.

  12. Target recognition for ladar range image using slice image

    Xia, Wenze; Han, Shaokun; Wang, Liang


    A shape descriptor and a complete shape-based recognition system using slice images as geometric feature descriptor for ladar range images are introduced. A slice image is a two-dimensional image generated by three-dimensional Hough transform and the corresponding mathematical transformation. The system consists of two processes, the model library construction and recognition. In the model library construction process, a series of range images are obtained after the model object is sampled at preset attitude angles. Then, all the range images are converted into slice images. The number of slice images is reduced by clustering analysis and finding a representation to reduce the size of the model library. In the recognition process, the slice image of the scene is compared with the slice image in the model library. The recognition results depend on the comparison. Simulated ladar range images are used to analyze the recognition and misjudgment rates, and comparison between the slice image representation method and moment invariants representation method is performed. The experimental results show that whether in conditions without noise or with ladar noise, the system has a high recognition rate and low misjudgment rate. The comparison experiment demonstrates that the slice image has better representation ability than moment invariants.

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

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


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

  14. Miniature Ground Mapping LADAR Project

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

  15. Comprehensive high-speed simulation software for ladar systems

    Kim, Seongjoon; Hwang, Seran; Son, Minsoo; Lee, Impyeong


    Simulation of LADAR systems is particularly important for the verification of the system design through the performance assessment. Although many researchers attempted to develop various kinds of LADAR simulators, most of them have some limitations in being practically used for the general design of diverse types of LADAR system. We thus attempt to develop high-speed simulation software that is applicable to different types of LADAR system. In summary, we analyzed the previous studies related to LADAR simulation and, based on those existing works, performed the sensor modeling in various aspects. For the high-speed operation, we incorporate time-efficient incremental coherent ray-tracing algorithms, 3D spatial database systems for efficient spatial query, and CUDA based parallel computing. The simulator is mainly composed of three modules: geometry, radiometry, and visualization modules. Regarding the experimental results, our simulation software could successfully generate the simulated data based on the pre-defined system parameters. The validation of simulation results is performed by the comparison with the real LADAR data, and the intermediate results are promising. We believe that the developed simulator can be widely useful for various fields.

  16. Anomaly Detection in Clutter using Spectrally Enhanced Ladar

    Chhabra, Puneet S; Hopgood, James R


    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 ...

  17. Ladar scene projector for a hardware-in-the-loop simulation system.

    Xu, Rui; Wang, Xin; Tian, Yi; Li, Zhuo


    In order to test a direct-detection ladar in a hardware-in-the-loop simulation system, a ladar scene projector is proposed. A model based on the ladar range equation is developed to calculate the profile of the ladar return signal. The influences of both the atmosphere and the target's surface properties are considered. The insertion delays of different channels of the ladar scene projector are investigated and compensated for. A target range image with 108 pixels is generated. The simulation range is from 0 to 15 km, the range resolution is 1.04 m, the range error is 1.28 cm, and the peak-valley error for different channels is 15 cm. PMID:27463932

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

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

  19. Doublet Pulse Coherent Laser Radar for Tracking of Resident Space Objects

    Prasad, Narasimha S.; Rudd, Van; Shald, Scott; Sandford, Stephen; Dimarcantonio, Albert


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

  20. Super-resolution for flash LADAR data

    Hu, Shuowen; Young, S. Susan; Hong, Tsai; Reynolds, Joseph P.; Krapels, Keith; Miller, Brian; Thomas, Jim; Nguyen, Oanh


    Flash laser detection and ranging (LADAR) systems are increasingly used in robotics applications for autonomous navigation and obstacle avoidance. Their compact size, high frame rate, wide field of view, and low cost are key advantages over traditional scanning LADAR devices. However, these benefits are achieved at the cost of spatial resolution. Super-resolution enhancement can be applied to improve the resolution of flash LADAR devices, making them ideal for small robotics applications. Previous work by Rosenbush et al. applied the super-resolution algorithm of Vandewalle et al. to flash LADAR data, and observed quantitative improvement in image quality in terms of number of edges detected. This study uses the super-resolution algorithm of Young et al. to enhance the resolution of range data acquired with a SwissRanger SR-3000 flash LADAR camera. To improve the accuracy of sub-pixel shift estimation, a wavelet preprocessing stage was developed and applied to flash LADAR imagery. The authors used the triangle orientation discrimination (TOD) methodology for a subjective evaluation of the performance improvement (measured in terms of probability of target discrimination and subject response times) achieved with super-resolution. Super-resolution of flash LADAR imagery resulted in superior probabilities of target discrimination at the all investigated ranges while reducing subject response times.

  1. Anti-ship missile tracking with a chirped AM ladar - Update: design, model predictions, and experimental results

    Redman, Brian; Ruff, William; Stann, Barry; Giza, Mark; Lawler, William; Dammann, John; Potter, William


    Shipboard infrared search and track (IRST) systems can detect sea-skimming, anti-ship missiles at long ranges. Since IRST systems cannot measure range and line-of-sight (LOS) velocity, they have difficulty distinguishing missiles from false targets and clutter. In a joint Army-Navy program, the Army Research Laboratory (ARL) is developing a ladar based on the chirped amplitude modulation (AM) technique to provide range and velocity measurements of potential targets handed-over by the distributed aperture system - IRST (DAS-IRST) being developed by the Naval Research Laboratory (NRL) and sponsored by the Office of Naval Research (ONR). Using the ladar's range and velocity data, false alarms and clutter will be eliminated, and valid missile targets' tracks will be updated. By using an array receiver, ARL's ladar will also provide 3D imagery of potential threats for force protection/situational awareness. The concept of operation, the Phase I breadboard ladar design and performance model results, and the Phase I breadboard ladar development program were presented in paper 5413-16 at last year's symposium. This paper will present updated design and performance model results, as well as recent laboratory and field test results for the Phase I breadboard ladar. Implications of the Phase I program results on the design, development, and testing of the Phase II brassboard ladar will also be discussed.

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

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


    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.

  3. Monostatic all-fiber scanning LADAR system.

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


    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

  4. Object-Based Benefits without Object-Based Representations

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


    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...

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

    Mateo, Ana Baselga


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

  6. Imaging of Airborne Synthetic Aperture Ladar under Platform Vibration Condition

    Ma Meng; Li Dao-jing; Du Jian-bo


    This study examines the imaging problems in airborne synthetic aperture ladar with single detector and dual detectors along tracks under platform vibration condition. Because platform vibrations affect imaging processing for short intervals negligibly, a method uniting the subaperture imaging and phase gradient autofocus is considered for single-detector ladar. To obtain long stripmap images in azimuth, the stripmap phase gradient autofocus method and the subaperture image mosaic process usin...

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

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


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

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

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

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

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

  10. Infrared-based object tracking

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


    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.

  11. Object-Based Image Compression

    Schmalz, Mark S.


    Image compression frequently supports reduced storage requirement in a computer system, as well as enhancement of effective channel bandwidth in a communication system, by decreasing the source bit rate through reduction of source redundancy. The majority of image compression techniques emphasize pixel-level operations, such as matching rectangular or elliptical sampling blocks taken from the source data stream, with exemplars stored in a database (e.g., a codebook in vector quantization or VQ). Alternatively, one can represent a source block via transformation, coefficient quantization, and selection of coefficients deemed significant for source content approximation in the decompressed image. This approach, called transform coding (TC), has predominated for several decades in the signal and image processing communities. A further technique that has been employed is the deduction of affine relationships from source properties such as local self-similarity, which supports the construction of adaptive codebooks in a self-VQ paradigm that has been called iterated function systems (IFS). Although VQ, TC, and IFS based compression algorithms have enjoyed varying levels of success for different types of applications, bit rate requirements, and image quality constraints, few of these algorithms examine the higher-level spatial structure of an image, and fewer still exploit this structure to enhance compression ratio. In this paper, we discuss a fourth type of compression algorithm, called object-based compression, which is based on research in joint segmentaton and compression, as well as previous research in the extraction of sketch-like representations from digital imagery. Here, large image regions that correspond to contiguous recognizeable objects or parts of objects are segmented from the source, then represented compactly in the compressed image. Segmentation is facilitated by source properties such as size, shape, texture, statistical properties, and spectral

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

    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)

  13. Classification of objects in images based on various object representations

    Cichocki, Radoslaw


    Object recognition is a hugely researched domain that employs methods derived from mathematics, physics and biology. This thesis combines the approaches for object classification that base on two features – color and shape. Color is represented by color histograms and shape by skeletal graphs. Four hybrids are proposed which combine those approaches in different manners and the hybrids are then tested to find out which of them gives best results.

  14. LADAR performance simulations with a high spectral resolution atmospheric transmittance and radiance model: LEEDR

    Roth, Benjamin D.; Fiorino, Steven T.


    In this study of atmospheric effects on Geiger Mode laser ranging and detection (LADAR), the parameter space is explored primarily using the Air Force Institute of Technology Center for Directed Energy's (AFIT/CDE) Laser Environmental Effects Definition and Reference (LEEDR) code. The expected performance of LADAR systems is assessed at operationally representative wavelengths of 1.064, 1.56 and 2.039 μm at a number of locations worldwide. Signal attenuation and background noise are characterized using LEEDR. These results are compared to standard atmosphere and Fast Atmospheric Signature Code (FASCODE) assessments. Scenarios evaluated are based on air-toground engagements including both down looking oblique and vertical geometries in which anticipated clear air aerosols are expected to occur. Engagement geometry variations are considered to determine optimum employment techniques to exploit or defeat the environmental conditions. Results, presented primarily in the form of worldwide plots of notional signal to noise ratios, show a significant climate dependence, but large variances between climatological and standard atmosphere assessments. An overall average absolute mean difference ratio of 1.03 is found when climatological signal-to-noise ratios at 40 locations are compared to their equivalent standard atmosphere assessment. Atmospheric transmission is shown to not always correlate with signal-to-noise ratios between different atmosphere profiles. Allowing aerosols to swell with relative humidity proves to be significant especially for up looking geometries reducing the signal-to-noise ratio several orders of magnitude. Turbulence blurring effects that impact tracking and imaging show that the LADAR system has little capability at a 50km range yet the turbulence has little impact at a 3km range.

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

    Kim, Seongjoon; Lee, Impyeong; Kwon, Yong Joon


    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. PMID:23823970

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

    Yong Joon Kwon


    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.

  17. View-based 3-D object retrieval

    Gao, Yue


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

  18. Speedy Object Detection Based on Shape

    Y. Jayanta Singh


    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.


    Y. Jayanta Singh


    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.

  20. Building a Knowledge Base from Learning Objects

    Fredlund, Per Kristen


    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...

  1. Object based attention and visual area LO.

    de-Wit, L.; Kentridge, R. W.; Milner, A D


    We investigated the neural basis of so-called “object-based attention” by examining patient D.F., who has visual form agnosia caused by bilateral damage to the lateral occipital (LO) area of the ventral visual stream. We tested D.F.’s object-based attention in two ways. In the first experiment, we used a spatial cueing procedure to compare the costs associated with shifting attention within versus between two separate outline figures. D.F. did not show the normal advantage of within-object ov...

  2. Range resolution improvement of eyesafe ladar testbed (ELT) measurements using sparse signal deconvolution

    Budge, Scott E.; Gunther, Jacob H.


    The Eyesafe Ladar Test-bed (ELT) is an experimental ladar system with the capability of digitizing return laser pulse waveforms at 2 GHz. These waveforms can then be exploited off-line in the laboratory to develop signal processing techniques for noise reduction, range resolution improvement, and range discrimination between two surfaces of similar range interrogated by a single laser pulse. This paper presents the results of experiments with new deconvolution algorithms with the hoped-for gains of improving the range discrimination of the ladar system. The sparsity of ladar returns is exploited to solve the deconvolution problem in two steps. The first step is to estimate a point target response using a database of measured calibration data. This basic target response is used to construct a dictionary of target responses with different delays/ranges. Using this dictionary ladar returns from a wide variety of surface configurations can be synthesized by taking linear combinations. A sparse linear combination matches the physical reality that ladar returns consist of the overlapping of only a few pulses. The dictionary construction process is a pre-processing step that is performed only once. The deconvolution step is performed by minimizing the error between the measured ladar return and the dictionary model while constraining the coefficient vector to be sparse. Other constraints such as the non-negativity of the coefficients are also applied. The results of the proposed technique are presented in the paper and are shown to compare favorably with previously investigated deconvolution techniques.

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

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


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

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

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


    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.

  5. Invariant object recognition based on extended fragments.

    Bart, Evgeniy; Hegdé, Jay


    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 system is actually capable of using this strategy remains unknown. Here, we show that human observers can achieve illumination invariance by using object fragments that carry the relevant information. To determine this, we have used novel, but naturalistic, 3-D visual objects called "digital embryos." Using novel instances of whole embryos, not fragments, we trained subjects to recognize individual embryos across illuminations. We then tested the illumination-invariant object recognition performance of subjects using fragments. We found that the performance was strongly correlated with the mutual information (MI) of the fragments, provided that MI value took variations in illumination into consideration. This correlation was not attributable to any systematic differences in task difficulty between different fragments. These results reveal two important principles of invariant object recognition. First, the subjects can achieve invariance at least in part by compensating for the changes in the appearance of small local features, rather than of whole objects. Second, the subjects do not always rely on generic or pre-existing invariance of features (i.e., features whose appearance remains largely unchanged by variations in illumination), and are capable of using learning to compensate for appearance changes when necessary. These psychophysical results closely fit the predictions of earlier computational studies of fragment-based invariant object recognition. PMID:22936910

  6. Invariant Object Recognition Based on Extended Fragments

    Evgeniy eBart


    Full Text Available 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 system is actually capable of using this strategy remains unknown. Here, we show that human observers can achieve illumination invariance by using object fragments that carry the relevant information. To determine this, we have used novel, but naturalistic, 3-D visual objects called ‘digital embryos’. Using novel instances of whole embryos, not fragments, we trained subjects to recognize individual embryos across illuminations. We then tested the illumination-invariant object recognition performance of subjects using fragments. We found that the performance was strongly correlated with the mutual information (MI of the fragments, provided that MI value took variations in illumination into consideration. This correlation was not attributable to any systematic differences in task difficulty between different fragments. These results reveal two important principles of invariant object recognition. First, the subjects can achieve invariance at least in part by compensating for the changes in the appearance of small local features, rather than of whole objects. Second, the subjects do not always rely on generic or pre-existing invariance of features (i.e., features whose appearance remains largely unchanged by variations in illumination, and are capable of using learning to compensate for appearance changes when necessary. These psychophysical results closely fit the predictions of earlier computational studies of fragment-based invariant object recognition.

  7. Advances in LADAR Components and Subsystems at Raytheon

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


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

  8. Circular object recognition based on shape parameters

    Chen Aijun; Li Jinzong; Zhu Bing


    To recognize circular objects rapidly in satellite remote sensing imagery, an approach using their geometry properties is presented.The original image is segmented to be a binary one by one dimension maximum entropy threshold algorithm and the binary image is labeled with an algorithm based on recursion technique.Then, shape parameters of all labeled regions are calculated and those regions with shape parameters satisfying certain conditions are recognized as circular objects.The algorithm is described in detail, and comparison experiments with the randomized Hough transformation (RHT) are also provided.The experimental results on synthetic images and real images show that the proposed method has the merits of fast recognition rate, high recognition efficiency and the ability of anti-noise and anti-jamming.In addition, the method performs well when some circular objects are little deformed and partly misshapen.

  9. Object tracking based on bit-planes

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


    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.

  10. Object Based Middleware for Grid Computing

    S. Muruganantham


    Full Text Available Problem statement: “Grid” computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications and, in some cases, high-performance orientation. The role of middleware is to ease the task of designing, programming and managing distributed applications by providing a simple, consistent and integrated distributed programming environment. Essentially, middleware is a distributed software layer, which abstracts over the complexity and heterogeneity of the underlying distributed environment with its multitude of network technologies, machine architectures, operating systems and programming languages. Approach: This study brought out the development of supportive middleware to manage resources and distributed workload across multiple administrative boundaries is of central importance to Grid computing. Active middleware services that perform look-up, scheduling and staging are being developed that allow users to identify and utilize appropriate resources that provide sustainable system and user-level qualities of service. Results: Different middleware platforms support different programming models. Perhaps the most popular model is object-based middleware in which applications are structured into objects that interact via location transparent method invocation. Conclusion: The Object Management Group’s CORBA platform offer an Interface Definition Language (IDL which is used to abstract over the fact that objects can be implemented in any suitable programming language, an object request broker which is responsible for transparently directing method invocations to the appropriate target object and a set of services such as naming, time, transactions, replication which further enhance the programming environment.

  11. Time reversed photonic beamforming of arbitrary waveform ladar arrays

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


    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.

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

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


    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

  13. Perceptual Object Extraction Based on Saliency and Clustering

    Qiaorong Zhang; Yafeng Zheng; Haibo Liu; Jing Shen; Guochang Gu


    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 reg...

  14. Invariant object recognition based on extended fragments

    Bart, Evgeniy; Hegdé, Jay


    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...

  15. Object Extraction Based on Evolutionary Morphological Processing

    LI Bin; PAN Li


    This paper introduces a novel technique for object detection using genetic algorithms and morphological processing. The method employs a kind of object oriented structure element, which is derived by genetic algorithms. The population of morphological filters is iteratively evaluated according to a statistical performance index corresponding to object extraction ability, and evolves into an optimal structuring element using the evolution principles of genetic search. Experimental results of road extraction from high resolution satellite images are presented to illustrate the merit and feasibility of the proposed method.

  16. Use of laser radar imagery in optical pattern recognition: the Optical Processor Enhanced Ladar (OPEL) Program

    Goldstein, Dennis H.; Mills, Stuart A.; Dydyk, Robert B.


    The Optical Processor Enhanced Ladar (OPEL) program is designed to evaluate the capabilities of a seeker obtained by integrating two state-of-the-art technologies, laser radar, or ladar, and optical correlation. The program is a thirty-two month effort to build, optimize, and test a breadboard seeker system (the OPEL System) that incorporates these two promising technologies. Laser radars produce both range and intensity image information. Use of this information in an optical correlator is described. A correlator with binary phase input and ternary amplitude and phase filter capability is assumed. Laser radar imagery was collected on five targets over 360 degrees of azimuth from 3 elevation angles. This imagery was then processed to provide training sets in preparation for filter construction. This paper reviews the ladar and optical correlator technologies used, outlines the OPEL program, and describes the OPEL system.

  17. Ontology Based Object Learning and Recognition

    Maillot, Nicolas


    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 ...

  18. Saliency-based object recognition in video

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


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

  19. Action modulates object-based selection

    Karina J Linnell; Humphreys, Glyn W; McIntyre, Dave B.; Laitinen, Sauli; Wing, Alan M.


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

  20. University collections and object-based pedagogies

    SIMPSON, Andrew; Hammond, Gina


    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...

  1. Interval-based Specification of Concurrent Objects

    Løvengreen, Hans Henrik; Sørensen, Morten U.


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

  2. Object formation in visual working memory: Evidence from object-based attention.

    Zhou, Jifan; Zhang, Haihang; Ding, Xiaowei; Shui, Rende; Shen, Mowei


    We report on how visual working memory (VWM) forms intact perceptual representations of visual objects using sub-object elements. Specifically, when objects were divided into fragments and sequentially encoded into VWM, the fragments were involuntarily integrated into objects in VWM, as evidenced by the occurrence of both positive and negative object-based attention effects: In Experiment 1, when subjects' attention was cued to a location occupied by the VWM object, the target presented at the location of that object was perceived as occurring earlier than that presented at the location of a different object. In Experiment 2, responses to a target were significantly slower when a distractor was presented at the same location as the cued object (Experiment 2). These results suggest that object fragments can be integrated into objects within VWM in a manner similar to that of visual perception. PMID:27253863

  3. Monitoring objects orbiting earth using satellite-based telescopes

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


    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.

  4. ROIC for gated 3D imaging LADAR receiver

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


    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%.

  5. Line imaging ladar using a laser-diode transmitter and FM/cw radar principles for submunition applications

    Stann, Barry L.; Abou-Auf, Ahmed; Ruff, William C.; Robinson, Dale; Liss, Brian; Potter, William; Sarama, Scott D.; Giza, Mark M.; Simon, Deborah R.; Frankel, Scott; Sztankay, Zoltan G.


    We describe the technical approach, component development, and test results of a line imager laser radar (ladar) being developed at the Army Research Laboratory (ARL) for smart munition applications. We obtain range information using a frequency modulation/continuous wave (FM/cw) technique implemented by directly amplitude modulating a near-IR diode laser transmitter with a radio frequency (rf) subcarrier that is linearly frequency modulated. The diode's output is collimated and projected to form a line illumination in the downrange image area. The returned signal is focused onto a line array of metal-semiconductor-metal (MSM) detectors where it is detected and mixed with a delayed replica of the laser modulation signal that modulates the responsivity of each detector. The output of each detector is an intermediate frequency (IF) signal (a product of the mixing process) whose frequency is proportional to the target range. This IF signal is continuously sampled over each period of the rf modulation. Following this, a N-channel signal processor based on field- programmable gate arrays (FPGA) calculates the discrete Fourier transform over the IF waveform in each pixel to establish the ranges to all the scatterers and their respective amplitudes. Over the past year, we constructed the fundamental building blocks of this ladar, which include a 3.5-W line illuminator, a wideband linear FM chirp modulator, a N-pixel MSM detector line array, and a N-channel FPGA signal processor. In this paper we report on the development and performance of each building block and the results of system tests conducted in the laboratory.

  6. Games based on active NFC objects : model and security requirements

    Fortat, Florent; LAURENT, Maryline; Simatic, Michel


    Cheating in video games is a critical financial matter for game developers. With games now integrating physical objects through NFC, new cheating techniques have emerged, including characteristic boosting of the objects, duplication of objects and introduction of new unauthorized objects. In this paper, we address this problem for games based on active NFC objects. Having active objects in a game allows for new possibilities of interaction yet to be seen, including offline interactions betwee...




    The Object-Oriented paradigm approaches the software development by representing real world entities into classes of software objects. Object oriented design patterns facilitate small scale and large scale design reuse. This paper presents an object oriented design pattern, Administrator Object, to address the User-Role assignment problem in Role Based Access Control (RBAC). Two alternative solutions are proposed. The pattern is presented according to the Gang of Four template.




    Full Text Available The Object-Oriented paradigm approaches the software development by representing real world entities into classes of software objects. Object oriented design patterns facilitate small scale and large scale design reuse. This paper presents an object oriented design pattern, Administrator Object, to address the User-Role assignment problem in Role Based Access Control (RBAC. Two alternative solutions are proposed. The pattern is presented according to the Gang of Four template.

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

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


    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.

  10. Attending to Motion: an object-based approach

    Belardinelli, Anna


    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...

  11. Perceptual Object Extraction Based on Saliency and Clustering

    Qiaorong Zhang


    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.

  12. Phase gradient algorithm method for three-dimensional holographic ladar imaging.

    Stafford, Jason W; Duncan, Bradley D; Rabb, David J


    Three-dimensional (3D) holographic ladar uses digital holography with frequency diversity to add the ability to resolve targets in range. A key challenge is that since individual frequency samples are not recorded simultaneously, differential phase aberrations may exist between them, making it difficult to achieve range compression. We describe steps specific to this modality so that phase gradient algorithms (PGA) can be applied to 3D holographic ladar data for phase corrections across multiple temporal frequency samples. Substantial improvement of range compression is demonstrated with a laboratory experiment where our modified PGA technique is applied. Additionally, the PGA estimator is demonstrated to be efficient for this application, and the maximum entropy saturation behavior of the estimator is analytically described. PMID:27409018


    XIANG Guishan; WANG Xuanyin; LIANG Dongtai


    In YCbCr colorspace, a method is proposed to reconstruct the background and extract moving objects based on the Gaussian model of chroma components. Background model is updated according to changes of chroma components. In order to eliminate the disturbance of shadow, a shadow detecting principle is proposed in YCbCr colorspace. A Kalman filter is introduced to estimate objects' positions in the image and then the pedestrian is tracked according to its information of shape. Experiments show that the background reconstruction and updating are successful, object extraction and shadow suppression are satisfactory, and real-time and reliable tracking is realized.

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

    Moussa, A.; El-Sheimy, N.


    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

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

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


    Topographic Light Detection and Ranging (LiDAR) technology has advanced greatly in the past decade. Pulse repetition rates of terrestrial and airborne systems havemultiplied thus vastly increasing data acquisition rates. Geiger-mode and FLASH LiDAR have also become far more mature technologies. However, a new and relatively unknown technology is maturing rapidly: Frequency-Modulated Continuous Wave Laser Detection and Ranging (FMCW-LADAR). Possessing attributes more akin to modern ra...

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

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


    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

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

    Sebari, Imane; He, Dong-Chen


    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.

  18. Classification problems in object-based representation systems

    Napoli, Amedeo


    Classification is a process that consists in two dual operations: generating a set of classes and then classifying given objects into the created classes. The class generation may be understood as a learning process and object classification as a problem-solving process. The goal of this position paper is to introduce and to make precise the notion of a classification problem in object-based representation systems, e.g. a query against a class hierarchy, to define a subsumption relation betwe...

  19. A proto-object-based computational model for visual saliency.

    Yanulevskaya, Victoria; Uijlings, Jasper; Geusebroek, Jan-Mark; Sebe, Nicu; Smeulders, Arnold


    State-of-the-art bottom-up saliency models often assign high saliency values at or near high-contrast edges, whereas people tend to look within the regions delineated by those edges, namely the objects. To resolve this inconsistency, in this work we estimate saliency at the level of coherent image regions. According to object-based attention theory, the human brain groups similar pixels into coherent regions, which are called proto-objects. The saliency of these proto-objects is estimated and incorporated together. As usual, attention is given to the most salient image regions. In this paper we employ state-of-the-art computer vision techniques to implement a proto-object-based model for visual attention. Particularly, a hierarchical image segmentation algorithm is used to extract proto-objects. The two most powerful ways to estimate saliency, rarity-based and contrast-based saliency, are generalized to assess the saliency at the proto-object level. The rarity-based saliency assesses if the proto-object contains rare or outstanding details. The contrast-based saliency estimates how much the proto-object differs from the surroundings. However, not all image regions with high contrast to the surroundings attract human attention. We take this into account by distinguishing between external and internal contrast-based saliency. Where the external contrast-based saliency estimates the difference between the proto-object and the rest of the image, the internal contrast-based saliency estimates the complexity of the proto-object itself. We evaluate the performance of the proposed method and its components on two challenging eye-fixation datasets (Judd, Ehinger, Durand, & Torralba, 2009; Subramanian, Katti, Sebe, Kankanhalli, & Chua, 2010). The results show the importance of rarity-based and both external and internal contrast-based saliency in fixation prediction. Moreover, the comparison with state-of-the-art computational models for visual saliency demonstrates the

  20. RFID and IP Based Object Identification in Ubiquitous Networking

    Nisha Vaghela


    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.

  1. Content-Based Object Movie Retrieval and Relevance Feedbacks

    Lee Greg C


    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.

  2. A Method of Object-based De-duplication

    Fang Yan


    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.

  3. Category vs. Object Knowledge in Category-based Induction

    Murphy, Gregory L.; Ross, Brian H.


    In one form of category-based induction, people make predictions about unknown properties of objects. There is a tension between predictions made based on the object’s specific features (e.g., objects above a certain size tend not to fly) and those made by reference to category-level knowledge (e.g., birds fly). Seven experiments with artificial categories investigated these two sources of induction by looking at whether people used information about correlated features within categories, sug...

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

    Lepetit, Vincent


    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

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

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


    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...

  6. A practical approach to object based requirements analysis

    Drew, Daniel W.; Bishop, Michael


    Presented here is an approach developed at the Unisys Houston Operation Division, which supports the early identification of objects. This domain oriented analysis and development concept is based on entity relationship modeling and object data flow diagrams. These modeling techniques, based on the GOOD methodology developed at the Goddard Space Flight Center, support the translation of requirements into objects which represent the real-world problem domain. The goal is to establish a solid foundation of understanding before design begins, thereby giving greater assurance that the system will do what is desired by the customer. The transition from requirements to object oriented design is also promoted by having requirements described in terms of objects. Presented is a five step process by which objects are identified from the requirements to create a problem definition model. This process involves establishing a base line requirements list from which an object data flow diagram can be created. Entity-relationship modeling is used to facilitate the identification of objects from the requirements. An example is given of how semantic modeling may be used to improve the entity-relationship model and a brief discussion on how this approach might be used in a large scale development effort.

  7. Laser Calibration Experiment for Small Objects in Space

    Campbell, Jonathan; Ayers, K.; Carreras, R.; Carruth, R.; Freestone, T.; Sharp, J.; Rawleigh, A.; Brewer, J.; Schrock, K.; Bell, L.; Howell, Joe (Technical Monitor)


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

  8. Object-based mapping of drumlins from DTMs

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


    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

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

    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.

  10. A new approach toward object-based change detection


    Object-based change detection has been the hotspot in remote sensing image processing.A new approach toward object-based change detection is proposed.The two different temporal images are unitedly segmented using the mean shift procedure to obtain corresponding objects.Then change detection is implemented based on the integration of corresponding objects’ intensity and texture differences.Experiments are conducted on both panchromatic images and multispectral images and the results show that the integrated measure is robust with respect to illumination changes and noise.Supplementary color detection is conducted to determine whether the color of the unchanged objects changes or not when dealing with multispectral images.Some verification work is carried out to show the accuracy of the proposed approach.

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

    Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan


    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.

  12. Vector ordinal optimization based multi-objective transmission planning

    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.

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

    Nguyen Thanh Binh


    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.

  14. A New RWA Algorithm Based on Multi-Objective


    In this article, we studied the associated research problems and challenges on routing and wavelength assignment (RWA) in WDM (wavelength division multiplexing) networks. Various RWA approaches are examined and compared. We proposed a new RWA algorithm based on multi-objective. In this new algorithm, we consider multiple network optimizing objectives to setup a lightpath with maximize profit and shortest path under the limited resources. By comparing and analyzing, the proposed algorithm is much better ...

  15. Spanish Tourist Behaviour: A Specific Objective-base Segmantation

    González, Pablo Rodríguez; Molina, Oscar


    This work uses data from the Spanish Tourism Demand Segments Survey (N=6900) conducted by the IESA-CSIC for Turismo Andaluz, SA. The objective of the paper is to develop a statistical segmentation or typology of Spanish tourists based on objective aspects of tourist behaviour measured in the survey including destinations visited, theme of the trip, lodging, transportation and travel group. Initial categorical data are reduced using multiple correspondence analysis and grouped through cluster ...

  16. Cauchy graph embedding based diffusion model for salient object detection.

    Tan, Yihua; Li, Yansheng; Chen, Chen; Yu, Jin-Gang; Tian, Jinwen


    Salient object detection has been a rather hot research topic recently, due to its potential applications in image compression, scene classification, image registration, and so forth. The overwhelming majority of existing computational models are designed based on computer vision techniques by using lots of image cues and priors. Actually, salient object detection is derived from the biological perceptual mechanism, and biological evidence shows that the spread of the spatial attention generates the object attention. Inspired by this, we attempt to utilize the emerging spread mechanism of object attention to construct a new computational model. A novel Cauchy graph embedding based diffusion (CGED) model is proposed to fulfill the spread process. Combining the diffusion model and attention prediction model, a salient object detection approach is presented through perceptually grouping the multiscale diffused attention maps. The effectiveness of the proposed approach is validated on the salient object dataset. The experimental results show that the CGED process can obviously improve the performance of salient object detection compared with the input spatial attention map, and the proposed approach can achieve performance comparable to that of state-of-the-art approaches. PMID:27140886

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

    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...

  18. A framework for Internet service evolution based on active object

    HU Hua; ZHANG Yang


    The wide use of Internet Service in distributed computing and e-business has made the evolution of Internet Service to be one of the most prevalent research fields in software development domain. Traditional methods for software development cannot adapt to the challenge of Internet Service oriented software development. In this paper, we propose a new paradigm for the evolution of Internet Service with active objects from the characteristics of Internet Service and principles of active objects. The paradigm uses an automatic monitoring mechanism of active object to detect and process evolution requirement in system based on Internet Service.

  19. Solid State Disk Object-Based Storage with Trim Commands

    Frankie, Tasha; Hughes, Gordon; Kreutz-Delgado, Ken


    This paper presents a model of NAND flash SSD utilization and write amplification when the ATA/ATAPI SSD Trim command is incorporated into object-based storage under a variety of user workloads, including a uniform random workload with objects of fixed size and a uniform random workload with objects of varying sizes. We first summarize the existing models for write amplification in SSDs for workloads with and without the Trim command, then propose an alteration of the models that utilizes a f...

  20. Using Morphlet-Based Image Representation for Object Detection

    Gorbatsevich, V. S.; Vizilter, Yu. V.


    In this paper, we propose an original method for objects detection based on a special tree-structured image representation - the trees of morphlets. The method provides robust detection of various types of objects in an image without employing a machine learning procedure. Along with a bounding box creation on a detection step, the method makes pre-segmentation, which can be further used for recognition purposes. Another important feature of the proposed approach is that there are no needs to use a running window as well as a features pyramid in order to detect the objects of different sizes.

  1. Segmentation of object-based video of gaze communication

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


    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....

  2. Object tracking based on two-dimensional PCA

    Xu, Fuyuan; Gu, Guohua; Kong, Xiaofang; Wang, Pengcheng; Ren, Kan


    In this paper, we present a novel object tracking method based on two-dimensional PCA. The low quality of images and the changes of the object appearance are very challenging for the object tracking. The representation of the training features is usually used to solve these challenges. Two-dimensional PCA (2DPCA) based on the image covariance matrix is constructed directly using the original image matrices. An appearance model is presented and its likelihood estimation has been established based on 2DPCA representation in this paper. Compared with the state-of-the-art methods, our method has higher reliability and real-time property. The performances of the proposed tracking method are quantitatively and qualitatively shown in experiments.

  3. Video Based Moving Object Tracking by Particle Filter

    Md. Zahidul Islam


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

  4. Reactor Network Synthesis Based on Instantaneous Objective Function Characteristic Curves

    张治山; 赵文; 王艳丽; 周传光; 袁希钢


    It is believed that whether the instantaneous objective function curves of plug-flow-reactor (PFR) and continuous-stirred-tank-reactor (CSTR) overlap or not, they have a consistent changing trend for complex reactions(steady state, isothermal and constant volume). As a result of the relation of the objective functions (selectivity or yield) to the instantaneous objective functions (instantaneous selectivity or instantaneous reaction rate), the optimal reactor network configuration can be determined according to the changing trend of the instantaneous objective function curves. Further, a recent partition strategy for the reactor network synthesis based on the instantaneous objective function characteristic curves is proposed by extending the attainable region partition strategy from the concentration space to the instantaneous objective function-unreacted fraction of key reactant space. In this paper,the instantaneous objective function is closed to be the instantaneous selectivity and several samples axe examined to illustrate the proposed method. The comparison with the previous work indicates it is a very convenient and practical systematic tool of the reactor network synthesis and seems also promising for overcoming the dimension limit of the attainable region partition strategy in the concentration space.

  5. Modeling of Heterogeneous Objects: An Approach Based on Implicit Functions

    Miller Gómez-Mora


    Full Text Available Modeling objects, their properties and relations is an important topic in computer science. In this sense, this research contributes to the framework of heterogeneous solid modeling, as well as the popular and intricate study of implicit solid representation. The approach presented here is broad and generic, but this article will focus on bio-CAD models, alluding to the existing extension and implementation in other fields. The overall aim of this work is to demonstrate that solid models of heterogeneous object can be built implicitly. This is shown to have promise in practical applications from biomedical computing to computer animation and engineering. The approach adopted here is based on the observation that current solid models cannot intrinsically represent multiphase geometric information along with the attribute information. This makes necessary to explore new modeling techniques in order to represent real-world objects. The availability of such modeling techniques remains central to the design, analysis, and fabrication of heterogeneous objects

  6. Concurrent Object-Oriented Programming Based on MPI

    鲁宏伟; 汪厚祥; 裴晓黎; 肖永玲


    Object-oriented model possesses inherent concurrency. Integration of concurrency and object-orientation is a promising new field. MPI is a message-passing standard and has been adopted by more and more systems. This paper proposes a novel approach to realize concurrent object-oriented programming based on Message-passing interface(MPI) in which future method communication is adopted between concurrent objects. A state behavior set is proposed to solve inheritance anomaly, and a bounded buffer is taken as an example to illustrate this proposal. The definition of ParaMPI class, which is the most important class in the concurrent class library,and implementation issues are briefly described.

  7. Inverse treatment planning using volume-based objective functions

    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

  8. Rule-Based Orientation Recognition Of A Moving Object

    Gove, Robert J.


    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

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

    Martí Bonmatí, Joan; Casals, Alícia


    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 ...

  10. A Learning Object Approach To Evidence based learning

    Zabin Visram; Bruce Elson; Patricia Reynolds


    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...

  11. Research on Virtual Object Tele-operation Based on Gesture


    A tele-operation method of virtual environment based on gesture is presented.Firstly,the design block diagram and the information flow of the virtual environment tele-operation simulation system are given.Secondly,the coordination transformation between virtual gesture and the tele-operated aircraft is presented.Finally,a tele-operation simulation system based on gesture is developed.And the simulation results demonstrate that there is more consistency between the virtual gesture and the moving object.

  12. Object based data access at the D0 experiment

    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

  13. COL : a logic-based language for complex objects

    Abiteboul, Serge; Grumbach, Stéphane


    A logic-based language for manipuling complex objects constructed using set and tuple conctructors is introduced. Under some stratification restrictions, the semantic of programs is given by a canonical minimal and casual model that can be computed using a finite sequence of fixpoints. Applications of the language to procedural data, semantic database models, heterogeneous databases integration, and Datalog queries evalutation are presented.

  14. Vision-based autonomous grasping of unknown piled objects

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

  15. Archive Design Based on Planets Inspired Logical Object Model

    Zierau, Eld; Johansen, Anders


    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...

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

    Yao, Jie; Cao, Qiang; Huang, Jianzhong


    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.

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

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


    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.

  18. Observed bodies generate object-based spatial codes.

    Taylor, Alison; Flynn, Maria; Edmonds, Caroline J; Gardner, Mark R


    Contemporary studies of spatial and social cognition frequently use human figures as stimuli. The interpretation of such studies may be complicated by spatial compatibility effects that emerge when researchers employ spatial responses, and participants spontaneously code spatial relationships about an observed body. Yet, the nature of these spatial codes - whether they are location- or object-based, and coded from the perspective of the observer or the figure - has not been determined. Here, we investigated this issue by exploring spatial compatibility effects arising for objects held by a visually presented whole-bodied schematic human figure. In three experiments, participants responded to the colour of the object held in the figure's left or right hand, using left or right key presses. Left-right compatibility effects were found relative to the participant's egocentric perspective, rather than the figure's. These effects occurred even when the figure was rotated by 90° to the left or to the right, and the coloured objects were aligned with the participant's midline. These findings are consistent with spontaneous spatial coding from the participant's perspective and relative to the normal upright orientation of the body. This evidence for object-based spatial coding implies that the domain general cognitive mechanisms that result in spatial compatibility effects may contribute to certain spatial perspective-taking and social cognition phenomena. PMID:27235754

  19. Fuzzy Distance-Based Range Queries over Uncertain Moving Objects

    Yi-Fei Chen; Xiao-Lin Qin; Liang Liu; Bo-Han Li


    Data obtained from real world are imprecise or uncertain due to the accuracy of positioning devices,updating protocols or characteristics of applications.On the other hand,users sometimes prefer to qualitatively express their requests with vague conditions and different parts of search region are in-equally important in some applications.We address the problem of efficiently processing the fuzzy range queries for uncertain moving objects whose whereabouts in time are not known exactly,for which the basic syntax is find objects always/sometimes near to the query issuer with the qualifying guarantees no less than a given threshold during a given temporal interval.We model the location uncertainty of moving objects on the utilization of probability density functions and describe the indeterminate boundary of query range with fuzzy set.We present the qualifying guarantee evaluation of objects,and propose pruning techniques based on the α-cut of fuzzy set to shrink the search space efficiently.We also design rules to reject non-qualifying objects and validate qualifying objects in order to avoid unnecessary costly numeric integrations in the refinement step.An extensive empirical study has been conducted to demonstrate the efficiency and effectiveness of algorithms under various experimental settings.

  20. A Primitive-Based 3D Object Recognition System

    Dhawan, Atam P.


    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.

  1. Object-Based Classification and Change Detection of Hokkaido, Japan

    Park, J. G.; Harada, I.; Kwak, Y.


    Topography and geology are factors to characterize the distribution of natural vegetation. Topographic contour is particularly influential on the living conditions of plants such as soil moisture, sunlight, and windiness. Vegetation associations having similar characteristics are present in locations having similar topographic conditions unless natural disturbances such as landslides and forest fires or artificial disturbances such as deforestation and man-made plantation bring about changes in such conditions. We developed a vegetation map of Japan using an object-based segmentation approach with topographic information (elevation, slope, slope direction) that is closely related to the distribution of vegetation. The results found that the object-based classification is more effective to produce a vegetation map than the pixel-based classification.

  2. Knowledge-Based Object Detection in Laser Scanning Point Clouds

    Boochs, F.; Karmacharya, A.; Marbs, A.


    Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.

  3. Rules-based object-relational databases ontology construction

    Chen Jia; Wu Yue


    To solve the problems of sharing and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is proposed first. Then, four types of ontology constructing rules including class, property, property characteristics, and property restrictions axe formalized affording to the model. Experiment results described in Web ontology language prove that our proposed approach is feasible for applying in the semantic objects project of semantic computing laboratory in UC Irvine. Our approach reduces about twenty percent constructing time compared with the ontology construction from relational databases.

  4. Agent-based Algorithm for Spatial Distribution of Objects

    Collier, Nathan


    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.

  5. Nanoscale synthesis and characterization of graphene-based objects

    Daisuke Fujita


    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.

  6. Performance Evaluation of Java Based Object Relational Mapping Tools

    Shoaib Mahmood Bhatti


    Full Text Available Object persistency is the hot issue in the form of ORM (Object Relational Mapping tools in industry as developers use these tools during software development. This paper presents the performance evaluation of Java based ORM tools. For this purpose, Hibernate, Ebean and TopLinkhave been selected as the ORM tools which are popular and open source. Their performance has been measured from execution point of view. The results show that ORM tools are the good option for the developers considering the system throughput in shorter setbacks and they can be used efficiently and effectively for performing mapping of the objects into the relational dominated world of database, thus creating a hope for a better and well dominated future of this technology.

  7. Features Extraction for Object Detection Based on Interest Point

    Amin Mohamed Ahsan


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

  8. Density-based clustering method in the moving object database

    ZHOU Xing; XIANG Shu; GE Jun-wei; LIU Zhao-hong; BAE Hae-young


    With the rapid advance of wireless communication, tracking the positions of the moving objects is becoming increasingly feasible and necessary. Because a large number of people use mobile phones, we must handle a large moving object database as well as the following problems. How can we provide the customers with high quality service, that means, how can we deal with so many enquiries within as less time as possible? Because of the large number of data, the gap between CPU speed and the size of main memory has increasing considerably. One way to reduce the time to handle enquiries is to reduce the I/O number between the buffer and the secondary storage. An effective clustering of the objects can minimize the I/O-cost between them. In this paper, according to the characteristic of the moving object database, we analyze the objects in buffer, according to their mappings in the two-dimension coordinate, and then develop a density-based clustering method to effectively reorganize the clusters. This new mechanism leads to the less cost of the I/O operation and the more efficient response to enquiries.

  9. Revisiting child-based objections to commercial surrogacy.

    Hanna, Jason K M


    Many critics of commercial surrogate motherhood argue that it violates the rights of children. In this paper, I respond to several versions of this objection. The most common version claims that surrogacy involves child-selling. I argue that while proponents of surrogacy have generally failed to provide an adequate response to this objection, it can be overcome. After showing that the two most prominent arguments for the child-selling objection fail, I explain how the commissioning couple can acquire parental rights by paying the surrogate only for her reproductive labor. My explanation appeals to the idea that parental rights are acquired by those who have claims over the reproductive labor that produces the child, not necessarily by those who actually perform the labor. This account clarifies how commercial surrogacy differs from commercial adoption. In the final section of the paper, I consider and reject three further child-based objections to commercial surrogacy: that it establishes a market in children's attributes, that it requires courts to stray from the best interests standard in determining custodial rights, and that it requires the surrogate to neglect her parental responsibilities. Since each of these objections fails, children's rights probably do not pose an obstacle to the acceptability of commercial surrogacy arrangements. PMID:20690918

  10. Knowledge-based simulation using object-oriented programming

    Sidoran, Karen M.


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

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

    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

  12. A Learning Object Approach To Evidence based learning

    Zabin Visram


    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

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

    Anirban Sarkar


    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

  14. Depth-Based Object Tracking Using a Robust Gaussian Filter

    Issac, Jan; Wüthrich, Manuel; Cifuentes, Cristina Garcia; Bohg, Jeannette; Trimpe, Sebastian; Schaal, Stefan


    We consider the problem of model-based 3D-tracking of objects given dense depth images as input. Two difficulties preclude the application of a standard Gaussian filter to this problem. First of all, depth sensors are characterized by fat-tailed measurement noise. To address this issue, we show how a recently published robustification method for Gaussian filters can be applied to the problem at hand. Thereby, we avoid using heuristic outlier detection methods that simply reject measurements i...

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

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


    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.

  16. Logical Object as a Basis of Knowledge Based Systems

    徐殿祥; 郑国梁


    This paper presents a framework called logical knowledge object (LKO),which is taken as a basis of the dependable development of knowledge based systems(KBSs).LKO combines logic programming and object-oriented programming paradigms,where objects are viewed as abstractions with states,constraints,behaviors and inheritance.The operational semantics defined in the style of natural semantics is simple and clear.A hybrid knowledge representation amalgamating rule,frame,semantic network and blackboard is available for both most structured and flat knowledge.The management of knowledge bases has been formally specified.Accordingly,LKO is well suited for the formal representation of knowledge and requirements of KBSs.Based on the framework,verification techniques are also explored to enhance the analysis of requirement specifications and the validation of KBSs.In addition,LKO provides a methodology for the development of KBSs,applying the concepts of rapid prototyping and top-down design to deal with changing and incomplete requirements,and to provide multiple abstract models of the domain,where formal methods might be used at each abstract level.

  17. An Object-Based Method for Chinese Landform Types Classification

    Ding, Hu; Tao, Fei; Zhao, Wufan; Na, Jiaming; Tang, Guo'an


    Landform classification is a necessary task for various fields of landscape and regional planning, for example for landscape evaluation, erosion studies, hazard prediction, et al. This study proposes an improved object-based classification for Chinese landform types using the factor importance analysis of random forest and the gray-level co-occurrence matrix (GLCM). In this research, based on 1km DEM of China, the combination of the terrain factors extracted from DEM are selected by correlation analysis and Sheffield's entropy method. Random forest classification tree is applied to evaluate the importance of the terrain factors, which are used as multi-scale segmentation thresholds. Then the GLCM is conducted for the knowledge base of classification. The classification result was checked by using the 1:4,000,000 Chinese Geomorphological Map as reference. And the overall classification accuracy of the proposed method is 5.7% higher than ISODATA unsupervised classification, and 15.7% higher than the traditional object-based classification method.

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

    Iryna Dronova


    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.

  19. Code Based Analysis for Object-Oriented Systems

    Swapan Bhattacharya; Ananya Kanjilal


    The basic features of object-oriented software makes it difficult to apply traditional testing methods in objectoriented systems. Control Flow Graph (CFG) is a well-known model used for identification of independent paths in procedural software. This paper highlights the problem of constructing CFG in object-oriented systems and proposes a new model named Extended Control Flow Graph (ECFG) for code based analysis of Object-Oriented (OO) software. ECFG is a layered CFG where nodes refer to methods rather than statements. A new metrics - Extended Cyclomatic Complexity (E-CC) is developed which is analogous to McCabe's Cyclomatic Complexity (CC) and refers to the number of independent execution paths within the OO software. The different ways in which CFG's of individual methods are connected in an ECFG are presented and formulas for E-CC for these different cases are proposed. Finally we have considered an example in Java and based on its ECFG, applied these cases to arrive at the E-CC of the total system as well as proposed a methodology for calculating the basis set, i.e., the set of independent paths for the OO system that will help in creation of test cases for code testing.

  20. Multiview-Based Cooperative Tracking of Multiple Human Objects

    Lien Kuo-Chin


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

  1. Multiview-Based Cooperative Tracking of Multiple Human Objects

    Kuo-Chin Lien


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

  2. Measurement of spatial object's exterior attitude based on linear CCD


    It is difficult to realize real-time measurement of exterior attitude by the traditional systems based on the area image sensor which have conflict between speed and accuracy.The subsystem for three-dimensional (3D) coordinate rcconstruction of point target (S3DCRPT) which is composed of three one-dimensional (1D) cameras based on linear charge-coupled device (CCD) can determine the distant light spots' spatial position. The attitude angle of the measured object is determined by the spatial solution while the coordinate reconstruction is separately carried on by the S3DCRPT with some point cooperation targets (PCTs) on the measured object. A new optical system is designed to solve the interference problem with one-to-one relationship between the PCTs and the S3DCRPT optical subsystems,which improves the measurement accuracy and saves space. The mathematical model of the attitude measurement is established,and partial and global calibrations are realized for the multi-camera attitude measurement system.The test results show the feasibility of the exterior attitude measurement based on linear CCD.

  3. Options-Based Multi-Objective Evaluation of Product Platforms

    Gonzalez-Zugasti, Javier P.; Otto, Kevin N.; Whitcomb, Clifford A.


    The article of record as published may be located at A platform is the set of elements and interfaces that are common to a family of products. Design teams must choose among feasible platform concepts upon which a product family could be based, often involving new technologies. Multiple performance objectives need to be considered. A standard approach is to convert the performance outcomes into financial figures, which can then ...

  4. Cloud Aggregation and Bursting for Object Based Sharable Environment

    Mr. Pradeep Kumar Tripathi


    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.

  5. Toward an efficient objective metric based on perceptual criteria

    Quintard, Ludovic; Larabi, Mohamed-Chaker; Fernandez-Maloigne, Christine


    Quality assessment is a very challenging problem and will still as is since it is difficult to define universal tools. So, subjective assessment is one adapted way but it is tedious, time consuming and needs normalized room. Objective metrics can be with reference, with reduced reference and with no-reference. This paper presents a study carried out for the development of a no-reference objective metric dedicated to the quality evaluation of display devices. Initially, a subjective study has been devoted to this problem by asking a representative panel (15 male and 15 female; 10 young adults, 10 adults and 10 seniors) to answer questions regarding their perception of several criteria for quality assessment. These quality factors were hue, saturation, contrast and texture. This aims to define the importance of perceptual criteria in the human judgment of quality. Following the study, the factors that impact the quality evaluation of display devices have been proposed. The development of a no-reference objective metric has been performed by using statistical tools allowing to separate the important axes. This no-reference metric based on perceptual criteria by integrating some specificities of the human visual system (HVS) has a high correlation with the subjective data.

  6. Object-based rapid change detection for disaster management

    Thunig, Holger; Michel, Ulrich; Ehlers, Manfred; Reinartz, Peter


    Rapid change detection is used in cases of natural hazards and disasters. This analysis lead to quick information about areas of damage. In certain cases the lack of information after catastrophe events is obstructing supporting measures within disaster management. Earthquakes, tsunamis, civil war, volcanic eruption, droughts and floods have much in common: people are directly affected, landscapes and buildings are destroyed. In every case geospatial data is necessary to gain knowledge as basement for decision support. Where to go first? Which infrastructure is usable? How much area is affected? These are essential questions which need to be answered before appropriate, eligible help can be established. This study presents an innovative strategy to retrieve post event information by use of an object-based change detection approach. Within a transferable framework, the developed algorithms can be implemented for a set of remote sensing data among different investigation areas. Several case studies are the base for the retrieved results. Within a coarse dividing into statistical parts and the segmentation in meaningful objects, the framework is able to deal with different types of change. By means of an elaborated normalized temporal change index (NTCI) panchromatic datasets are used to extract areas which are destroyed, areas which were not affected and in addition areas which are developing new for cases where rebuilding has already started. The results of the study are also feasible for monitoring urban growth.

  7. Object-based Analysis for Extraction of Dominant Tree Species

    Meiyun; SHAO; Xia; JING; Lu; WANG


    As forest is of great significance for our whole development and the sustainable plan is so focus on it. It is very urgent for us to have the whole distribution,stock volume and other related information about that. So the forest inventory program is on our schedule. Aiming at dealing with the problem in extraction of dominant tree species,we tested the highly hot method-object-based analysis. Based on the ALOS image data,we combined multi-resolution in e Cognition software and fuzzy classification algorithm. Through analyzing the segmentation results,we basically extract the spruce,the pine,the birch and the oak of the study area. Both the spectral and spatial characteristics were derived from those objects,and with the help of GLCM,we got the differences of each species. We use confusion matrix to do the Classification accuracy assessment compared with the actual ground data and this method showed a comparatively good precision as 87% with the kappa coefficient 0. 837.

  8. Reactive underwater object inspection based on artificial electric sense.

    Lebastard, Vincent; Boyer, Frédéric; Lanneau, Sylvain


    Weakly electric fish can perform complex cognitive tasks based on extracting information from blurry electric images projected from their immediate environment onto their electro-sensitive skin. In particular they can be trained to recognize the intrinsic properties of objects such as their shape, size and electric nature. They do this by means of novel perceptual strategies that exploit the relations between the physics of a self-generated electric field, their body morphology and the ability to perform specific movement termed probing motor acts (PMAs). In this article we artificially reproduce and combine these PMAs to build an autonomous control strategy that allows an artificial electric sensor to find electrically contrasted objects, and to orbit around them based on a minimum set of measurements and simple reactive feedback control laws of the probe's motion. The approach does not require any simulation models and could be implemented on an autonomous underwater vehicle (AUV) equipped with artificial electric sense. The AUV has only to satisfy certain simple geometric properties, such as bi-laterally (left/right) symmetrical electrodes and possess a reasonably high aspect (length/width) ratio. PMID:27458187

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

    Smith, D T; Ball, K.; Swalwell, R.; Schenk, T.


    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 ...

  10. Performance Analysis of Interaction between Smart Glasses and Smart Objects Using Image-Based Object Identification

    Rumiński, Jacek; Bujnowski, Adam; Kocejko, Tomasz; Wtorek, Jerzy; Andrushevich, Alexey; Biallas, Martin; Kistler, Rolf


    We propose the use of smart glasses to collaborate with smart objects in the Internet of Things environment. Particularly we are focusing on new interaction methods and the analysis of acceptable reaction times in the process of object recognition using smart glasses. We evaluated the proposed method using user studies and experiments with three different smart glasses: Google Glass, Epson Moverio, and the developed eGlasses platform. We conclude that using the proposed method it is possible ...

  11. Strength of object representation: its key role in object-based attention for determining the competition result between Gestalt and top-down objects.

    Zhao, Jingjing; Wang, Yonghui; Liu, Donglai; Zhao, Liang; Liu, Peng


    It was found in previous studies that two types of objects (rectangles formed according to the Gestalt principle and Chinese words formed in a top-down fashion) can both induce an object-based effect. The aim of the present study was to investigate how the strength of an object representation affects the result of the competition between these two types of objects based on research carried out by Liu, Wang and Zhou [(2011) Acta Psychologica, 138(3), 397-404]. In Experiment 1, the rectangles were filled with two different colors to increase the strength of Gestalt object representation, and we found that the object effect changed significantly for the different stimulus types. Experiment 2 used Chinese words with various familiarities to manipulate the strength of the top-down object representation. As a result, the object-based effect induced by rectangles was observed only when the Chinese word familiarity was low. These results suggest that the strength of object representation determines the result of competition between different types of objects. PMID:26041271

  12. RFID and IP Based Object Identification in Ubiquitous Networking

    Nisha Vaghela; Parikshit Mahalle


    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...

  13. Mobile object retrieval in server-based image databases

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


    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.

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

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


    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).

  15. Multiple-input multiple-output synthetic aperture ladar system for wide-range swath with high azimuth resolution.

    Tang, Yu; Qin, Bao; Yan, Yun; Xing, Mengdao


    For the trade-off between the high azimuth resolution and the wide-range swath in the single-input single-output synthetic aperture ladar (SAL) system, the range swath of the SAL system is restricted to a narrow range, this paper proposes a multiple-input multiple-output (MIMO) synthetic aperture ladar system. The MIMO system adopts a low pulse repetition frequency (PRF) to avoid a range ambiguity for the wide-range swath and in azimuth adopts the multi-channel method to achieve azimuth high resolution from the unambiguous azimuth wide-spectrum signal, processed through adaptive digital beam-forming technology. Simulations and analytical results are presented. PMID:26906593

  16. Adaptive Multi-Objective Optimization Based on Feedback Design

    窦立谦; 宗群; 吉月辉; 曾凡琳


    The problem of adaptive multi-objective optimization(AMOO) has received extensive attention due to its practical significance.An important issue in optimizing a multi-objective system is adjusting the weighting coefficients of multiple objectives so as to keep track of various conditions.In this paper,a feedback structure for AMOO is designed.Moreover,the reinforcement learning combined with hidden biasing information is applied to online tuning weighting coefficients of objective functions.Finally,the prop...

  17. Model-Based Multi-Objective Reinforcement Learning

    Wiering, Marco; Withagen, Maikel; Drugan, Madalina


    This paper describes a novel multi-objective reinforcement learning algorithm. The proposed algorithm first learns a model of the multi-objective sequential decision making problem, after which this learned model is used by a multi-objective dynamic programming method to compute Pareto op-timal poli




    The paper presents the object detection for dynamic texture scenes using illumination based techniques. They are two types of illumination technique. First one is illumination based background subtraction (ILBS) and second one is illumination based frame difference (ILFS). Illumination frame difference is identifying the objects accurately in dynamic texture scene compare to illumination background subtraction. It has less computation complexity, less computation cost and less spa...


    J. Shi


    Full Text Available Unmanned aerial vehicles (UAV have been widely used to capture and down-link real-time videos/images. However, their role as a low-cost airborne platform for capturing high-resolution, geo-referenced still imagery has not been fully utilized. The images obtained from UAV are advantageous over remote sensing images as they can be obtained at a low cost and potentially no risk to human life. However, these images are distorted due to the noise generated by the rotary wings which limits the usefulness of such images. One potential application of such images is to detect changes between the images of the same area which are collected over time. Change detection is of widespread interest due to a large number of applications, including surveillance and civil infrastructure. Although UAVs can provide images with high resolution in a portable and easy way, such images only cover small parts of the entire field of interest and are often with high deformation. Until now, there is not much application of change detection for UAV images. Also the traditional pixel-based change detection method does not give satisfactory results for such images. In this paper, we have proposed a novel object-based method for change detection using UAV images which can overcome the effect of deformation and can fully utilize the high resolution capability of UAV images. The developed method can be divided into five main blocks: pre-processing, image matching, image segmentation and feature extraction, change detection and accuracy evaluation. The pre-processing step is further divided into two sub-steps: the first sub-step is to geometrically correct the bi-temporal image based on the geo-reference information (GPS/INS installed on the UAV system, and the second sub-step is the radiometric normalization using a histogram method. The image matching block uses the well-known scale-invariant feature transform (SIFT algorithm to match the same areas in the images and then

  20. Object-based classification of semi-arid wetlands

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


    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.

  1. Object Recognition Algorithm Utilizing Graph Cuts Based Image Segmentation

    Zhaofeng Li


    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


    F. Boochs; Karmacharya, A.; Marbs, A.


    Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human e...

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

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


    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...

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

    Altosaar, Toomas


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

  5. Object Tracking Approach based on Mean Shift Algorithm

    Xiaojing Zhang; Yajie Yue; Chenming Sha


    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...

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

    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.…

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

    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.......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...

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

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


    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...

  9. Remote sensing clustering analysis based on object-based interval modeling

    He, Hui; Liang, Tianheng; Hu, Dan; Yu, Xianchuan


    In object-based clustering, image data are segmented into objects (groups of pixels) and then clustered based on the objects' features. This method can be used to automatically classify high-resolution, remote sensing images, but requires accurate descriptions of object features. In this paper, we ascertain that interval-valued data model is appropriate for describing clustering prototype features. With this in mind, we developed an object-based interval modeling method for high-resolution, multiband, remote sensing data. We also designed an adaptive interval-valued fuzzy clustering method. We ran experiments utilizing images from the SPOT-5 satellite sensor, for the Pearl River Delta region and Beijing. The results indicate that the proposed algorithm considers both the anisotropy of the remote sensing data and the ambiguity of objects. Additionally, we present a new dissimilarity measure for interval vectors, which better separates the interval vectors generated by features of the segmentation units (objects). This approach effectively limits classification errors caused by spectral mixing between classes. Compared with the object-based unsupervised classification method proposed earlier, the proposed algorithm improves the classification accuracy without increasing computational complexity.

  10. A Biological Hierarchical Model Based Underwater Moving Object Detection

    Jie Shen


    Full Text Available 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.

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

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


    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

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

    Youmans, Douglas G.


    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.

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

    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)

  14. Dominant object detection for autonomous vision-based surveillance

    Celik, H.


    The deployment of visual surveillance and monitoring systems has reached massive proportions. Consequently, a need to automate the processes involved in retrieving useful information from surveillance videos, such as detecting and counting objects, and interpreting their individual and joint behavio

  15. Adaptive Multi-Objective Optimization Based on Feedback Design

    DOU Liqian; ZONG Qun; JI Yuehui; ZENG Fanlin


    The problem of adaptive multi-objective optimization(AMOO)has received extensive attention due to its practical significance.An important issue in optimizing a multi-objective system is adjusting the weighting coefficients of multiple objectives so as to keep track of various conditions.In this paper,a feedback structure for AMOO is designed.Moreover,the reinforcement learning combined with hidden biasing information is applied to online tuning weighting coefficients of objective functions.Finally,the proposed approach is applied to the optimization design problem of an elevator group control system.Simulation results show that AMOO has the best average performance at up-peak traffic profile,and its average waiting time reaches 22 s.AMOO is suitable for various traffic patterns,and it is also superior to the majority of algorithms at down-peak traffic profile.

  16. A Biological Hierarchical Model Based Underwater Moving Object Detection

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


    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...

  17. An Approach to Absolute Position Control based on Object Coordinate

    Nakano, Keisuke; Murakami, Toshiyuki

    This paper describes an accurate position control in object coordinate. In case the motion control of industrial robot placed in global coordinate is considered in object coordinate, it is preferable and convenient to decide its motion by the teaching of robot operator. However the teaching procedure requires much time and effort. Moreover, as often as relative position between robot and object is changed, the operator needs to do the teaching operation again. To improve the above issue, it is required to develop the strategy that decides the robot motion without the teaching operation. This paper proposes a control strategy that is not required the teaching operation and enables to realize the desired motion without affecting the relative position error between the robot and the target object in object coordinate defined by PSD (Position Sensitive Detector). In the proposed approach, the estimation algorithm of the kinetic transformation between global and object coordinates is introduced by using PSD output, and the error of coordinate transformation estimated by the proposed approach is compensated in global coordinate. The validity of the proposed method is shown by simulations and experiments.

  18. Topic Modelling for Object-Based Classification of Vhr Satellite Images Based on Multiscale Segmentations

    Shen, Li; Wu, Linmei; Li, Zhipeng


    Multiscale segmentation is a key prerequisite step for object-based classification methods. However, it is often not possible to determine a sole optimal scale for the image to be classified because in many cases different geo-objects and even an identical geo-object may appear at different scales in one image. In this paper, an object-based classification method based on mutliscale segmentation results in the framework of topic modelling is proposed to classify VHR satellite images in an entirely unsupervised fashion. In the stage of topic modelling, grayscale histogram distributions for each geo-object class and each segment are learned in an unsupervised manner from multiscale segments. In the stage of classification, each segment is allocated a geo-object class label by the similarity comparison between the grayscale histogram distributions of each segment and each geo-object class. Experimental results show that the proposed method can perform better than the traditional methods based on topic modelling.

  19. Drifting Recovery Base Concept for GEO Derelict Object Capture

    Bacon, John B.


    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.

  20. Fast calculation of object infrared spectral scattering based on CUDA

    Li, Liang-chao; Niu, Wu-bin; Wu, Zhen-sen


    Computational unified device architecture (CUDA) is used for paralleling the spectral scattering calculation from non-Lambertian object of sky and earth background irradiation. The bidirectional reflectance distribution function (BRDF) of five parameter model is utilized in object surface element scattering calculation. The calculation process is partitioned into many threads running in GPU kernel and each thread computes a visible surface element infrared spectral scattering intensity in a specific incident direction, all visible surface elements' intensity are weighted and averaged to obtain the object surface scattering intensity. The comparison of results of the CPU calculation and CUDA parallel calculation of a cylinder shows that the CUDA parallel calculation speed improves more than two hundred times in meeting the accuracy, with a high engineering value.

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

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


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

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

    Bhavya Mehta


    Full Text Available 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 have proposed a model that expresses change evolution in terms of class hierarchies. As the changes evolve so does the class hierarchy, it can be further extended and existing classes can be extended.

  3. Ontology-Based Annotation of Learning Object Content

    Gasevic, Dragan; Jovanovic, Jelena; Devedzic, Vladan


    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…

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

    WANG, Hong-bin; Liu, Yu-hua


    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…




    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.

  6. ICT Competence-Based Learning Object Recommendations for Teachers

    Sergis, Stylianos; Zervas, Panagiotis; Sampson, Demetrios G.


    Recommender Systems (RS) have been applied in the Technology enhanced Learning (TeL) field for facilitating, among others, Learning Object (LO) selection and retrieval. Most of the existing approaches, however, aim at accommodating the needs of learners and teacher-oriented RS are still an under-investigated field. Moreover, the systems that focus…

  7. Bandwidth trading under misaligned objectives: decentralized measurement-based control

    Mandjes, M.R.H.; Ramakrishnan, M.


    This paper studies the interplay between a profit-maximizing network and a number of users competing for the finite bandwidth on each link. In our setting, the objectives of the network and the users are ‘misaligned’, in that the prices that optimize the network’s profit do not maximize the aggregat

  8. Application of Object-Based Industrial Controls for Cryogenics

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


    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.

  9. Development of learning object from IP-based television programme

    Fallahkhair, Sanaz


    The TAMALLE+[1, 2] is a prototype system that supports learners in their television viewing, enhancing informal language learning via interactive television and mobile phones. In this paper we describe a learner-centred study designed to elicit criteria for selection of those language learning object whose annotation or explanation through TAMALLE+ system could best enhance the advanced learner’s understanding of popular broadcast television programmes in English. We identified two main areas...

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

    Lerch, Alexander


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

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

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


    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.

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

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


    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.

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

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


    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...

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

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


    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.

  15. Video object's behavior analyzing based on motion history image and hidden markov model

    Meng Fanfeng; Qu Zhenshen; Zeng Qingshuang; Li li


    A novel method was proposed, which extracted video object's track and analyzed video object's behavior. Firstly, this method tracked the video object based on motion history image, and obtained the coordinate-based track sequence and orientation-based track sequence of the video object. Then the proposed hidden markov model (HMM) based algorithm was used to analyze the behavior of video object with the track sequence as input. Experimental results on traffic object show that this method can achieve the statistics of a mass of traffic objects' behavior efficiently, can acquire the reasonable velocity behavior curve of traffic object, and can recognize traffic object's various behaviors accurately. It provides a base for further research on video object behavior.

  16. Semantic Map Building Based on Object Detection for Indoor Navigation

    Jinfu Yang


    Full Text Available Building a map of the environment is a prerequisite for mobile robot navigation. In this paper, we present a semantic map building method for indoor navigation of a robot using only the image sequence acquired by a monocular camera installed on the robot. First, a topological map of the environment is created, where each key frame forms a node of the map represented as visual words (VWs. The edges between two adjacent nodes are built from relative poses obtained by performing a novel pose estimation approach, called one point RANSAC camera pose estimation (ORPE. Then, taking advantage of an improved deformable part model (iDPM for object detection, the topological map is extended by assigning semantic attributes to the nodes. Extensive experimental evaluations demonstrate the effectiveness of the proposed monocular SLAM method.

  17. Digital Microdroplet Ejection Technology-Based Heterogeneous Objects Prototyping

    Na Li


    Full Text Available 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.

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

    Ranjith Kumar Goud


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

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

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


    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

  20. Automated Detection of Objects Based on Sérsic Profiles

    Cabrera, Guillermo; Miller, C.; Harrison, C.; Vera, E.; Asahi, T.


    We present the results of a new astronomical object detection and deblending algorithm when applied to Sloan Digital Sky Survey data. Our algorithm fits PSF-convolved Sérsic profiles to elliptical isophotes of source candidates. The main advantage of our method is that it minimizes the amount and complexity of real-time user input relative to many commonly used source detection algorithms. Our results are compared with 1D radial profile Sérsic fits. Our long-term goal is to use these techniques in a mixture-model environment to leverage the speed and advantages of machine learning. This approach will have a great impact when re-processing large data-sets and data-streams from next generation telescopes, such as the LSST and the E-ELT.

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

    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

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

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


    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.

  3. Identifying Objective EEG Based Markers of Linear Vection in Depth

    Palmisano, Stephen; Barry, Robert J.; De Blasio, Frances M.; Fogarty, Jack S.


    This proof-of-concept study investigated whether a time-frequency EEG approach could be used to examine vection (i.e., illusions of self-motion). In the main experiment, we compared the event-related spectral perturbation (ERSP) data of 10 observers during and directly after repeated exposures to two different types of optic flow display (each was 35° wide by 29° high and provided 20 s of motion stimulation). Displays consisted of either a vection display (which simulated constant velocity forward self-motion in depth) or a control display (a spatially scrambled version of the vection display). ERSP data were decomposed using time-frequency Principal Components Analysis (t–f PCA). We found an increase in 10 Hz alpha activity, peaking some 14 s after display motion commenced, which was positively associated with stronger vection ratings. This followed decreases in beta activity, and was also followed by a decrease in delta activity; these decreases in EEG amplitudes were negatively related to the intensity of the vection experience. After display motion ceased, a series of increases in the alpha band also correlated with vection intensity, and appear to reflect vection- and/or motion-aftereffects, as well as later cognitive preparation for reporting the strength of the vection experience. Overall, these findings provide support for the notion that EEG can be used to provide objective markers of changes in both vection status (i.e., “vection/no vection”) and vection strength. PMID:27559328

  4. Design of Objects Tracking System Based on ARM Embedded Platform

    XU Mei; SONG Yong-duan; LV Shao-dong; LIU Zhi-long; HUANG Cong-ying


    In recent years, according to the need of intelligent video surveillance system increasing rapidly in metropolitan cities ,a design based on S3C2440 microprocessor and embedded Linux operating system is adopted for real-time video target tracking. However, it is very challenging as embedded systems usually afford limited processing power and limited resources. Therefore, to address this problem, a real-time tracking algorithm using multi-features based on compressive sensing is proposed and implemented. The algorithm uses multiple matrix as the projection matrix of the compressive sensing and the compressed date as the multiple features to extract useful information needed by tracking process. Functions and libraries in OpenCV which were developed by Intel Corporation are utilized for building the tracking algorithms. It is tested with variant video sequences and the results show that the algorithm achieves stable tracking for the target moved of the light changed.

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

    Marian Pompiliu CRISTESCU


    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.

  6. Hierarchical Object-Based Visual Attention for Machine Vision

    Sun, Yaoru


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

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

    Jagdish Lal Raheja; Umesh Kumar


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

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

    LI, Kun; Meng, Max Q.-H.


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

  9. Web-based visualization of spatial objects in 3DGIS

    ZHANG LiQiang; GUO ZhiFeng; KANG ZhiZhong; ZHANG LiXin; ZHANG XingMing; YANG Ling


    Adaptive rendering large and complex spatial data has become an important research issue In a 3DGIS application.In order to transmit the data to the client efficiently,this paper proposes a node-layer data model to manage the 3D scene.Because the large spatial data and limited network bandwidth are the main bottlenecks of web-based 3DGIS,a client/server architecture including progressive transmission methods and multiresolution representations,together with the spatial index,are developed to improve the performance.All this makes the application quite scalable.Experimental results reveal that the application works appropriately.

  10. From neural-based object recognition toward microelectronic eyes

    Sheu, Bing J.; Bang, Sa Hyun


    Engineering neural network systems are best known for their abilities to adapt to the changing characteristics of the surrounding environment by adjusting system parameter values during the learning process. Rapid advances in analog current-mode design techniques have made possible the implementation of major neural network functions in custom VLSI chips. An electrically programmable analog synapse cell with large dynamic range can be realized in a compact silicon area. New designs of the synapse cells, neurons, and analog processor are presented. A synapse cell based on Gilbert multiplier structure can perform the linear multiplication for back-propagation networks. A double differential-pair synapse cell can perform the Gaussian function for radial-basis network. The synapse cells can be biased in the strong inversion region for high-speed operation or biased in the subthreshold region for low-power operation. The voltage gain of the sigmoid-function neurons is externally adjustable which greatly facilitates the search of optimal solutions in certain networks. Various building blocks can be intelligently connected to form useful industrial applications. Efficient data communication is a key system-level design issue for large-scale networks. We also present analog neural processors based on perceptron architecture and Hopfield network for communication applications. Biologically inspired neural networks have played an important role towards the creation of powerful intelligent machines. Accuracy, limitations, and prospects of analog current-mode design of the biologically inspired vision processing chips and cellular neural network chips are key design issues.

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

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


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

  12. Multi-objective optimization of process based on resource capability


    To improve the practicability, suitability and accuracy of the trade-off among time, cost and quality of a process, a method based on resource capability is introduced. Through analyzing the relationship between an activity and its' supporting resource, the model trades off the time, cost and quality by changing intensity of labor or changing the types of supporting resource or units of labor of resource in a certain time respectively according to the different types of its' supporting resources. Through contrasting this method with the model of unit time cost corresponding to different quality levels and inter-related linear programming model of time, cost and quality for process optimizing, it is shown that this model does not only cover the above two models but also can describe some conditions the above two models can not express. The method supports to select different function to optimize a process according to different types of its supporting resource.

  13. Actin-based propulsion of spatially extended objects

    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.

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

    Zhu, Wei; Calchi Novati, S.; Gould, A.; Udalski, A.; Han, C.; Shvartzvald, Y.; Ranc, C.; Jørgensen, U. G.; Poleski, R.; Bozza, V.; Beichman, C.; Bryden, G.; Carey, S.; Gaudi, B. S.; Henderson, C. B.; Pogge, R. W.; Porritt, I.; Wibking, B.; Yee, J. C.; SPITZER Team; Pawlak, M.; Szymański, M. K.; Skowron, J.; Mróz, P.; Kozłowski, S.; Wyrzykowski, Ł.; Pietrukowicz, P.; Pietrzyński, G.; Soszyński, I.; Ulaczyk, K.; OGLE Group; Choi, J.-Y.; Park, H.; Jung, Y. K.; Shin, I.-G.; Albrow, M. D.; Park, B.-G.; Kim, S.-L.; Lee, C.-U.; Cha, S.-M.; Kim, D.-J.; Lee, Y.; KMTNET Group; Friedmann, M.; Kaspi, S.; Maoz, D.; WISE Group; Hundertmark, M.; Street, R. A.; Tsapras, Y.; Bramich, D. M.; Cassan, A.; Dominik, M.; Bachelet, E.; Dong, Subo; Figuera Jaimes, R.; Horne, K.; Mao, S.; Menzies, J.; Schmidt, R.; Snodgrass, C.; Steele, I. A.; Wambsganss, J.; RoboNeT Team; Skottfelt, J.; Andersen, M. I.; Burgdorf, M. J.; Ciceri, S.; D'Ago, G.; Evans, D. F.; Gu, S.-H.; Hinse, T. C.; Kerins, E.; Korhonen, H.; Kuffmeier, M.; Mancini, L.; Peixinho, N.; Popovas, A.; Rabus, M.; Rahvar, S.; Tronsgaard, R.; Scarpetta, G.; Southworth, J.; Surdej, J.; von Essen, C.; Wang, Y.-B.; Wertz, O.; MiNDSTEP Group


    We report on the mass and distance measurements of two single-lens events from the 2015 Spitzer microlensing campaign. With both finite-source effect and microlens parallax measurements, we find that the lens of OGLE-2015-BLG-1268 is very likely a brown dwarf (BD). Assuming that the source star lies behind the same amount of dust as the Bulge red clump, we find the lens is a 45 ± 7 {M}{{J}} BD at 5.9 ± 1.0 kpc. The lens of of the second event, OGLE-2015-BLG-0763, is a 0.50 ± 0.04 {M}ȯ star at 6.9 ± 1.0 kpc. We show that the probability to definitively measure the mass of isolated microlenses is dramatically increased once simultaneous ground- and space-based observations are conducted.

  15. Additivity of Feature-Based and Symmetry-Based Grouping Effects in Multiple Object Tracking.

    Wang, Chundi; Zhang, Xuemin; Li, Yongna; Lyu, Chuang


    Multiple object tracking (MOT) is an attentional process wherein people track several moving targets among several distractors. Symmetry, an important indicator of regularity, is a general spatial pattern observed in natural and artificial scenes. According to the "laws of perceptual organization" proposed by Gestalt psychologists, regularity is a principle of perceptual grouping, such as similarity and closure. A great deal of research reported that feature-based similarity grouping (e.g., grouping based on color, size, or shape) among targets in MOT tasks can improve tracking performance. However, no additive feature-based grouping effects have been reported where the tracking objects had two or more features. "Additive effect" refers to a greater grouping effect produced by grouping based on multiple cues instead of one cue. Can spatial symmetry produce a similar grouping effect similar to that of feature similarity in MOT tasks? Are the grouping effects based on symmetry and feature similarity additive? This study includes four experiments to address these questions. The results of Experiments 1 and 2 demonstrated the automatic symmetry-based grouping effects. More importantly, an additive grouping effect of symmetry and feature similarity was observed in Experiments 3 and 4. Our findings indicate that symmetry can produce an enhanced grouping effect in MOT and facilitate the grouping effect based on color or shape similarity. The "where" and "what" pathways might have played an important role in the additive grouping effect. PMID:27199875

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

    Koenig, Xavier; Padgett, Deborah; DeFelippis, Daniel


    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...

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

    Jagdish Lal Raheja


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

  18. A Knowledge-Based Approach to Describe and Adapt Learning Objects

    Bouzeghoub, Amel; Defude, Bruno; Duitama, John Freddy; Lecocq, Claire


    Our claim is that semantic metadata are required to allow a real reusing and assembling of learning objects. Our system is based on three models used to describe the domain, learners, and learning objects. The learning object model is inspired from knowledge representation proposals. A learning object can be reused directly or can be combined with…

  19. Attentional spreading to task-irrelevant object features: Experimental support and a 3-step model of attention for object-based selection and feature-based processing modulation

    Detlef eWegener


    Full Text Available Directing attention to a specific feature of an object has been linked to different forms of attentional modulation. Object-based attention theory founds on the finding that even task-irrelevant features at the selected object are subject to attentional modulation, while feature-based attention theory proposes a global processing benefit for the selected feature even at other objects. Most studies investigated either the one or the other form of attention, leaving open the possibility that both object- and feature-specific attentional effects do occur at the same time and may just represent two sides of a single attention system. We here investigate this issue by testing attentional spreading within and across objects, using reaction time measurements to changes of attended and unattended features on both attended and unattended objects. We asked subjects to report color and speed changes occurring on one of two overlapping random dot patterns, presented at the center of gaze. The key property of the stimulation was that only one of the features (e.g. motion direction was unique for each object, whereas the other feature (e.g. color was shared by both. The results of two experiments show that co-selection of unattended features even occurs when those features have no means for selecting the object. At the same time, they demonstrate that this processing benefit is not restricted to the selected object but spreads to the task-irrelevant one. We conceptualize these findings by a 3-step model of attention that assumes a task-dependent top-down gain, object-specific feature selection based on task- and binding characteristics, and a global feature-specific processing enhancement. The model allows for the unification of a vast amount of experimental results into a single model, and makes various experimentally testable predictions for the interaction of object- and feature-specific processes.

  20. A Growth-Cone Model for the Spread of Object-Based Attention during Contour Grouping

    Pooresmaeili, Arezoo; Roelfsema, Pieter R


    BACKGROUND: Object-based attention can group image elements of spatially extended objects into coherent representations, but its mechanisms have remained unclear. The mechanisms for object-based attention may include shape-selective neurons in higher visual cortical areas that feed back to lower are

  1. Fast object tracking based on template matching and region information fusion extraction

    Liu, Liman; Chen, Yun; Liu, Haihua


    In this paper, a fast object tracking algorithm based on template matching and region information fusion extraction is proposed. In the prediction framework, the data connection task is achieved by object template and object information extraction. And then the object is tracked accurately by using the object motion information. We handle the tracking shift by using the confidence estimation strategy. The experiments show that the proposed algorithm has robust performance.

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

    Hölbling, Daniel; Friedl, Barbara; Eisank, Clemens


    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

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

    Hermann, Alice; Ferré, Sébastien; Ducassé, Mireille


    International audience 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 object...

  4. A Machine Learning based Efficient Software Reusability Prediction Model for Java Based Object Oriented Software

    Surbhi Maggo


    Full Text Available Software reuse refers to the development of new software systems with the likelihood of completely or partially using existing components or resources with or without modification. Reusability is the measure of the ease with which previously acquired concepts and objects can be used in new contexts. It is a promising strategy for improvements in software quality, productivity and maintainability as it provides for cost effective, reliable (with the consideration that prior testing and use has eliminated bugs and accelerated (reduced time to market development of the software products. In this paper we present an efficient automation model for the identification and evaluation of reusable software components to measure the reusability levels (high, medium or low of procedure oriented Java based (object oriented software systems. The presented model uses a metric framework for the functional analysis of the Object oriented software components that target essential attributes of reusability analysis also taking into consideration Maintainability Index to account for partial reuse. Further machine learning algorithm LMNN is explored to establish relationships between the functional attributes. The model works at functional level rather than at structural level. The system is implemented as a tool in Java and the performance of the automation tool developed is recorded using criteria like precision, recall, accuracy and error rate. The results gathered indicate that the model can be effectively used as an efficient, accurate, fast and economic model for the identification of procedure based reusable components from the existing inventory of software resources.

  5. A Dynamic Object Behavior Model and Implementation Based on Computational Reflection

    HE Cheng-wan; HE Fei; HE Ke-qing


    A dynamic object behavior model based on computational reflection is proposed. This model consists of function level and meta level, the meta objects in meta level manage the base objects and behaviors in function level, including dynamic binding and unbinding of base object and behavior.We implement this model with RoleJava Language, which is our self linguistic extension of the Java Language. Meta Objects are generated automatically at compile-time, this makes the reflecton mechanism transparent to programmers. Finally an example applying this model to a banking system is presented.

  6. Optical MEMS-based arrays

    Ruffin, Paul B.


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

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

    Liang-Chia Chen


    Full Text Available 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 targets underlining an automated search in the range images using an initial process of object segmentation to subdivide all possible objects in the scenes and then applying a process of object recognition based on geometric constraints and a curvature-based histogram for object recognition. The developed method has been verified through experimental tests for its feasibility confirmation.

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

    Shahnawaz Talpur


    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

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

    Aneissha Chebolu


    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.

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

    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)

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

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


    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…

  12. Spatial Object Aggregation Based on Data Structure,Local Triangulation and Hierarchical Analyzing Method


    This paper focuses on the methods and process of spatial aggregation based on semantic and geometric characteristics of spatial objects and relations among the objects with the help of spatial data structure (Formal Data Structure),the Local Constrained Delaunay Triangulations and semantic hierarchy.The adjacent relation among connected objects and unconnected objects has been studied through constrained triangle as elementary processing unit in aggregation operation.The hierarchical semantic analytical matrix is given for analyzing the similarity between objects types and between objects.Several different cases of aggregation have been presented in this paper.

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

    Paglieroni, David W.; Beer, Reginald N.


    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.

  14. Logical Foundations of Object-Oriented and Frame-Based Languages

    Kifer, Michael; Lausen, Georg; Wu, James


    We propose a novel logic, called Frame Logic (abbr., F-logic), that accounts in a clean, declarative fashion for most of the structural aspects of object-oriented and frame-based languages. These features include object identity, complex objects, inheritance, polymorphic types, methods, encapsulation, and others. In a sense, F-logic stands in the same relationship to the object-oriented paradigm as classical predicate calculus stands to relational programming. The syntax of F-logic is higher-...

  15. Point pattern match-based change detection in a constellation of previously detected objects

    Paglieroni, David W.


    A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

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

    MacLennan, Bruce J.


    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

  17. 基于Object-Z的UML对象模型的形式化%The Formalization of Object Model in UML Based on Object-Z

    杨卫东; 蔡希尧


    UML is the main visual Object-oriented modeling language currently, which is used widely and supported by most CASE tools. Comparing with traditional Object-oriented methods, LML describes its semantics and syntax more rigouly by using metamodel and Object Constrain Language. But some important concepts in UML are not specified clearly. This paper presents a formal specification for object model of UML, mainly includes the concepts of class, association, association class, aggregation, and inheritance, etc, so that the analyse, verification, refine, and consistent cheking can be applied to object model.

  18. An attitude-based reasoning strategy to enhance interaction with augmented objects

    Iglesias Alvarez, Josué; Gómez Cordero, David; Bernardos Barbolla, Ana M.; Casar Corredera, Jose Ramon


    This paper describes a mobile-based system to interact with objects in smart spaces, where the offer of resources may be extensive. The underlying idea is to use the augmentation capabilities of the mobile device to enable it as user-object mediator. In particular, the paper details how to build an attitude-based reasoning strategy that facilitates user-object interaction and resource filtering. The strategy prioritizes the available resources depending on the spatial history of the user, his...

  19. Robust Online Object Tracking Based on Feature Grouping and 2DPCA

    Ming-Xin Jiang; Jun-Xing Zhang; Min Li


    We present an online object tracking algorithm based on feature grouping and two-dimensional principal component analysis (2DPCA). Firstly, we introduce regularization into the 2DPCA reconstruction and develop an iterative algorithm to represent an object by 2DPCA bases. Secondly, the object templates are grouped into a more discriminative image and a less discriminative image by computing the variance of the pixels in multiple frames. Then, the projection matrix is learned according to the m...

  20. Object-Based Image Analysis Beyond Remote Sensing - the Human Perspective

    Blaschke, T.; Lang, S.; Tiede, D.; Papadakis, M.; Györi, A.


    We introduce a prototypical methodological framework for a place-based GIS-RS system for the spatial delineation of place while incorporating spatial analysis and mapping techniques using methods from different fields such as environmental psychology, geography, and computer science. The methodological lynchpin for this to happen - when aiming to delineate place in terms of objects - is object-based image analysis (OBIA).

  1. An object-based approach to image/video-based synthesis and processing for 3-D and multiview televisions

    Chan, SC; Ng, KT; Ho, KL; Gan, ZF; Shum, HY


    This paper proposes an object-based approach to a class of dynamic image-based representations called "plenoptic videos," where the plenoptic video sequences are segmented into image-based rendering (IBR) objects each with its image sequence, depth map, and other relevant information such as shape and alpha information. This allows desirable functionalities such as scalability of contents, error resilience, and interactivity with individual IBR objects to be supported. Moreover, the rendering...

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

    Pedersen, G. B. M.


    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.

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

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


    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...

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

    J. Fernandez Galarreta


    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.

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

    Liping Wang


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

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

    Ronaldo Lima Rocha Campos


    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.

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

    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

  8. Retrieving top-k prestige-based relevant spatial web objects

    Cao, Xin; Cong, Gao; Jensen, Christian S.


    The location-aware keyword query returns ranked objects that are near a query location and that have textual descriptions that match query keywords. This query occurs inherently in many types of mobile and traditional web services and applications, e.g., Yellow Pages and Maps services. Previous...... prestige-based relevance to capture both the textual relevance of an object to a query and the effects of nearby objects. Based on this, a new type of query, the Location-aware top-k Prestige-based Text retrieval (LkPT) query, is proposed that retrieves the top-k spatial web objects ranked according to...... both prestige-based relevance and location proximity. We propose two algorithms that compute LkPT queries. Empirical studies with real-world spatial data demonstrate that LkPT queries are more effective in retrieving web objects than a previous approach that does not consider the effects of nearby...

  9. A Computational Model of Visual Attention Based on Space and Object

    Shuhong Li


    Full Text Available Object-based visual attention has got more and more attention in image processing. A computational model of visual attention based on space and object is proposed in this study. Firstly spatial visual saliency of each pixel is calculated and edges of the input image are extracted. Salient edges are obtained according to the visual saliency of each edge. Secondly, a graph-based clustering process is done to get the homogeneity regions of the image. Then the most salient homogeneity regions are extracted based on their spatial visual saliency. Perceptual objects can be extracted by combining salient edges and salient regions. Attention value of each perceptual object is computed according to the area and saliency. Focus of attention is shifted among these perceptual objects in terms of the attention value. The proposed computational model was tested on lots of natural images. Experiment results indicate that our model is valid and effective.

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

    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

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

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


    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.

  12. Wringing out objects for programming and modeling component-based systems

    Spacek, Petr; Dony, Christophe; Tibermacine, Chouki; Fabresse, Luc


    International audience Languages and technologies used to implement component-based software are not component-based, i.e. while the design phase happens in the component world, the programming phase occurs in the object-oriented world. When an object-oriented language is used for the programming stage, then the original component-based design vanish, because component concepts like requirements and architectures are not treated explicitly. This makes it difficult to keep model and its imp...

  13. An Object-Based Fast Motion Estimation Algorithm in MPEG-4

    SUN Lei; ZHANG Wen-jun; YU Song-yu; LIU Xun


    This paper presented an object-based fast motion estimation (ME) algorithm for object-based texture coding in moving picture experts group four (MPEG-4), which takes full advantage of the shape information of video object. Compared with the full search (FS) algorithm, the proposed algorithm can significantly speed the ME process. The speed of ME using the proposed algorithm is faster than that using new three-step search (NTSS), four-step search (4SS), diamond search (DS), and block-based gradient descent search (BBGDS) algorithms with similar motion compensation (MC) errors. The proposed algorithm can be combined with other fast ME algorithm to make the ME process faster.

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

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


    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



    The new MPEG-4 video coding standard enables content-based functions. In order to support the new standard, frames should be decomposed into Video Object Planes (VOP),each VOP representing a moving object. This paper proposes an image segmentation method to separate moving objects from image sequences. The proposed method utilizes the spatial-temporal information. Spatial segmentation is applied to divide each image into connected areas and to find precise object boundaries of moving objects. To locate moving objects in image sequences,two consecutive image frames in the temporal direction are examined and a hypothesis testing is performed with Neyman-Pearson criterion. Spatial segmentation produces a spatial segmentation mask, and temporal segmentation yields a change detection mask that indicates moving objects and the background. Then spatial-temporal merging can be used to get the final results. This method has been tested on several images. Experimental results show that this segmentation method is efficient.

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

    Simon, Arnaud; Napoli, Amedeo


    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...

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

    Jason Sherba; Leonhard Blesius; Jerry Davis


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

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

    Vu, Trung-Dung; Aycard, Olivier


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

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

    Akram Moh. Alkouz


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

  20. Object Detection Based on Template Matching through Use of Best-So-Far ABC

    Anan Banharnsakun


    Full Text Available Best-so-far ABC is a modified version of the artificial bee colony (ABC algorithm used for optimization tasks. This algorithm is one of the swarm intelligence (SI algorithms proposed in recent literature, in which the results demonstrated that the best-so-far ABC can produce higher quality solutions with faster convergence than either the ordinary ABC or the current state-of-the-art ABC-based algorithm. In this work, we aim to apply the best-so-far ABC-based approach for object detection based on template matching by using the difference between the RGB level histograms corresponding to the target object and the template object as the objective function. Results confirm that the proposed method was successful in both detecting objects and optimizing the time used to reach the solution.

  1. Object Detection Based on Template Matching through Use of Best-So-Far ABC


    Best-so-far ABC is a modified version of the artificial bee colony (ABC) algorithm used for optimization tasks. This algorithm is one of the swarm intelligence (SI) algorithms proposed in recent literature, in which the results demonstrated that the best-so-far ABC can produce higher quality solutions with faster convergence than either the ordinary ABC or the current state-of-the-art ABC-based algorithm. In this work, we aim to apply the best-so-far ABC-based approach for object detection based on template matching by using the difference between the RGB level histograms corresponding to the target object and the template object as the objective function. Results confirm that the proposed method was successful in both detecting objects and optimizing the time used to reach the solution. PMID:24812556

  2. Object detection based on template matching through use of best-so-far ABC.

    Banharnsakun, Anan; Tanathong, Supannee


    Best-so-far ABC is a modified version of the artificial bee colony (ABC) algorithm used for optimization tasks. This algorithm is one of the swarm intelligence (SI) algorithms proposed in recent literature, in which the results demonstrated that the best-so-far ABC can produce higher quality solutions with faster convergence than either the ordinary ABC or the current state-of-the-art ABC-based algorithm. In this work, we aim to apply the best-so-far ABC-based approach for object detection based on template matching by using the difference between the RGB level histograms corresponding to the target object and the template object as the objective function. Results confirm that the proposed method was successful in both detecting objects and optimizing the time used to reach the solution. PMID:24812556

  3. Object tracking and creation of linking information for distributed movie-based web-browsing system

    Hiraiwa, Atsunobu; Fuse, Keisuke; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki


    This paper proposes a new approach to automatically extract an accurate object from video streams. The new approach provides a useful tool creating linking information for a distributed movie-based Web-browsing system, and consists of a skip- labeling algorithm for feature-based segmentation, and a shrink-merge tracking algorithm for tracking an object. This skip-labeling algorithm can be used to segment an image into integrated regions of the same feature. The segmented regions belong to such a texture area as waves or forest. The shrink- merge tracking algorithm is executed, based on the time continuity of moving-objects, using morphological image processing, such as dilation and erosion. The dilation and erosion are repeatedly executed using the projection processing in which the object area in a next frame is derived from the object area in a current frame. The shrink-merge tracking algorithm can also project the area of a rotating- object in a current frame on the rotating-object containing the newly appearing regions in the next frame. The newly automated object extraction method works satisfactorily for the objects which move non-linearly within the video streams including MPEG and Motion JPEG, and works satisfactorily in approximately 450 frames, each with a full frame size of 704 X 480 pixels at video frame rate of 30 fps. This paper finally demonstrates that object-based linking information for a movie-based Web-browsing system contains information of objects obtained by the fully automated extraction from video- streams.

  4. An Objective Structured Clinical Examination to Assess Problem-Based Learning

    Salinitri, Francine D.; O'Connell, Mary Beth; Garwood, Candice L.; Lehr, Victoria Tutag; Abdallah, Karina


    Objectives. To compare pharmacy students’ performance on an objective structured clinical examination (OSCE) to their performance on a written examination for the assessment of problem-based learning (PBL); and to determine students’ and faculty members’ perceptions of OSCEs for PBL evaluations.

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

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


    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…



    Video object extraction is a key technology in content-based video coding. A novel video object extracting algorithm by two Dimensional (2-D) mesh-based motion analysis is proposed in this paper. Firstly, a 2-D mesh fitting the original frame image is obtained via feature detection algorithm.Then, higher order statistics motion analysis is applied on the 2-D mesh representation to get an initial motion detection mask. After post-processing, the final segmenting mask is quickly obtained. And hence the video object is effectively extracted. Experimental results show that the proposed algorithm combines the merits of mesh-based segmenting algorithms and pixel-based segmenting algorithms, and hereby achieves satisfactory subjective and objective performance while dramatically increasing the segmenting speed.

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

    Helen J. Chatterjee


    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.

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

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

  9. Representation of spatial relations and structures in object-based knowledge representation systems

    Le Ber, Florence; Napoli, Amedeo


    This paper is concerned with representing spatial structures in object-based knowledge representation systems (OKR systems). Spatial structures are defined as sets of objects related with qualitative spatial relations. We focus on topological relations from the RCC-8 theory, their recognition on raster images, and their reification in an OKR system. Spatial structures and relations have been implemented and used in a knowledge-based system for satellite image interpretation

  10. Research Letter: Sensor-Based Systems and the Objective Measure of Physical Activity

    Tuso, Phillip


    Similar to medication adherence, objective measures of physical activity may allow physicians to improve activity rates among individual patients and patient populations, which should improve health care outcomes. Sensor-based systems may become a best practice for objective measurement of physical activity and the management of physical activity programs. Given the ease of tracking with these new devices and the ability to upload information automatically, a sensor-based system has the poten...

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

    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

  12. Home-Explorer: Ontology-Based Physical Artifact Search and Hidden Object Detection System

    Bin Guo


    Full Text Available A new system named Home-Explorer that searches and finds physical artifacts in a smart indoor environment is proposed. The view on which it is based is artifact-centered and uses sensors attached to the everyday artifacts (called smart objects in the real world. This paper makes two main contributions: First, it addresses, the robustness of the embedded sensors, which is seldom discussed in previous smart artifact research. Because sensors may sometimes be broken or fail to work under certain conditions, smart objects become hidden ones. However, current systems provide no mechanism to detect and manage objects when this problem occurs. Second, there is no common context infrastructure for building smart artifact systems, which makes it difficult for separately developed applications to interact with each other and uneasy for them to share and reuse knowledge. Unlike previous systems, Home-Explorer builds on an ontology-based knowledge infrastructure named Sixth-Sense, which makes it easy for the system to interact with other applications or agents also based on this ontology. The hidden object problem is also reflected in our ontology, which enables Home-Explorer to deal with both smart objects and hidden objects. A set of rules for deducing an object's status or location information and for locating hidden objects are described and evaluated.

  13. General moving objects recognition method based on graph embedding dimension reduction algorithm

    Yi ZHANG; Jie YANG; Kun LIU


    Effective and robust recognition and tracking of objects are the key problems in visual surveillance systems. Most existing object recognition methods were designed with particular objects in mind. This study presents a general moving objects recognition method using global features of targets. Targets are extracted with an adaptive Gaussian mixture model and their silhouette images are captured and unified. A new objects silhouette database is built to provide abundant samples to train the subspace feature. This database is more convincing than the previous ones. A more effective dimension reduction method based on graph embedding is used to obtain the projection eigenvector. In our experiments, we show the effective performance of our method in addressing the moving objects recognition problem and its superiority compared with the previous methods.

  14. Spatio-temporal Compensation Based Object Detection for Video Surveillance Systems

    LI Ren-jie; YU Song-yu; XIONG Hong-kai


    Moving object detection in video surveillance is an important step.This paper addresses an automatic object detection algorithm based on spatio-temporal compensation for video surveillance.Temporal difference of the pairs of two frames with a k-frame distance is utilized to obtain coarse object masks.Usually,object regions in these coarse masks have discontinuous boundaries and some holes.Region growing with the distance constraint is proposed to compensate these coarse object regions in spatial domain,followed by filling holes.The added distance constraint can prevent object regions from growing infinitely.The proposed fining holes method is simple and effective.To solve the temporarily stopping problem of moving objects,temporal compensation is proposed to compensate the object mask by utilizing temporal coherence of moving objects in temporal domain.The proposed detection algorithm can extract moving objects as completely as possible.Experimental results have successfully demonstrated the validity of the proposed algorithm.

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

    L. DJEROU,


    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.

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

    Yuan Ni


    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.

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

    Qian Zhang


    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.

  18. Differences between predictions of how a reflection behaves based on the behaviour of an object, and how an object behaves based on the behaviour of its reflection.

    Bianchi, Ivana; Bertamini, Marco; Savardi, Ugo


    We studied adults' understanding of the relationship between objects and their reflections. Two studies investigated whether adults performed in a similar way when asked to predict the movement of a reflection in a flat mirror based on the movement of the corresponding object or, vice versa, predict the movement of the material object based on the movement of its reflection. We used simple movements in the experiments: movements in a straight line at various angles with respect to the mirror. Despite the simplicity of the task, some of the participants made incorrect predictions in a percentage of cases ranging from 0% to 54%, depending on the angle. Asymmetries between the two directions of prediction emerged, in particular in terms of types of error. Results confirmed a cognitive difference between deriving the reflected (virtual) world from the "real" (material) world and vice versa. In particular the expectation that something will be opposite in a mirror is more salient when people imagine how a reflection will be with respect to the material world rather than when they imagine how the material world will be with respect to a reflection. PMID:26322914

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

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


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

  20. Semi-Automated Object-Based Classification of Coral Reef Habitat using Discrete Choice Models

    Steven Saul


    Full Text Available As for terrestrial remote sensing, pixel-based classifiers have traditionally been used to map coral reef habitats. For pixel-based classifiers, habitat assignment is based on the spectral or textural properties of each individual pixel in the scene. More recently, however, object-based classifications, those based on information from a set of contiguous pixels with similar properties, have found favor with the reef mapping community and are starting to be extensively deployed. Object-based classifiers have an advantage over pixel-based in that they are less compromised by the inevitable inhomogeneity in per-pixel spectral response caused, primarily, by variations in water depth. One aspect of the object-based classification workflow is the assignment of each image object to a habitat class on the basis of its spectral, textural, or geometric properties. While a skilled image interpreter can achieve this task accurately through manual editing, full or partial automation is desirable for large-scale reef mapping projects of the magnitude which are useful for marine spatial planning. To this end, this paper trials the use of multinomial logistic discrete choice models to classify coral reef habitats identified through object-based segmentation of satellite imagery. Our results suggest that these models can attain assignment accuracies of about 85%, while also reducing the time needed to produce the map, as compared to manual methods. Limitations of this approach include misclassification of image objects at the interface between some habitat types due to the soft gradation in nature between habitats, the robustness of the segmentation algorithm used, and the selection of a strong training dataset. Finally, due to the probabilistic nature of multinomial logistic models, the analyst can estimate a map of uncertainty associated with the habitat classifications. Quantifying uncertainty is important to the end-user when developing marine spatial

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

    Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan


    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.

  2. Recognition of 3-D objects based on Markov random field models

    HUANG Ying; DING Xiao-qing; WANG Sheng-jin


    The recognition of 3-D objects is quite a difficult task for computer vision systems.This paper presents a new object framework,which utilizes densely sampled grids with different resolutions to represent the local information of the input image.A Markov random field model is then created to model the geometric distribution of the object key nodes.Flexible matching,which aims to find the accurate correspondence map between the key points of two images,is performed by combining the local similarities and the geometric relations together using the highest confidence first method.Afterwards,a global similarity is calculated for object recognition. Experimental results on Coil-100 object database,which consists of 7 200 images of 100 objects,are presented.When the numbers of templates vary from 4,8,18 to 36 for each object,and the remaining images compose the test sets,the object recognition rates are 95.75 %,99.30 %,100.0 % and 100.0 %,respectively.The excellent recognition performance is much better than those of the other cited references,which indicates that our approach is well-suited for appearance-based object recognition.

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

    Moon Nammee


    Full Text Available 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 the visual sensor is not dedicated to object tracking and deployed for other applications. The acoustic sensor mainly tracks multiple objects, and the visual sensor supports the tracking task only when the acoustic sensor has a difficulty. Several techniques based on particle filtering are used for multiple object tracking by the acoustic sensor, and the limitations of the acoustic sensor are discussed to identify the need for the visual sensor cooperation. Performance of the triggering-based cooperation by the two visual sensors is evaluated and compared with a periodic cooperation in a real environment.

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

    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

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

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


    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.

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

    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

  7. Object-oriented image coding scheme based on DWT and Markov random field

    Zheng, Lei; Wu, Hsien-Hsun S.; Liu, Jyh-Charn S.; Chan, Andrew K.


    In this paper, we introduce an object-oriented image coding algorithm to differentiate regions of interest (ROI) in visual communications. Our scheme is motivated by the fact that in visual communications, image contents (objects) are not equally important. For a given network bandwidth budget, one should give the highest transmission priority to the most interesting object, and serve the remaining ones at lower priorities. We propose a DWT based Multiresolution Markov Random Field technique to segment image objects according to their textures. We show that this technique can effectively distinguish visual objects and assign them different priorities. This scheme can be integrated with our ROI compression coder, the Generalized Self-Similarity Tress codex, for networking applications.

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

    Hindy, Nicholas C; Turk-Browne, Nicholas B


    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

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

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

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

    Waligora, Marcin; Różyńska, Joanna; Piasecki, Jan


    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

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

    Geng Zhang


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

  12. Use of Image Based Modelling for Documentation of Intricately Shaped Objects

    Marčiš, M.; Barták, P.; Valaška, D.; Fraštia, M.; Trhan, O.


    In the documentation of cultural heritage, we can encounter three dimensional shapes and structures which are complicated to measure. Such objects are for example spiral staircases, timber roof trusses, historical furniture or folk costume where it is nearly impossible to effectively use the traditional surveying or the terrestrial laser scanning due to the shape of the object, its dimensions and the crowded environment. The actual methods of digital photogrammetry can be very helpful in such cases with the emphasis on the automated processing of the extensive image data. The created high resolution 3D models and 2D orthophotos are very important for the documentation of architectural elements and they can serve as an ideal base for the vectorization and 2D drawing documentation. This contribution wants to describe the various usage of image based modelling in specific interior spaces and specific objects. The advantages and disadvantages of the photogrammetric measurement of such objects in comparison to other surveying methods are reviewed.

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

    Frank Yeong-Sung Lin


    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.

  14. Proposed educational objectives for hospital-based dentists during catastrophic events and disaster response.

    Psoter, Walter J; Herman, Neal G; More, Frederick G; Park, Patricia; Robbins, Miriam; Rekow, E Dianne; Ryan, James M; Triola, Marc M; Glotzer, David


    The purpose of this project was to define education and training requirements for hospital-based dentists to efficiently and meaningfully participate in a hospital disaster response. Eight dental faculty with hospital-based training and/or military command and CBRNE (chemical, biological, radiological, nuclear, and explosive) expertise were recruited as an expert panel. A consensus set of recommended educational objectives for hospital-based dentists was established using the following process: 1) identify assumptions supported by all expert panelists, 2) determine current advanced dental educational training requirements, and 3) conduct additional training and literature review by various panelists and discussions with other content and systems experts. Using this three-step process, educational objectives that the development group believed necessary for hospital-based dentists to be effective in treatment or management roles in times of a catastrophic event were established. These educational objectives are categorized into five thematic areas: 1) disaster systems, 2) triage/medical assessment, 3) blast and burn injuries, 4) chemical agents, and 5) biological agents. Creation of training programs to help dentists acquire these educational objectives would benefit hospital-based dental training programs and strengthen hospital surge manpower needs. The proposed educational objectives are designed to stimulate discussion and debate among dental, medical, and public health professionals about the roles of dentists in meeting hospital surge manpower needs. PMID:16896086

  15. The application of equivalent uniform dose-based objective function in intensity modulated radiation therapy

    Objective: To propose an objective function based on equivalent uniform dose (EUD) to investigate the feasibility of its application in IMRT optimization. Methods: Both EUD-based and dose- based objective functions were applied to optimize the IMRT plan for 6 lung cancer patients. Genetic algorithm was selected and the population size, number of generation, mutation rate and crossover frequency were 101, 100, 0.008 and 0.8. The algorithm was implemented in C program and the dose calculation model was based on three-dimensional pencil beams. Results: It was found that EUD-based criteria provided better target coverage and was capable of improving the sparing of critical structures beyond the specified requirements. The penalty function led to much-improved target dose homogeneity. The average calculated EUD for organs at risk, normal tissue and tumor were 9.32 Gy, 35.21 Gy and 83.76 Gy. The corresponding data for the dose-based plan were 12.20 Gy, 36.96 Gy and 86.21 Gy. Conclusions: Equivalent uniform dose based objective function needs only a small number of parameters and allows the exploration of a much larger universe of solutions. It is nice derivability and convexity. It also could be a surrogate of biologic index such as tumor control probability and normal tissue complication probability. (authors)

  16. Photo-based participatory research : exploring the objectives of visiting a historical district

    Naoi, Taketo; Yamada, Takanobu; Iijima, Shoji; Kumazawa, Takayuki


    This study quantitatively investigates relationships between visitors’ objectives for visiting a historical district,using photo-based participatory research. Thirty Japanese undergraduates majoring in commerce and 27 Japaneseadults with an interest in architecture and/or town planning were asked to photograph noteworthy settings in ahistorical district and rate to what extent each setting portrayed nine objectives on scales. The ratings weresubjected to exploratory and confirmatory factor an...

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

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


    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 t...

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

    Edmund T eRolls


    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 ...

  19. Object-based Representation and Classification of Spatial Structures and Relations

    Le Ber, Florence; Napoli, Amedeo


    This paper is concerned with the representation and the classification of spatial relations and structures in an object-based knowledge representation system. In this system, spatial structures are defined as sets of spatial entities connected with topological relations. Relations are represented by objects with their own properties. We propose to define two types of properties: the first ones are concerned with relations as concepts while the second are concerned with relations as links betw...

  20. A drifting trajectory prediction model based on object shape and stochastic mo-tion features

    王胜正; 聂皓冰; 施朝健


    There is a huge demand to develop a method for marine search and rescue (SAR) operators automatically predicting the most probable searching area of the drifting object. This paper presents a novel drifting prediction model to improve the accuracy of the drifting trajectory computation of the sea-surface objects. First, a new drifting kinetic model based on the geometry characteristics of the objects is proposed that involves the effects of the object shape and stochastic motion features in addition to the traditional factors of wind and currents. Then, a computer simulation-based method is employed to analyze the stochastic motion features of the drifting objects, which is applied to estimate the uncertainty parameters of the stochastic factors of the drifting objects. Finally, the accuracy of the model is evaluated by comparison with the flume experimental results. It is shown that the proposed method can be used for various shape objects in the drifting trajectory prediction and the maritime search and rescue decision-making system.

  1. Investigation of Vision-based Underwater Object Detection with Multiple Datasets

    Dario Lodi Rizzini


    Full Text Available In this paper, we investigate the potential of vision-based object detection algorithms in underwater environments using several datasets to highlight the issues arising in different scenarios. Underwater computer vision has to cope with distortion and attenuation due to light propagation in water, and with challenging operating conditions. Scene segmentation and shape recognition in a single image must be carefully designed to achieve robust object detection and to facilitate object pose estimation. We describe a novel multi-feature object detection algorithm conceived to find human-made artefacts lying on the seabed. The proposed method searches for a target object according to a few general criteria that are robust to the underwater context, such as salient colour uniformity and sharp contours. We assess the performance of the proposed algorithm across different underwater datasets. The datasets have been obtained using stereo cameras of different quality, and diverge for the target object type and colour, acquisition depth and conditions. The effectiveness of the proposed approach has been experimentally demonstrated. Finally, object detection is discussed in connection with the simple colour-based segmentation and with the difficulty of tri-dimensional processing on noisy data.

  2. Multi-Objective Optimization and Analysis Model of Sintering Process Based on BP Neural Network

    ZHANG Jun-hong; XIE An-guo; SHEN Feng-man


    A multi-objective optimization and analysis model of the sintering process based on BP neural network is presented. Genetic algorithms are combined to simplify the BP neural network, which can reduce the learning time and increase the forecasting accuracy of the network model. This model has been experimented in the sintering process, and the production cost, the energy consumption, the quality (revolving intensity), and the output are considered at the same time. Moreover, the relation between some factors and the multi-objectives has been analyzed, and the results are consistent with the process. Different objectives are emphasized at different practical periods, and this can provide a theoretical basis for the manager.

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

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

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

    Sunil T. D


    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.

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

    Ryder, R. M.; Inamdar, B.


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

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

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


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

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

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


    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.

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

    Saini, Deepika; Kumar, Sanjeev


    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.

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

    Zhang, Caiyun


    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.

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

    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)


    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.

  11. Multi Objective Test Suite Reduction for GUI Based Software Using NSGA-II

    Neha Chaudhary


    Full Text Available Regression Testing is a performed to ensure modified code does not have any unintended side effect on the software. If regression testing is performed with retest-all method it will be very time consuming as testing activity. Therefore test suite reduction methods are used to reduce the size of original test suite. Objective of test suite reduction is to reduce those test cases which are redundant or less important in their fault revealing capability. Test suite reduction can only be used when time is critical to run all test cases and selective testing can only be done. Various methods exist in the literature related to test suite reduction of traditional software. Most of the methods are based of single objective optimization. In case of multi objective optimization of test suite, usually researchers assign different weight values to different objectives and combine them as single objective. However in test suite reduction multiple Pareto-optimal solutions are present, it is difficult to select one test case over other. Since GUI based software is our concern there exist very few reduction techniques and none of them consider multiple objective based reduction. In this work we propose a new test suite reduction technique based on two objectives, event weight and number of faults identified by test case. We evaluated our results for 2 different applications and we achieved 20% reduction in test suite size for both applications. In Terp Paint 3.0 application compromise 15.6% fault revealing capability and for Notepad 11.1% fault revealing capability is reduced.

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

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


    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

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

    Kompatsiaris Ioannis


    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.

  14. Class-Based Garbage Collection in Object-Oriented Programming Environments

    张武生; 黄启峰; 沈美明; 郑纬民


    Many garbage collection algorithms have been proposed, but few address the special needs of long-running server programs. Server applications usually run for years and spawn many threads, so they create and discard thousands of objects. Therefore, efficient garbage collection is especially important for those applications. This paper presents a class-based garbage collector for object-oriented programming environments that classifies objects by their types to achieve better gradualness. Grouping objects of the same type into a group, with a limited type-lock, a mutator cache and the lease protocol will reduce memory fragmentation, which is especially important for the efficiency of long-running server applications. This class-based collector partitions the heap space by type, which provides better concurrency than the traditional mark-sweep collector, and its reusable garbaged object pool also reduces the object allocation overhead. This paper also discusses the implementation details, such as the mutator cache and the lease protocol, and techniques to achieve better accuracy.

  15. 逆合成孔径成像激光雷达微多普勒效应分析及特征提取%Analysis of Micro-Doppler Effect and Feature Extraction of Target in Inverse Synthetic Aperture Imaging Ladar

    何劲; 张群; 罗迎; 杨小优


    研究了基于逆合成孔径成像激光雷达的目标微多普勒效应,分析了激光信号高载频和大带宽对目标微动点一维距离像的影响,在此基础上建立了相应的微多普勒特征参数方程并讨论了快时间对微多普勒效应的影响.针对逆合成孔径成像激光雷达系统目标微多普勒效应的特点,提出了一种结合二值数学形态学腐蚀膨胀运算和推广Hough变换的目标微多普勒特征提取方法.仿真实验验证了文中微多普勒效应理论分析和微多普勒特征提取算法的正确性,并证明了逆合成孔径成像激光雷达对厘米或毫米量级微动观测的有效性.%The micro-Doppler effect based on the inverse synthetic imaging ladar is studied, and the influence of the high carrier frequency and the bandwidth of laser signal on the range profiles is also analyzed.Furthermore, the corresponding parameters equation of micro-Doppler is constructed and then the influence of the fast-time on the micro-Doppler effect is also discussed. Based on the Extended Hough Transform and the erosion and dilation operations in binary mathematical morphology, a novel extraction method of micro-Doppler effect is proposed for the inverse synthetic imaging ladar accordingly. The simulations are given to verify the theoretical derivation and the validity of the proposed method. In addition, the validity of the measurement of the inverse synthetic imaging ladar for the micro-motion at the centimeter-level or the millimeter-level is also illustrated in the simulations.

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

    Masatomo Inui


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

  17. Multi-objective optimization of membrane structures based on Pareto Genetic Algorithm

    SAN Bing-bing; SUN Xiao-ying; WU Yue


    A multi-objective optimization method based on Pareto Genetic Algorithm is presented for shape design of membrane structures from a structural view point.Several non-dimensional variables are defined as optimization variables,which are decision factors of shapes of membrane structures.Three objectives are proposed including maximization of stiffness,maximum uniformity of stress and minimum reaction under external loads.Pareto Muhi-objective Genetic Algorithm is introduced to solve the Pareto solutions.Consequently,the dependence of the optimality upon the optimization variables is derived to provide guidelines on how to determine design parameters.Moreover,several examples illustrate the proposed methods and applications.The study shows that the multi-objective optimization method in this paper is feasible and efficient for membrane structures; the research on Pareto solutions can provide explicit and useful guidelines for shape design of membrane structures.

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

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

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

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


    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

  20. Full-viewpoint 3D Space Object Recognition Based on Kernel Locality Preserving Projections

    Meng Gang; Jiang Zhiguo; Liu Zhengyi; Zhang Haopeng; Zhao Danpei


    Space object recognition plays an important role in spatial exploitation and surveillance,followed by two main problems:lacking of data and drastic changes in viewpoints.In this article,firstly,we build a three-dimensional (3D) satellites dataset named BUAA Satellite Image Dataset (BUAA-SID 1.0) to supply data for 3D space object research.Then,based on the dataset,we propose to recognize full-viewpoint 3D space objects based on kemel locality preserving projections (KLPP).To obtain more accurate and separable description of the objects,firstly,we build feature vectors employing moment invariants,Fourier descriptors,region covariance and histogram of oriented gradients.Then,we map the features into kernel space followed by dimensionality reduction using KLPP to obtain the submanifold of the features.At last,k-nearest neighbor (kNN) is used to accomplish the classification.Experimental results show that the proposed approach is more appropriate for space object recognition mainly considering changes of viewpoints.Encouraging recognition rate could be obtained based on images in BUAA-SID 1.0,and the highest recognition result could achieve 95.87%.

  1. A Machine Learning based Efficient Software Reusability Prediction Model for Java Based Object Oriented Software

    Surbhi Maggo; Chetna Gupta


    Software reuse refers to the development of new software systems with the likelihood of completely or partially using existing components or resources with or without modification. Reusability is the measure of the ease with which previously acquired concepts and objects can be used in new contexts. It is a promising strategy for improvements in software quality, productivity and maintainability as it provides for cost effective, reliable (with the consideration that prior testing and use has...

  2. Automated detection of lunar craters based on object-oriented approach

    YUE ZongYu; LIU JianZhong; WU GanGuo


    The object-oriented approach is a powerful method in making classification. With the segmentation of images to objects, many features can be calculated based on the objects so that the targets can be distinguished. However, this method has not been applied to lunar study. In this paper we attempt to apply this method to detecting lunar craters with promising results. Craters are the most obvious features on the moon and they are important for lunar geologic study. One of the important questions in lunar research is to estimate lunar surface ages by examination of crater density per unit area. Hence,proper detection of lunar craters is necessary. Manual crater identification is inefficient, and a more efficient and effective method is needed. This paper describes an object-oriented method to detect lunar craters using lunar reflectance images. In the method, many objects were first segmented from the image based on size, shape, color, and the weights to every layer. Then the feature of "contrast to neighbor objects" was selected to identify craters from the lunar image. In the next step, by merging the adjacent objects belonging to the same class, almost every crater can be taken as an independent object except several very big craters in the study area. To remove the crater rays diagnosed as craters,the feature of "length/width" was further used with suitable parameters to finish recognizing craters.Finally, the result was exported to ArcGIS for manual modification to those big craters and the number of craters was acquired.

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

    Rolls, Edmund T.


    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

  4. D Modelling and Interactive Web-Based Visualization of Cultural Heritage Objects

    Koeva, M. N.


    Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interactive visualization, 3D models are highly effective and intuitive for present-day users who have stringent requirements and high expectations. Depending on the complexity of the objects for the specific case, various technological methods can be applied. The selected objects in this particular research are located in Bulgaria - a country with thousands of years of history and cultural heritage dating back to ancient civilizations. This motivates the preservation, visualisation and recreation of undoubtedly valuable historical and architectural objects and places, which has always been a serious challenge for specialists in the field of cultural heritage. In the present research, comparative analyses regarding principles and technological processes needed for 3D modelling and visualization are presented. The recent problems, efforts and developments in interactive representation of precious objects and places in Bulgaria are presented. Three technologies based on real projects are described: (1) image-based modelling using a non-metric hand-held camera; (2) 3D visualization based on spherical panoramic images; (3) and 3D geometric and photorealistic modelling based on architectural CAD drawings. Their suitability for web-based visualization are demonstrated and compared. Moreover the possibilities for integration with additional information such as interactive maps, satellite imagery, sound, video and specific information for the objects are described. This comparative study

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

    Sharari, T. M.


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

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



    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.

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

    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))


    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.).

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

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


    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

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

    Muhammad Kamal


    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.

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

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


    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...

  11. Personalised learning object based on multi-agent model and learners’ learning styles

    Noppamas Pukkhem


    A multi-agent model is proposed in which learning styles and a word analysis technique to create a learning object recommendation system are used. On the basis of a learning style-based design, a concept map combination model is proposed to filter out unsuitable learning concepts from a given course. Our learner model classifies learners into eight styles and implements compatible computational methods consisting of three recommendations: i) non-personalised, ii) preferred feature-based, and ...

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

    Bahadır KARASULU


    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 a...

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

    Guo, Ziyuan


    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 ...

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

    Ming Xue; Hua Yang; Shibao Zheng; Yi Zhou; Zhenghua Yu


    To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT) is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU) strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a...

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

    Williams, Mary-Anne; Sims, Aidan


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

  16. Flexibility on storage-release based distributed hydrologic modeling with object-oriented approach

    Kang, Kwangmin; Merwade, Venkatesh; Chun, Jong Ahn; Timlin, Dennis


    With the availability of advanced hydrologic data in public domain such as remote sensed and climate change scenario data, there is a need for a modeling framework that is capable of using these data to simulate and extend hydrologic processes with multidisciplinary approaches for sustainable water resources management. To address this need, a storage-release based distributed hydrologic model (STORE DHM) is developed based on an object-oriented approach. The model is tested for demonstrating model flexibility and extensibility to know how to well integrate object-oriented approach to further hydrologic research issues, e.g., reconstructing missing precipitation in this study, without changing its main frame. Moreover, the STORE DHM is applied to simulate hydrological processes with multiple classes in the Nanticoke watershed. This study also describes a conceptual and structural framework of object-oriented inheritance and aggregation characteristics under the STORE DHM. In addition, NearestMP (missing value estimation based on nearest neighborhood regression) and KernelMP (missing value estimation based on Kernel Function) are proposed for evaluating STORE DHM flexibility. And then, STORE DHM runoff hydrographs compared with NearestMP and KernelMP runoff hydrographs. Overall results from these comparisons show promising hydrograph outputs generated by the proposed two classes. Consequently, this study suggests that STORE DHM with an object-oriented approach will be a comprehensive water resources modeling tools by adding additional classes for toward developing through its flexibility and extensibility.

  17. A general simulation model developing process based on five-object framework

    胡安斌; 伞冶; 陈建明; 陈永强


    Different paradigms that relate verification and validation to the simulation model have different development process. A simulation model developing process based on Five-Object Framework (FOF) is discussed in this paper. An example is given to demonstrate the applications of the proposed method.

  18. A Model for the Design of Puzzle-Based Games Including Virtual and Physical Objects

    Melero, Javier; Hernandez-Leo, Davinia


    Multiple evidences in the Technology-Enhanced Learning domain indicate that Game-Based Learning can lead to positive effects in students' performance and motivation. Educational games can be completely virtual or can combine the use of physical objects or spaces in the real world. However, the potential effectiveness of these approaches…

  19. A Note on Classification-Based Reasoning and Semi-Structured Objects

    Napoli, Amedeo


    In this talk, we present a work in progress on the representation and manipulation of semi-structured data in an object-based representation environment. This research work is carried out in the field of knowledge representation and reasoning in order to build intelligent systems (according to artificial intelligence standards).

  20. Ensemble-based multi-objective optimization of on-off control devices under geological uncertainty

    Fonseca, R.M.; Leeuwenburgh, O.; Rossa, E.D.; Hof, P.M.J. van den; Jansen, J.D.


    We consider robust ensemble-based (EnOpt) multi-objective production optimization of on-off inflow control devices (ICDs) for a sector model inspired on a real-field case. The use of on-off valves as optimization variables leads to a discrete control problem. We propose a re-parameterization of such

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

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


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

  2. Geomorphological change detection using object-based feature extraction from multi-temporal LIDAR data

    A.C. Seijmonsbergen; N.S. Anders; W. Bouten


    Multi-temporal LiDAR DTMs are used for the development and testing of a method for geomorphological change analysis in western Austria. Our test area is located on a mountain slope in the Gargellen Valley in western Austria. Six geomorphological features were mapped by using stratified Object-Based

  3. Development of E-Mart Based on Object-Oriented Databases (OODB)

    SUN Li; WANG Li; LIU Hao-shuang


    Focusing on the development of electronic-mart (e-mart)based on object-oriented databases (OODB), the concepts of integrated electronic-commerce (ecommerce) environment and e-mart are introduced, and the basic characteristics of OODB Jasmine are described.In addition, the database mode and hierarchy of e-mart are discussed in derail.

  4. A Framework Relating Outcomes Based Education and the Taxonomy of Educational Objectives.

    Andrich, David


    Articulates a framework that can place the Outcomes Based Education movement in a historical context and by so doing advance its discourse on assessment. Reviews the development and structure of the Taxonomy of Educational Objectives (B. Bloom et al., 1956) and the structure of Student Outcome Statements in Western Australia and explores the…

  5. Development of Management System for Regional Pollution Source Based on SuperMap Objects


    Based on the integration of and SuperMap Objects(tool software of component GIS),the management system of regional pollution source is developed.It mainly includes the demand analysis of system,function design,database construction,program design and concrete realization in the management aspect of pollution source.

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

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


    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

  7. Adaptive Morphological Feature-Based Object Classifier for a Color Imaging System

    McDowell, Mark; Gray, Elizabeth


    Utilizing a Compact Color Microscope Imaging System (CCMIS), a unique algorithm has been developed that combines human intelligence along with machine vision techniques to produce an autonomous microscope tool for biomedical, industrial, and space applications. This technique is based on an adaptive, morphological, feature-based mapping function comprising 24 mutually inclusive feature metrics that are used to determine the metrics for complex cell/objects derived from color image analysis. Some of the features include: Area (total numbers of non-background pixels inside and including the perimeter), Bounding Box (smallest rectangle that bounds and object), centerX (x-coordinate of intensity-weighted, center-of-mass of an entire object or multi-object blob), centerY (y-coordinate of intensity-weighted, center-of-mass, of an entire object or multi-object blob), Circumference (a measure of circumference that takes into account whether neighboring pixels are diagonal, which is a longer distance than horizontally or vertically joined pixels), . Elongation (measure of particle elongation given as a number between 0 and 1. If equal to 1, the particle bounding box is square. As the elongation decreases from 1, the particle becomes more elongated), . Ext_vector (extremal vector), . Major Axis (the length of a major axis of a smallest ellipse encompassing an object), . Minor Axis (the length of a minor axis of a smallest ellipse encompassing an object), . Partial (indicates if the particle extends beyond the field of view), . Perimeter Points (points that make up a particle perimeter), . Roundness [(4(pi) x area)/perimeter(squared)) the result is a measure of object roundness, or compactness, given as a value between 0 and 1. The greater the ratio, the rounder the object.], . Thin in center (determines if an object becomes thin in the center, (figure-eight-shaped), . Theta (orientation of the major axis), . Smoothness and color metrics for each component (red, green, blue

  8. Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

    LIU Yongxue; LI Manchun; MAO Liang; XU Feifei; HUANG Shuo


    With the wide use of high-resolution remotely sensed imagery, the object-oriented remotely sensed information classification pattern has been intensively studied. Starting with the definition of object-oriented remotely sensed information classification pattern and a literature review of related research progress, this paper sums up 4 developing phases of object-oriented classification pattern during the past 20 years. Then, we discuss the three aspects of methodology in detail, namely remotely sensed imagery segmentation, feature analysis and feature selection, and classification rule generation, through comparing them with remotely sensed information classification method based on per-pixel. At last, this paper presents several points that need to be paid attention to in the future studies on object-oriented RS information classification pattern: 1) developing robust and highly effective image segmentation algorithm for multi-spectral RS imagery; 2) improving the feature-set including edge, spatial-adjacent and temporal characteristics; 3) discussing the classification rule generation classifier based on the decision tree; 4) presenting evaluation methods for classification result by object-oriented classification pattern.

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

    Watanabe, Keishiro; Okamoto, Jun; Kurita, Takaaki


    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.

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

    Akram Moh. Alkouz


    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.

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

    Edmund T eRolls


    Full Text Available 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 modelin which invariant representations can be built by self-organizing learning based on the temporal and spatialstatistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associativesynaptic learning rule with a short term memory trace, and/or it can use spatialcontinuity in Continuous Spatial Transformation learning which does not require a temporal trace. The model of visual processing in theventral cortical stream can build representations of objects that are invariant withrespect to translation, view, size, and also lighting. The modelhas been extended to provide an account of invariant representations in the dorsal visualsystem of the global motion produced by objects such as looming, rotation, and objectbased movement. The model has been extended to incorporate top-down feedback connectionsto model the control of attention by biased competition in for example spatial and objectsearch tasks. The model has also been extended to account for how the visual system canselect single objects in complex visual scenes, and how multiple objects can berepresented in a scene. The model 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.

  12. Feature- and object-based attentional modulation in the human auditory "where" pathway.

    Krumbholz, Katrin; Eickhoff, Simon B; Fink, Gereon R


    Attending to a visual stimulus feature, such as color or motion, enhances the processing of that feature in the visual cortex. Moreover, the processing of the attended object's other, unattended, features is also enhanced. Here, we used functional magnetic resonance imaging to show that attentional modulation in the auditory system may also exhibit such feature- and object-specific effects. Specifically, we found that attending to auditory motion increases activity in nonprimary motion-sensitive areas of the auditory cortical "where" pathway. Moreover, activity in these motion-sensitive areas was also increased when attention was directed to a moving rather than a stationary sound object, even when motion was not the attended feature. An analysis of effective connectivity revealed that the motion-specific attentional modulation was brought about by an increase in connectivity between the primary auditory cortex and nonprimary motion-sensitive areas, which, in turn, may have been mediated by the paracingulate cortex in the frontal lobe. The current results indicate that auditory attention can select both objects and features. The finding of feature-based attentional modulation implies that attending to one feature of a sound object does not necessarily entail an exhaustive processing of the object's unattended features. PMID:18271742

  13. Locating the position of objects in non-line-of-sight based on time delay estimation

    Wang, Xue-Feng; Wang, Yuan-Qing; Su, Jin-Shan; Yang, Xing-Yu


    Non-line-of-sight imaging detection is to detect hidden objects by indirect light and intermediary surface (diffuser). It has very important significance in indirect access to an object or dangerous object detection, such as medical treatment and rescue. An approach to locating the positions of hidden objects is proposed based on time delay estimation. The time delays between the received signals and the source signal can be obtained by correlation analysis, and then the positions of hidden objects will be located. Compared with earlier systems and methods, the proposed approach has some modifications and provides significant improvements, such as quick data acquisition, simple system structure and low cost, and can locate the positions of hidden objects as well: this technology lays a good foundation for developing a practical system that can be used in real applications. Project supported by the National Science and Technology Major Project of China (Grant No. AHJ2011Z001) and the Major Research Project of Yili Normal University (Grant No. 2016YSZD05).

  14. Automatic 3D object recognition and reconstruction based on neuro-fuzzy modelling

    Samadzadegan, Farhad; Azizi, Ali; Hahn, Michael; Lucas, Curo

    Three-dimensional object recognition and reconstruction (ORR) is a research area of major interest in computer vision and photogrammetry. Virtual cities, for example, is one of the exciting application fields of ORR which became very popular during the last decade. Natural and man-made objects of cities such as trees and buildings are complex structures and automatic recognition and reconstruction of these objects from digital aerial images but also other data sources is a big challenge. In this paper a novel approach for object recognition is presented based on neuro-fuzzy modelling. Structural, textural and spectral information is extracted and integrated in a fuzzy reasoning process. The learning capability of neural networks is introduced to the fuzzy recognition process by taking adaptable parameter sets into account which leads to the neuro-fuzzy approach. Object reconstruction follows recognition seamlessly by using the recognition output and the descriptors which have been extracted for recognition. A first successful application of this new ORR approach is demonstrated for the three object classes 'buildings', 'cars' and 'trees' by using aerial colour images of an urban area of the town of Engen in Germany.

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

    Huber, David J.; Khosla, Deepak


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

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

    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

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

    Anastasia Polychronaki


    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.

  18. Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

    WANG Ya-lin; MA Jie; GUI Wei-hua; YANG Chun-hua; ZHANG Chuan-fu


    A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0 %, which effectively stabilizes the agglomerate compositions and the permeability.

  19. Multi-objective optimization of stamping forming process of head using Pareto-based genetic algorithm

    周杰; 卓芳; 黄磊; 罗艳


    To obtain the optimal process parameters of stamping forming, finite element analysis and optimization technique were integrated via transforming multi-objective issue into a single-objective issue. A Pareto-based genetic algorithm was applied to optimizing the head stamping forming process. In the proposed optimal model, fracture, wrinkle and thickness varying are a function of several factors, such as fillet radius, draw-bead position, blank size and blank-holding force. Hence, it is necessary to investigate the relationship between the objective functions and the variables in order to make objective functions varying minimized simultaneously. Firstly, the central composite experimental (CCD) with four factors and five levels was applied, and the experimental data based on the central composite experimental were acquired. Then, the response surface model (RSM) was set up and the results of the analysis of variance (ANOVA) show that it is reliable to predict the fracture, wrinkle and thickness varying functions by the response surface model. Finally, a Pareto-based genetic algorithm was used to find out a set of Pareto front, which makes fracture, wrinkle and thickness varying minimized integrally. A head stamping case indicates that the present method has higher precision and practicability compared with the“trial and error”procedure.

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

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


    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.

  1. Serial grouping of 2D-image regions with object-based attention in humans.

    Jeurissen, Danique; Self, Matthew W; Roelfsema, Pieter R


    After an initial stage of local analysis within the retina and early visual pathways, the human visual system creates a structured representation of the visual scene by co-selecting image elements that are part of behaviorally relevant objects. The mechanisms underlying this perceptual organization process are only partially understood. We here investigate the time-course of perceptual grouping of two-dimensional image-regions by measuring the reaction times of human participants and report that it is associated with the gradual spread of object-based attention. Attention spreads fastest over large and homogeneous areas and is slowed down at locations that require small-scale processing. We find that the time-course of the object-based selection process is well explained by a 'growth-cone' model, which selects surface elements in an incremental, scale-dependent manner. We discuss how the visual cortical hierarchy can implement this scale-dependent spread of object-based attention, leveraging the different receptive field sizes in distinct cortical areas. PMID:27291188

  2. A vague-set-based fuzzy multi-objective decision making model for bidding purchase

    WANG Zhou-jing; QIAN Edward Y.


    A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bidding purchase process. A group of decision-makers (DMs) first independently assess bidding plans according to their experience and preferences, and these assessments may be expressed as linguistic terms, which are then converted to fuzzy numbers. The resulting decision matrices are then transformed to objective membership grade matrices. The lower bound of satisfaction and upper bound of dissatisfaction are used to determine each bidding plan's supporting, opposing, and neutral objective sets, which together determine the vague value of a bidding plan. Finally, a score function is employed to rank all bidding plans. A new score function based on vague sets is introduced in the model and a novel method is presented for calculating the lower bound of satisfaction and upper bound of dissatisfaction. In a vague-set-based fuzzy multi-objective decision making model, different valuations for upper and lower bounds of satisfaction usually lead to distinct ranking results. Therefore, it is crucial to effectively contain DMs' arbitrariness and subjectivity when these values are determined.

  3. Stability Analysis of Ranking Alternatives Based on Subjective and Objective Weight

    JIANG Yan; ZUO Bao-he; YUE Chao-yuan


    Weights of criteria are used to assess the relative importance of the different criteria in multicriteria analysis, which can influence ranking result more or less depending on the multicriteria decisionmaking method used. In this paper, the influences of alternatives' ranking result associated with the change of weight are discussed by making use of the concept of weight stability intervals based on subjective and objective integrated weighting approach. Meamwhile, A model of weight proportion stability intervals is proposed. a numeral example is used to illuminate how many increment of objective weight can change the ranking results determined by subjective weight.

  4. Network Analysis Modeling Towards GIS Based on Object-Relation Database

    YUE Peng; WANG Yandong; GONG Jianya; HUANG Xianfeng


    This paper compares the differences between the mathematical model in graph theory and GIS network analysis model. Thus it claims that the GIS network analysis model needs to solve. Then this paper introduces the spatial data management methods in object-relation database for GIS and discusses its effects on the network analysis model. Finally it puts forward the GIS network analysis model based on the object-relation database. The structure of the model is introduced in detail and research is done to the internal and external memory data structure of the model. The results show that it performs well in practice.

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

    Stuikys, Vytautas


    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

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

    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

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

    Supakit Fuangkaew; Karn Patanukhom


    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...

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

    Heras Evangelio Rubén


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

  9. Design for Sustainability of Industrial Symbiosis based on Emergy and Multi-objective Particle Swarm Optimization

    Ren, Jingzheng; Liang, Hanwei; Dong, Liang;


    Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative...... performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied...... approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable...

  10. Design of object surveillance system based on enhanced fish-eye lens

    Jianhui Wu; Kuntao Yang; Qiaolian Xiang; Nanyang Zhang


    A new method is proposed for the object surveillance system based on the enhanced fish-eye lens and the high speed digital signal processor (DSP). The improved fish-eye lens images an ellipse picture on the charge-coupled device (CCD) surface, which increases both the utilization rate of the 4:3 rectangular CCD and the imaging resolution, and remains the view angle of 183°. The algorithm of auto-adapted renewal background subtraction (ARBS) is also explored to extract the object from the monitoring image. The experimental result shows that the ARBS algorithm has high anti-jamming ability and high resolution, leading to excellent object detecting ability from the enhanced elliptical fish-eye image under varies en-vironments. This system has potential applications in different security monitoring fields due to its wide monitoring space, simple structure, working stability, and reliability.

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

    Fei Cai


    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.

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

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


    utilization (action knowledge). Here we show that the left ventral premotor cortex is activated during categorization of "both" fruit/vegetables and articles of clothing, relative to animals and nonmanipulable man-made objects. This observation suggests that action knowledge may not be important for the...... processing of man-made objects per se, but rather for the processing of manipulable objects in general, whether natural or man-made. These findings both support psycholinguistic theories suggesting that certain lexical categories may evolve from, and the act of categorization rely upon, motor-based knowledge...... of action equivalency, and have important implications for theories of category specificity. Thus, the finding that the processing of vegetables/fruit and articles of clothing give rise to similar activation is difficult to account for should knowledge representations in the brain be truly...

  13. Multidisciplinary design optimization of vehicle instrument panel based on multi-objective genetic algorithm

    Wang, Ping; Wu, Guangqiang


    Typical multidisciplinary design optimization(MDO) has gradually been proposed to balance performances of lightweight, noise, vibration and harshness(NVH) and safety for instrument panel(IP) structure in the automotive development. Nevertheless, plastic constitutive relation of Polypropylene(PP) under different strain rates, has not been taken into consideration in current reliability-based and collaborative IP MDO design. In this paper, based on tensile test under different strain rates, the constitutive relation of Polypropylene material is studied. Impact simulation tests for head and knee bolster are carried out to meet the regulation of FMVSS 201 and FMVSS 208, respectively. NVH analysis is performed to obtain mainly the natural frequencies and corresponding mode shapes, while the crashworthiness analysis is employed to examine the crash behavior of IP structure. With the consideration of lightweight, NVH, head and knee bolster impact performance, design of experiment(DOE), response surface model(RSM), and collaborative optimization(CO) are applied to realize the determined and reliability-based optimizations, respectively. Furthermore, based on multi-objective genetic algorithm(MOGA), the optimal Pareto sets are completed to solve the multi-objective optimization(MOO) problem. The proposed research ensures the smoothness of Pareto set, enhances the ability of engineers to make a comprehensive decision about multi-objectives and choose the optimal design, and improves the quality and efficiency of MDO.

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

    Jaewoon Lee


    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.

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

    Yan Sun


    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.

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

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


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

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

    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.)

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

    Hussam K. Abdul-Ameer


    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.

  19. Measurement of a discontinuous object based on a dual-frequency grating

    Qiao Nao-Sheng; Cai Xin-Hua; Yao Chun-Mei


    The dual-frequency grating measurement theory is proposed in order to carry out the measurement of a discontinuous object. Firstly, the reason why frequency spectra are produced by low frequency gratings and high frequency gratings in the field of frequency is analysed, and the relationship between the wrapped-phase and the unwrappingphase is discussed. Secondly, a method to combine the advantages of the two kinds of gratings is proposed: one stripe is produced in the mutation part of the object measured by a suitable low frequency grating designed by MATLAB, then the phase produced by the low frequency grating need not be unfolded. The integer series of stripes is produced by a high frequency grating designed by MATLAB based on the frequency ratio of the two kinds of gratings and the high frequency wrapped-phase, and the high frequency unwrapping-phase is then obtained. In order to verify the correctness of the theoretical analysis, a steep discontinuous object of 600×600 pixels and 10.00 mm in height is simulated and a discontinuous object of ladder shape which is 32.00 mm in height is used in experiment. Both the simulation and the experiment can restore the discontinuous object height accurately by using the dual-frequency grating measurement theory.

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

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


    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

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

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


    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

  2. The research of object selection method based on rough set in map generalization

    Li, Wenjing; Long, Yi; Lin, Zhiyong


    Object selection is an important technical problem in the process of map generalization. Considering creative-thinking characteristic of map generalization process, the paper bring the Rough Set theory from spatial data mine field to map generalization field, put forward a new thought for map generalization based on classification idea of Rough Set. The method of Rough Set which has the benefit on enormous data with the imperfection and non-precision character has become a new tool to make research on spatial data mining. The paper analyzes the imperfection characters of geo-spatial data processing based on Rough Set and the selection problem in the processing of map generalization with classification thought; presents the thought that map generalization is a kind of classification for map objects. The method mentioned in this paper use different spatial and attribute information as different point of view to observe the map objects. The result of the classification is ordered by the weightiness of all kinds of factors. In the end, a river objects selection test validates the rough set map generalization method mentioned in this paper.

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

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


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

  4. Object-Oriented Change Detection for Remote Sensing Images Based on Multi-Scale Fusion

    Feng, Wenqing; Sui, Haigang; Tu, Jihui


    In the process of object-oriented change detection, the determination of the optimal segmentation scale is directly related to the subsequent change information extraction and analysis. Aiming at this problem, this paper presents a novel object-level change detection method based on multi-scale segmentation and fusion. First of all, the fine to coarse segmentation is used to obtain initial objects of different sizes; then, according to the features of the objects, Change Vector Analysis is used to obtain the change detection results of various scales. Furthermore, in order to improve the accuracy of change detection, this paper introduces fuzzy fusion and two kinds of decision level fusion methods to get the results of multi-scale fusion. Based on these methods, experiments are done with SPOT5 multi-spectral remote sensing imagery. Compared with pixel-level change detection methods, the overall accuracy of our method has been improved by nearly 10%, and the experimental results prove the feasibility and effectiveness of the fusion strategies.

  5. Three dimensional reconstruction of irregular object with indigent texture based on structured light

    Zheng, Li; Zhang, Jianqing; Zhan, Zongqian


    In this paper we describe three dimensional (3D) reconstruction of irregular object lack of texture based on structured light techniques. This system uses a CCD camera synchronized with the DLP projector captures the images, from which the 3D shape of the object is reconstructed. With the characteristic of the right image obtained from the projector and collinearity equations, the spacial point coordinates on the surface of the irregular object are obtained quickly by space intersection. As the grid table is rotating, the projector and the CCD camera are always fixed. Then all the point coordinates of different surfaces are computed in the same reference frame while the interior and exterior orientation elements of the CCD camera and projector are obtained in each different point of view. A CCD camera is also used to capture images for texture mapping. The untouched method based on close-range photogrammetry can be successfully adapted to reconstruct various kinds of shapes and some soft objects in the diverse areas.

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

    Mirko M. Stojiljković


    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.

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

    Trunfio, Paolo


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

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

    Ali Alharbi


    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.

  9. A Model-Based Approach to Object-Oriented Software Metrics

    梅宏; 谢涛; 杨芙清


    The need to improve software productivity and software quality has put for-ward the research on software metrics technology and the development of software metrics toolto support related activities. To support object-oriented software metrics practice effectively,a model-based approach to object-oriented software metrics is proposed in this paper. Thisapproach guides the metrics users to adopt the quality metrics model to measure the object-oriented software products. The development of the model can be achieved by using a top-downapproach. This approach explicitly proposes the conception of absolute normalization computa-tion and relative normalization computation for a metrics model. Moreover, a generic softwaremetrics tool - Jade Bird Object-Oriented Metrics Tool (JBOOMT) is designed to implementthis approach. The parser-based approach adopted by the tool makes the information of thesource program accurate and complete for measurement. It supports various customizablehierarchical metrics models and provides a flexible user interface for users to manipulate themodels. It also supports absolute and relative normalization mechanisms in different situations.

  10. Object Detection and Tracking Method of AUV Based on Acoustic Vision

    ZHANG Tie-dong; WAN Lei; ZENG Wen-jing; XU Yu-ru


    This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation,underwater acoustic images segmentation and underwater objects tracking.This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor.First,the real-time data flow (underwater acoustic images) is pre-processed to form the whole underwater acoustic image,and the relevant position information of objects is extracted and determined.An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method.Second,a representation of region information is created in light of the Gaussian particle filter.The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness.Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed.They show that the proposed method can detect and track the moving objects underwater online,and it is effective and robust.

  11. Robust Online Object Tracking Based on Feature Grouping and 2DPCA

    Ming-Xin Jiang


    Full Text Available We present an online object tracking algorithm based on feature grouping and two-dimensional principal component analysis (2DPCA. Firstly, we introduce regularization into the 2DPCA reconstruction and develop an iterative algorithm to represent an object by 2DPCA bases. Secondly, the object templates are grouped into a more discriminative image and a less discriminative image by computing the variance of the pixels in multiple frames. Then, the projection matrix is learned according to the more discriminative image and the less discriminative image, and the samples are projected. The object tracking results are obtained using Bayesian maximum a posteriori probability estimation. Finally, we employ a template update strategy which combines incremental subspace learning and the error matrix to reduce tracking drift. Compared with other popular methods, our method reduces the computational complexity and is very robust to abnormal changes. Both qualitative and quantitative evaluations on challenging image sequences demonstrate that the proposed tracking algorithm achieves more favorable performance than several state-of-the-art methods.


    A. Hadavand


    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%.

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

    Djalalian, Amir; Mukhtar, Rami; Zukerman, Moshe


    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.

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

    Stéphanie Jehan-Besson


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

  15. Performance Evaluation of RTLS Based on Active RFID Power Measurement for Dense Moving Objects

    Kim, Taekyu; Lee, Jin; Lee, Seungbeom; Park, Sin-Chong

    Tracking a large quantity of moving target tags simultaneously is essential for the localization and guidance of people in welfare facilities like hospitals and sanatoriums for the aged. The locating system using active RFID technology consists of a number of fixed RFID readers and tags carried by the target objects, or senior people. We compare the performances of several determination algorithms which use the power measurement of received signals emitted by the moving active RFID tags. This letter presents a study on the effect of collision in tracking large quantities of objects based on active RFID real time location system (RTLS). Traditional trilateration, fingerprinting, and well-known LANDMARC algorithm are evaluated and compared with varying number of moving tags through the SystemC-based computer simulation. From the simulation, we show the tradeoff relationship between the number of moving tags and estimation accuracy.

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

    Satish, Laika


    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.

  17. Computation of Edge-Edge-Edge Events Based on Conicoid Theory for 3-D Object Recognition

    WU Chenye; MA Huimin


    The availability of a good viewpoint space partition is crucial in three dimensional (3-D) object rec-ognition on the approach of aspect graph. There are two important events depicted by the aspect graph ap-proach, edge-edge-edge (EEE) events and edge-vertex (EV) events. This paper presents an algorithm to compute EEE events by characteristic analysis based on conicoid theory, in contrast to current algorithms that focus too much on EV events and often overlook the importance of EEE events. Also, the paper provides a standard flowchart for the viewpoint space partitioning based on aspect graph theory that makes it suitable for perspective models. The partitioning result best demonstrates the algorithm's efficiency with more valu-able viewpoints found with the help of EEE events, which can definitely help to achieve high recognition rate for 3-D object recognition.

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

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


    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

  19. A novel space-based observation strategy for GEO objects based on daily pointing adjustment of multi-sensors

    Hu, Yun-peng; Li, Ke-bo; Xu, Wei; Chen, Lei; Huang, Jian-yu


    Space-based visible (SBV) program has been proved to be with a large advantage to observe geosynchronous earth orbit (GEO) objects. With the development of SBV observation started from 1996, many strategies have come out for the purpose of observing GEO objects more efficiently. However it is a big challenge to visit all the GEO objects in a relatively short time because of the distribution characteristics of GEO belt and limited field of view (FOV) of sensor. And it's also difficult to keep a high coverage of the GEO belt every day in a whole year. In this paper, a space-based observation strategy for GEO objects is designed based on the characteristics of the GEO belt. The mathematical formula of GEO belt is deduced and the evolvement of GEO objects is illustrated. There are basically two kinds of orientation strategies for most observation satellites, i.e., earth-oriented and inertia-directional. Influences of both strategies to their own observation regions are analyzed and compared with each other. A passive optical instrument with daily attitude-adjusting strategies is proposed to increase the daily coverage rate of GEO objects in a whole year. Furthermore, in order to observe more GEO objects in a relatively short time, the strategy of a satellite with multi-sensors is proposed. The installation parameters between different sensors are optimized, more than 98% of GEO satellites can be observed every day and almost all the GEO satellites can be observed every two days with 3 sensors (FOV: 6° × 6°) on the satellite under the strategy of daily pointing adjustment in a whole year.

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

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


    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 ...

  1. Creating telecommunication services based on object-oriented frameworks and SDL

    Sinnott, R. O.; Kolberg, M.


    This paper describes the tools and techniques being applied in the TINA Open Service Creation Architecture (TOSCA) project to develop object-oriented models of distributed telecommunication services in SDL. The paper also describes the way in which Tree and Tabular Combined Notation (TTCN) test cases are derived from these models and subsequently executed against the CORBA-based implementations of these services through a TTCN/CORBA gateway.

  2. Home-Explorer: Ontology-Based Physical Artifact Search and Hidden Object Detection System

    Bin Guo; Satoru Satake; Michita Imai


    A new system named Home-Explorer that searches and finds physical artifacts in a smart indoor environment is proposed. The view on which it is based is artifact-centered and uses sensors attached to the everyday artifacts (called smart objects) in the real world. This paper makes two main contributions: First, it addresses, the robustness of the embedded sensors, which is seldom discussed in previous smart artifact research. Because sensors may sometimes be broken or fail to work under certai...

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

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


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

  4. Semantic annotation of multilingual learning objects based on a domain ontology

    Knoth, Petr


    One of the important tasks in the use of learning resources in e-learning is the necessity to annotate learning objects with appropriate metadata. However, annotating resources by hand is time consuming and difficult. Here we explore the problem of automatic extraction of metadata for description of learning resources. First, theoretical constraints for gathering certain types of metadata important for e-learning systems are discussed. Our approach to annotation is then outlined. This is base...

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

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


    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...

  6. Review: Formal Methods for Open Object-Based Distributed Systems V

    Liquori, Luigi


    Distributed System V (FMOODS) is not a book. It is a luxurious conference proceeding, edited in 2002 under the "shield" of IFIP TC6-WG6.1. FMOODS conference bring researchers from various fields: formal methods (model checking, abstract interpretation, type theory, Hoare-logic, etc.), distributed systems (CSP, pi-calculus, ambients, petri nets, actors, agents, ORB's, etc.), and "all around" object-based theory and practice. Applications in the above fields are various, crucial and pragmatic. ...

  7. Evidence-Based Robust Design of Deflection Actions for Near Earth Objects

    Zuiani, Federico; Vasile, Massimiliano; Gibbings, Alison


    This paper presents a novel approach to the robust design of deflection actions for Near Earth Objects (NEO). In particular, the case of deflection by means of Solar-pumped Laser ablation is studied here in detail. The basic idea behind Laser ablation is that of inducing a sublimation of the NEO surface, which produces a low thrust thereby slowly deviating the asteroid from its initial Earth threatening trajectory. This work investigates the integrated design of the Space-based Laser system a...


    Koeva, M. N.


    Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interact...

  9. Comparing Machine Learning Classifiers for Object-Based Land Cover Classification Using Very High Resolution Imagery

    Yuguo Qian; Weiqi Zhou; Jingli Yan; Weifeng Li; Lijian Han


    This study evaluates and compares the performance of four machine learning classifiers—support vector machine (SVM), normal Bayes (NB), classification and regression tree (CART) and K nearest neighbor (KNN)—to classify very high resolution images, using an object-based classification procedure. In particular, we investigated how tuning parameters affect the classification accuracy with different training sample sizes. We found that: (1) SVM and NB were superior to CART and KNN, and both could...

  10. A Java-based Smart Object Model for use in Digital Learning Environments

    Pushpagiri, Vara Prashanth


    The last decade has seen the scope of digital library usage extend from data warehousing and other common library services to building quality collections of electronic resources and providing web-based information retrieval mechanisms for distributed learning. This is clear from the number of ongoing research initiatives aiming to provide dynamic learning environments. A major task in providing learning environments is to define a resource model (learning object). The flexibility of the ...

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

    Jansen, Petra; Lehmann, Jennifer


    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...

  12. Application Mapping and Communication Synthesis for Object-Oriented Platform-Based Design

    Grüttner, Kim


    Platform-based design of embedded systems on a chip consists of the parallel functional application specification, configuration of the hardware platform (i.e. connection of processing, memory and physical communication channels) and mapping of the application description on the processing, memory and communication resources of the hardware platform. The main contribution of this work is the seamless object-oriented modelling and automatic refinement of communication. In the application model...

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

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


    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...

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

    Wang, Hui; Han, Shensheng


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

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

    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

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

    Maggi Kelly


    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.

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

    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


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

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

    Jaworska, T.


    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.

  19. Automated Visual Inspection: Position Identification of Object for Industrial Robot Application based on Color and Shape

    Muralindran Mariappan


    Full Text Available Inspection task is traditionally carried out by human. However, Automated Visual Inspection (AVI has gradually become more popular than human inspection due to the advantageous in the aspect of high precision and short processing time. Therefore, this paper proposed a system which identifies the object’s position for industrial robot based on colors and shapes where, red, green, blue and circle, square, triangle are recognizable. The proposed system is capable to identify the object’s position in three modes, either based on color, shape or both color and shape of the desired objects. During the image processing, RGB color space is utilized by the proposed system while winner take all approach is used to classify the color of the object through the evaluation of the pixel’s intensity value of the R, G and B channel. Meanwhile, the shapes and position of the objects are determined based on the compactness and the centroid of the region respectively. Camera settings, such as brightness, contrast and exposure is another important factor which can affect the performance of the proposed system. Lastly, a Graphical User Interface was developed. The experimental result shows that the developed system is highly efficient when implemented in the selected database.

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

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


    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.

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

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


    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.

  2. Geomorphological change detection using object-based feature extraction from multi-temporal LIDAR data

    Seijmonsbergen, A. C.; Anders, N.S.; W. Bouten


    Multi-temporal LiDAR DTMs are used for the development and testing of a method for geomorphological change analysis in western Austria. Our test area is located on a mountain slope in the Gargellen Valley in western Austria. Six geomorphological features were mapped by using stratified Object-Based Image Analysis (OBIA) and segmentation optimization using 1m LiDAR DTMs of 2002 and 2005. Based on the 2002 data, the scale parameter for each geomorphological feature was optimized by comparing ma...

  3. 基于UniNet的对象概念研究%Object Concepts Research Based on UniNet

    周国富; 余鹏; 袁崇义


    This paper discusses concepts on object from UniNet view and shows that there exists the flow of controlin object system except for exchanging of messages between objects. Meanwhile, the paper presents an independent mechanism of object communication separated from object that will result in a more general reuse of object. With helpof the control flow and the data flow, UniNet can describe not only the static features, but also the dynamic featuresof object system, which naturally solve the inheritance anomaly and the flow of data and control. In addition, based on UniNet specification, the object system can be verified easily and create the program code automatically.

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

    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

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

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


    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.

  6. Objective Evaluation Method of Steering Comfort Based on Movement Quality Evaluation of Driver Steering Maneuver

    YANG Yiyong; LIU Yahui; WANG Man; JI Run; JI Xuewu


    The existing research of steering comfort mainly focuses on the subjective evaluation, aiming at designing and optimizing the steering system. In the development of steering system, especially the evaluation of steering comfort, the objective evaluation methods considered the kinematic characteristics of driver steering maneuver are not proposed, which means that the objective evaluation of steering cannot be conducted with the evaluation of kinematic characteristics of driver in steering maneuver. In order to propose the objective evaluation methods of steering comfort, the evaluation of steering movement quality of driver is developed on the basis of the study of the kinematic characteristics of steering maneuver. First, the steering motion trajectories of the driver in both comfortable and certain extreme uncomfortable operation conditions are detected using the Vicon motion capture system. The operation conditions are under the restrictions of the vertical height and horizontal distance between steering wheel center and the H-point of driver, and the steering resisting torque else. Next, the movement quality evaluation of driver steering maneuver is assessed using twelve kinds of evaluation indices based on the kinematic analyses of the steering motion trajectories to propose an objective evaluation method. Finally, an integrated discomfort index of steering maneuver is proposed on the basis of the regression analysis of subjective evaluation rating and the movement quality evaluation indices, including the Jerk, Discomfort and Joint Torque indices. The test results show that the proposed integrated discomfort index gives a good fitting with the subjective evaluation of discomfort, which means it can be used to evaluate or predict the discomfort level of steering maneuver. This paper proposes an objective evaluation method of steering comfort based on the movement quality evaluation of driver steering maneuver.

  7. 6DoF object pose measurement by a monocular manifold-based pattern recognition technique

    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)

  8. High Quality Prime Farmland extraction pattern based on object-oriented image analysis

    Liu, Yong-xue; Li, Man-chun; Chen, Zhen-jie; Li, Fei-xue; Zhang, Yu; Zhao, Bo; Tan, Lu


    High Quality Prime Farmland (HQPF) is high, stable yields based on land consolidation of prime farmland, and has its important impact upon China's food security. To make clear the status-in-quo of the HQPF is important to its construction and management. However, it is difficult to get the spatial distribution information of the constructed HQPF enough rapidly in mountainous area using ground investigation, as well as hard to satisfy the requirements of large-scale promotion. A HQPF extraction framework based on object-oriented image analysis is discussed and applied to aerial imageries of Tonglu County. The approach can be divided into 3 steps: image segmentation, feature analysis & feature selection and extraction rules generation. In the image segmentation procedure, canny operator is used in edge detection, an edge growth algorithm is used to link discontinuous edge, and region labelling is carried out to generate image object. In the feature analysis & selection procedure, object-oriented feature analysis and feature selection methods are also discussed to construct a feature subset with fine divisibility for HQPF extraction. In the extraction rules generation procedure, the C4.5 algorithm is used to establish and trim the decision tree, then HQPF decision rules are generated from the decision tree. Compared with supervised classification (MLC classifier, ERDAS 8.7) and another object-oriented image analysis method (FNEA, e-Cognition4.0), the accuracy assessment shows that the extraction results by the object-oriented extraction patters have a high level of category consistency, size consistency and shape consistency.


    Kalaivani Rajagopal


    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.

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

    Strasser, Thomas; Lang, Stefan


    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%.

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

    Kang Ling


    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.

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

    Guerra, C; Pascucci, V


    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.

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

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


    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. Uncertain Training Data Edition for Automatic Object-Based Change Map Extraction

    Hajahmadi, S.; Mokhtarzadeh, M.; Mohammadzadeh, A.; Valadanzouj, M. J.


    Due to the rapid transformation of the societies, and the consequent growth of the cities, it is necessary to study these changes in order to achieve better control and management of urban areas and assist the decision-makers. Change detection involves the ability to quantify temporal effects using multi-temporal data sets. The available maps of the under study area is one of the most important sources for this reason. Although old data bases and maps are a great resource, it is more than likely that the training data extracted from them might contain errors, which affects the procedure of the classification; and as a result the process of the training sample editing is an essential matter. Due to the urban nature of the area studied and the problems caused in the pixel base methods, object-based classification is applied. To reach this, the image is segmented into 4 scale levels using a multi-resolution segmentation procedure. After obtaining the segments in required levels, training samples are extracted automatically using the existing old map. Due to the old nature of the map, these samples are uncertain containing wrong data. To handle this issue, an editing process is proposed according to K-nearest neighbour and k-means algorithms. Next, the image is classified in a multi-resolution object-based manner and the effects of training sample refinement are evaluated. As a final step this classified image is compared with the existing map and the changed areas are detected.

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

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


    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.

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

    Tugrul Talaslioglu


    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

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

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


    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.

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

    Pandu Sandi Pratama


    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].

  19. A web product data management system based on Simple Object Access Protocol


    A new web product data management architecture is presented. The three-tier web architecture and Simple Object Access Protocol (SOAP) are combined to build the web-based product data management (PDM) system which includes three tiers: the user services tier, the business services tier, and the data services tier. The client service component uses the serverside technology, and Extensible Markup Language (XML) web service which uses SOAP as the communication protocol is chosen as the business service component. To illustrate how to build a web-based PDM system using the proposed architecture,a case PDM system which included three logical tires was built. To use the security and central management features of the database, a stored procedure was recommended in the data services tier. The business object was implemented as an XML web service so that client could use standard internet protocols to communicate with the business object from any platform. In order to satisfy users using all sorts of browser, the server-side technology and Microsoft ASP.NET was used to create the dynamic user interface.

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

    Sharari T. M.


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

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

    Bahadır KARASULU


    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

  2. Job-shop Scheduling with Multi-objectives Based on Genetic Algorithms

    周亚勤; 李蓓智; 陈革


    The technology of production planning and scheduling is one of the critical technologies that decide whether the automated manufacturing systems can get the expected economy. Job shop scheduling belongs to the special class of NP-hard problems. Most of the algorithms used to optimize this class of problems have an exponential time; that is, the computation time increases exponentially with problem size. In scheduling study, makespan is often considered as the main objective. In this paper, makespan, the due date request of the key jobs, the availability of the key machine, the average wait-time of the jobs, and the similarities between the jobs and so on are taken into accotmt based on the application of mechanical engineering. The job shop scheduling problem with multi-objectives is analyzed and studied by using genetic algorithms based on the mechanics of genetics and natural selection. In this research, the tactics of the coding and decoding and the design of the genetic operators, along with the description of the mathematic model of the multi-objective functions,are presented. Finally an illu-strative example is given to testify the validity of this algorithm.

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

    T. K. Jana


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

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

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


    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. A portable, GUI-based, object-oriented client-server architecture for computer-based patient record (CPR) systems.

    Schleyer, T K


    Software applications for computer-based patient records require substantial development investments. Portable, open software architectures are one way to delay or avoid software application obsolescence. The Clinical Management System at Temple University School of Dentistry uses a portable, GUI-based, object-oriented client-server architecture. Two main criteria determined this approach: preservation of investment in software development and a smooth migration path to a Computer-based Patient Record. The application is separated into three layers: graphical user interface, database interface, and application functionality Implementation with generic cross-platform development tools ensures maximum portability. PMID:7662879

  6. ROCIT : a visual object recognition algorithm based on a rank-order coding scheme.

    Gonzales, Antonio Ignacio; Reeves, Paul C.; Jones, John J.; Farkas, Benjamin D.


    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.

  7. Phantoms for diffuse optical imaging based on totally absorbing objects, part 2: experimental implementation

    Martelli, Fabrizio; Ninni, Paola Di; Zaccanti, Giovanni; Contini, Davide; Spinelli, Lorenzo; Torricelli, Alessandro; Cubeddu, Rinaldo; Wabnitz, Heidrun; Mazurenka, Mikhail; Macdonald, Rainer; Sassaroli, Angelo; Pifferi, Antonio


    We present the experimental implementation and validation of a phantom for diffuse optical imaging based on totally absorbing objects for which, in the previous paper [J. Biomed. Opt. 18(6), 066014, (2013)], we have provided the basic theory. Totally absorbing objects have been manufactured as black polyvinyl chloride (PVC) cylinders and the phantom is a water dilution of intralipid-20% as the diffusive medium and India ink as the absorber, filled into a black scattering cell made of PVC. By means of time-domain measurements and of Monte Carlo simulations, we have shown the reliability, the accuracy, and the robustness of such a phantom in mimicking typical absorbing perturbations of diffuse optical imaging. In particular, we show that such a phantom can be used to generate any absorption perturbation by changing the volume and position of the totally absorbing inclusion.

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

    Jinchang Ren


    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.

  9. Observational Iinearization and tracking objective excitation control strategy based on phasor measurement unit

    QIU Xiaoyan; LI Xingyuan; WANG Xiaoyan


    To improve the transient stability ofmultimachine power systems,observational linearization and tracking objective excitation control laws were derived from the phasor measurement unit (PMU),observational linearization,and tracking objective control theory based on synchronized coordinates and reference generator coordinates.The control strategies utilized real-time state variables obtained by PMU to linearize the state equations of the system,and then the linear optimal control strategy was used to design excitation controllers.The inaccuracy of the local linearization method and the complexity of the system models designed in the exact linearization method for nonlinear systems were avoided.Therefore,the control strategies were applied in real time.Simulation results show that the proposed method can improve the transient stability of power systems more efficiently than nonlinear optimal excitation control.

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

    L. Monika Moskal


    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.

  11. Evolutionary Algorithm based on simulated annealing for the multi-objective optimization of combinatorial problems

    Elias David Nino Ruiz


    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%.



    Taking AutoCAD2000 as platform, an algorithm for the reconstruction of surface from scattered data points based on VBA is presented. With this core technology customers can be free from traditional AutoCAD as an electronic board and begin to create actual presentation of real-world objects. VBA is not only a very powerful tool of development, but with very simple syntax. Associating with those solids, objects and commands of AutoCAD 2000, VBA notably simplifies previous complex algorithms, graphical presentations and processing, etc. Meanwhile, it can avoid appearance of complex data structure and data format in reverse design with other modeling software. Applying VBA to reverse engineering can greatly improve modeling efficiency and facilitate surface reconstruction.

  13. Balancing Multiple Objectives Using a Classification-Based Forest Management System in Changbai Mountains, China

    Zhao, Fuqiang; Yang, Jian; Liu, Zhihua; Dai, Limin; He, Hong S.


    Contemporary forest management often consists of multiple objectives, including restoration of human-impacted forested landscapes toward their range of natural variability (RNV) and sustainable levels of timber production. Balancing multiple management objectives is often challenging due to intrinsic conflicts between these objectives and a lack of reference conditions for evaluating the effectiveness of forest restoration efforts. We used a spatially explicit forest landscape model to assess how well a classification-based forest management (CFM) system could achieve multiple objectives in a Korean pine broadleaf mixed forest ecosystem at Changbai Mountain in Northeast China. The CFM system divided the forest landscape into three management areas (Commercial Forest, Special Ecological Welfare Forest, and General Ecological Welfare Forest), each with its own management objectives and prescriptions, but with an overall goal of increasing the ecological and economic sustainability of the entire landscape. The zoning approach adopted in the Chinese CFM system is very similar to the TRIAD approach that is being advocated for managing public forests in Canada. In this study, a natural disturbance scenario and seven harvest scenarios (one identical to the current harvest regime and six alternative scenarios) were simulated to examine how tree species composition, age structure, and timber production at the landscape level can be affected by different strategies under the CFM system. The results indicated that the current forest management regime would not only fail to reach the designated timber production level but also move the forest landscape far away from its RNV. In order to return the currently altered forest landscape to approach its RNV while providing a stable level of timber production over time, harvest intensities should be reduced to a level that is equivalent to the amount of timber removals that would occur under the natural disturbances; and the

  14. Multi-Objective Fuzzy Optimum Design Based on Reliability for Offshore Jacket Platforms

    康海贵; 刘未; 翟钢军; 徐发淙; 封盛


    In consideration of the fuzzy constraint boundary and through analysis of structural reliability, a model of structural fuzzy optimum design is established based on reliability for offshore jacket platforms. According to the characteristics of offshore jacket platforms, the tolerance coefficient of the constraint boundary is determined with the fuzzy optimization method. The optimum level cut set λ *, which is the intersection of the fuzzy constraint set and fuzzy objective set, is determined with the bound search method, and then the fuzzy optimum solution to the fuzzy optimization problem is obtained. The central offshore platform SZ36-1 is designed with the fuzzy optimum model based on reliability; the results are compared with those from deterministic optimum design and fuzzy optimum design. The tendency of design variables in the above three methods and its reasons are analyzed. The results of an example show that the fuzzy optimum design based on reliability is stable and reliable.

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

    Dickey-Collas, Mark; Engelhard, Georg H.; Rindorf, Anna;


    whether maintaining the reserves of prey biomass or a more integral approach of monitoring mortality rates across the trophic system is more robust under the ecosystem approach. In terms of trophic energy transfer, stability, and resilience of the ecosystem, FF should be considered as both a sized......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......-based pool of biomass and as species components of the system by managers and modellers. Policy developers should not consider the knowledge base robust enough to embark on major projects of ecosystem engineering. Management plans appear able to maintain sustainable exploitation in the short term. Changes in...

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

    Feroze Kaliyadan


    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.

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

    Š. Valčuha


    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

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

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


    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.

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

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


    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.

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

    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

  1. A new optimization algorithm based on a combination of particle swarm optimization, convergence and divergence operators for single-objective and multi-objective problems

    Mahmoodabadi, M. J.; Bagheri, A.; Nariman-zadeh, N.; Jamali, A.


    Particle swarm optimization (PSO) is a randomized and population-based optimization method that was inspired by the flocking behaviour of birds and human social interactions. In this work, multi-objective PSO is modified in two stages. In the first stage, PSO is combined with convergence and divergence operators. Here, this method is named CDPSO. In the second stage, to produce a set of Pareto optimal solutions which has good convergence, diversity and distribution, two mechanisms are used. In the first mechanism, a new leader selection method is defined, which uses the periodic iteration and the concept of the particle's neighbour number. This method is named periodic multi-objective algorithm. In the second mechanism, an adaptive elimination method is employed to limit the number of non-dominated solutions in the archive, which has influences on computational time, convergence and diversity of solution. Single-objective results show that CDPSO performs very well on the complex test functions in terms of solution accuracy and convergence speed. Furthermore, some benchmark functions are used to evaluate the performance of periodic multi-objective CDPSO. This analysis demonstrates that the proposed algorithm operates better in three metrics through comparison with three well-known elitist multi-objective evolutionary algorithms. Finally, the algorithm is used for Pareto optimal design of a two-degree of freedom vehicle vibration model. The conflicting objective functions are sprung mass acceleration and relative displacement between sprung mass and tyre. The feasibility and efficiency of periodic multi-objective CDPSO are assessed in comparison with multi-objective modified NSGAII.

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

    Eloisa Valenza


    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.

  3. Object-based glacier mapping in the Hohe Tauern Mountains of Austria

    Aubrey Robson, Benjamin; Hölbling, Daniel; Nuth, Christopher; Olaf Dahl, Svein


    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

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

    Eloisa eValenza; Laura eFranchin; Hermann eBulf


    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...

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

    Pasam, Gopi Krishna; Manohar, T. Gowri


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

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

    Wenbiao Li


    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.

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

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


    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.

  8. Common toxicities and objective response rate in metastatic colorectal cancer patients treated with irinotecan based regimens

    Liu Huang; Xin Liao; Qianqian Yu; Qiang Fu; Kai Qin; Huanlei Wu; Lihong Zhang; Xianglin Yuan


    Objective: The aim of our study was to investigate if common toxicities are correlated to objective response rate (ORR) in metastatic colorectal cancer (mCRC) patients treated by irinotecan based regimens. Methods: Univariate and multivariate logistic regression analyses were performed to evaluate correlations between common toxicities and binary ORR in 106 mCRC patients from a prospective cohort treated with irinotecan based regimens. Results: The most frequent severe toxicities (Grade 3/4) were as follows: neutropenia (27.4%), diarrhea (16.9%), leucopenia (12.6%), vomiting (3.2%) and thrombocytopenia (2.1%). Thrombocytosis was observed in 25 (26.3%) patients. ORR was 25.3%. Thrombocytopenia (P = 0.014), line of chemotherapy (P = 0.028) and thrombocytosis (P = 0.033) were correlated with ORR in univariate analysis. In multivariate analysis, thrombocytopenia (odds ratio [OR] = 8.600, 95% confidence interval [CI] = 1.705–43.385, P = 0.009) and first line chemotherapy (OR = 5.155, 95% CI = 1.153–23.256, P = 0.032) positively related to ORR. Conclusion: Throm-bocytopenia may be an indicator of ORR in mCRC patients treated by irinotecan plus 5-fluorouracil/capecitabine. Evidence is not strong enough to prove that irinotecan based regimens-induced diarrhea, leucopenia, neutropenia or vomiting is associ-ated with ORR.

  9. A part-based probabilistic model for object detection with occlusion.

    Chunhui Zhang

    Full Text Available The part-based method has been a fast rising framework for object detection. It is attracting more and more attention for its detection precision and partial robustness to the occlusion. However, little research has been focused on the problem of occlusion overlapping of the part regions, which can reduce the performance of the system. This paper proposes a part-based probabilistic model and the corresponding inference algorithm for the problem of the part occlusion. The model is based on the Bayesian theory integrally and aims to be robust to the large occlusion. In the stage of the model construction, all of the parts constitute the vertex set of a fully connected graph, and a binary variable is assigned to each part to indicate its occlusion status. In addition, we introduce a penalty term to regularize the argument space of the objective function. Thus, the part detection is formulated as an optimization problem, which is divided into two alternative procedures: the outer inference and the inner inference. A stochastic tentative method is employed in the outer inference to determine the occlusion status for each part. In the inner inference, the gradient descent algorithm is employed to find the optimal positions of the parts, in term of the current occlusion status. Experiments were carried out on the Caltech database. The results demonstrated that the proposed method achieves a strong robustness to the occlusion.

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

    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


    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.


    Zhang Lele; Tan Nanlin; Zhang Huadi; Liu Cai


    To simulate the process of cold roll-forming process, a new method is adopted.The theoretical foundation of this method is an elastic-plastic large deformation spline finite strip method based on object-oriented programming.Combined with the computer graphics technology, the visual simulation of cold roll-forming is completed and the system is established.By analyzing common channel steel, the process is shown and explained including theory method, model and result display.So the simulation system is already a kind of mature and effective tool to analyze the process of cold roll forming.

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

    Juel, Anders

    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......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...... consistency of satellite imagery, with the high spatial resolution of aerial imagery....

  13. MO-Miner: A Data Mining Tool Based on Multi-Objective Genetic Algorithms

    Oliveira, Gina M. B.; Martins, Luiz G. A.; C, Maria; Takiguti, S.


    The application of a multi-objective GA-based environment named MO-miner, inspired by the family of algorithms NSGA and designed to discover accurate and interesting dependence modeling rules, was investigated in this work. Our investigation was performed by applying MO-miner to two distinct public data sets named Nursery and Zoo, composed by 12960 and 101 registers, respectively. The accuracy and the interestingness of the rules mined by MO-miner were compared with those found by a single-ob...

  14. Multi-agent reinforcement learning based on policies of global objective


    In general-sum games, taking all agent's collective rationality into account, we define agents' global objective,and propose a novel multi-agent reinforcement learning(RL) algorithm based on global policy. In each learning step, all agents commit to select the global policy to achieve the global goal. We prove this learning algorithm converges given certain restrictions on stage games of learned Q values, and show that it has quite lower computation time complexity than already developed multi-agent learning algorithms for general-sum games. An example is analyzed to show the algorithm' s merits.

  15. Solving multi-object radar cross section based on wide-angle parabolic equation method

    Huang Zhixiang; Wu Qiong; Wu Xianliang


    Based on a Padé approximation, a wide-angle parabolic equation method is introduced for computing the multiobject radar cross section (RCS) for the first time. The method is a paraxial version of the scalar wave equation, which solves the field by marching them along the paraxial direction. Numerical results show that a single wide-angle parabolic equation run can compute multi-object RCS efficiently for angles up to 45°.The method provides a new and efficient numerical method for computation electromagnetics.

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

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


    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.

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

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

  18. Effective and efficient visual description based on local binary patterns and gradient distribution for object recognition

    Zhu, Chao


    This thesis is dedicated to the problem of machine-based visual object recognition, which has become a very popular and important research topic in recent years because of its wide range of applications such as image/video indexing and retrieval, security access control, video monitoring, etc. Despite a lot of e orts and progress that have been made during the past years, it remains an open problem and is still considered as one of the most challenging problems in computer vision community, m...


    XU Jiuping


    This paper presents a general solution procedure and an interactive fuzzy satisfying method for a kind of fuzzy multi-objective linear programming problems based on interval valued fuzzy sets. Firstly, a fuzzy set of the fuzzy solutions, which can be focused on providing complete information for the final decision, can be obtained by the proposed tolerance analysis of a non-dominated set. Secondly, the satisfying solution for the decisionmaker can be derived from Pareto optimal solutions by updating the current reference membership levels on the basis of the current levels of the membership functions together with the trade-off rates between the membership functions.

  20. Method of Designing Missile Controller Based on Multi-Objective Optimization

    LIN Bo; MENG Xiu-yun; LIU Zao-zhen


    A method of designing robust controller based on genetic algorithm is presented in order to overcome the drawback of manual modification and trial in designing the control system of missile. Specification functions which reflect the dynamic performance in time domain and robustness in frequency domain are presented,then dynamic/static performance, control cost and robust stability are incorporated into a multi-objective optimization problem. Genetic algorithm is used to solve the problem and achieve the optimal controller directly.Simulation results show that the controller provides a good stability and offers a good dynamic performance in a large flight envelope. The results also validate the effectiveness of the method.

  1. Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization.

    Ren, Jingzheng; Liang, Hanwei; Dong, Liang; Sun, Lu; Gao, Zhiqiu


    Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision. PMID:27110990

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

    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

  3. Real-time framework for tensor-based image enhancement for object classification

    Cyganek, Bogusław; Smołka, Bogdan


    In many practical situations visual pattern recognition is vastly burdened by low quality of input images due to noise, geometrical distortions, as well as low quality of the acquisition hardware. However, although there are techniques of image quality improvements, such as nonlinear filtering, there are only few attempts reported in the literature that try to build these enhancement methods into a complete chain for multi-dimensional object recognition such as color video or hyperspectral images. In this work we propose a joint multilinear signal filtering and classification system built upon the multi-dimensional (tensor) approach. Tensor filtering is performed by the multi-dimensional input signal projection into the tensor subspace spanned by the best-rank tensor decomposition method. On the other hand, object classification is done by construction of the tensor sub-space constructed based on the Higher-Order Singular Value Decomposition method applied to the prototype patters. In the experiments we show that the proposed chain allows high object recognition accuracy in the real-time even from the poor quality prototypes. Even more importantly, the proposed framework allows unified classification of signals of any dimensions, such as color images or video sequences which are exemplars of 3D and 4D tensors, respectively. The paper discussed also some practical issues related to implementation of the key components of the proposed system.

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

    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

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

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


    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.

  6. Culture belief based multi-objective hybrid differential evolutionary algorithm in short term hydrothermal scheduling

    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.


    Kamyab Tahernezhadiani


    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.

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

    Jason Sherba


    Full Text Available LiDAR-derived slope models may be used to detect abandoned logging roads in steep forested terrain. An object-based classification approach of abandoned logging road detection was employed in this study. First, a slope model of the study site in Marin County, California was created from a LiDAR derived DEM. Multiresolution segmentation was applied to the slope model and road seed objects were iteratively grown into candidate objects. A road classification accuracy of 86% was achieved using this fully automated procedure and post processing increased this accuracy to 90%. In order to assess the sensitivity of the road classification to LiDAR ground point spacing, the LiDAR ground point cloud was repeatedly thinned by a fraction of 0.5 and the classification procedure was reapplied. The producer’s accuracy of the road classification declined from 79% with a ground point spacing of 0.91 to below 50% with a ground point spacing of 2, indicating the importance of high point density for accurate classification of abandoned logging roads.

  9. Cooperative Moving Object Segmentation using Two Cameras based on Background Subtraction and Image Registration

    Zhigao Cui


    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.

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

    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.

  11. A grid based multi-objective evolutionary algorithm for the optimization of power plants

    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.

  12. Image analysis based grading of bladder carcinoma. Comparison of object, texture and graph based methods and their reproducibility.

    Choi, H K; Jarkrans, T; Bengtsson, E; Vasko, J; Wester, K; Malmström, P U; Busch, C


    The possibility that computerized image analysis could increase the reproducibility of grading of bladder carcinoma as compared to conventional subjective grading made by pathologists was investigated. Object, texture and graph based analysis were carried out from Feulgen stained histological tissue sections. The object based features were extracted from gray scale images, binary images obtained by thresholding the nuclei and several other images derived through image processing operations. The textural features were based on the spatial gray-tone co-occurrence probability matrices and the graph based features were extracted from the minimum spanning trees connecting all nuclei. The large numbers of extracted features were evaluated in relation to subjective grading and to factors related to prognosis using multivariate statistical methods and multilayer backpropagation neural networks. All the methods were originally developed and tested on material from one patient and then tested for reproducibility on entirely different patient material. The results indicate reasonably good reproducibility for the best sets of features. In addition, image analysis based grading showed almost identical correlation to mitotic density and expression of p53 protein as subjective grading. It should thus be possible to use this kind of image analysis as a prognostic tool for bladder carcinoma. PMID:9373709

  13. An Overview of 3d Topology for Ladm-Based Objects

    Zulkifli, N. A.; Rahman, A. A.; van Oosterom, P.


    This paper reviews 3D topology within Land Administration Domain Model (LADM) international standard. It is important to review characteristic of the different 3D topological models and to choose the most suitable model for certain applications. The characteristic of the different 3D topological models are based on several main aspects (e.g. space or plane partition, used primitives, constructive rules, orientation and explicit or implicit relationships). The most suitable 3D topological model depends on the type of application it is used for. There is no single 3D topology model best suitable for all types of applications. Therefore, it is very important to define the requirements of the 3D topology model. The context of this paper is a 3D topology for LADM-based objects.

  14. Objective evaluation of pronunciation of standard Chinese final based on formant pattern

    DONG Bin; ZHAO Qingwei; YAN Yonghong


    A method used for objective evaluation of pronunciation of finals in standard Chinese is presented. The formant pattern of final is selected as the main feature and an improved evaluation algorithm based on Support Vector Machine is proposed. In this algorithm, two-level classification strategy is employed. A full-classification model and a sub-classification model are trained for each final. The pronunciation quality is evaluated based on the classification results of this two-level strategy with scoring model of each final. The new evaluation method is compared with traditional methods such as Hidden Markov Model (HMM) posterior probability scoring method and feature of Mel-Frequency Cepstrum Coefficients (MFCC), and the results show that the performance is effectively improved by the proposed method. The correlation of scores between human testers and machine has achieved 82%.

  15. Research on Object Model-Based Architecture for Service Robot System

    邵鹏鸣; 李成刚; 吴翰声


    An object model-based software architecture for service robot system is presented, which addresses both software engineering issues such as reuse, extensibility, and management of complexity as well as system engineering issues like scalability, reactivity, and robustness. A novel approach to the service robot system architecture is discussed. Cognitive psychology is considered in designing the software system, i.e., a humans way of vision and planning is applied. The planner can incorporate the users request into its task selection mechanism and generate plans biased toward picking the most reliable task execution in a given situation, and the planner can alter task selection based on changes that occur in dynamic and uncertain environments.




    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.

  17. Real-time object tracking based on scale-invariant features employing bio-inspired hardware.

    Yasukawa, Shinsuke; Okuno, Hirotsugu; Ishii, Kazuo; Yagi, Tetsuya


    We developed a vision sensor system that performs a scale-invariant feature transform (SIFT) in real time. To apply the SIFT algorithm efficiently, we focus on a two-fold process performed by the visual system: whole-image parallel filtering and frequency-band parallel processing. The vision sensor system comprises an active pixel sensor, a metal-oxide semiconductor (MOS)-based resistive network, a field-programmable gate array (FPGA), and a digital computer. We employed the MOS-based resistive network for instantaneous spatial filtering and a configurable filter size. The FPGA is used to pipeline process the frequency-band signals. The proposed system was evaluated by tracking the feature points detected on an object in a video. PMID:27268260

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

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


    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

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

    Khelifa, Dejrriri; Mimoun, Malki


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

  20. Object based change detection of Central Asian Tugai vegetation with very high spatial resolution satellite imagery

    Gärtner, Philipp; Förster, Michael; Kurban, Alishir; Kleinschmit, Birgit


    Ecological restoration of degraded riparian Tugai forests in north-western China is a key driver to combat desertification in this region. Recent restoration efforts attempt to recover the forest along with its most dominant tree species, Populus euphratica. The present research observed the response of natural vegetation using an object based change detection method on QuickBird (2005) and WorldView2 (2011) data. We applied the region growing approach to derived Normalized Difference Vegetation Index (NDVI) values in order to identify single P. euphratica trees, delineate tree crown areas and quantify crown diameter changes. Results were compared to 59 reference trees. The findings confirmed a positive tree crown growth and suggest a crown diameter increase of 1.14 m, on average. On a single tree basis, tree crown diameters of larger crowns were generally underestimated. Small crowns were slightly underestimated in QuickBird and overestimated in Worldview2 images. The results of the automated tree crown delineation show a moderate relation to field reference data with R20052: 0.36 and R20112: 0.48. The object based image analysis (OBIA) method proved to be applicable in sparse riparian Tugai forests and showed great suitability to evaluate ecological restoration efforts in an endangered ecosystem.