WorldWideScience

Sample records for ladar based object

  1. Microdoppler ladar systems

    Science.gov (United States)

    Otaguro, Wil; Hayes, Cecil

    2000-10-01

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

  2. Photographic-based target models for LADAR applications

    Science.gov (United States)

    Jack, James T.; Delashmit, Walter H.

    2009-05-01

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

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

    CERN Document Server

    Mateo, Ana Baselga

    2015-01-01

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

  4. Spectral ladar: towards active 3D multispectral imaging

    Science.gov (United States)

    Powers, Michael A.; Davis, Christopher C.

    2010-04-01

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

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

    Science.gov (United States)

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

    2014-03-20

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

  6. Anomaly detection in clutter using spectrally enhanced LADAR

    Science.gov (United States)

    Chhabra, Puneet S.; Wallace, Andrew M.; Hopgood, James R.

    2015-05-01

    Discrete return (DR) Laser Detection and Ranging (Ladar) systems provide a series of echoes that reflect from objects in a scene. These can be first, last or multi-echo returns. In contrast, Full-Waveform (FW)-Ladar systems measure the intensity of light reflected from objects continuously over a period of time. In a camflouaged 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 signature that does not conform to a prior expectation, represented using a learnt subspace (dictionary) and set of coefficients that capture co-occurring local-patterns using an overlapping temporal window. A modified optimization scheme is proposed for subspace learning based on stochastic approximations. The objective function is augmented with a discriminative term that represents the subspace's separability properties and supports anomaly characterisation. The algorithm detects several man-made objects and anomalous spectra hidden in a dense clutter of vegetation and also allows tree species classification.

  7. EO Scanned Micro-LADAR Project

    Data.gov (United States)

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

  8. EO Scanned Micro-LADAR Project

    Data.gov (United States)

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

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

    Science.gov (United States)

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

    2014-06-01

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

  10. Miniature Ground Mapping LADAR Project

    Data.gov (United States)

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

  11. Nonscanned ladar imaging and applications

    Science.gov (United States)

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

    1993-10-01

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

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

    Science.gov (United States)

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

    2015-05-01

    The Space Dynamics Laboratory (SDL), working with Naval Research Laboratory (NRL) and industry leaders Advanced Scientific Concepts (ASC) and Hood Technology Corporation, has developed a small SWAP (size, weight, and power) 3D imaging flash ladar (LAser Detection And Ranging) sensor system concept design for small tactical unmanned air systems (STUAS). The design utilizes an ASC 3D flash ladar camera and laser in a Hood Technology gyro-stabilized gimbal system. The design is an autonomous, intelligent, geo-aware sensor system that supplies real-time 3D terrain and target images. Flash ladar and visible camera data are processed at the sensor using a custom digitizer/frame grabber with compression. Mounted in the aft housing are power, controls, processing computers, and GPS/INS. The onboard processor controls pointing and handles image data, detection algorithms and queuing. The small SWAP 3D imaging flash ladar sensor system generates georeferenced terrain and target images with a low probability of false return and <10 cm range accuracy through foliage in real-time. The 3D imaging flash ladar is designed for a STUAS with a complete system SWAP estimate of <9 kg, <0.2 m3 and <350 W power. The system is modeled using LadarSIM, a MATLAB® and Simulink®- based ladar system simulator designed and developed by the Center for Advanced Imaging Ladar (CAIL) at Utah State University. We will present the concept design and modeled performance predictions.

  13. Probabilistic analysis of linear mode vs. Geiger mode APD FPAs for advanced LADAR enabled interceptors

    Science.gov (United States)

    Williams, George M.; Huntington, Andrew S.

    2006-05-01

    To meet evolving ballistic missile threats, advanced seekers will include a multi-modal imaging capability in which a passive single- or multi-band infrared focal plane array (FPA) shares a common aperture with an active laser radar (LADAR) receiver - likely, a photon-counting LADAR receiver that can resolve photon times of arrival with sub-nanosecond resolution. The overall success of such a system will depend upon its photon detection efficiency and sensitivity to upset by spurious detection events. In the past, to perform photon counting functions, it has generally been necessary to operate near infrared (NIR) avalanche photodiode (APD) FPAs in Geiger Mode. Linear Mode APDs could not provide enough proportional gain with sufficiently low noise to make the photocurrent from a single photon detectible using existing amplifier technology. However, recent improvements in APDs, sub-micron CMOS technology, and concomitant amplifier designs, have made Linear Mode single-photon-counting APDs (SPADs) possible. We analyze the potential benefits of a LADAR receiver based on Linear Mode SPADs, which include: 1) the ability to obtain range information from more than one object in a pixel's instantaneous-field-of-view (IFOV), 2) a lower false alarm rate, 3) the ability to detect targets behind debris, 4) an advantage in the endgame, when stronger reflected signals allow dark current rejection via thresholding, and 5) the ability to record signal intensity, which can be used to increase kill efficiency. As expected, multiple laser shots of the same scene improves the target detection probability.

  14. Extracting and analyzing micro-Doppler from ladar signatures

    Science.gov (United States)

    Tahmoush, Dave

    2015-05-01

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

  15. Synthetic aperture ladar concept for infrastructure monitoring

    Science.gov (United States)

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

    2014-10-01

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

  16. Eyesafe imaging LADAR/infrared seeker technologies

    Science.gov (United States)

    Barenz, J.; Baumann, R.; Tholl, H. D.

    2005-05-01

    A compact dual mode seeker is under development at Diehl BGT Defence (DBD) addressing autonomous guidance, target detection and classification/identification for extended air defence (EAD) and ballistic missile defence (BMD). The dual mode sensor consists of an imaging infrared sensor and an imaging LADAR sensor both in snapshot mode. This paper presents the concept of the dual mode sensor and shows the current development status. Critical components such as a compact laser source, fiber-array for image plane sampling, and wavelength selective infrared beam splitter are presented in detail. Single Spot and 3D-LADAR-measurements were performed with a seeker lab-setup to demonstrate the system.

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

    CERN Document Server

    Mateo, Ana Baselga

    2015-01-01

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

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

    Data.gov (United States)

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

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

    Data.gov (United States)

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

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

    Science.gov (United States)

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

    2015-06-01

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

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

    Science.gov (United States)

    Neilsen, Kevin D.; Budge, Scott E.

    2013-11-01

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

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

    Science.gov (United States)

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

    2015-08-01

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

  3. 3D-LZ helicopter ladar imaging system

    Science.gov (United States)

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

    2010-04-01

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

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

    Science.gov (United States)

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

    2012-08-01

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

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

    Scientific Electronic Library Online (English)

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

    2011-06-01

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

  6. View-based 3-D object retrieval

    CERN Document Server

    Gao, Yue

    2014-01-01

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

  7. Object-based attention influences saccade latency.

    Science.gov (United States)

    Senturk, Gozde; Greenberg, Adam; Liu, Taosheng

    2015-09-01

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

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

    OpenAIRE

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

    2011-01-01

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

  9. Object-based sound source modeling

    OpenAIRE

    Tolonen, Tero

    2000-01-01

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

  10. Spatio-activity based object detection

    CERN Document Server

    Springett, Jarrad

    2008-01-01

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

  11. Object Based Middleware for Grid Computing

    Directory of Open Access Journals (Sweden)

    S. Muruganantham

    2010-01-01

    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.

  12. Object-based coding through multigrid representation

    Science.gov (United States)

    Marichal, Xavier; De Vleeschouwer, Christophe; Delmot, Thierry; Macq, Benoit M. M.

    1996-03-01

    This paper presents a very low bit-rate coding algorithm based on image split in order to represent it through an adaptive multigrid supported by a binary tree structure. Independently of its tree representation, the picture is segmented via a watershed procedure and several criteria are combined to automatically extract interesting areas of the image. This object information is not transmitted but used to reduce picture complexity, and therefore the bit-rate, while keeping a good subjective quality. This is achieved by a merge procedure which homogenizes values of the tree subblocks belonging to a same non-interesting object. This treatment affects both intra- and inter-images. For intra-images, the resulting tree structure is entropy coded while its leaves are encoded through a DPCM procedure followed by a multi- huffman coder. For inter-images, a motion field is adaptated by an adaptative block matching algorithm which is a kind of BMA for which blocksize is chosen in order to reach a sufficient level of confidence. Residues, essential to correct motion compensation artifacts, are sent through local intra-trees or, if the bit-rate allows it, through DCT blocks, allowing to reach an arbitrary level of quality. During the reconstruction step, an object oriented approach combined with the use of overlapping functions allows to reduce block artifacts while keeping sharp edges.

  13. ROIC for gated 3D imaging LADAR receiver

    Science.gov (United States)

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

    2013-09-01

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

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

    International Nuclear Information System (INIS)

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

  15. OBJECT TRACKING INITIALIZATION BASED ON AUTOMATIC MOVING OBJECT DETECTION: A SURVEY PAPER

    Directory of Open Access Journals (Sweden)

    Andrea Noreen D'silva

    2014-06-01

    Full Text Available In this paper we present new methods for object tracking initialization using automated moving object detection based on background subtraction. The new methods are integrated into the realtime object tracking system we previously proposed. Our proposed new background model updating method and adaptive thresholding are used to produce a foreground object mask for object tracking initialization. Traditional background subtraction method detects moving objects by subtracting the background model from the current image.

  16. Invariant object recognition based on extended fragments

    OpenAIRE

    Bart, Evgeniy; Hegdé, Jay

    2012-01-01

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

  17. Invariant Object Recognition Based on Extended Fragments

    OpenAIRE

    EvgeniyBart

    2012-01-01

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

  18. MATHEMATICAL BASED APPROACH FOR OBJECT CLASSIFICATION

    OpenAIRE

    Prakash, K; Dr. B. Nagarajan

    2014-01-01

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

  19. Monitoring objects orbiting earth using satellite-based telescopes

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-06-30

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

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

    DEFF Research Database (Denmark)

    Kingo, Osman Skjold; Krøjgaard, Peter

    2011-01-01

    Five experiments investigated the importance of shape and object manipulation when 12-month-olds were given the task of individuating objects representing exemplars of kinds in an event-mapping design. In Experiments 1 and 2, results of the study from Xu, Carey, and Quint (2004, Experiment 4) were partially replicated, showing that infants were able to individuate two natural-looking exemplars from different categories, but not two exemplars from the same category. In Experiment 3, infants faile...

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

    Science.gov (United States)

    Roque, Nelson; Boot, Walter R

    2015-09-01

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

  2. Fusion of video and radar comparison to 3D ladar for activity recognition

    Science.gov (United States)

    Tahmoush, Dave

    2015-05-01

    Determining hostile or suspicious activities within a civilian population can be challenging. Incorporating automated techniques for classifying activities can significantly reduce the operator workload. Utilizing 3D sensor modalities such as ladar can provide a strong capability for recognizing dismount activities. However, fusing multiple modalities, such as video in conjunction with radar, could provide a cheaper alternative for wide-area coverage. This work utilizes a single point-of-view 3D imaging system to approximate ladar captured data. Activity classification is done on the full 3D extracted motion, achieving 86% correct classification. Simulation of video-only activity classification is done by reducing the radial motion resolution and increasing the radial velocity error, and shows good performance on a significant number of activities. Simulation of radar-only classification is done by reducing the angular resolution and increasing the angular velocity error and shows good performance on a roughly orthogonal set of activities. Fusing the simulated radar and video data together at different fusion levels and comparing to the 3D ladar system gives an estimate of the loss in classification capability when using the less expensive fusion system.

  3. THE ADMINISTRATOR OBJECT PATTERN FOR ROLE-BASED ACCESS CONTROL

    OpenAIRE

    S. R. KODITUWAKKU

    2010-01-01

    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.

  4. Content-Based Object Movie Retrieval and Relevance Feedbacks

    OpenAIRE

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

    2007-01-01

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

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

    Science.gov (United States)

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

    2014-10-14

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

  6. Fast Moving Object Segmentation Based On Active Contours

    OpenAIRE

    Huimin Zhang; Zhiyong Duan; Zhongjie Zhu; Yuer Wang

    2012-01-01

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

  7. Agents as objects with knowledge base state

    CERN Document Server

    Skarmeas, Nikolaos

    1999-01-01

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

  8. Graph-Based Approach for 3D Object Duplicate Detection

    OpenAIRE

    Vajda, Peter; Dufaux, Frederic; Ha M., Thien; Ebrahimi, touradj

    2009-01-01

    In this paper, we consider the challenging problem of object duplicate detection and localization. Several applications require efficient object duplicate detection methods, such as automatic video and image tagging, video surveillance, and high level image or video search. In this paper, a novel graph-based approach for 3D object duplicate detection in still images is proposed. A graph model is used to represent the spatial information of the object in order to avoid making an explicit 3D ob...

  9. Application of Moving Object Tracking Based on Kalman Filter Algorithm

    OpenAIRE

    Xiao Zhansheng

    2013-01-01

    The moving object module matching method base on Kalman Filter (KF) algorithm which proposed to solve the problem of traditional moving object matching method’s, that fault of huge searching range and weakness in real-time processing. Relative to traditional module matching method, the method mentioned here effectively improved the speed and the accuracy of object tracking. This method has tripled the object matching speed of traditional tracking method.

  10. Fast Moving Object Segmentation Based On Active Contours

    Directory of Open Access Journals (Sweden)

    Huimin Zhang

    2012-04-01

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

  11. Perceptual Object Extraction Based on Saliency and Clustering

    Directory of Open Access Journals (Sweden)

    Qiaorong Zhang

    2010-08-01

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

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

    Science.gov (United States)

    Carlotto, Mark J.

    2015-05-01

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

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

    OpenAIRE

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

    2012-01-01

    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...

  14. Stereovision-Based Object Segmentation for Automotive Applications

    OpenAIRE

    Fu Shan; Thompson Chris; Huang Yingping

    2005-01-01

    Obstacle detection and classification in a complex urban area are highly demanding, but desirable for pedestrian protection, stop & go, and enhanced parking aids. The most difficult task for the system is to segment objects from varied and complicated background. In this paper, a novel position-based object segmentation method has been proposed to solve this problem. According to the method proposed, object segmentation is performed in two steps: in depth map ( - plane) and in layered i...

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

    Science.gov (United States)

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

    2013-01-01

    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 advantage of proto-objects as units of analysis. PMID:24281243

  16. Content-Based Object Movie Retrieval and Relevance Feedbacks

    Directory of Open Access Journals (Sweden)

    Lee Greg C

    2007-01-01

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

  17. A Method of Object-based De-duplication

    Directory of Open Access Journals (Sweden)

    Fang Yan

    2011-12-01

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

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

    CERN Document Server

    Lepetit, Vincent

    2014-01-01

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

  19. Stereovision-Based Object Segmentation for Automotive Applications

    Directory of Open Access Journals (Sweden)

    Fu Shan

    2005-01-01

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

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    F.Regragui

    2010-01-01

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

  2. Object Tracking Based on Local Sparse Appearance Model

    Directory of Open Access Journals (Sweden)

    Jihong Deng

    2015-08-01

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

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

    Science.gov (United States)

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

    2008-05-20

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

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

    OpenAIRE

    Xiaofei Xu; Jindan Feng; Dechen Zhan; Lanshun Nie

    2010-01-01

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

  5. A primitive-based 3D object recognition system

    Science.gov (United States)

    Dhawan, Atam P.

    1988-01-01

    An intermediate-level knowledge-based system for decomposing segmented data into three-dimensional primitives was developed to create an approximate three-dimensional description of the real world scene from a single two-dimensional perspective view. A knowledge-based approach was also developed for high-level primitive-based matching of three-dimensional objects. Both the intermediate-level decomposition and the high-level interpretation are based on the structural and relational matching; moreover, they are implemented in a frame-based environment.

  6. Video Based Moving Object Tracking by Particle Filter

    Directory of Open Access Journals (Sweden)

    Md. Zahidul Islam

    2009-03-01

    Full Text Available Usually, the video based object tracking deal with non-stationary image stream that changes over time. Robust and Real time moving object tracking is a problematic issue in computer vision research area. Most of the existing algorithms are able to track only inpredefined and well controlled environment. Some cases, they 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.

  7. Novel Scheme for Object-based Embedded Image Coding

    Directory of Open Access Journals (Sweden)

    Yuer Wang

    2012-11-01

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

  8. Maritime target identification in flash-ladar imagery

    Science.gov (United States)

    Armbruster, Walter; Hammer, Marcus

    2012-05-01

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

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

    CERN Document Server

    LaMont, Colin H

    2015-01-01

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

  10. A View-Based Approach to Three Dimensional Object Recognition

    Directory of Open Access Journals (Sweden)

    Xu Sheng

    2009-01-01

    Full Text Available To improve the performance of three-dimensional object recognition systems, we propose a view-based method in this study. First we extract wavelet moments, texture features and color moments from the 2D view images of 3D objects. Wavelet moments have the multi-resolution properties in addition to the invariant properties under translation, scaling and rotation. Texture features can distinguish objects which have similar shapes and different appearance. Color moments are robust and insensitive to the size and pose of objects. Support Vector Machine (SVM is chosen as classifier. Then the feature subset selection and SVM parameters optimization are accomplished automatically and simultaneously using Genetic Algorithm (GA in an evolutionary way. We assessed our method based on the original and noise corrupted 3D object dataset COIL-100. One hundred percent correct rate of recognition was obtained when the number of presented training views for each object was 36 (10 degrees interval and 18 (20 degrees interval. When the number of training views was reduced, the correct rate of recognition was also satisfied.

  11. Inverse treatment planning using volume-based objective functions

    International Nuclear Information System (INIS)

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

  12. Multi-objective Optimization Problem Based on Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Li Heng

    2013-01-01

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

  13. Ground-based optical observation system for LEO objects

    Science.gov (United States)

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

    2015-08-01

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

  14. Improved Brain Tumor Detection Using Object Based Segmentation

    OpenAIRE

    Harneet Kaur; Sukhwinder Kaur

    2014-01-01

    This paper has focused on the brain tumor detection techniques. The brain tumor detection is a very important vision application in the medical field. This work has firstly presented a review on various well known techniques for automatic segmentation of heterogeneous image data that takes a step toward bridging the gap between bottom-up affinity-based segmentation methods and top-down generative model based approaches. The main objective of the work is to explore various techniques to detect...

  15. Context-based classification of objects in cartographic data

    OpenAIRE

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

    2002-01-01

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

  16. Archive Design Based on Planets Inspired Logical Object Model

    DEFF Research Database (Denmark)

    Zierau, Eld; Johansen, Anders

    2008-01-01

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

  17. Vision-based autonomous grasping of unknown piled objects

    International Nuclear Information System (INIS)

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

  18. Phase detection experiment for the down-looking synthetic aperture imaging ladar with electro-optic modulation

    Science.gov (United States)

    Lu, Zhiyong; Sun, Jianfeng; Zhi, Ya'nan; Zhang, Ning; Liu, Liren

    2014-09-01

    The down-looking synthetic aperture imaging ladar (SAIL) with electro-optic modulation was proposed. The measurement uses electrically controlled scanner to produce beams with spatial parabolic phase difference, which consists of electro-optic crystal and cylindrical lens. Due to the high modulation rate without mechanical scanning, this technique has a great potential for applications in extensive synthetic aperture imaging ladar fields. The phase mapping of electrically controlled scanner under the different applied voltage is achieved and measured by the polarized digital holographic interferometry. The phase mappings of the scanner in the down-looking SAIL with the o-polarized light and e-polarized light are obtained. The linear phase distribution and the parabolic phase distribution are observed after applying the external electric field. The corresponding analyses and discussions are proposed to explain the phenomena.

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

    Science.gov (United States)

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

    1996-10-01

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

  20. Algebraic Analysis of Object-Based Key Assignment Schemes

    Directory of Open Access Journals (Sweden)

    Khair Eddin Sabri

    2014-08-01

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

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

    Science.gov (United States)

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

    2009-02-01

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

  2. Multi Objective AODV Based On a Realistic Mobility Model

    Directory of Open Access Journals (Sweden)

    Hamideh Babaei

    2010-05-01

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

  3. Agent-based Algorithm for Spatial Distribution of Objects

    KAUST Repository

    Collier, Nathan

    2012-06-02

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

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

    Directory of Open Access Journals (Sweden)

    Bin Xu

    2013-12-01

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

  5. Nanoscale synthesis and characterization of graphene-based objects

    Directory of Open Access Journals (Sweden)

    Daisuke Fujita

    2011-01-01

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

  6. 3D object recognition based on local descriptors

    Science.gov (United States)

    Jakab, Marek; Benesova, Wanda; Racev, Marek

    2015-01-01

    In this paper, we propose an enhanced method of 3D object description and recognition based on local descriptors using RGB image and depth information (D) acquired by Kinect sensor. Our main contribution is focused on an extension of the SIFT feature vector by the 3D information derived from the depth map (SIFT-D). We also propose a novel local depth descriptor (DD) that includes a 3D description of the key point neighborhood. Thus defined the 3D descriptor can then enter the decision-making process. Two different approaches have been proposed, tested and evaluated in this paper. First approach deals with the object recognition system using the original SIFT descriptor in combination with our novel proposed 3D descriptor, where the proposed 3D descriptor is responsible for the pre-selection of the objects. Second approach demonstrates the object recognition using an extension of the SIFT feature vector by the local depth description. In this paper, we present the results of two experiments for the evaluation of the proposed depth descriptors. The results show an improvement in accuracy of the recognition system that includes the 3D local description compared with the same system without the 3D local description. Our experimental system of object recognition is working near real-time.

  7. Improved Brain Tumor Detection Using Object Based Segmentation

    Directory of Open Access Journals (Sweden)

    Harneet Kaur

    2014-07-01

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

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

    Science.gov (United States)

    Yao, Jie; Cao, Qiang; Li, Huaiyang

    2008-12-01

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

  9. A Learning Object Approach To Evidence based learning

    Directory of Open Access Journals (Sweden)

    Zabin Visram

    2005-06-01

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

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

    Science.gov (United States)

    Campbell, Jonathan W.

    2002-09-01

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

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

    Science.gov (United States)

    Easley, Glenn R.; Colonna, Flavia

    2004-04-01

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

  12. Proxy caching based on object location considering semantic usage

    OpenAIRE

    Rochat, Philippe; Thompson, Stuart

    1999-01-01

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

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

    OpenAIRE

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

    2014-01-01

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

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

    Science.gov (United States)

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

    2013-03-01

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

  15. Robust object recognition based on HMAX model architecture

    Science.gov (United States)

    Chang, Yongxin; Xu, Zhiyong; Zhang, Jing; Fu, Chengyu; Gao, Chunming

    2012-11-01

    In this paper, we describe in detail the hierarchical model and X (HMAX) model of Riesenhuber and Poggio. The HMAX model, accounting for visual processing and making plausible predictions founded on prior information, is built up by alternating simple cell layers and complex cell layers. We generalize the principal facts about the ventral visual stream and argue hierarchy of brain areas to mediate object recognition in visual cortex. Then, in order to obtain the futures of object, we implement Gabor filters and alternately apply template matching and maximum operations for input image. Finally according to the target feature saliency and position information, we introduce a novel algorithm for object recognition in clutter based on the HMAX architecture. The improved model is competitive with current recognizing algorithms on standard database, such as the UICI car and the Caltech101 database including a large number of diverse categories. We also prove that the approach combining spatial position information of parts with the feature fusing can further promotes the recognition rate. The experimental results demonstrate that the proposed approach can recognize objects more precisely and the performance outperforms the standard model.

  16. Multiview-Based Cooperative Tracking of Multiple Human Objects

    Directory of Open Access Journals (Sweden)

    Lien Kuo-Chin

    2008-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Rui Cao

    2015-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Eirik Borgen

    1990-01-01

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

  19. An object-based methodology for knowledge representation

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-11-01

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

  20. Adaptive color correction based on object color classification

    Science.gov (United States)

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

    1998-09-01

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

  1. Cloud Aggregation and Bursting for Object Based Sharable Environment

    Directory of Open Access Journals (Sweden)

    Mr. Pradeep Kumar Tripathi

    2011-09-01

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

  2. Interactive object modelling based on piecewise planar surface patches.

    Science.gov (United States)

    Prankl, Johann; Zillich, Michael; Vincze, Markus

    2013-06-01

    Detecting elements such as planes in 3D is essential to describe objects for applications such as robotics and augmented reality. While plane estimation is well studied, table-top scenes exhibit a large number of planes and methods often lock onto a dominant plane or do not estimate 3D object structure but only homographies of individual planes. In this paper we introduce MDL to the problem of incrementally detecting multiple planar patches in a scene using tracked interest points in image sequences. Planar patches are reconstructed and stored in a keyframe-based graph structure. In case different motions occur, separate object hypotheses are modelled from currently visible patches and patches seen in previous frames. We evaluate our approach on a standard data set published by the Visual Geometry Group at the University of Oxford [24] and on our own data set containing table-top scenes. Results indicate that our approach significantly improves over the state-of-the-art algorithms. PMID:24511219

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

    Directory of Open Access Journals (Sweden)

    Runhe Huang

    2008-11-01

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

  4. 3D imaging LADAR with linear array devices: laser, detector and ROIC

    Science.gov (United States)

    Kameyama, Shumpei; Imaki, Masaharu; Tamagawa, Yasuhisa; Akino, Yosuke; Hirai, Akihito; Ishimura, Eitaro; Hirano, Yoshihito

    2009-07-01

    This paper introduces the recent development of 3D imaging LADAR (LAser Detection And Ranging) in Mitsubishi Electric Corporation. The system consists of in-house-made key devices which are linear array: the laser, the detector and the ROIC (Read-Out Integrated Circuit). The laser transmitter is the high power and compact planar waveguide array laser at the wavelength of 1.5 micron. The detector array consists of the low excess noise Avalanche Photo Diode (APD) using the InAlAs multiplication layer. The analog ROIC array, which is fabricated in the SiGe- BiCMOS process, includes the Trans-Impedance Amplifiers (TIA), the peak intensity detectors, the Time-Of-Flight (TOF) detectors, and the multiplexers for read-out. This device has the feature in its detection ability for the small signal by optimizing the peak intensity detection circuit. By combining these devices with the one dimensional fast scanner, the real-time 3D range image can be obtained. After the explanations about the key devices, some 3D imaging results are demonstrated using the single element key devices. The imaging using the developed array devices is planned in the near future.

  5. Object-based landslide detection in different geographic regions

    Science.gov (United States)

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

    2015-04-01

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

  6. Resultados a curto prazo de ceratotomia lamelar pediculada (LASIK) para correção de hipermetropia com o sistema Ladar Vision de excimer laser / Short-term results of hyperopic laser in situ keratomileusis (LASIK) with the Ladar Vision excimer laser system

    Scientific Electronic Library Online (English)

    Larissa Madeira, Nunes; Cláudia Maria, Francesconi; Mauro, Campos; Paulo, Schor.

    2004-02-01

    Full Text Available OBJETIVO: Avaliar a eficácia e a segurança do LASIK (ceratotomia lamelar pediculada) hipermetrópico utilizando-se o sistema Ladar Vision de excimer laser. MÉTODOS: Foram analisados, retrospectivamente, 28 olhos de 17 pacientes com hipermetropia de +1,00 a +3,00 D (grupo 1) e 29 olhos de 18 pacientes [...] com hipermetropia de + 3,25 a + 6,00 D (grupo 2), submetidos à cirurgia de LASIK, com o Sistema Ladar Vision de excimer laser. Acuidade visual sem correção, melhor acuidade visual corrigida e refração sob cicloplegia foram avaliadas em um, três e seis meses de pós-operatório. RESULTADOS: No grupo 1, o equivalente esférico médio pré-operatório, sob cicloplegia, era de + 2,14 ± 0,64 D, passando para + 0,44 ± 0,38 D no sexto mês de pós-operatório. No grupo 2, o equivalente esférico médio pré-operatório era de +4,26 ± 0,75 D, diminuindo para +1,14 ± 0,63 D no sexto mês de pós-operatório. 3,4% dos olhos do grupo 2 perderam três linhas de visão no primeiro mês de pós-operatório. No grupo 1, não houve perda de duas ou mais linhas de visão. CONCLUSÕES: O LASIK hipermetrópico com o sistema Ladar Vision mostrou-se procedimento eficaz e seguro. Pacientes do grupo 2 parecem estar sob maior risco de perda de linhas de melhor acuidade visual corrigida no pós-operatório. Abstract in english PURPOSE: To analyze the efficacy and safety of hyperopic laser in situ keratomileusis using the Ladar Vision excimer laser system. METHODS: Twenty-eight eyes of 17 patients with hyperopia from +1.00 to +3.00 D (group 1), and 29 eyes of 18 patients with hyperopia from +3.25 to +6.00 D (group 2) that [...] had LASIK for hyperopia with the Ladar Vision, were retrospectively analyzed. Uncorrected visual acuity, best spectacle-corrected visual acuity and cycloplegic refraction were evaluated 1 , 3 and 6 months after surgery. RESULTS: In group 1, the mean preoperative cycloplegic spherical equivalent (SE) was +2.14 ± 0.64 D and 6-month postoperative SE was +0.44 ± 0.38 D. In group 2, the mean preoperative SE was +4.26 ± 0.75 D and the 6-month postoperative SE was +1.14 ± 0.63 D. 3.4% of the eyes in group 2 and none of the eyes in group 1 lost 2 or more lines of best spectacle-corrected visual acuity in the first postoperative month. CONCLUSIONS: LASIK with the Ladar Vision excimer laser system is an effective and safe procedure to correct hyperopia. Patients in group 2 appear to be at greater risk for loss of lines of best spectacle-corrected visual acuity.

  7. Objective Mixed and Manually Controlled Data Base OMG

    Science.gov (United States)

    Kratzsch, T.; Rohn, M.

    2009-09-01

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

  8. An object-oriented model-base system frame

    Science.gov (United States)

    Zhang, Longqi; Liu, Yalan; Zhang, Zhenlong; Yan, Shouyong

    2007-06-01

    The present object-oriented model representing way have not fully addressed the issues of model inheritance for general users, increase the difficulty of maintenance and model composition, and make the interrelation among models more complex. This paper aims to make improvement in model presenting way and put forward a new model-base system frame, which can implement model inheritance for general users and its data and method are thought separately of as descriptive model (DM) and operative model (OM). The definition of operative model and descriptive ones, model representing way, correlation and how to ensure their consistency and inter-dependency were discussed in detail. Based on the frame, our group developed STA-MMS which can be incorporated into other decision support system (DSS) to manage models and to help users to build new models by reusing existing model resources in the system without modifying code. The architecture of STA-MMS system and its essential functions are defined. Procedures for model generalization, representation and composition are developed according to object-oriented concepts and methods. Finally, we examine how STA-MMS and its associated procedures and techniques are implemented in a prototype StaGIS to facilitate the construction, retrieval and execution of analytical models in the statistic analyzing process.

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

    Directory of Open Access Journals (Sweden)

    Rong Chai

    2014-04-01

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

  10. RFID and IP Based Object Identification in Ubiquitous Networking

    OpenAIRE

    Nisha Vaghela; Parikshit Mahalle

    2012-01-01

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

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

    Science.gov (United States)

    Belu, N.; Ionescu, L. M.; Misztal, A.; Maz?re, A.

    2015-11-01

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

  12. Noise Based Detection and Segmentation of Nebulous Objects

    CERN Document Server

    Akhlaghi, Mohammad

    2015-01-01

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

  13. Object-based classification of semi-arid wetlands

    Science.gov (United States)

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

    2011-01-01

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

  14. Object Recognition Algorithm Utilizing Graph Cuts Based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Zhaofeng Li

    2014-02-01

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

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

    DEFF Research Database (Denmark)

    Schultz, Ulrik Pagh

    2001-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-04-28

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

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

    Science.gov (United States)

    Holzinger, Andreas; Kleinberger, Thomas; Muller, Paul

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

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

    Science.gov (United States)

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

    2009-01-01

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

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

    Science.gov (United States)

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

    2015-06-01

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

  20. 3D model-based still image object categorization

    OpenAIRE

    Petre, Raluca Diana; Zaharia, Titus

    2011-01-01

    This paper proposes a novel recognition scheme algorithm for semantic labeling of 2D object present in still images. The principle consists of matching unknown 2D objects with categorized 3D models in order to infer the semantics of the 3D object to the image. We tested our new recognition framework by using the MPEG-7 and Princeton 3D model databases in order to label unknown images randomly selected from the web. Results obtained show promising performances, with recognition rate up to 84%,...

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

    Directory of Open Access Journals (Sweden)

    A. Bentellis

    2009-01-01

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

  2. Segmentation-based multi-class semantic object detection

    OpenAIRE

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

    2011-01-01

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

  3. Vision-based grasp tracking for planar objects

    OpenAIRE

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

    2008-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1990-11-01

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

  5. Drifting Recovery Base Concept for GEO Derelict Object Capture

    Science.gov (United States)

    Bacon, John B.

    2009-01-01

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

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

    DEFF Research Database (Denmark)

    Wang, Qi; Zhang, Chunyu

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Zhiyu Zhou

    2014-01-01

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

  8. Aircraft Simulator Designing based on Object Oriented Methodologies

    Directory of Open Access Journals (Sweden)

    Rahul Kosarwal

    2012-03-01

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

  9. Object-Based Epistemology at a Creationist Museum

    Science.gov (United States)

    Wendel, Paul J.

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    D.Vikram

    2015-03-01

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

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

    Science.gov (United States)

    WANG, Hong-bin; Liu, Yu-hua

    2008-01-01

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

  12. Effective RFID-based Object Tracking for Manufacturing

    OpenAIRE

    Brusey, James; McFarlane, Duncan C

    2009-01-01

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

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

    OpenAIRE

    Lerch, Alexander

    2008-01-01

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

  14. Application of Object-Based Industrial Controls for Cryogenics

    CERN Document Server

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

    2002-01-01

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

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

    DEFF Research Database (Denmark)

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

    2014-01-01

    The concerns of sustainability and climate change have posed a significant growth of renewable energy associated with smart grid technologies. Various uncertainties are the major problems need to be handled by transmission system operator (TSO) planning. This paper mainly focuses on three uncertain factors, i.e. load growth, generation capacity and line faults, and aims to enhance the transmission system via the multi-objective TSO planning (MOTP) approach. The proposed MOTP approach optimizes t...

  16. Real-time Object Detection Based on ARM9

    Directory of Open Access Journals (Sweden)

    M.Vijay babu

    2013-09-01

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

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

    OpenAIRE

    Slavik, Pavel; Cmolik, Ladislav; Mikovec, Zdenek

    2005-01-01

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

  18. Sustainable System Management with Fisher Information based Objectives

    Science.gov (United States)

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

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

    Directory of Open Access Journals (Sweden)

    Ranjith Kumar Goud

    2014-10-01

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

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

    OpenAIRE

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

    2013-01-01

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

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

    Science.gov (United States)

    Hölbling, Daniel; Friedl, Barbara; Eisank, Clemens

    2014-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Marian Pompiliu CRISTESCU

    2006-01-01

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

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

    OpenAIRE

    Eirik Borgen; Henning Neerland; Strandhagen, Jan O.

    1990-01-01

    This paper describes SIMMEK, a computer-based tool for performing analysis of manufacturing systems, developed at the Production Engineering Laboratory, NTH-SINTEF. Its main use will be in analysis of job shop type of manufacturing. But certain facilities make it suitable for FMS as well as a production line manufacturing. This type of simulation is very useful in analysis of any types of changes that occur in a manufacturing system. These changes may be investments in new machines or equipme...

  4. Model-Based Testing of Object-Oriented Systems

    OpenAIRE

    Rumpe, Bernhard

    2014-01-01

    This paper discusses a model-based approach to testing as a vital part of software development. It argues that an approach using models as central development artifact needs to be added to the portfolio of software engineering techniques, to further increase efficiency and flexibility of the development as well as quality and reusability of results. Then test case modeling is examined in depth and related to an evolutionary approach to model transformation. A number of test ...

  5. Tracking object's type changes with fuzzy based fusion rule

    OpenAIRE

    Tchamova, Albena; Dezert, Jean; Florentin SMARANDACHE

    2009-01-01

    In this paper the behavior of three combinational rules for temporal/sequential attribute data fusion for target type estimation are analyzed. The comparative analysis is based on: Dempster's fusion rule proposed in Dempster-Shafer Theory; Proportional Conflict Redistribution rule no. 5 (PCR5), proposed in Dezert-Smarandache Theory and one alternative class fusion rule, connecting the combination rules for information fusion with particular fuzzy operators, focusing on the t...

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

    OpenAIRE

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

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Liang-Chia Chen

    2013-07-01

    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. From neural-based object recognition toward microelectronic eyes

    Science.gov (United States)

    Sheu, Bing J.; Bang, Sa Hyun

    1994-01-01

    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.

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

    Directory of Open Access Journals (Sweden)

    Aneissha Chebolu

    2013-05-01

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

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

    CERN Document Server

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

    2015-01-01

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

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

    International Nuclear Information System (INIS)

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

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

    CERN Document Server

    Koenig, Xavier; Padgett, Deborah; DeFelippis, Daniel

    2015-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jagdish Lal Raheja

    2010-09-01

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

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

    Directory of Open Access Journals (Sweden)

    Miguel Jesús Torres-Ruiz

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Jie Hu

    2014-09-01

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

  16. Object oriented image analysis based on multi-agent recognition system

    Science.gov (United States)

    Tabib Mahmoudi, Fatemeh; Samadzadegan, Farhad; Reinartz, Peter

    2013-04-01

    In this paper, the capabilities of multi-agent systems are used in order to solve object recognition difficulties in complex urban areas based on the characteristics of WorldView-2 satellite imagery and digital surface model (DSM). The proposed methodology has three main steps: pre-processing of dataset, object based image analysis and multi-agent object recognition. Classified regions obtained from object based image analysis are used as input datasets in the proposed multi-agent system in order to modify/improve results. In the first operational level of the proposed multi-agent system, various kinds of object recognition agents modify initial classified regions based on their spectral, textural and 3D structural knowledge. Then, in the second operational level, 2D structural knowledge and contextual relations are used by agents for reasoning and modification. Evaluation of the capabilities of the proposed object recognition methodology is performed on WorldView-2 imagery over Rio de Janeiro (Brazil) which has been collected in January 2010. According to the obtained results of the object based image analysis process, contextual relations and structural descriptors have high potential to modify general difficulties of object recognition. Using knowledge based reasoning and cooperative capabilities of agents in the proposed multi-agent system in this paper, most of the remaining difficulties are decreased and the accuracy of object based image analysis results is improved for about three percent.

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

    OpenAIRE

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

    2013-01-01

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

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

    OpenAIRE

    Kuo-Shih Tseng; Angela Chih-Wei Tang

    2009-01-01

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

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

    OpenAIRE

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

    2015-01-01

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

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

    OpenAIRE

    Yunna Wu; Zezhong Li; Lirong Liu

    2013-01-01

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

  1. Analysis of the Limits of Graph-Based Object Duplicate Detection

    OpenAIRE

    Vajda, Peter; Goldmann, Lutz; Ebrahimi, touradj

    2009-01-01

    In this paper, we consider the evaluation of graph-based object duplicate detection. Several applications require accurate and efficient object duplicate detection methods, such as automatic video and image tag propagation, video surveillance, and high level image or video search. In this paper, a graph-based approach for 3D object duplicate detection in still images is evaluated. We perform an experimental comparison of our algorithm on different parameter settings and therefore is a recomme...

  2. User-drawn sketch-based 3D object retrieval using sparse coding

    OpenAIRE

    Yoon, Sang Min; Yoon, Gang-Joon; Schreck, Tobias

    2015-01-01

    3D object retrieval from user-drawn (sketch) queries is one of the important research issues in the areas of pattern recognition and computer graphics for simulation, visualization, and Computer Aided Design. The performance of any content-based 3D object retrieval system crucially depends on the availability of effective descriptors and similarity measures for this kind of data. We present a sketch-based approach for improving 3D object retrieval effectiveness by optimizing the representatio...

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

    DEFF Research Database (Denmark)

    Mahalle, Parikshit N.; Prasad, Neeli R.

    2013-01-01

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

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

    Science.gov (United States)

    Suh, Jihyun; Abrams, Richard A

    2015-12-01

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

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

    DEFF Research Database (Denmark)

    Cao, Xin; Cong, Gao

    2010-01-01

    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 work considers the potential results of such a query as being independent when ranking them. However, a relevant result object with nearby objects that are also relevant to the query is likely to be preferable over a relevant object without relevant nearby objects. The paper proposes the concept of 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 objects; and they show that the proposed algorithms are scalable and outperform a baseline approach significantly.

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

    Directory of Open Access Journals (Sweden)

    Kuo-Shih Tseng

    2009-01-01

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

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

    Science.gov (United States)

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

    2015-06-01

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

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

    Directory of Open Access Journals (Sweden)

    J. Fernandez Galarreta

    2014-09-01

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

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

    OpenAIRE

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

    2008-01-01

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

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

    International Nuclear Information System (INIS)

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

  11. Object and image indexing based on region connection calculus and oriented matroid theory

    OpenAIRE

    Staffetti, Ernesto; Grau Saldes, Antoni; Serratosa Casanelles, Francesc; Sanfeliu Cortés, Alberto

    2005-01-01

    In this paper a novel method for indexing views of 3D objects is presented. The topological properties of the regions of views of an object or of a set of objects are used to define an index based on region connection calculus and oriented matroid theory. Both are formalisms for qualitative spatial representation and reasoning and are complementary in the sense that, whereas region connection calculus characterize connectivity of couples of connected regions of views, oriented matroids encode...

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

    OpenAIRE

    Akram Moh. Alkouz

    2006-01-01

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

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

    OpenAIRE

    Vu, Trung-Dung; Aycard, Olivier

    2009-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

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

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

    Jason Sherba; Leonhard Blesius; Jerry Davis

    2014-01-01

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

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

    Science.gov (United States)

    Banharnsakun, Anan; Tanathong, Supannee

    2014-01-01

    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

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

    Science.gov (United States)

    Price, Jeffery R.

    2006-05-02

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

  19. A Novel Abandoned Object Detection System Based on Three-Dimensional Image Information

    Directory of Open Access Journals (Sweden)

    Yiliang Zeng

    2015-03-01

    Full Text Available A new idea of an abandoned object detection system for road traffic surveillance systems based on three-dimensional image information is proposed in this paper to prevent traffic accidents. A novel Binocular Information Reconstruction and Recognition (BIRR algorithm is presented to implement the new idea. As initial detection, suspected abandoned objects are detected by the proposed static foreground region segmentation algorithm based on surveillance video from a monocular camera. After detection of suspected abandoned objects, three-dimensional (3D information of the suspected abandoned object is reconstructed by the proposed theory about 3D object information reconstruction with images from a binocular camera. To determine whether the detected object is hazardous to normal road traffic, road plane equation and height of suspected-abandoned object are calculated based on the three-dimensional information. Experimental results show that this system implements fast detection of abandoned objects and this abandoned object system can be used for road traffic monitoring and public area surveillance.

  20. A novel abandoned object detection system based on three-dimensional image information.

    Science.gov (United States)

    Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Gao, Jing; Zou, Jinlin

    2015-01-01

    A new idea of an abandoned object detection system for road traffic surveillance systems based on three-dimensional image information is proposed in this paper to prevent traffic accidents. A novel Binocular Information Reconstruction and Recognition (BIRR) algorithm is presented to implement the new idea. As initial detection, suspected abandoned objects are detected by the proposed static foreground region segmentation algorithm based on surveillance video from a monocular camera. After detection of suspected abandoned objects, three-dimensional (3D) information of the suspected abandoned object is reconstructed by the proposed theory about 3D object information reconstruction with images from a binocular camera. To determine whether the detected object is hazardous to normal road traffic, road plane equation and height of suspected-abandoned object are calculated based on the three-dimensional information. Experimental results show that this system implements fast detection of abandoned objects and this abandoned object system can be used for road traffic monitoring and public area surveillance. PMID:25806869

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

    International Nuclear Information System (INIS)

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

  2. Instructional Design Issues in Computer-Based Reading: Reinforcement and Objectives.

    Science.gov (United States)

    Blanchard, Jay S.

    1987-01-01

    This review of cognitive development research in the area of computer-based reading instruction focuses on reinforcement and instructional objectives. Differences between extrinsic and intrinsic reinforcement and motivation are discussed, types of objectives and learner characteristics are described, and implications for instructional design are…

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

    Science.gov (United States)

    Cho, Dongbin; Proctor, Robert W.

    2010-01-01

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

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

    Science.gov (United States)

    Dhawan, Atam P.

    1988-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Helen J. Chatterjee

    2010-01-01

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

  6. Two models of unawareness: comparing the object-based and the subjective-state-space approaches

    OpenAIRE

    Board, Oliver J.; Chung, Kim-Sau; Schipper, Burkhard C.

    2009-01-01

    In this paper we compare two different approaches to modeling unawareness: the object-based approach of Board and Chung (2007) and the subjective-state-space approach of Heifetz, Meier and Schipper (2006).

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

    International Nuclear Information System (INIS)

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

  8. A Novel Abandoned Object Detection System Based on Three-Dimensional Image Information

    OpenAIRE

    Zeng, Yiliang; Lan, Jinhui; Ran, Bin; Gao, Jing; Zou, Jinlin

    2015-01-01

    A new idea of an abandoned object detection system for road traffic surveillance systems based on three-dimensional image information is proposed in this paper to prevent traffic accidents. A novel Binocular Information Reconstruction and Recognition (BIRR) algorithm is presented to implement the new idea. As initial detection, suspected abandoned objects are detected by the proposed static foreground region segmentation algorithm based on surveillance video from a monocular camera. After det...

  9. Neural network based 2D/3D fusion for robotic object recognition

    OpenAIRE

    Filliat, David

    2014-01-01

    We present a neural network based fusion approach for real- time robotic object recognition which integrates 2D and 3D descriptors in a flexible way. The presented recognition architecture is coupled to a real-time segmentation step based on 3D data, since a focus of our investigations is real-world operation on a mobile robot. As recognition must operate on imperfect segmentation results, we conduct tests of recognition performance using complex everyday objects in order to quantify the over...

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

    OpenAIRE

    Wies?aw PAMU?A

    2009-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Wies?aw PAMU?A

    2009-01-01

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

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

    International Nuclear Information System (INIS)

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

  13. 3D models-based semantic labeling of 2D objects

    OpenAIRE

    Petre, Raluca Diana; Titus, Zaharia

    2011-01-01

    This paper tackles the issue of still image object categorization. The objective is to infer the semantics of 2D objects present in natural images. The principle of the proposed approach consists of exploiting categorized 3D synthetic models in order to identify unknown 2D objects, based on 2D/3D matching techniques. Notably, we use 2D/3D shape indexing methods, where 3D models are described through a set of 2D views. Experimental results carried out on both MPEG-7 and Princeton 3D mesh test ...

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

    OpenAIRE

    Signore, Oreste; Loffredo, Mario

    1993-01-01

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

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

    OpenAIRE

    Biermann, Enrico; Modica, Tony

    2008-01-01

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

  16. Object-driven block-based algorithm for the compression of stereo image pairs

    Science.gov (United States)

    Edirisinghe, Eran A.; Jiang, Jianmin; Bez, Helmut E.

    1999-10-01

    In this paper, we propose a novel object driven, block based algorithm for the compression of stereo image pairs. The algorithm effectively combines the simplicity and adaptability of the existing block based stereo image compression techniques with an edge/contour based object extraction technique to determine appropriate compression strategy for various areas of the right image. Extensive experiments carried out support that significant improvements of up to 20% in compression ratio can be achieved by the proposed algorithm, compared with the existing stereo image compression techniques. Yet the reconstructed image quality is maintained at an equivalent level in terms of PSNR values. In terms of visual quality, the right image reconstructed by the proposed algorithm does not incur any noticeable effect compared with the outputs of the best algorithms. The proposed algorithm performs object extraction and matching between the reconstructed left frame and the original right frame to identify those objects that match but are displaced by varying amounts due to binocular parallax. Different coding strategies are then applied separately to internal areas and the bounding areas for each identified object. Based on the mean squared matching error of the internal blocks and a selected threshold, a decision is made whether or not to encode the predictive errors inside these objects. The output bit stream includes entropy coding of object disparity, block disparity and possibly some errors, which fail to meet the threshold requirement in the proposed algorithm.

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

    Directory of Open Access Journals (Sweden)

    Reza Oji

    2012-10-01

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

  18. Learning Membership Functions in a Function-Based Object Recognition System

    CERN Document Server

    Woods, K; Hall, L; Bowyer, K; Stark, L

    1995-01-01

    Functionality-based recognition systems recognize objects at the category level by reasoning about how well the objects support the expected function. Such systems naturally associate a ``measure of goodness'' or ``membership value'' with a recognized object. This measure of goodness is the result of combining individual measures, or membership values, from potentially many primitive evaluations of different properties of the object's shape. A membership function is used to compute the membership value when evaluating a primitive of a particular physical property of an object. In previous versions of a recognition system known as Gruff, the membership function for each of the primitive evaluations was hand-crafted by the system designer. In this paper, we provide a learning component for the Gruff system, called Omlet, that automatically learns membership functions given a set of example objects labeled with their desired category measure. The learning algorithm is generally applicable to any problem in which...

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

    OpenAIRE

    Aubert Gilles; Jehan-Besson Stéphanie; Barlaud Michel

    2002-01-01

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

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

    Directory of Open Access Journals (Sweden)

    L. DJEROU,

    2012-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Qian Zhang

    2009-04-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

    Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

    2013-01-01

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

  4. 3D object following based on visual information for Unmanned Aerial Vehicles

    OpenAIRE

    Mondragon Bernal, Ivan Fernando; Campoy Cervera, Pascual; Olivares Méndez, Miguel Ángel; Martínez Luna, Carol Viviana

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Moon Nammee

    2010-01-01

    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.

  6. 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.

    Science.gov (United States)

    Bianchi, Ivana; Bertamini, Marco; Savardi, Ugo

    2015-10-01

    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

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

    Science.gov (United States)

    Amonou, Isabelle; Duhamel, Pierre

    2000-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Geng Zhang

    2013-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Frank Yeong-Sung Lin

    2010-08-01

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

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

    OpenAIRE

    Keller, Sascha; Marx, Andreas

    2011-01-01

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

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

    OpenAIRE

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

    2009-01-01

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

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

    OpenAIRE

    Kalaivani Rajagopal; Lakshmi Ponnusamy

    2014-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

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

    OpenAIRE

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

    2008-01-01

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

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

    DEFF Research Database (Denmark)

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

    2004-01-01

    A number of emerging applications of data management technology involve the monitoring and querying of large quantities of continuous variables, e.g., the positions of mobile service users, termed moving objects. In such applications, large quantities of state samples obtained via sensors are streamed to a database. Indexes for moving objects must support queries efficiently, but must also support frequent updates. Indexes based on minimum bounding regions (MBRs) such as the R-tree exhibit high ...

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

    OpenAIRE

    Cea Ramirez, Aldo; Bajic, Eddy

    2007-01-01

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

  17. A Hybrid Simplex Multi-Objective Evolutionary Algorithm Based on A New Fitness Assignment Strategy

    OpenAIRE

    Xiaofang Guo; Yuping Wang

    2013-01-01

    In multi-objective evolutionary algorithms (MOEAs), the traditional fitness assignment strategy based on Pareto dominance is ineffective in sorting out the high-quality solutions when the number of the objective is large. Recently, many scholars have used preference order (PO) ranking approach as an optimality criterion in the ranking stage of MOEAs. The experiment shows that the algorithms equipped with the PO ranking procedures can have a better convergence to the true Pareto surface, but a...

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

    OpenAIRE

    Levi?nik, Toni

    2008-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Sunil T. D

    2014-06-01

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

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

    Science.gov (United States)

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

    1992-07-01

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

  1. Object-Based Multiple Foreground Video Co-Segmentation via Multi-State Selection Graph.

    Science.gov (United States)

    Fu, Huazhu; Xu, Dong; Zhang, Bao; Lin, Stephen; Ward, Rabab Kreidieh

    2015-11-01

    We present a technique for multiple foreground video co-segmentation in a set of videos. This technique is based on category-independent object proposals. To identify the foreground objects in each frame, we examine the properties of the various regions that reflect the characteristics of foregrounds, considering the intra-video coherence of the foreground as well as the foreground consistency among the different videos in the set. Multiple foregrounds are handled via a multi-state selection graph in which a node representing a video frame can take multiple labels that correspond to different objects. In addition, our method incorporates an indicator matrix that for the first time allows accurate handling of cases with common foreground objects missing in some videos, thus preventing irrelevant regions from being misclassified as foreground objects. An iterative procedure is proposed to optimize our new objective function. As demonstrated through comprehensive experiments, this object-based multiple foreground video co-segmentation method compares well with related techniques that co-segment multiple foregrounds. PMID:26068314

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

    Science.gov (United States)

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

    2013-10-01

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

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

    Science.gov (United States)

    Xue, Cunjin; Dong, Qing; Qin, Lijuan

    2015-08-01

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

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

    Science.gov (United States)

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

    2015-11-01

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

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

    Science.gov (United States)

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

    2015-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Mohsen Naderpour

    2014-08-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-03-01

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

  8. Review of holographic-based three-dimensional object recognition techniques [invited].

    Science.gov (United States)

    Tsang, P W M; Poon, T-C; Liu, J-P; Situ, W C

    2014-09-20

    With the advancement of computing and optical technologies, it is now possible to capture digital holograms of real-life object scenes. Theoretically, through the analysis of a hologram, the three-dimensional (3D) objects coded on the hologram can be identified. However, being different from an optical image, a hologram is composed of complicated fringes that cannot be analyzed easily with traditional computer vision methods. Over the years, numerous important research investigations have been attempted to provide viable solutions to this problem. The aim of this work is three-fold. First, we provide a quick walkthrough on the overall development of holographic-based 3D object recognition (H3DOR) in the past five decades, from film-based approaches to digital-based innovation. Second, we describe in more detail a number of selected H3DOR methods that are introduced at different timelines, starting from the late sixties and then from the seventies, where viable digital holographic-based 3D recognition methods began to emerge. Finally, we present our work on digital holographic, pose-invariant 3D object recognition that is based on a recently introduced virtual diffraction plane framework. As our method has not been reported elsewhere, we have included some experimental results to demonstrate the feasibility of the approach. PMID:25322141

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

    Directory of Open Access Journals (Sweden)

    Vasileios Mezaris

    2004-06-01

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

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

    Science.gov (United States)

    Ding, Hao; Li, Xudong; Zhao, Huijie

    2013-03-01

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

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

    Directory of Open Access Journals (Sweden)

    Masatomo Inui

    2015-07-01

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

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

    ?l?zak, Dominik; Sosnowski, ?ukasz

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

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

    Directory of Open Access Journals (Sweden)

    Weiqi Zhou

    2014-04-01

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

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

    CERN Document Server

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

    2005-01-01

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

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

    Science.gov (United States)

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

    2015-08-01

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

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

    Directory of Open Access Journals (Sweden)

    Mehmet S. Guzel

    2015-02-01

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

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

    Science.gov (United States)

    Sharari, T. M.

    2015-03-01

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

  19. Entropy-based metrics for the analysis of partial and total occlusion in video object tracking

    OpenAIRE

    Loutas, E.; Pitas, I; Nikou, C.

    2010-01-01

    Metrics measuring tracking reliability under occlusion that are based on mutual information and do not resort to ground truth data are proposed. Metrics for both the initialisation of the region to be tracked as well as for measuring the performance of the tracking algorithm are presented. The metrics variations may be interpreted as a quantitative estimate of changes in the tracking region due to occlusion, sudden movement or deformation of the tracked object. Performance metrics based on th...

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

    OpenAIRE

    G.Suganthi; Reeba Korah; N.Seetharaman

    2014-01-01

    An artificial neural network (ANN) model with a simple architecture containing a single hidden layer is presented to discriminate the landmine objects from the acquired infrared images. The proposed method consists of preprocessing, segmentation, feature extraction and ANN based classification. Texture features based on gray level co-occurrence matrix (GLCM) are considered as inputs to the neural network classifier. The proposed method is tested on the infrared images acquired from two dif...

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

    OpenAIRE

    A. Gorbenko

    2013-01-01

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

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

    OpenAIRE

    Rongjun Qin

    2014-01-01

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

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

    OpenAIRE

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

    2014-01-01

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

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

    OpenAIRE

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

    2011-01-01

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

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

    Marshall, Neil; Buteau, Chantal

    2014-01-01

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

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

    Science.gov (United States)

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

    1999-01-01

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

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

    Science.gov (United States)

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

    2012-01-01

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

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

    DEFF Research Database (Denmark)

    Gu, Tao; Chen, Shaxun

    2010-01-01

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

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

    Science.gov (United States)

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

    2015-06-01

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

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

    Science.gov (United States)

    Suh, Woonsuk; Lee, Eunseok

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

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

    Directory of Open Access Journals (Sweden)

    Akram Moh. Alkouz

    2006-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Shiyan Pang

    2014-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Nandika Sood

    2011-11-01

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

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

    Directory of Open Access Journals (Sweden)

    Ms. Nandika Sood

    2011-09-01

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

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

    Science.gov (United States)

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

    2016-01-01

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

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

    Science.gov (United States)

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

    2014-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Chandra Mani Sharma

    2012-01-01

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

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

    Science.gov (United States)

    Huber, David J.; Khosla, Deepak

    2010-04-01

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

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

    Science.gov (United States)

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

    2014-11-01

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

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

    Directory of Open Access Journals (Sweden)

    S.N. Qasem

    2010-01-01

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

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

    Science.gov (United States)

    Huang, Jian; Hu, Weidong

    2014-01-01

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

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    R K Jena

    2014-05-01

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

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

    OpenAIRE

    Jacob, Alexander

    2011-01-01

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

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

    Ding, Zhiming; Huang, Guangyan

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

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

    OpenAIRE

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

    2009-01-01

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

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

    CERN Document Server

    Stuikys, Vytautas

    2015-01-01

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

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

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Søren

    2004-01-01

    A new lossless compression scheme for bilevel images targeted at binary shapes of image and video objects is presented. The scheme is based on a local analysis of the digital straightness of the causal part of the object boundary, which is used in the context definition for arithmetic encoding. Tested on individual images of binary shapes and binary layers of digital maps the algorithm outperforms PWC, JBIG and MPEG-4 CAE. On the binary shapes the code lengths are reduced by 21%, 25%, and 42%, r...

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

    DEFF Research Database (Denmark)

    Stegmann, Mikkel Bille; Forchhammer, SØren

    2002-01-01

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

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

    International Nuclear Information System (INIS)

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

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

    DEFF Research Database (Denmark)

    Civilis, A.; Jensen, Christian SØndergaard

    2005-01-01

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

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

    DEFF Research Database (Denmark)

    Civilis, Alminas; Jensen, Christian SØndergaard

    2005-01-01

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

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

    Science.gov (United States)

    Zhang, Shuqun; Furia, Bryan

    2014-09-01

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

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

    Science.gov (United States)

    Hartman, Leo; Melanson, Philip; Piggott, Stephen

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

  17. Multi-objective Structural Optimization Base on Improved NSGA-II Algorithm

    Directory of Open Access Journals (Sweden)

    M.Z. Lai

    2013-01-01

    Full Text Available A kind of fast and elitist multi-objective genetic algorithm (nondominated sorting genetic algorithm -II was presented to solve high dimension and multi-modal optimal problems. T His fuzzy information could be converted into a mathematically well-structured problem based on fuzzy optimal theory. And the improved crossover operator of NSGA-II was applied to obtain the optimal solution. According to the test results on a typical test function and an application on the structural fuzzy multi-objective optimization of three-bar truss, more reasonable distributed solutions could be obtained and the diversity of the solutions could be maintained. It provides beneficial references for engineering application of fuzzy multi-objective structure optimization.

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

    Directory of Open Access Journals (Sweden)

    Fei Cai

    2011-03-01

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

  19. Geometrically-correct projection-based texture mapping onto a deformable object.

    Science.gov (United States)

    Fujimoto, Yuichiro; Smith, Ross T; Taketomi, Takafumi; Yamamoto, Goshiro; Miyazaki, Jun; Kato, Hirokazu; Thomas, Bruce H

    2014-04-01

    Projection-based Augmented Reality commonly employs a rigid substrate as the projection surface and does not support scenarios where the substrate can be reshaped. This investigation presents a projection-based AR system that supports deformable substrates that can be bent, twisted or folded. We demonstrate a new invisible marker embedded into a deformable substrate and an algorithm that identifies deformations to project geometrically correct textures onto the deformable object. The geometrically correct projection-based texture mapping onto a deformable marker is conducted using the measurement of the 3D shape through the detection of the retro-reflective marker on the surface. In order to achieve accurate texture mapping, we propose a marker pattern that can be partially recognized and can be registered to an object?s surface. The outcome of this work addresses a fundamental vision recognition challenge that allows the underlying material to change shape and be recognized by the system. Our evaluation demonstrated the system achieved geometrically correct projection under extreme deformation conditions. We envisage the techniques presented are useful for domains including prototype development, design, entertainment and information based AR systems. PMID:24650981

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

    Directory of Open Access Journals (Sweden)

    Jaewoon Lee

    2015-02-01

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

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

    Science.gov (United States)

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

    2013-12-01

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

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

    Directory of Open Access Journals (Sweden)

    Yan Sun

    2015-09-01

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

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

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

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

    2015-03-01

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

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

    Science.gov (United States)

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

    2015-05-15

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

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

    Directory of Open Access Journals (Sweden)

    Ming Li

    2012-10-01

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

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

    Directory of Open Access Journals (Sweden)

    Stéphanie Jehan-Besson

    2002-06-01

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

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

    Directory of Open Access Journals (Sweden)

    Anastasia Polychronaki

    2013-11-01

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

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

    Science.gov (United States)

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

    2010-01-01

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

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

    CERN Document Server

    Trunfio, Paolo

    2014-01-01

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

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

    Science.gov (United States)

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

    2010-05-01

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

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

    CERN Document Server

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

    2009-01-01

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

  13. Job Scheduling Model for Cloud Computing Based on Multi-Objective Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Jing Liu

    2013-01-01

    Full Text Available Cloud computing is an emerging high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. To improve the overall performance of cloud computing, with the deadline constraint, a task scheduling model is established for reducing the system power consumption of cloud computing and improving the profit of service providers. For the scheduling model, a solving method based on multi-objective genetic algorithm (MO-GA is designed and the research is focused on encoding rules, crossover operators, selection operators and the method of sorting Pareto solutions. Based on open source cloud computing simulation platform CloudSim, compared to existing scheduling algorithms, the results show that the proposed algorithm can obtain a better solution, and it provides a balance for the performance of multiple objects.

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

    OpenAIRE

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

    2012-01-01

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

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

    OpenAIRE

    Acker, Jürgen; Henrich, Dominik

    2003-01-01

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

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

    OpenAIRE

    Sungdae Sim; Chee Sun Won; Kyhyun Um; Wei Song; Kyungeun Cho

    2012-01-01

    Mobile robot operators must make rapid decisions based on information about the robot’s surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot’s array of sensors, but some upper parts of objects are beyond the sensors’ measurements and these parts are missing in the terrain reco...

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

    OpenAIRE

    Khaled N. Elsayed

    2013-01-01

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

  18. The comfort performance of wool light fabrics based on subjective, objective evaluation

    OpenAIRE

    Broega, A. C., ed. lit.; Silva, Maria Elisabete

    2008-01-01

    The textile and clothing industry, aware of the marketing evolution cannot neglect the requests of comfort, which has been an increased and actual exigency of the clothing goods consumers. There is an urgent need to evaluate and quantify the comfort properties of textile in general. This work aims to make a study of the different types of lightweight wool fabrics, based on the objective evaluation of thermophysiological and sensorial comfort, according to real preferences, with the g...

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

    DEFF Research Database (Denmark)

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

    2014-01-01

    The North Sea provides a useful model for considering forage fish (FF) within ecosystem-based management as it has a complex assemblage of FF species. This paper is designed to encourage further debate and dialogue between stakeholders about management objectives. Changing the management of fisheries on FF will have economic consequences for all fleets in the North Sea. The predators that are vulnerable to the depletion of FF are Sandwich terns, great skua and common guillemots, and to a lesser ...

  20. Component-based tool for verifying applications using object-oriented patterns

    OpenAIRE

    Reynoso, Luis A.; Buccella, Agustina; Flores, Andrés P.; Aranda, Gabriela N.

    2002-01-01

    Applying design patterns is considered a helpful technique for designing software systems. Patterns description, however, results not sufficiently precise providing a weak understanding and making it difficult to be certain when a pattern is being used correctly. We have formally specified a metamodel where properties of patterns and object-oriented design can be rigorously described. In the present work, our formal basis is used to build a component-based tool for verifying proper applicatio...

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

    OpenAIRE

    Terzic, Kasim; Rodrigues, J. M. F.; du Buf, J. M. H.

    2013-01-01

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

  2. Job Scheduling Model for Cloud Computing Based on Multi-Objective Genetic Algorithm

    OpenAIRE

    Jing Liu; Xing-Guo Luo; Xing-Ming Zhang; Fan Zhang; Bai-Nan Li

    2013-01-01

    Cloud computing is an emerging high performance computing environment with a large scale, heterogeneous collection of autonomous systems and flexible computational architecture. To improve the overall performance of cloud computing, with the deadline constraint, a task scheduling model is established for reducing the system power consumption of cloud computing and improving the profit of service providers. For the scheduling model, a solving method based on multi-objective genetic algorithm (...

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

    OpenAIRE

    Aronsson, Peter; Fritzson, Peter

    2001-01-01

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

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

    DEFF Research Database (Denmark)

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

    2005-01-01

    With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects. This scenario is characterized by large volumes of updates, for which reason location update technologies become important. A setting is assumed in which a central database stores a representation of each m...

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

    DEFF Research Database (Denmark)

    Civilis, Alminas; Jensen, Christian Søndergaard; Saltenis, Simonas

    2005-01-01

    With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects. This scenario is characterized by large volumes of updates, for which reason location update technologies become important. A setting is assumed in which a central database stores a representation of each m...

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

    DEFF Research Database (Denmark)

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

    2010-01-01

    Human activity recognition is an important task which has many potential applications. In recent years, researchers from pervasive computing are interested in deploying on-body sensors to collect observations and applying machine learning techniques to model and recognize activities. Supervised machine learning techniques typically require an appropriate training process in which training data need to be labeled manually. In this paper, we propose an unsupervised approach based on object-use ?ng...

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

    DEFF Research Database (Denmark)

    Kjems, Erik; Kolá?, Jan

    2014-01-01

    One of the major development efforts within the GI Science domain are pointing at real time information coming from geographic referenced features in general. At the same time 3D City models are mostly justified as being objects for visualization purposes rather than constituting the foundation of a geographic data representation of the world. The combination of 3D city models and real time information based systems though can provide a whole new setup for data fusion within an urban environment...

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

    OpenAIRE

    Ms. Nandika Sood; Mr. Amit Sinhal

    2011-01-01

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

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

    OpenAIRE

    Wang, Hui; Han, Shensheng

    2009-01-01

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

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

    OpenAIRE

    Elsen, Catherine; Darses, Françoise; Leclercq, Pierre

    2010-01-01

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

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

    Science.gov (United States)

    Bisquert, Mar; Bégué, Agnès; Deshayes, Michel

    2015-05-01

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

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

    International Nuclear Information System (INIS)

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Niemeyer, Irmgard [TU Bergakademie Freiberg (Germany). Inst. for Mine-Surveying and Geodesy; Canty, Morton J. [Forschungszentrum Juelich (Germany). Programme Group Systems Analysis and Technology Evaluation (STE)

    2003-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Maggi Kelly

    2011-11-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

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

    OpenAIRE

    Anan Banharnsakun; Supannee Tanathong

    2014-01-01

    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 ba...

  18. A Strategy for Grasping unknown Objects based on Co-Planarity and Colour Information

    DEFF Research Database (Denmark)

    Popovic, Mila; Kraft, Dirk; Bodenhagen, Leon; Baseski, Emre; Pugeault, Nicolas; Kragic, Danica; Asfour, Tamim; Krüger, Norbert

    2010-01-01

    In this work, we describe and evaluate a grasping mechanism that does not make use of any specific object prior knowledge. The mechanism makes use of second-order relations between visually extracted multi-modal 3D features provided by an early cognitive vision system. More specifically, the algorithm is based on two relations covering geometric information in terms of a co-planarity constraint as well as appearance based information in terms of co-occurrence of colour properties. We show that o...

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

    Directory of Open Access Journals (Sweden)

    Rongjun Qin

    2014-08-01

    Full Text Available There have been increasing demands for automatically monitoring urban areas in very high detail, and the Unmanned Aerial Vehicle (UAV with auto-navigation (AUNA system offers such capability. This study proposes an object-based hierarchical method to detect changes from UAV images taken at different times. It consists of several steps. In the first step, an octocopter with AUNA capability is used to acquire images at different dates. These images are registered automatically, based on SIFT (Scale-Invariant Feature Transform feature points, via the general bundle adjustment framework. Thus, the Digital Surface Models (DSMs and orthophotos can be generated for raster-based change analysis. In the next step, a multi-primitive segmentation method combining the spectral and geometric information is proposed for object-based analysis. In the final step, a multi-criteria decision analysis is carried out concerning the height, spectral and geometric coherence, and shape regularity for change determination. Experiments based on UAV images with five-centimeter ground resolution demonstrate the effectiveness of the proposed method, leading to the conclusion that this method is practically applicable for frequent monitoring.

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

    Directory of Open Access Journals (Sweden)

    Kalaivani Rajagopal

    2014-03-01

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

  1. 6DoF object pose measurement by a monocular manifold-based pattern recognition technique

    International Nuclear Information System (INIS)

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

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

    Science.gov (United States)

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

    2008-03-01

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

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

    Science.gov (United States)

    Bybee, Taylor C.; Budge, Scott E.

    2015-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Xiaoyong Zhang

    2012-11-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

    Guerra, C; Pascucci, V

    2004-12-13

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

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

    Science.gov (United States)

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

    2013-12-01

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

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    Kang Ling

    2009-02-01

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

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

    International Nuclear Information System (INIS)

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

  10. A Hybrid Simplex Multi-Objective Evolutionary Algorithm Based on A New Fitness Assignment Strategy

    Directory of Open Access Journals (Sweden)

    Xiaofang Guo

    2013-02-01

    Full Text Available In multi-objective evolutionary algorithms (MOEAs, the traditional fitness assignment strategy based on Pareto dominance is ineffective in sorting out the high-quality solutions when the number of the objective is large. Recently, many scholars have used preference order (PO ranking approach as an optimality criterion in the ranking stage of MOEAs. The experiment shows that the algorithms equipped with the PO ranking procedures can have a better convergence to the true Pareto surface, but are ineffective to maintain a set of well-distributed solutions over the Pareto surface. In order to overcome above shortcomings, a new algorithm is proposed which adopts a new fitness assignment strategy using the information of the individual preference order ranking and the individual density. In this way,  it is helpful to guide the individuals to more sparse areas in the Pareto Front. At the same time, the proposed algorithm effectively combines multi-objective evolutionary algorithm with the Nelder-Mead simplex search to get a balance between the exploration and exploitation abilities. In each generation, the algorithm adopts a parallel hybrid way to evolve two subsets simultaneously, and the population will be improved by both evolution algorithm and simplex search. The proposed algorithm has been compared with other MOEAs on some many-objective problems by experiments. The experimental results indicate that the proposed algorithm achieves a better performance in convergence and diversity.

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    M. V. Krishnamurthy

    1993-04-01

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

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

    Indian Academy of Sciences (India)

    Tugrul Talaslioglu

    2013-02-01

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

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

    Science.gov (United States)

    Engström, Philip; Axelsson, Maria; Karlsson, Mikael

    2013-05-01

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

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

    Directory of Open Access Journals (Sweden)

    Pandu Sandi Pratama

    2012-12-01

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

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

    Science.gov (United States)

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

    2013-04-01

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

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

    Science.gov (United States)

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

    2015-07-01

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

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

    Directory of Open Access Journals (Sweden)

    Quoc Tuan Vo

    2013-01-01

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

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

    Science.gov (United States)

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

    2011-11-01

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

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

    Directory of Open Access Journals (Sweden)

    T. K. Jana

    2014-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Ming Xue

    2014-02-01

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

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

    Directory of Open Access Journals (Sweden)

    R. Vanitha

    2014-06-01

    Full Text Available This paper proposes the application of Differential Evolution (DE algorithm based Weighted Additive Fuzzy Goal Programming (WAFGP in solving a Multi objective Optimal Power Flow (MOPF problem. The multiple objectives considered are maximizing the loadability, minimizing the total real power loss and minimizing the overall system cost which comprises of installation cost of FACTS devices and generation fuel cost. The optimal solution for this MOPF problem is obtained by optimally sizing and placing a Thyristor Controlled Series Capacitor (TCSC in the power system. The constraints considered in this MOPF are the generators’ real and reactive power limits and their voltage limits, transmission lines’ loading capability limits, TCSC limits along with system’s equality and inequality constraints. The Line Stability Index (LSI is used to determine the critically loaded transmission lines in the power system. IEEE 30 bus system is used for testing and validating the results.

  3. A Genetic-Algorithm-Based Explicit Description of Object Contour and its Ability to Facilitate Recognition.

    Science.gov (United States)

    Wei, Hui; Tang, Xue-Song

    2015-11-01

    Shape representation is an extremely important and longstanding problem in the field of pattern recognition. Closed contour, which refers to shape contour, plays a crucial role in the comparison of shapes. Because shape contour is the most stable, distinguishable, and invariable feature of an object, it is useful to incorporate it into the recognition process. This paper proposes a method based on genetic algorithms. The proposed method can be used to identify the most common contour fragments, which can be used to represent the contours of a shape category. The common fragments clarify the particular logics included in the contours. This paper shows that the explicit representation of the shape contour contributes significantly to shape representation and object recognition. PMID:25546870

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

    Science.gov (United States)

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

    2015-09-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2004-06-01

    This document describes ROCIT, a neural-inspired object recognition algorithm based on a rank-order coding scheme that uses a light-weight neuron model. ROCIT coarsely simulates a subset of the human ventral visual stream from the retina through the inferior temporal cortex. It was designed to provide an extensible baseline from which to improve the fidelity of the ventral stream model and explore the engineering potential of rank order coding with respect to object recognition. This report describes the baseline algorithm, the model's neural network architecture, the theoretical basis for the approach, and reviews the history of similar implementations. Illustrative results are used to clarify algorithm details. A formal benchmark to the 1998 FERET fafc test shows above average performance, which is encouraging. The report concludes with a brief review of potential algorithmic extensions for obtaining scale and rotational invariance.

  6. WWW-based access to object-oriented clinical databases: the KHOSPAD project.

    Science.gov (United States)

    Pinciroli, F; Portoni, L; Combi, C; Violante, F F

    1998-09-01

    KHOSPAD is a project aiming at improving the quality of the process of patient care concerning general practitioner-patient-hospital relationships, using current information and networking technologies. The studied application field is a cardiology division, with hemodynamic laboratory and the population of PTCA patients. Data related to PTCA patients are managed by ARCADIA, an object-oriented database management system developed for the considered clinical setting. We defined a remotely accessible view of ARCADIA medical record, suitable for general practitioners (GPs) caring patients after PTCA, during the follow-up period. Using a PC, a modem and Internet, an authorized GP can consult remotely the medical records of his PTCA patients. Main features of the application are related to the management and display of complex data, specifically characterized by multimedia and temporal features, based on an object-oriented temporal data model. PMID:9861510

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

    Directory of Open Access Journals (Sweden)

    Elias David Nino Ruiz

    2013-05-01

    Full Text Available This paper states a novel hybrid-metaheuristic based on the Theory of Deterministic Swapping, Theory of Evolution and Simulated Annealing Metaheuristic for the multi-objective optimization of combinatorial problems. The proposed algorithm is named EMSA. It is an improvement of MODS algorithm. Unlike MODS, EMSA works using a search direction given through the assignation of weights to each function of the combinatorial problem to optimize. Also, in order to avoid local optimums, EMSA uses crossover strategy of Genetic Algorithm. Lastly, EMSA is tested using well know instances of the Bi-Objective Traveling Salesman Problem (TSP from TSPLIB. Its results were compared with MODS Metaheuristic (its precessor. The comparison was made using metrics from the specialized literature such as Spacing, Generational Distance, Inverse Generational Distance and Non-Dominated Generation Vectors. In every case, the EMSA results on the metrics were always better and in some of those cases, the superiority was 100%.

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

    Directory of Open Access Journals (Sweden)

    Jinchang Ren

    2010-04-01

    Full Text Available Automatic recognition of highlights from videos is a fundamental and challenging problem for content-based indexing and retrieval applications. In this paper, we propose techniques to solve this problem using knowledge supported extraction of semantics, and compressed-domain processing is employed for efficiency. Firstly, knowledgebased rules are utilized for shot detection on extracted DCimages, and statistical skin detection is applied for human object detection. Secondly, through filtering outliers in motion vectors, improved detection of camera motions like zooming, panning and tilting are achieved. Video highlight high-level semantics are then automatically extracted via low-level analysis in the detection of human objects and camera motion events, and finally these highlights are taken for shot-level annotation, indexing and retrieval. Results using a large test video data set have demonstrated the accuracy and robustness of the proposed techniques.

  9. Target Object Identification and Location Based on Multi-sensor Fusion

    Directory of Open Access Journals (Sweden)

    Yong Jiang

    2013-03-01

    Full Text Available For an unknown environment, how to make a mobile robot identify a target object and locate it autonomously, this is a very challenging question. In this paper, a novel multi-sensor fusion method based on a camera and a laser range finder (LRF for mobile manipulations is proposed. Although a camera can acquire large quantities of information, it does not directly get the 3D data of the environment. Moreover, the camera image processing is complex and easily influenced from the change in ambient light. In view of the ability of the LRF to directly get the 3D coordinates of the environment and its stability against outside influence, and the superiority of the camera to acquire rich color information, the combination of the two sensors by making use of their advantages is employed to obtain more accurate measurement as well as to simplify information processing. To overlay the camera image with the measurement point cloud of the pitching LRF and to reconstruct the 3D image which includes pixel depth information, the homogeneous transformation model of the system is built. Then, based on the combination of the color features from the camera image and the shape features from the LRF measurement data, the autonomous identification and location of target object are achieved. In order to extract the shape features of the object, a two-step method is introduced, and a sliced point cloud algorithm is proposed for the preliminary classification of the measurement data of the LRF. The effectiveness of the proposed method is validated by the experimental testing and analysis carried out on the mobile manipulator platform. The experimental results show that by this method, the robot can not only identify target object autonomously, but also determine whether it can be operated, and acquire a proper grasping location.

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

    Science.gov (United States)

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

    2010-06-01

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

  11. Object-based gully system prediction from medium resolution imagery using Random Forests

    Science.gov (United States)

    Shruthi, Rajesh B. V.; Kerle, Norman; Jetten, Victor; Stein, Alfred

    2014-07-01

    Erosion, in particular gully erosion, is a widespread problem. Its mapping is crucial for erosion monitoring and remediation of degraded areas. In addition, mapping of areas with high potential for future gully erosion can be used to assist prevention strategies. Good relations with topographic variables collected from the field are appropriate for determining areas susceptible to gullying. Image analysis of high resolution remotely sensed imagery (HRI) in combination with field verification has proven to be a good approach, although dependent on expensive imagery. Automatic and semi-automatic methods, such as object-oriented analysis (OOA), are rapid and reproducible. However, HRI data are not always available. We therefore attempted to identify gully systems using statistical modeling of image features from medium resolution imagery, here ASTER. These data were used for determining areas within gully system boundaries (GSB) using a semi-automatic method based on OOA. We assess if the selection of useful object features can be done in an objective and transferable way, using Random Forests (RF) for prediction of gully systems at regional scale, here in the Sehoul region, near Rabat, Morocco. Moderate success was achieved using a semi-automatic object-based RF model (out-of-bag error of 18.8%). Besides compensating for the imbalance between gully and non-gully classes, the procedure followed in this study enabled us to balance the classification error rates. The user's and producer's accuracy of the data with a balanced set of class showed an improved accuracy of the spatial estimates of gully systems, when compared to the data with imbalanced class. The model over-predicted the area within the GSB (13-27%), but its overall performance demonstrated that medium resolution satellite images contain sufficient information to identify gully systems, so that large areas can be mapped with relatively little effort and acceptable accuracy.

  12. Object-Based Crop Species Classification Based on the Combination of Airborne Hyperspectral Images and LiDAR Data

    Directory of Open Access Journals (Sweden)

    Xiaolong Liu

    2015-01-01

    Full Text Available Identification of crop species is an important issue in agricultural management. In recent years, many studies have explored this topic using multi-spectral and hyperspectral remote sensing data. In this study, we perform dedicated research to propose a framework for mapping crop species by combining hyperspectral and Light Detection and Ranging (LiDAR data in an object-based image analysis (OBIA paradigm. The aims of this work were the following: (i to understand the performances of different spectral dimension-reduced features from hyperspectral data and their combination with LiDAR derived height information in image segmentation; (ii to understand what classification accuracies of crop species can be achieved by combining hyperspectral and LiDAR data in an OBIA paradigm, especially in regions that have fragmented agricultural landscape and complicated crop planting structure; and (iii to understand the contributions of the crop height that is derived from LiDAR data, as well as the geometric and textural features of image objects, to the crop species’ separabilities. The study region was an irrigated agricultural area in the central Heihe river basin, which is characterized by many crop species, complicated crop planting structures, and fragmented landscape. The airborne hyperspectral data acquired by the Compact Airborne Spectrographic Imager (CASI with a 1 m spatial resolution and the Canopy Height Model (CHM data derived from the LiDAR data acquired by the airborne Leica ALS70 LiDAR system were used for this study. The image segmentation accuracies of different feature combination schemes (very high-resolution imagery (VHR, VHR/CHM, and minimum noise fractional transformed data (MNF/CHM were evaluated and analyzed. The results showed that VHR/CHM outperformed the other two combination schemes with a segmentation accuracy of 84.8%. The object-based crop species classification results of different feature integrations indicated that incorporating the crop height information into the hyperspectral extracted features provided a substantial increase in the classification accuracy. The combination of MNF and CHM produced higher classification accuracy than the combination of VHR and CHM, and the solely MNF-based classification results. The textural and geometric features in the object-based classification could significantly improve the accuracy of the crop species classification. By using the proposed object-based classification framework, a crop species classification result with an overall accuracy of 90.33% and a kappa of 0.89 was achieved in our study area.

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

    Science.gov (United States)

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

    2015-04-01

    Up-to-date and frequent glacier outlines are a necessity for many applications within glaciology. While multispectral band ratios are a comparatively robust method for automatically classifying clean ice on a pixel-based level, semi- or fully automated glacier inventories are complicated by spectral similarities between classes such as debris-covered glacier ice and the surrounding bedrock and moraines, or between clean ice and turbid pro-glacial water. Most glacier inventories therefore require a great deal of manual correction. Here, we present a glacier inventory of the Hohe Tauern Mountains in the Central Eastern Alps in Austria. Numerous glaciers, including the Pasterze Glacier, which is the longest glacier in the Eastern Alps, shape this mountainous region. The mapping of glaciers is based on object-based image analysis (OBIA) using both high resolution (HR) satellite imagery from Landsat 8 and a digital elevation model (DEM) derived from Airborne Laser Scanning (ALS) data. We automatically classify clean ice, debris-covered ice and glacial lakes. Image objects are created by applying the multiresolution segmentation algorithm implemented in the eCognition (Trimble) software. The resulting image objects are classified using a combination of various features, whereby a focus was put on the selection of robust features that are ideally applicable for mapping large areas, for example spectral indices such as the Normalized Differenced Vegetation Index (NDVI), Normalized Difference Snow and Ice Index (NDSI), Normalised Difference Water Index (NDWI), Land and Water Mask (LWK) and a ratio of the SWIR and NIR spectral bands. The ability of OBIA to incorporate optical and elevation data and to individually address data-specific characteristics helps differentiate debris-covered ice from surrounding features not only by using spectral properties but also based on morphological and topographic parameters, while the inclusion of rulesets relying on contextuality, size and shape and hierarchical criteria allow semantic corrections of shadow and supra-glacial lakes. In addition, the absence of the 'salt and pepper' effect often found when using pixel-based methods reduce the amount of post-processing and manual correction necessary. The results are compared to the Randolph Glacier Inventory, although given that over Austria this inventory was based on imagery from 2003 the comparability with such databases is limited. Against the background of the lack of up-to-data data and the fact that glaciers undergo steady changes, and thus, are a highly important indicator of climate change, it can be said there is a need for reliable methods for mapping and monitoring glaciers. The presented method based on remote sensing data and OBIA is one promising way to tackle these issues.

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

    Science.gov (United States)

    Pasam, Gopi Krishna; Manohar, T. Gowri

    2015-07-01

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

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

    Science.gov (United States)

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

    2015-05-01

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

  16. Object based change detection in urban area using KTH-SEG

    OpenAIRE

    Bergsjö, Joline

    2014-01-01

    Today more and more people are moving to the cities around the world. This puts a lot of strain on the infrastructure as the cities grow in both width and height. To be able to monitor the ongoing change remote sensing is an effective tool and ways to make it even more effective, better and easier to use are constantly sought after. One way to monitor change detection is object based change detection. The idea has been around since the seventies, but it wasn’t until the early 2000 when it was...

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

    DEFF Research Database (Denmark)

    Juel, Anders

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

  18. Mapping of crop calendar events by object-based analysis of MODIS and ASTER images

    Directory of Open Access Journals (Sweden)

    A.I. De Castro

    2014-06-01

    Full Text Available A method to generate crop calendar and phenology-related maps at a parcel level of four major irrigated crops (rice, maize, sunflower and tomato is shown. The method combines images from the ASTER and MODIS sensors in an object-based image analysis framework, as well as testing of three different fitting curves by using the TIMESAT software. Averaged estimation of calendar dates were 85%, from 92% in the estimation of emergence and harvest dates in rice to 69% in the case of harvest date in tomato.

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

    OpenAIRE

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

    2008-01-01

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

  20. FAST AND RELIABLE OBJECT CLASSIFICATION IN VIDEO BASED ON A 3D GENERIC MODEL

    OpenAIRE

    Zuniga, Marcos; Bremond, François; Thonnat, Monique

    2006-01-01

    We propose a new object classification approach for monocular video sequences, which allows to classify objects modelled independently from the camera position and object orientation. To achieve this independence, a simple 3D object model that represents an object as a parallelepiped is proposed. The approach is able to give good estimates of object dimensions and proposes visual reliability measures for the object dimensions. These measures give a representation of the visibility of the esti...

  1. Intuitive terrain reconstruction using height observation-based ground segmentation and 3D object boundary estimation.

    Science.gov (United States)

    Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

    2012-01-01

    Mobile robot operators must make rapid decisions based on information about the robot's surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot's array of sensors, but some upper parts of objects are beyond the sensors' measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances. PMID:23235454

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

    Directory of Open Access Journals (Sweden)

    Sungdae Sim

    2012-12-01

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

  3. Cooperative Moving Object Segmentation using Two Cameras based on Background Subtraction and Image Registration

    Directory of Open Access Journals (Sweden)

    Zhigao Cui

    2014-03-01

    Full Text Available Moving camera, such as PTZ (pan-tilt-zoom camera, has been widely applied in visual surveillance system. However, it’s difficult to extract moving objects because of the dynamic background caused by the camera motion. In this paper, a novel framework for moving object segmentation exploiting two cameras collaboration is presented by combining background subtraction and image registration method. The proposed method uses one static camera to capture large-view images at low resolution, and one moving camera (i.e. PTZ camera to capture local-view images at high resolution. Different with methods using a single moving camera, the moving objects can be effectively segmented in the static camera image by background subtraction method. Then image registration method can be applied to extract moving region in the moving camera image. To deal with the resolution and intensity discrepancy between two synchronized images, we design a practical three-step image registration method, which has higher registration accuracy than traditional feature based method. Experimental results on outdoor scene demonstrate the effectiveness and robustness of proposed approach.

  4. An object-oriented hybrid knowledge representation method based on the ASME code

    International Nuclear Information System (INIS)

    In this paper knowledge based system technology is adopted in the application process of the ASME boiler and pressure vessel core section III for bettering design quality and efficiency of nuclear component. At present no a single knowledge representation method could express all of the ASME code's rules sufficiently, integrally and exactly. An object-oriented hybrid knowledge representation method (OOHKRM) is presented in the paper. The rule expression of the ASME code is divided into three modes such as statement, list and graphic illustration by detailed analyzing the organization characteristics and rules of the code. According to the differences of knowledge features, knowledge of the ASME code is classified approximately into three main categories: illustrative knowledge, procedural knowledge, and Meta knowledge, which are represented by list, frame, production rule and Petri net respectively for expressing the knowledge integrally and exactly. A knowledge Petri net model is also defined for the same reason. Moreover, several class objects corresponding to different types of knowledge are defined especially. The method not only reserves merits of the other four used representation methods, but also processes characteristics of object-oriented technologies. Consequently, the method has good universality while it is used to represent the knowledge of ASME codes or other engineering standards. (author)

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1997-05-01

    In hazardous applications such as remediation of buried waste and dismantlement of radioactive facilities, robots are an attractive solution. Sensing to recognize and locate objects is a critical need for robotic operations in unstructured environments. An accurate 3-D model of objects in the scene is necessary for efficient high level control of robots. Drawing upon concepts from supervisory control, the authors have developed an interactive system for creating object models from range data, based on simulated annealing. Site modeling is a task that is typically performed using purely manual or autonomous techniques, each of which has inherent strengths and weaknesses. However, an interactive modeling system combines the advantages of both manual and autonomous methods, to create a system that has high operator productivity as well as high flexibility and robustness. The system is unique in that it can work with very sparse range data, tolerate occlusions, and tolerate cluttered scenes. The authors have performed an informal evaluation with four operators on 16 different scenes, and have shown that the interactive system is superior to either manual or automatic methods in terms of task time and accuracy.

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

    Science.gov (United States)

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

    2015-05-01

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

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

    DEFF Research Database (Denmark)

    Wörgötter, Florentin; Aksoy, E. E.

    2013-01-01

    Humans can perform a multitude of different actions with their hands (manipulations). In spite of this, so far there have been only a few attempts to represent manipulation types trying to understand the underlying principles. Here we first discuss how manipulation actions are structured in space and time. For this we use as temporal anchor points those moments where two objects (or hand and object) touch or un-touch each other during a manipulation. We show that by this one can define a relatively small tree-like manipulation ontology. We find less than 30 fundamental manipulations. The temporal anchors also provide us with information about when to pay attention to additional important information, for example when to consider trajectory shapes and relative poses between objects. As a consequence a highly condensed representation emerges by which different manipulations can be recognized and encoded. Examples of manipulations recognition and execution by a robot based on this representation are given at theend of this study.

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

    International Nuclear Information System (INIS)

    In hazardous applications such as remediation of buried waste and dismantlement of radioactive facilities, robots are an attractive solution. Sensing to recognize and locate objects is a critical need for robotic operations in unstructured environments. An accurate 3-D model of objects in the scene is necessary for efficient high level control of robots. Drawing upon concepts from supervisory control, the authors have developed an interactive system for creating object models from range data, based on simulated annealing. Site modeling is a task that is typically performed using purely manual or autonomous techniques, each of which has inherent strengths and weaknesses. However, an interactive modeling system combines the advantages of both manual and autonomous methods, to create a system that has high operator productivity as well as high flexibility and robustness. The system is unique in that it can work with very sparse range data, tolerate occlusions, and tolerate cluttered scenes. The authors have performed an informal evaluation with four operators on 16 different scenes, and have shown that the interactive system is superior to either manual or automatic methods in terms of task time and accuracy

  9. A grid based multi-objective evolutionary algorithm for the optimization of power plants

    International Nuclear Information System (INIS)

    There is an increasing need for optimization of energy conversion systems, in particular concerning energy consumption and efficiency to reduce their environmental impact. Usually, optimization is based on designers' backgrounds, which are able to analyze system performances and modify appropriate operating parameters. However, if these changes aim to optimize simultaneously multiple conflicting objectives, the task becomes quite complex and the use of sophisticated tools is mandatory. This paper presents a multi-objective optimization method that permits solutions that simultaneously satisfy multiple conflicting objectives to be determined. The optimization process is carried out by using an evolutionary algorithm developed around an innovative technique that consists of partitioning the solution search space (i.e., a population of solutions) into parallel corridors. Within these corridors, 'header' solutions are trapped to be then involved in a reproduction process of new populations by using genetic operators. The proposed methodology is coupled to specific power plant models that are used to optimize two different power plants: (i) a cogeneration thermal plant and (ii) an advanced steam power station. In both cases the proposed technique has shown to be very powerful, robust and reliable. Further, this methodology can be used as an effective tool to find the set of best solutions and thus providing a realistic support to the decision-making.

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

    Science.gov (United States)

    Yu, Hongsheng; Jin, Weiqi; Liu, Xiusheng

    2010-10-01

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

  11. Culture belief based multi-objective hybrid differential evolutionary algorithm in short term hydrothermal scheduling

    International Nuclear Information System (INIS)

    Highlights: ? Culture belief is integrated into multi-objective differential evolution. ? Chaotic sequence is imported to improve evolutionary population diversity. ? The priority of convergence rate is proved in solving hydrothermal problem. ? The results show the quality and potential of proposed algorithm. - Abstract: A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic emission (SHOSEE) problem. This problem is formulated for compromising thermal cost and emission issue while considering its complicated non-linear constraints with non-smooth and non-convex characteristics. The proposed algorithm integrates a modified multi-objective differential evolutionary algorithm into the computation model of culture algorithm (CA) as well as some communication protocols between population space and belief space, three knowledge structures in belief space are redefined according to these problem-solving characteristics, and in the differential evolution a chaotic factor is embedded into mutation operator for avoiding the premature convergence by enlarging the search scale when the search trajectory reaches local optima. Furthermore, a new heuristic constraint-handling technique is utilized to handle those complex equality and inequality constraints of SHOSEE problem. After the application on hydrothermal scheduling system, the efficiency and stability of the proposed CB-MOHDE is verified by its more desirable results in comparison to other method established recently, and the simulation results also reveal that CB-MOHDE can be a promising alternative for solving SHOSEE.

  12. Ladar signature simulation

    Science.gov (United States)

    Estep, Jeffrey A.; Gu, Zu-Han

    1992-09-01

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

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

    Science.gov (United States)

    Schmalz, Mark S.; Ritter, Gerhard X.

    2004-10-01

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

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

    Directory of Open Access Journals (Sweden)

    G.Suganthi

    2014-09-01

    Full Text Available An artificial neural network (ANN model with a simple architecture containing a single hidden layer is presented to discriminate the landmine objects from the acquired infrared images. The proposed method consists of preprocessing, segmentation, feature extraction and ANN based classification. Texture features based on gray level co-occurrence matrix (GLCM are considered as inputs to the neural network classifier. The proposed method is tested on the infrared images acquired from two different soil types namely black cotton soil and Maharashtra sand. The ability of the back propagation neural network in discriminating the landmines from the clutters in the infrared images acquired from inhomogeneous soil is discussed. The results of the field experiments carried out at the outdoor land mine detection test facility, DRDO, Pune are presented. The results are encouraging.

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

    International Nuclear Information System (INIS)

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-07-01

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

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

    Science.gov (United States)

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

    2015-02-01

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

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

    Science.gov (United States)

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

    2012-04-01

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

  19. Multi-objective experimental design for (13)C-based metabolic flux analysis.

    Science.gov (United States)

    Bouvin, Jeroen; Cajot, Simon; D'Huys, Pieter-Jan; Ampofo-Asiama, Jerry; Anné, Jozef; Van Impe, Jan; Geeraerd, Annemie; Bernaerts, Kristel

    2015-10-01

    (13)C-based metabolic flux analysis is an excellent technique to resolve fluxes in the central carbon metabolism but costs can be significant when using specialized tracers. This work presents a framework for cost-effective design of (13)C-tracer experiments, illustrated on two different networks. Linear and non-linear optimal input mixtures are computed for networks for Streptomyces lividans and a carcinoma cell line. If only glucose tracers are considered as labeled substrate for a carcinoma cell line or S. lividans, the best parameter estimation accuracy is obtained by mixtures containing high amounts of 1,2-(13)C2 glucose combined with uniformly labeled glucose. Experimental designs are evaluated based on a linear (D-criterion) and non-linear approach (S-criterion). Both approaches generate almost the same input mixture, however, the linear approach is favored due to its low computational effort. The high amount of 1,2-(13)C2 glucose in the optimal designs coincides with a high experimental cost, which is further enhanced when labeling is introduced in glutamine and aspartate tracers. Multi-objective optimization gives the possibility to assess experimental quality and cost at the same time and can reveal excellent compromise experiments. For example, the combination of 100% 1,2-(13)C2 glucose with 100% position one labeled glutamine and the combination of 100% 1,2-(13)C2 glucose with 100% uniformly labeled glutamine perform equally well for the carcinoma cell line, but the first mixture offers a decrease in cost of $ 120 per ml-scale cell culture experiment. We demonstrated the validity of a multi-objective linear approach to perform optimal experimental designs for the non-linear problem of (13)C-metabolic flux analysis. Tools and a workflow are provided to perform multi-objective design. The effortless calculation of the D-criterion can be exploited to perform high-throughput screening of possible (13)C-tracers, while the illustrated benefit of multi-objective design should stimulate its application within the field of (13)C-based metabolic flux analysis. PMID:26265092

  20. UNCERTAIN TRAINING DATA EDITION FOR AUTOMATIC OBJECT-BASED CHANGE MAP EXTRACTION

    Directory of Open Access Journals (Sweden)

    S. Hajahmadi

    2013-09-01

    Full Text Available 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.

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

    Science.gov (United States)

    Khelifa, Dejrriri; Mimoun, Malki

    2012-11-01

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

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

    DEFF Research Database (Denmark)

    Kjems, Erik; Kolá?, Jan

    2014-01-01

    One of the major development efforts within the GI Science domain are pointing at real time information coming from geographic referenced features in general. At the same time 3D City models are mostly justified as being objects for visualization purposes rather than constituting the foundation of a geographic data representation of the world. The combination of 3D city models and real time information based systems though can provide a whole new setup for data fusion within an urban environment and provide time critical information preserving our limited resources in the most sustainable way. Using 3D models with consistent object definitions give us the possibility to avoid troublesome abstractions of reality, and design even complex urban systems fusing information from various sources of data. These systems are difficult to design with the traditional software development approach based on major software packages and traditional data exchange. The data stream is varying from domain to domain and from system to system why it is almost impossible to design an unifying system taking care of all thinkable instances now and in the future within one constraint software design complex. On several occasions we have been advocating for a new and advanced formulation of real world features using the concept of Geospatial Managed Objects (GMO). This chapter presents the outcome of the InfraWorld project, a 4 million Euro project financed primarily by the Norwegian Research Council where the concept of GMO’s have been applied in various situations on various running platforms of an urban system. The paper will be focusing on user experiences and interfaces rather then core technical and developmental issues. The project was primarily focusing on prototyping rather than realistic implementations.

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

    Directory of Open Access Journals (Sweden)

    Saka Kezia

    2013-03-01

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

  4. An object based approach for coastline extraction from Quickbird multispectral images

    Directory of Open Access Journals (Sweden)

    Massimiliano Basile Giannini

    2014-12-01

    Full Text Available Because of the reduced dimensions of pixels, in the last years high resolution satellite images (Quickbird, IKONOS, GeoEye, ….. are considered very important data to extract information for coastline monitoring and engineering opera planning. They can integrate detail topographic maps and aerial photos so to contribute to modifications recognition and coastal dynamics reconstruction. Many studies have been carried out on coastline detection from high resolution satellite images: unsupervised and supervised classification, segmentation, NDVI (Normalized Difference Vegetation Index and NDWI (Normalized Difference Water Index are only some of the methodological aspects that have been already considered and experimented. This paper is aimed to implement an object based approach to extract coastline from Quickbird multispectral imagery. Domitian area near Volturno River mouth in Campania Region (Italy, an interesting zone for its dynamics and evolution, is considered. Object based approach is developed for automatic detection of coastline from Quickbird imagery using the Feature Extraction Workflow implemented in ENVI Zoom software. The resulting vector polyline is performed using the smoothing algorithm named PAEK (Polynomial Approximation with Exponential Kernel.

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

    Science.gov (United States)

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

    2015-07-01

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

  6. Application of In-Segment Multiple Sampling in Object-Based Classification

    Directory of Open Access Journals (Sweden)

    Nataša ?uri?

    2014-12-01

    Full Text Available When object-based analysis is applied to very high-resolution imagery, pixels within the segments reveal large spectral inhomogeneity; their distribution can be considered complex rather than normal. When normality is violated, the classification methods that rely on the assumption of normally distributed data are not as successful or accurate. It is hard to detect normality violations in small samples. The segmentation process produces segments that vary highly in size; samples can be very big or very small. This paper investigates whether the complexity within the segment can be addressed using multiple random sampling of segment pixels and multiple calculations of similarity measures. In order to analyze the effect sampling has on classification results, statistics and probability value equations of non-parametric two-sample Kolmogorov-Smirnov test and parametric Student’s t-test are selected as similarity measures in the classification process. The performance of both classifiers was assessed on a WorldView-2 image for four land cover classes (roads, buildings, grass and trees and compared to two commonly used object-based classifiers—k-Nearest Neighbor (k-NN and Support Vector Machine (SVM. Both proposed classifiers showed a slight improvement in the overall classification accuracies and produced more accurate classification maps when compared to the ground truth image.

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

    International Nuclear Information System (INIS)

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

  8. Object-based approach to national land cover mapping using HJ satellite imagery

    Science.gov (United States)

    Zhang, Lei; Li, Xiaosong; Yuan, Quanzhi; Liu, Yu

    2014-01-01

    To meet the carbon storage estimate in ecosystems for a national carbon strategy, we introduce a consistent database of China land cover. The Chinese Huan Jing (HJ) satellite is proven efficient in the cloud-free acquisition of seasonal image series in a monsoon region and in vegetation identification for mesoscale land cover mapping. Thirty-eight classes of level II land cover are generated based on the Land Cover Classification System of the United Nations Food and Agriculture Organization that follows a standard and quantitative definition. Twenty-four layers of derivative spectral, environmental, and spatial features compose the classification database. Object-based approach characterizing additional nonspectral features is conducted through mapping, and multiscale segmentations are applied on object boundary match to target real-world conditions. This method sufficiently employs spatial information, in addition to spectral characteristics, to improve classification accuracy. The algorithm of hierarchical classification is employed to follow step-by-step procedures that effectively control classification quality. This algorithm divides the dual structures of universal and local trees. Consistent universal trees suitable to most regions are performed first, followed by local trees that depend on specific features of nine climate stratifications. The independent validation indicates the overall accuracy reaches 86%.

  9. A Step Forward To Component-based Software Cost Estimation in Object-oriented Environment

    CERN Document Server

    Ahmed, Nadeem; Qureshi, M Rizwan Jameel

    2012-01-01

    Software cost estimation (SCE) of a project is pivotal to the acceptance or rejection of the development of software project. Various SCE techniques have been in practice with their own strengths and limitations. The latest of these is object-oriented one. Currently object-oriented approach for SCE is based on Line of Code (LOC), function points, functions and classes etc. Relatively less attention has been paid to the SCE in component-based software engineering (CBSE). So there is a pressing need to search parameters/variables that have a vital role for the SCE using CBSE which is taken up in this paper. This paper further looks at level of significance of all the parameters/variables thus searched. The time is being used as an independent variable because time is a parameter which is almost, all previous in one. Therefore this approach may be in a way an alternate of all previous approaches. Infact the underlying research ultimately may lead towards SCE of complex systems, using CBSE, in a scientific, syste...

  10. Evidence-based robust design of deflection actions for near Earth objects

    Science.gov (United States)

    Zuiani, Federico; Vasile, Massimiliano; Gibbings, Alison

    2012-10-01

    This paper presents a novel approach to the robust design of deflection actions for near Earth objects (NEO). In particular, the case of deflection by means of solar-pumped laser ablation is studied here in detail. The basic idea behind laser ablation is that of inducing a sublimation of the NEO surface, which produces a low thrust thereby slowly deviating the asteroid from its initial Earth threatening trajectory. This work investigates the integrated design of the space-based laser system and the deflection action generated by laser ablation under uncertainty. The integrated design is formulated as a multi-objective optimisation problem in which the deviation is maximised and the total system mass is minimised. Both the model for the estimation of the thrust produced by surface laser ablation and the spacecraft system model are assumed to be affected by epistemic uncertainties (partial or complete lack of knowledge). Evidence Theory is used to quantify these uncertainties and introduce them in the optimisation process. The propagation of the trajectory of the NEO under the laser-ablation action is performed with a novel approach based on an approximated analytical solution of Gauss' variational equations. An example of design of the deflection of asteroid Apophis with a swarm of spacecraft is presented.

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

    Science.gov (United States)

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

    2015-04-01

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

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

    OpenAIRE

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

    2008-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Taylor Sawyer

    2011-03-01

    Full Text Available The Accreditation Council for Graduate Medical Education (ACGME requires U.S. physician training programs to teach and evaluate their trainees in six core competencies. Developing innovative methods to meet the ACGME requirements is an ongoing area of research in medical education. Here we describe the development of the Competency-based Objective Resident Education using Virtual Patients (CORE-VP system, a web-based virtual patient simulator to teach and measure the ACGME core competencies. The user interface was built on Wavemaker technology including AJAX and javascript. A Flash component allows graphical navigation of the physical exam and linking of digital images and video to desired anatomic areas. The system contains tools for case authorship, management and execution and permits linking of files or web-based hypermedia content. Each case is designed to mimic a real-life patient encounter and includes history, physical exam, laboratory/ radiology, diagnosis and management. Automa­ted, multi-factorial, evaluation metrics were developed for each ACGME core competency. Upon completion of a case trainees receive immediate feedback in the form of an automated Performance Summary. We have developed a web-based virtual patient simulator called CORE-VP to teach and measure the ACGME core competencies. Work is currently underway to test and validate the system.

  14. Design based Object-Oriented Metrics to Measure Coupling and Cohesion

    Directory of Open Access Journals (Sweden)

    PREETI GULIA

    2011-11-01

    Full Text Available The object oriented design and object oriented development environment are currently popular in software organizations due to the object oriented programming languages. As the object oriented technology enters into software organizations, it has created new challenges for the companies which used only product metrics as atool for monitoring, controlling and maintaining the software product. This paper presents the new object oriented metrics namely for coupling of class by counting the number of associated classes within a class & total associated class and cohesion at the method and function level for cohesion to estimates object oriented software. In order to this, we discuss in this paper object oriented issues and measures with analysis of object oriented metrics through coupling and cohesion to check the complexity with weight count method. We also discuses the estimation process after analysis of proposed object oriented metrics to measures and check the better performance of object oriented metrics in comparison to other object oriented metrics.

  15. Mapping Arctic Ocean Coastline Change With Landsat Archive Data And Object-Based Image Analysis

    Science.gov (United States)

    Hulslander, D.

    2010-12-01

    The melting of arctic permafrost is a significant effect of climate change. The combination of rising sea level, longer periods of ice-free conditions in the Arctic Ocean and melting permafrost can greatly accelerate coastline changes in general and arctic coastal erosion in particular. Anderson et al. (2009; Geology News) have measured erosion rates of 15 m per year at sites along the Alaskan Arctic Ocean coastline dominated by ice-cemented peats and silt-rich permafrost. With over 45,000 km of Arctic Ocean coastline, it is important that coastline movement and transgressive oceanic regimes be mapped and tracked with accurate data. Determining historic coastal erosion rates for this region is as important as mapping the current extent of the phenomenon to create as complete a picture as possible and locate where rapid erosion is an emergent process. The extent of the area involved combined with its inaccessibility and inhospitable conditions makes geologic remote sensing an appropriate tool for characterizing Arctic Ocean coastal erosion. Traditional weaknesses associated with using remote sensing in the geosciences have included a lack of historical data or baseline information as well as difficulties in systematization of feature mapping. Using object-based image analysis on Landsat archive data can overcome these issues and may allow for a potential multi-decadal map of Arctic Ocean coastline changes. The Landsat family of sensors (MSS 1-3 and TM/ETM 4, 5, and 7) have been providing imagery as frequently as every 16 days since July 1972. The frequent revisits maximize the chance of getting cloud-free imagery at least once per year in most study areas. Also, Landsat data are well characterized, extensively studied, and freely available from the USGS EROS Data Center Archive, making it an ideal and stable source of data for mapping the Arctic Ocean coastline. Delineating large sections of coastline from imagery by hand digitization would be impractical due to the time, labor and expense involved with manual polyline and map layer creation. Furthermore, differences in interpretation by analysts can create data quality and reliability issues. Object-based image analysis techniques have been shown (Hulslander et al., 2008; GEOBIA 2008 Proceedings) to produce results comparable to those from analysts, but can also do so in a reproducible fashion that can be automated. Here, results indicate that using object-based image analysis on Landsat archive data can produce coastline maps in the arctic which clearly show coastline dynamics and trends over decades. Furthermore, these preliminary results also show that a pan-Arctic Ocean coastline map could be produced on a roughly triennial basis for the past 30-plus years using these techniques.

  16. Motor imagery vs. object-based visual imagery in adolescents with Autism Spectrum Disorder.

    Science.gov (United States)

    Chen, Ya-Ting; Chen, Hao-Ling; Tsou, Kuo-Su; Wong, Ching-Ching; Fang, Yang-Tan; Wu, Chien-Te

    2015-09-01

    Mental representation of actions is one of the essential components for social interaction and communication, and quite a few studies propose that social cognition deficits observed in ASD can be attributed to their aberrant action representation. Nevertheless, the hypothesis remains inconclusive primarily because most previous studies address this issue either through motor imitation that is contaminated by the requirement of overt motor replication, or through passive action observation that lacks active manipulation of action representation. In the current study, we aimed to investigate the characteristics of action representation in adolescents with ASD through motor imagery (MI) that requires both active manipulation and embodiments of action representation. We recruited 22 participants with ASD and 22 typically developing controls (TDC) to perform a hand-rotation and an object-rotation task. In the hand-rotation task (involves kinesthetic MI), participants were required to judge the laterality of a 3-D model image of a bare-hand (the transitive condition) or a hand-with-spoon (the intransitive condition) that rotates with different angles. In the object rotation task (involves object-based visual imagery), they were required to judge whether the drawer is on the right or on the left side of a desk that also rotates with different angles. Our results reveal that the two groups performed both tasks with compatible accuracy, but ASD is significantly slower than TDC only in the hand rotation task. Furthermore, both groups showed significant biomechanical constraint effects, indicating the usage of kinesthetic MI during the hand rotation task. Our findings suggest inefficient but not dysfunctional kinesthetic MI in individuals with ASD, an implication of preserved action representation. Unlike several previous findings in which ASD tends to use visual-spatial strategy to solve mental rotations of body parts, our data show that they can still spontaneously use kinesthetic MI when necessary. Meeting abstract presented at VSS 2015. PMID:26326330

  17. Cyndi: a multi-objective evolution algorithm based method for bioactive molecular conformational generation

    Directory of Open Access Journals (Sweden)

    Li Honglin

    2009-03-01

    Full Text Available Abstract Background Conformation generation is a ubiquitous problem in molecule modelling. Many applications require sampling the broad molecular conformational space or perceiving the bioactive conformers to ensure success. Numerous in silico methods have been proposed in an attempt to resolve the problem, ranging from deterministic to non-deterministic and systemic to stochastic ones. In this work, we described an efficient conformation sampling method named Cyndi, which is based on multi-objective evolution algorithm. Results The conformational perturbation is subjected to evolutionary operation on the genome encoded with dihedral torsions. Various objectives are designated to render the generated Pareto optimal conformers to be energy-favoured as well as evenly scattered across the conformational space. An optional objective concerning the degree of molecular extension is added to achieve geometrically extended or compact conformations which have been observed to impact the molecular bioactivity (J Comput -Aided Mol Des 2002, 16: 105–112. Testing the performance of Cyndi against a test set consisting of 329 small molecules reveals an average minimum RMSD of 0.864 Å to corresponding bioactive conformations, indicating Cyndi is highly competitive against other conformation generation methods. Meanwhile, the high-speed performance (0.49 ± 0.18 seconds per molecule renders Cyndi to be a practical toolkit for conformational database preparation and facilitates subsequent pharmacophore mapping or rigid docking. The copy of precompiled executable of Cyndi and the test set molecules in mol2 format are accessible in Additional file 1. Conclusion On the basis of MOEA algorithm, we present a new, highly efficient conformation generation method, Cyndi, and report the results of validation and performance studies comparing with other four methods. The results reveal that Cyndi is capable of generating geometrically diverse conformers and outperforms other four multiple conformer generators in the case of reproducing the bioactive conformations against 329 structures. The speed advantage indicates Cyndi is a powerful alternative method for extensive conformational sampling and large-scale conformer database preparation.

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

    DEFF Research Database (Denmark)

    Dickey-Collas, M.; Engelhard, G. H.

    2014-01-01

    The North Sea provides a useful model for considering forage fish (FF) within ecosystem-based management as it has a complex assemblage of FF species. This paper is designed to encourage further debate and dialogue between stakeholders about management objectives. Changing the management of fisheries on FF will have economic consequences for all fleets in the North Sea. The predators that are vulnerable to the depletion of FF are Sandwich terns, great skua and common guillemots, and to a lesser extent, marine mammals. Comparative evaluations of management strategies are required to consider whether maintaining the reserves of prey biomass or a more integral approach of monitoring mortality rates across the trophic system is more robust under the ecosystem approach. In terms of trophic energy transfer, stability, and resilience of the ecosystem, FF should be considered as both a sized-based pool of biomass and as species components of the system by managers and modellers. Policy developers should not consider the knowledge base robust enough to embark on major projects of ecosystem engineering. Management plans appear able to maintain sustainable exploitation in the short term. Changes in the productivity of FF populations are inevitable so management should remain responsive and adaptive.

  19. Task Scheduling Model Based on Multi-Agent and Multi-Objective Dynamical Scheduling Algorithm

    Directory of Open Access Journals (Sweden)

    Zhanjie Wang

    2014-06-01

    Full Text Available With the increasing number of nodes in distributed systems, the complexity of task scheduling also increases. Therefore, how to schedule tasks reasonably is becoming more and more significant. Most traditional algorithms only consider a single condition without thinking over dynamic characteristic of system and tasks and lack of comprehensive measures. Therefore they cannot meet the needs of distributed systems. To solve these problems, we establish a distributed task scheduling model based on multi-agent in this paper, build a negotiation scheduling mechanism based on the model and propose distributed multi-objective dynamical scheduling algorithm (DMOD. In the algorithm, each node is capable of independent decision-making and dynamical evaluation rules make a comprehensive evaluation of task completion time, system load and communication traffic. DMOD, MinMin and the algorithm based on tree structure (BTS are compared through simulation experiments. Experimental results show that DMOD reduces communication traffic without increasing task completion time, avoids performance degradation caused by sharp increase of system load and communication traffic in distributed system and therefore improves system stability and task execution efficiency

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

    Science.gov (United States)

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

    2015-01-01

    Phase-retrieval problems of one-dimensional (1D) signals are known to suffer from ambiguity that hampers their recovery from measurements of their Fourier magnitude, even when their support (a region that confines the signal) is known. Here we demonstrate sparsity-based coherent diffraction imaging of 1D objects using extreme-ultraviolet radiation produced from high harmonic generation. Using sparsity as prior information removes the ambiguity in many cases and enhances the resolution beyond the physical limit of the microscope. Our approach may be used in a variety of problems, such as diagnostics of defects in microelectronic chips. Importantly, this is the first demonstration of sparsity-based 1D phase retrieval from actual experiments, hence it paves the way for greatly improving the performance of Fourier-based measurement systems where 1D signals are inherent, such as diagnostics of ultrashort laser pulses, deciphering the complex time-dependent response functions (for example, time-dependent permittivity and permeability) from spectral measurements and vice versa. PMID:26345495

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

    DEFF Research Database (Denmark)

    Dickey-Collas, Mark; Engelhard, Georg H.

    2014-01-01

    The North Sea provides a useful model for considering forage fish (FF) within ecosystem-based management as it has a complex assemblage of FF species. This paper is designed to encourage further debate and dialogue between stakeholders about management objectives. Changing the management of fisheries on FF will have economic consequences for all fleets in the North Sea. The predators that are vulnerable to the depletion of FF are Sandwich terns, great skua and common guillemots, and to a lesser extent, marine mammals. Comparative evaluations of management strategies are required to consider whether maintaining the reserves of prey biomass or a more integral approach of monitoring mortality rates across the trophic system is more robust under the ecosystem approach. In terms of trophic energy transfer, stability, and resilience of the ecosystem, FF should be considered as both a sized-based pool of biomass and as species components of the system by managers and modellers. Policy developers should not consider the knowledge base robust enough to embark on major projects of ecosystem engineering. Management plans appear able to maintain sustainable exploitation in the short term. Changes in the productivity of FF populations are inevitable so management should remain responsive and adaptive

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

    International Nuclear Information System (INIS)

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

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

    Directory of Open Access Journals (Sweden)

    Billur Barshan

    2008-12-01

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

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

    Science.gov (United States)

    Barshan, Billur

    2008-01-01

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

  5. Inference and Plausible Reasoning in a Natural Language Understanding System Based on Object-Oriented Semantics

    CERN Document Server

    Ostapov, Yuriy

    2012-01-01

    Algorithms of inference in a computer system oriented to input and semantic processing of text information are presented. Such inference is necessary for logical questions when the direct comparison of objects from a question and database can not give a result. The following classes of problems are considered: a check of hypotheses for persons and non-typical actions, the determination of persons and circumstances for non-typical actions, planning actions, the determination of event cause and state of persons. To form an answer both deduction and plausible reasoning are used. As a knowledge domain under consideration is social behavior of persons, plausible reasoning is based on laws of social psychology. Proposed algorithms of inference and plausible reasoning can be realized in computer systems closely connected with text processing (criminology, operation of business, medicine, document systems).

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

    CERN Document Server

    Ostapov, Yuriy

    2011-01-01

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

  7. Object-Oriented Technology-Based Software Library for Operations of Water Reclamation Centers

    Science.gov (United States)

    Otani, Tetsuo; Shimada, Takehiro; Yoshida, Norio; Abe, Wataru

    SCADA systems in water reclamation centers have been constructed based on hardware and software that each manufacturer produced according to their design. Even though this approach used to be effective to realize real-time and reliable execution, it is an obstacle to cost reduction about system construction and maintenance. A promising solution to address the problem is to set specifications that can be used commonly. In terms of software, information model approach has been adopted in SCADA systems in other field, such as telecommunications and power systems. An information model is a piece of software specification that describes a physical or logical object to be monitored. In this paper, we propose information models for operations of water reclamation centers, which have not ever existed. In addition, we show the feasibility of the information model in terms of common use and processing performance.

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

    Directory of Open Access Journals (Sweden)

    Ashraf A. Shahin

    2015-04-01

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

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

    Science.gov (United States)

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

    2008-03-01

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

  10. Differentiating spatial and object-based effects on attention: an event-related brain potential study with peripheral cueing.

    OpenAIRE

    He, X.; Humphreys, G; Fan, S; Chen, L; Han, S.

    2008-01-01

    Do spatial attention and object attention modulate visual processing in similar ways? Previously we have found a dissociation between these two forms of attention on ERP measures of sensory processing under conditions of peripheral cueing, with spatial attention effects associated with changes over anterior scalp regions and object attention effects associated with changes over posterior regions (He, X., Fan, S., Zhou, K., Chen, L., 2004. Cue validity and object-based attention. J. Cogn. Neur...

  11. Analysis of uncertainty in multi-temporal object-based classification

    Science.gov (United States)

    Löw, Fabian; Knöfel, Patrick; Conrad, Christopher

    2015-07-01

    Agricultural management increasingly uses crop maps based on classification of remotely sensed data. However, classification errors can translate to errors in model outputs, for instance agricultural production monitoring (yield, water demand) or crop acreage calculation. Hence, knowledge on the spatial variability of the classier performance is important information for the user. But this is not provided by traditional assessments of accuracy, which are based on the confusion matrix. In this study, classification uncertainty was analyzed, based on the support vector machines (SVM) algorithm. SVM was applied to multi-spectral time series data of RapidEye from different agricultural landscapes and years. Entropy was calculated as a measure of classification uncertainty, based on the per-object class membership estimations from the SVM algorithm. Permuting all possible combinations of available images allowed investigating the impact of the image acquisition frequency and timing, respectively, on the classification uncertainty. Results show that multi-temporal datasets decrease classification uncertainty for different crops compared to single data sets, but there was no "one-image-combination-fits-all" solution. The number and acquisition timing of the images, for which a decrease in uncertainty could be realized, proved to be specific to a given landscape, and for each crop they differed across different landscapes. For some crops, an increase of uncertainty was observed when increasing the quantity of images, even if classification accuracy was improved. Random forest regression was employed to investigate the impact of different explanatory variables on the observed spatial pattern of classification uncertainty. It was strongly influenced by factors related with the agricultural management and training sample density. Lower uncertainties were revealed for fields close to rivers or irrigation canals. This study demonstrates that classification uncertainty estimates by the SVM algorithm provide a valuable addition to traditional accuracy assessments. This allows analyzing spatial variations of the classifier performance in maps and also differences in classification uncertainty within the growing season and between crop types, respectively.

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

    Directory of Open Access Journals (Sweden)

    M. T. L. Estomata

    2012-07-01

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

  13. Estimation of Trees Outside Forests using IRS High Resolution data by Object Based Image Analysis

    Science.gov (United States)

    Pujar, G. S.; Reddy, P. M.; Reddy, C. S.; Jha, C. S.; Dadhwal, V. K.

    2014-11-01

    Assessment of Trees outside forests (TOF) is widely being recognized as a pivotal theme, in sustainable natural resource management, due to their role in offering variety of goods, such as timber, fruits and fodder as well as services like water, carbon, biodiversity. Forest Conservation efforts involving reduction of deforestation and degradation may have to increasingly rely on alternatives provided by TOF in catering to economic demands in forest edges. Spatial information systems involving imaging, analysis and monitoring to achieve objectives under protocols like REDD+, require incorporation of information content from areas under forest as well as trees outside forests, to aid holistic decisions. In this perspective, automation in retrieving information on area under trees, growing outside forests, using high resolution imaging is essential so that measuring and verification of extant carbon pools, are strengthened. Retrieval of this tree cover is demonstrated herewith, using object based image analysis in a forest edge of dry deciduous forests of Eastern Ghats, in Khammam district of Telangana state of India. IRS high resolution panchromatic 2.5 m data (Cartosat-1 Orthorectified) used in tandem with 5.8 m multispectral LISS IV data, discerns tree crowns and clusters at a detailed scale and hence semi-automated approach is attempted to classify TOF from a pair of image from relatively crop and cloud free season. Object based image analysis(OBIA) approach as implemented in commercial suite of e-Cognition (Ver 8.9) consists of segmentation at user defined scale followed by application of wide range of spectral, textural and object geometry based parameters for classification. Software offers innovative blend of raster and vector features that can be juxtaposed flexibly, across scales horizontally or vertically. Segmentation was carried out at multiple scales to discern first the major land covers, such as forest, water, agriculture followed by that at a finer scale, within cultivated landscape. Latter scale aimed to segregate TOF in configurations such as individual or scattered crowns, linear formations and patch TOF. As per the adopted norms in India for defining tree cover, units up to 1 ha area were considered as candidate TOF. Classification of fine scale (at 10) segments was accomplished using size, shape and texture. A customised parameter involving ratio of area of segment to its main skeleton length discerned linear formations consistently. Texture of Cartosat-1 2.5 m data was also used segregate tree cover from smoother crop patches in patch TOF category. In view of the specificity of the landscape character, continuum of cultivated area (b) and pockets of cultivation within forest (c) as well as the entire study area (a) were considered as three envelopes for evaluating the accuracy of the method. Accuracies not less than 75.1 per cent were reported in all the envelopes with a kappa accuracy of not less than 0.58. Overall accuracy of entire study area was 75.9 per cent with Kappa of 0.59 followed by 75.1 per cent ( Kappa: 0.58 ) of agricultural landscape (b). In pockets of cultivation context(c) accuracy was higher at 79.2 per cent ( Kappa: 0.64 ) possibly due to smaller population. Assessment showed that 1,791 ha of 24,140 ha studied (7.42 %) was under tree cover as per the definitions adopted. Strength of accuracy demonstrated obviously points to the potential of IRS high resolution data combination in setting up procedures to monitor the TOF in Indian context using OBIA approach so as to cater to the evolving demands of resource assessment and monitoring.

  14. Mapping gully-affected areas in the region of Taroudannt, Morocco based on Object-Based Image Analysis (OBIA)

    Science.gov (United States)

    d'Oleire-Oltmanns, Sebastian; Marzolff, Irene; Tiede, Dirk; Blaschke, Thomas

    2015-04-01

    The need for area-wide landform mapping approaches, especially in terms of land degradation, can be ascribed to the fact that within area-wide landform mapping approaches, the (spatial) context of erosional landforms is considered by providing additional information on the physiography neighboring the distinct landform. This study presents an approach for the detection of gully-affected areas by applying object-based image analysis in the region of Taroudannt, Morocco, which is highly affected by gully erosion while simultaneously representing a major region of agro-industry with a high demand of arable land. Various sensors provide readily available high-resolution optical satellite data with a much better temporal resolution than 3D terrain data which lead to the development of an area-wide mapping approach to extract gully-affected areas using only optical satellite imagery. The classification rule-set was developed with a clear focus on virtual spatial independence within the software environment of eCognition Developer. This allows the incorporation of knowledge about the target objects under investigation. Only optical QuickBird-2 satellite data and freely-available OpenStreetMap (OSM) vector data were used as input data. The OSM vector data were incorporated in order to mask out plantations and residential areas. Optical input data are more readily available for a broad range of users compared to terrain data, which is considered to be a major advantage. The methodology additionally incorporates expert knowledge and freely-available vector data in a cyclic object-based image analysis approach. This connects the two fields of geomorphology and remote sensing. The classification results allow conclusions on the current distribution of gullies. The results of the classification were checked against manually delineated reference data incorporating expert knowledge based on several field campaigns in the area, resulting in an overall classification accuracy of 62%. The error of omission accounts for 38% and the error of commission for 16%, respectively. Additionally, a manual assessment was carried out to assess the quality of the applied classification algorithm. The limited error of omission contributes with 23% to the overall error of omission and the limited error of commission contributes with 98% to the overall error of commission. This assessment improves the results and confirms the high quality of the developed approach for area-wide mapping of gully-affected areas in larger regions. In the field of landform mapping, the overall quality of the classification results is often assessed with more than one method to incorporate all aspects adequately.

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

    Science.gov (United States)

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

    2015-10-01

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

  16. A modified teaching–learning based optimization for multi-objective optimal power flow problem

    International Nuclear Information System (INIS)

    Highlights: • A new modified teaching–learning based algorithm is proposed. • A self-adaptive wavelet mutation strategy is used to enhance the performance. • To avoid reaching a large repository size, a fuzzy clustering technique is used. • An efficiently smart population selection is utilized. • Simulations show the superiority of this algorithm compared with other ones. - Abstract: In this paper, a modified teaching–learning based optimization algorithm is analyzed to solve the multi-objective optimal power flow problem considering the total fuel cost and total emission of the units. The modified phase of the optimization algorithm utilizes a self-adapting wavelet mutation strategy. Moreover, a fuzzy clustering technique is proposed to avoid extremely large repository size besides a smart population selection for the next iteration. These techniques make the algorithm searching a larger space to find the optimal solutions while speed of the convergence remains good. The IEEE 30-Bus and 57-Bus systems are used to illustrate performance of the proposed algorithm and results are compared with those in literatures. It is verified that the proposed approach has better performance over other techniques

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

    Directory of Open Access Journals (Sweden)

    Cheng Lin

    2015-04-01

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

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

    Science.gov (United States)

    Wang, Bin; Zhao, Yue-jin

    2008-12-01

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

  19. Discussion of related problems in herbal prescription science based on objective indications of herbs

    Directory of Open Access Journals (Sweden)

    Xing-jiang XIONG

    2010-01-01

    Full Text Available Herbal prescription science is a bridge between basic and clinical subjects in traditional Chinese medicine (TCM. In studying the doctrines in the general textbook Herbal Prescription Science and applying them to clinical practice, it was found that they are imprecise and inapplicable. Based on the analysis of Suanzaoren Decoction, Xiaoqinglong Decoction, Jichuan Decoction, etc., the authors point out that this problem is due to the current pathogenesis-based research approach of the herbal prescription science. It is proposed that correspondence between formula and syndrome is the core of the herbal prescription science. In order to solve such a problem, searching for corresponding relationship between an herb or a formula and the signs and symptoms of a syndrome or disease should be the most important task in research of herbal prescription science, for emphasis on attention to the objective indications and evidence in clinical utilization of herbal formulas is the major feature of the herbal prescription science according to medication experience in the long history of TCM.

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

    International Nuclear Information System (INIS)

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

  1. Colour-based Object Detection and Tracking for Autonomous Quadrotor UAV

    Science.gov (United States)

    Kadouf, Hani Hunud A.; Mohd Mustafah, Yasir

    2013-12-01

    With robotics becoming a fundamental aspect of modern society, further research and consequent application is ever increasing. Aerial robotics, in particular, covers applications such as surveillance in hostile military zones or search and rescue operations in disaster stricken areas, where ground navigation is impossible. The increased visual capacity of UAV's (Unmanned Air Vehicles) is also applicable in the support of ground vehicles to provide supplies for emergency assistance, for scouting purposes or to extend communication beyond insurmountable land or water barriers. The Quadrotor, which is a small UAV has its lift generated by four rotors and can be controlled by altering the speeds of its motors relative to each other. The four rotors allow for a higher payload than single or dual rotor UAVs, which makes it safer and more suitable to carry camera and transmitter equipment. An onboard camera is used to capture and transmit images of the Quadrotor's First Person View (FPV) while in flight, in real time, wirelessly to a base station. The aim of this research is to develop an autonomous quadrotor platform capable of transmitting real time video signals to a base station for processing. The result from the image analysis will be used as a feedback in the quadrotor positioning control. To validate the system, the algorithm should have the capacity to make the quadrotor identify, track or hover above stationary or moving objects.

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

    International Nuclear Information System (INIS)

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

  3. Robust Stereo-Vision Based 3D Object Reconstruction for the Assistive Robot FRIEND

    OpenAIRE

    COJBASIC, Z.; Graser, A; GRIGORESCU, S. M.; RISTIC-DURRANT, D.; NIKOLIC, V.

    2011-01-01

    A key requirement of assistive robot vision is the robust 3D object reconstruction in complex environments for reliable autonomous object manipulation. In this paper the idea is presented of achieving high robustness of a complete robot vision system against external influences such as variable illumination by including feedback control of the object segmentation in stereo images. The approach used is to change the segmentation parameters in closed-loop so that object features extraction ...

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

    Science.gov (United States)

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

    2015-11-01

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

  5. Evaluation of Sustainable Development Indicators With Fuzzy TOPSIS Based on Subjective and Objective Weights

    Directory of Open Access Journals (Sweden)

    Nang Idayu Nik Zahari

    2012-04-01

    Full Text Available ABSTRACT: Sustainable development aims at improving and maintaining the well-being of people and the ecology. However, this paper focuses only on the ecological aspects. The selection of the proper ecological protection determinant plays a very important role in improving the environment of Malaysia. This paper will propose a method from Wang and Lee (2009, and Yong (2006 which applies a fuzzy TOPSIS method -- based on subjective and objective weights – to make the required selection. Four alternatives will be tested which are: prevent pollution (A1, conservation (A2, well-manage (A3, and public awareness (A4. Along with these, four criteria need to be considered: water quality factor (C1, land integrity factor (C2, air quality factor (C3, and biodiversity factor (C4. Finally, a numerical example of ecological protection determinant selection is used to illustrate the proposed method. ABSTRAK: Pembangunan lestari bermatlamat memperbaiki dan mengekalkan kesejahteraan rakyat serta ekologi. Walau bagaimanapun, kertas kajian ini hanya memberi tumpuan kepada aspek-aspek ekologi. Pemilihan penentu perlindungan serta keselamatan bagi aspek ekologi memainkan peranan yang amat penting dalam meningkatkan kualiti alam sekitar di Malaysia. Kertas kajian ini telah menggunakan kaedah Wang dan Lee (2009 dan Yong (2006 yang mengaplikasikan kaedah TOPSIS kabur berdasarkan pemberat subjektif dan objektif. Terdapat empat alternatif yang akan diuji iaitu: pencegahan pencemaran (A1, pemuliharaan (A2, pengurusan yang baik (A3, kesedaran orang awam (A4. Selain itu, terdapat empat kriteria yang perlu dipertimbangkan: faktor kualiti air (C1, faktor kualiti tanah (C2, faktor kualiti udara (C3, faktor kepelbagaian biologi (C4. Kesimpulannya, contoh pengiraan untuk memperoleh penentu pemilihan perlindungan ekologi telah digunakan bagi menunjukkan kaedah yang dicadangkan.KEYWORDS: sustainable development; ecological factors; subjective and objective weight; fuzzy TOPSIS

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

    Science.gov (United States)

    Hund, Alycia M.; Foster, Emily K.

    2008-01-01

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

  7. The Effects of Attention Pre-Allocation and Target-Background Integration on Object-Based Attention

    OpenAIRE

    Hu, Fengpei; Jiao, Changyong; Zhao, Songpo; Dong, Huahua; LIU, XIAO; Yi, Yuji; Wang, Jun

    2015-01-01

    Object-based attention has been documented as an important mechanism with which to control attention in several studies. To date, two main hypotheses have been proposed to interpret object-based attention: attention spreading and prioritization of search. There is evidence that supports these hypotheses in the literature. In the present study, we sought to compare these two hypotheses systematically by manipulating two factors: the integration of the target and background and the presence of ...

  8. A Geographical Information Systems for Transportation (GIS-T) Object Based Data Model for Road Infrastructure Maintenance in Uganda

    OpenAIRE

    Ndandiko, Lydia

    2013-01-01

    This paper presents an object based Geographical Information Systems for Transportation (GIS-T) data model for road maintenance in Uganda. It is a result of a PhD undertaking whose main objective was to develop a framework within which the use of Geographic Information Technologies could be enhanced as decision support tools for road infrastructure maintenance in Uganda. The model is based on data requirements of the road maintenance sector and is a means towards estab...

  9. IMAGING-BASED OPTICAL CALIPER FOR OBJECTS IN HOT MANUFACTURING PROCESSES

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Howard

    2013-04-03

    OG Technologies, Inc. (OGT), in conjunction with its industrial and academic partners, proposes to develop an �Imaging-Based Optical Caliper (hereafter referred to as �OC�) for Objects in Hot Manufacturing Processes�. The goal is to develop and demonstrate the OC with the synergy of OGT�s current technological pool and other innovations to provide a light weight, robust, safe and accurate portable dimensional measurement device for hot objects with integrated wireless communication capacity to enable real time process control. The technical areas of interest in this project are the combination of advanced imaging, Sensor Fusion, and process control. OGT believes that the synergistic interactions between its current set of technologies and other innovations could deliver products that are viable and have high impact in the hot manufacture processes, such as steel making, steel rolling, open die forging, and glass industries, resulting in a new energy efficient control paradigm in the operations through improved yield, prolonged tool life and improved quality. In-line dimension measurement and control is of interest to the steel makers, yet current industry focus is on the final product dimension only instead of whole process due to the limit of man power, system cost and operator safety concerns. As sensor technologies advances, the industry started to see the need to enforce better dimensional control throughout the process, but lack the proper tools to do so. OGT along with its industrial partners represent the indigenous effort of technological development to serve the US steel industry. The immediate market that can use and get benefited from the proposed OC is the Steel Industry. The deployment of the OC has the potential to provide benefits in reduction of energy waste, CO2 emission, waste water amount, toxic waste, and so forth. The potential market after further expended function includes Hot Forging and Freight Industries. The OC prototypes were fabricated, and were progressively tested on-site in several steel mill and hot forging facilities for evaluation. Software refinements and new calibration procedures were also carried out to overcome the discovered glitches. Progress was presented to the hot manufacture facilities worldwide. Evidence showed a great interest and practical need for this product. OGT is in the pilot commercialization mode for this new development. The R&D team also successfully developed a 3D measurement function with no additional investment of hardware or equipment to measure low or room temperature object dimensions. Several tests were conducted in the reality environment to evaluate the measurement results. This new application will require additional development in product design.

  10. Development of a Relap based Nuclear Plant Analyser with 3-D graphics using OpenGL and Object Relap

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Young Jin [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2010-10-15

    A 3-D Graphic Nuclear Plant Analyzer (NPA) program was developed using GLScene and the TRelap. GLScene is an OpenGL based 3D graphics library for the Delphi object-oriented program language, and it implements the OpenGL functions in forms suitable for programming with Delphi. TRelap is an object wrapper developed by the author to easily implement the Relap5 thermal hydraulic code under object oriented programming environment. The 3-D Graphic NPA was developed to demonstrate the superiority of the object oriented programming approach in developing complex programs

  11. Error analysis of marker-based object localization using a single-plane XRII

    International Nuclear Information System (INIS)

    The role of imaging and image guidance is increasing in surgery and therapy, including treatment planning and follow-up. Fluoroscopy is used for two-dimensional (2D) guidance or localization; however, many procedures would benefit from three-dimensional (3D) guidance or localization. Three-dimensional computed tomography (CT) using a C-arm mounted x-ray image intensifier (XRII) can provide high-quality 3D images; however, patient dose and the required acquisition time restrict the number of 3D images that can be obtained. C-arm based 3D CT is therefore limited in applications for x-ray based image guidance or dynamic evaluations. 2D-3D model-based registration, using a single-plane 2D digital radiographic system, does allow for rapid 3D localization. It is our goal to investigate - over a clinically practical range - the impact of x-ray exposure on the resulting range of 3D localization precision. In this paper it is assumed that the tracked instrument incorporates a rigidly attached 3D object with a known configuration of markers. A 2D image is obtained by a digital fluoroscopic x-ray system and corrected for XRII distortions (±0.035 mm) and mechanical C-arm shift (±0.080 mm). A least-square projection-Procrustes analysis is then used to calculate the 3D position using the measured 2D marker locations. The effect of x-ray exposure on the precision of 2D marker localization and on 3D object localization was investigated using numerical simulations and x-ray experiments. The results show a nearly linear relationship between 2D marker localization precision and the 3D localization precision. However, a significant amplification of error, nonuniformly distributed among the three major axes, occurs, and that is demonstrated. To obtain a 3D localization error of less than ±1.0 mm for an object with 20 mm marker spacing, the 2D localization precision must be better than ±0.07 mm. This requirement was met for all investigated nominal x-ray exposures at 28 cm FOV, and for all but the lowest two at 40 cm FOV. However, even for those two nominal exposures, the expected 3D localization error is less than ±1.2 mm. The tracking precision was ±0.65 mm for the out-of-plane translations, ±0.05 mm for in-plane translations, and ±0.05 deg. for the rotations. The root mean square (RMS) difference between the true and projection-Procrustes calculated location was 1.07 mm. It is believed these results show the potential of this technique for dynamic evaluations or real-time image guidance using a single x-ray source and XRII detector.

  12. Distribution Network Expansion Planning Based on Multi-objective PSO Algorithm

    DEFF Research Database (Denmark)

    Zhang, Chunyu; Ding, Yi

    2013-01-01

    This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO algorithm was proposed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the proposed multi-objective planning approach and the improved multi-objective PSO have been verified by the 18-node typical system.

  13. Object-based auditory facilitation of visual search for pictures and words with frequent and rare targets

    OpenAIRE

    Iordanescu, Lucica; Grabowecky, Marcia; Suzuki, Satoru

    2010-01-01

    Auditory and visual processes demonstrably enhance each other based on spatial and temporal coincidence. Our recent results on visual search have shown that auditory signals also enhance visual salience of specific objects based on multimodal experience. For example, we tend to see an object (e.g., a cat) and simultaneously hear its characteristic sound (e.g., “meow”), to name an object when we see it, and to vocalize a word when we read it, but we do not tend to see a word (e.g., cat) and si...

  14. Robust Mobile Object Tracking Based on Multiple Feature Similarity and Trajectory Filtering

    CERN Document Server

    Chau, Duc Phu; Thonnat, Monique; Corvee, Etienne

    2011-01-01

    This paper presents a new algorithm to track mobile objects in different scene conditions. The main idea of the proposed tracker includes estimation, multi-features similarity measures and trajectory filtering. A feature set (distance, area, shape ratio, color histogram) is defined for each tracked object to search for the best matching object. Its best matching object and its state estimated by the Kalman filter are combined to update position and size of the tracked object. However, the mobile object trajectories are usually fragmented because of occlusions and misdetections. Therefore, we also propose a trajectory filtering, named global tracker, aims at removing the noisy trajectories and fusing the fragmented trajectories belonging to a same mobile object. The method has been tested with five videos of different scene conditions. Three of them are provided by the ETISEO benchmarking project (http://www-sop.inria.fr/orion/ETISEO) in which the proposed tracker performance has been compared with other seven...

  15. Education and Professional Outreach for Scientists: Producing and Leveraging EPO Objects for Inquiry-Based Learning

    Science.gov (United States)

    Koppers, A. A.; Staudigel, H.

    2007-12-01

    Most Education and Professional Outreach (EPO) by scientists reaches relatively small audiences. Most scientists also see their contributions to K-12 teaching rather limited due to their lack of experience in primary and secondary school education. These limitations remain a major barrier in bridging the gap between science and education, and in optimizing the effectiveness of EPO by scientists. As part of the Enduring Resources for Earth Science Education (ERESE) project, we have started to use web- templates in our EPO creation (http://earthref.org/ERESE). These templates are now being developed into web- based tools and services that will be served from the ERESE website and archived by the National Science Digital Library (NSDL). At EarthRef.org these EPO objects can be linked to teaching materials in the ERDA digital archive that can be displayed in a fashion allowing selection based on expert level and file type, in what we dubbed the "resource matrix" view. This is a powerful search mechanism for learners of all levels in which they can pre-screen materials to their own level, while allowing them to venture up to higher expert levels or to explore more simple cases at lower levels. This stimulates inquiry- based learning by permitting as much roaming freedom as possible in a "science-data- based" online environment. The current EarthRef.org and ERESE collections include websites for scientific projects, for classes taught and for expeditions, as well as a wide range of materials including press releases, video footage, science illustrations, interviews, data and diagrams, student reports and lesson plans. This collection is representative for EPO in any STEM discipline and provides much interesting materials that are useful for education. Our main goal is to provide scientists with tools so they can obtain an easy-to-use and highly leveraged outlet for their EPO efforts, where they can reach substantial numbers of learners and educators, and where their materials are archived as enduring resources for re-use by many.

  16. Aquarius' Object-Oriented, Plug and Play Component-Based Flight Software

    Science.gov (United States)

    Murray, Alexander; Shahabuddin, Mohammad

    2013-01-01

    The Aquarius mission involves a combined radiometer and radar instrument in low-Earth orbit, providing monthly global maps of Sea Surface Salinity. Operating successfully in orbit since June, 2011, the spacecraft bus was furnished by the Argentine space agency, Comision Nacional de Actividades Espaciales (CONAE). The instrument, built jointly by NASA's Caltech/JPL and Goddard Space Flight Center, has been successfully producing expectation-exceeding data since it was powered on in August of 2011. In addition to the radiometer and scatterometer, the instrument contains an command & data-handling subsystem with a computer and flight software (FSW) that is responsible for managing the instrument, its operation, and its data. Aquarius' FSW is conceived and architected as a Component-based system, in which the running software consists of a set of Components, each playing a distinctive role in the subsystem, instantiated and connected together at runtime. Component architectures feature a well-defined set of interfaces between the Components, visible and analyzable at the architectural level (see [1]). As we will describe, this kind of an architecture offers significant advantages over more traditional FSW architectures, which often feature a monolithic runtime structure. Component-based software is enabled by Object-Oriented (OO) techniques and languages, the use of which again is not typical in space mission FSW. We will argue in this paper that the use of OO design methods and tools (especially the Unified Modeling Language), as well as the judicious usage of C++, are very well suited to FSW applications, and we will present Aquarius FSW, describing our methods, processes, and design, as a successful case in point.

  17. Incidental and context-responsive activation of structure- and function-based action features during object identification.

    Science.gov (United States)

    Lee, Chia-lin; Middleton, Erica; Mirman, Daniel; Kalénine, Solène; Buxbaum, Laurel J

    2013-02-01

    Previous studies suggest that action representations are activated during object processing, even when task-irrelevant. In addition, there is evidence that lexical-semantic context may affect such activation during object processing. Finally, prior work from our laboratory and others indicates that function-based ("use") and structure-based ("move") action subtypes may differ in their activation characteristics. Most studies assessing such effects, however, have required manual object-relevant motor responses, thereby plausibly influencing the activation of action representations. The present work uses eyetracking and a Visual World Paradigm task without object-relevant actions to assess the time course of activation of action representations, as well as their responsiveness to lexical-semantic context. In two experiments, participants heard a target word and selected its referent from an array of four objects. Gaze fixations on nontarget objects signal activation of features shared between targets and nontargets. The experiments assessed activation of structure-based (Experiment 1) or function-based (Experiment 2) distractors, using neutral sentences ("S/he saw the....") or sentences with a relevant action verb (Experiment 1: "S/he picked up the...."; Experiment 2: "S/he used the...."). We observed task-irrelevant activations of action information in both experiments. In neutral contexts, structure-based activation was relatively faster-rising but more transient than function-based activation. Additionally, action verb contexts reliably modified patterns of activation in both Experiments. These data provide fine-grained information about the dynamics of activation of function-based and structure-based actions in neutral and action-relevant contexts, in support of the "Two Action System" model of object and action processing (e.g., Buxbaum & Kalénine, 2010). PMID:22390294

  18. Interactive Application Development Policy Object 3D Virtual Tour History Pacitan District based Multimedia

    Directory of Open Access Journals (Sweden)

    Bambang Eka Purnama

    2013-04-01

    Full Text Available Pacitan has a wide range of tourism activity. One of the tourism district is Pacitan historical attractions. These objects have a history tour of the educational values, history and culture, which must be maintained and preserved as one tourism asset Kabupeten Pacitan. But the history of the current tour the rarely visited and some of the students also do not understand the history of each of these historical attractions. Hence made a information media of 3D virtual interactive applications Pacitan tour history in the form of interactive CD applications. The purpose of the creation of interactive applications is to introduce Pacitan history tours to students and the community. Creating interactive information media that can provide an overview of the history of the existing tourist sites in Pacitan The benefits of this research is the students and the public will get to know the history of historical attractions Pacitan. As a media introduction of historical attractions and as a medium of information to preserve the historical sights. Band is used in the manufacturing methods Applications 3D Virtual Interactive Attractions: History-Based Multimedia Pacitan authors used the method library, observation and interviews. Design using 3ds Max 2010, Adobe Director 11.5, Adobe Photoshop CS3 and Corel Draw. The results of this research is the creation of media interakif information that can provide knowledge about the history of Pacitan.

  19. Bi-Objective Optimization Based on Compromise Method for Horizontal Fragmentation in Relational Data Warehouses

    Directory of Open Access Journals (Sweden)

    Mohamed Barr

    2013-06-01

    Full Text Available Generally, research that dealt with the selection problems for optimization techniques or structures in relational data ware houses supports these problems by considering only a single criterion of optimization. The optimization criteria may be the response time of query execution, the number of inputs/outputs between the main memory and the disk, the space allocated to store the index or materialized views, or the number fragments required by the administrator of the data warehouse when using the fragmentation technique. The present work deals with the problem of selecting the horizontal fragmentation technique while considering both the number of I/O between memory and disk during decisional queries and the number of fragments, as two objective functions to minimize. To reduce the scope of choice solutions, we are based on a scalar method, called compromise method. The method is complemented by the principle of Pareto front to infer the best solutions. The study has been experimented on APB1 benchmark of data warehouse.

  20. Development of novel hybrid flexure-based microgrippers for precision micro-object manipulation.

    Science.gov (United States)

    Mohd Zubir, Mohd Nashrul; Shirinzadeh, Bijan; Tian, Yanling

    2009-06-01

    This paper describes the process of developing a microgripper that is capable of high precision and fidelity manipulation of micro-objects. The design adopts the concept of flexure-based hinges on its joints to provide the rotational motion, thus eliminating the inherent nonlinearities associated with the application of conventional rigid hinges. A combination of two modeling techniques, namely, pseudorigid body model and finite element analysis was utilized to expedite the prototyping procedure, which leads to the establishment of a high performance mechanism. A new hybrid compliant structure integrating cantilever beam and flexural hinge configurations within microgripper mechanism mainframe has been developed. This concept provides a novel approach to harness the advantages within each individual configuration while mutually compensating the limitations inherent between them. A wire electrodischarge machining technique was utilized to fabricate the gripper out of high grade aluminum alloy (Al 7075T6). Experimental studies were conducted on the model to obtain various correlations governing the gripper performance as well as for model verification. The experimental results demonstrate high level of compliance in comparison to the computational results. A high amplification characteristic and maximum achievable stroke of 100 microm can be achieved. PMID:19566225

  1. Cluster Analysis Algorithms Based on the Gradient Descent Procedure of a Fuzzy Objective Function

    Energy Technology Data Exchange (ETDEWEB)

    Rhee, H.S. [Dongyang Technology Junior College, Seoul (Korea, Republic of); Oh, K.W. [Sogang University, Seoul (Korea, Republic of)

    1997-12-01

    Fuzzy clustering has been playing an important role in solving many problems. Fuzzy c-Means(FCM) algorithm is most frequently used for fuzzy clustering. But some fixed point of FCM algorithm, known as Tucker`s counter example, is not a reasonable solution. Moreover, FCM algorithm is impossible to perform the on-line learning since it is basically a batch learning scheme. This paper presents unsupervised learning networks as an attempt to improve shortcomings of the conventional clustering algorithm. This model integrates optimization function of FCM algorithm into unsupervised learning networks. The learning rule of the proposed scheme is a result of formal derivation based on the gradient descent procedure of a fuzzy objective function. Using the result of formal derivation, two algorithms for fuzzy cluster analysis, the batch learning version and on- line learning version, are devised. They are tested on several data sets and compared with FCM. The experimental results show that the proposed algorithms find out the reasonable solution on Tucker`s counter example. (author). 11 refs., 3 figs.

  2. Design and implementation of an XML based object-oriented detector description database for CMS

    International Nuclear Information System (INIS)

    This thesis deals with the development of a detector description database (DDD) for the compact muon solenoid (CMS) experiment at the large hadron collider (LHC) located at the European organization for nuclear research (CERN). DDD is a fundamental part of the CMS offline software with its main applications, simulation and reconstruction. Both are in need of different models of the detector in order to efficiently solve their specific tasks. In the thesis the requirements to a detector description database are analyzed and the chosen solution is described in detail. It comprises the following components: an XML based detector description language, a runtime system that implements an object-oriented transient representation of the detector, and an application programming interface to be used by client applications. One of the main aspects of the development is the design of the DDD components. The starting point is a domain model capturing concisely the characteristics of the problem domain. The domain model is transformed into several implementation models according to the guidelines of the model driven architecture (MDA). Implementation models and appropriate refinements thereof are foundation for adequate implementations. Using the MDA approach, a fully functional prototype was realized in C++ and XML. The prototype was successfully tested through seamless integration into both the simulation and the reconstruction framework of CMS. (author)

  3. Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis

    Directory of Open Access Journals (Sweden)

    Jane Southworth

    2010-12-01

    Full Text Available Savanna ecosystems are an important component of dryland regions and yet are exceedingly difficult to study using satellite imagery. Savannas are composed are varying amounts of trees, shrubs and grasses and typically traditional classification schemes or vegetation indices cannot differentiate across class type. This research utilizes object based classification (OBC for a region in Namibia, using IKONOS imagery, to help differentiate tree canopies and therefore woodland savanna, from shrub or grasslands. The methodology involved the identification and isolation of tree canopies within the imagery and the creation of tree polygon layers had an overall accuracy of 84%. In addition, the results were scaled up to a corresponding Landsat image of the same region, and the OBC results compared to corresponding pixel values of NDVI. The results were not compelling, indicating once more the problems of these traditional image analysis techniques for savanna ecosystems. Overall, the use of the OBC holds great promise for this ecosystem and could be utilized more frequently in studies of vegetation structure.

  4. Robust Stereo-Vision Based 3D Object Reconstruction for the Assistive Robot FRIEND

    Directory of Open Access Journals (Sweden)

    COJBASIC, Z.

    2011-11-01

    Full Text Available A key requirement of assistive robot vision is the robust 3D object reconstruction in complex environments for reliable autonomous object manipulation. In this paper the idea is presented of achieving high robustness of a complete robot vision system against external influences such as variable illumination by including feedback control of the object segmentation in stereo images. The approach used is to change the segmentation parameters in closed-loop so that object features extraction is driven to a desired result. Reliable feature extraction is necessary to fully exploit a neuro-fuzzy classifier which is the core of the proposed 2D object recognition method, predecessor of 3D object reconstruction. Experimental results on the rehabilitation assistive robotic system FRIEND demonstrate the effectiveness of the proposed method.

  5. A Compound Object Authoring and Publishing Tool for Literary Scholars based on the IFLA-FRBR

    Directory of Open Access Journals (Sweden)

    Anna Gerber

    2009-10-01

    Full Text Available This paper presents LORE (Literature Object Re-use and Exchange, a light-weight tool which is designed to allow literature scholars and teachers to author, edit and publish compound information objects encapsulating related digital resources and bibliographic records. LORE enables users to easily create OAI-ORE-compliant compound objects, which build on the IFLA FRBR model, and also enables them to describe and publish them to an RDF repository as Named Graphs. Using the tool, literary scholars can create typed relationships between individual atomic objects using terms from a bibliographic ontology and can attach metadata to the compound object. This paper describes the implementation and user interface of the LORE tool, as developed within the context of an ongoing case study being conducted in collaboration with AustLit: The Australian Literature Resource, which focuses on compound objects for teaching and research within the Australian literature studies community.

  6. Intermediary object for participative design processes based on the ergonomic work analysis

    DEFF Research Database (Denmark)

    Souza da Conceição, Carolina; Duarte, F.; Broberg, Ole

    2012-01-01

    The objective of this paper is to present and discuss the use of an intermediary object, built from the ergonomic work analysis, in a participative design process. The object was a zoning pattern, developed as a visual representation ‘mapping’ of the interrelations among the functional units of the offshore accommodations module. The ergonomic work analysis is a method that favors the identification of everyday problems, so having direct link to participatory structures. And the developed zoning...

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

    OpenAIRE

    Pandu Sandi Pratama; Sang Kwun Jeong; Soon Sil Park; Sang Bong Kim

    2013-01-01

    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 navigatio...

  8. Multiple Objects Tracking with Location Matching and Adaptive Windowing Based on SIFT Algorithm

    OpenAIRE

    Seok-Wun Ha

    2013-01-01

    Multiple objects tracking have been an interesting research topic in computer vision and its related fields. It is a very important work to detect exactly the consecutive multiple objects and to track them effectively. In this paper, we propose a robust tracking system that utilizes several techniques such as multiple objects detection from multi-lateral histogram, location matching of the feature descriptor from Scale Invariant Feature Transform (SIFT) algorithm, and adaptive win...

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

    OpenAIRE

    Federico Prandi; Raffaella Brumana; Francesco Fassi

    2010-01-01

    Three dimensional object extraction and recognition (OER) from geographic data has been definitely one of more important topic in photogrammetry for quite a long time. Today, the capability of rapid generating high-density DSM increases the supply of geographic information but the discrete nature of the measuring makes more difficult to recognize correctly and to extract 3D objects from these surface. The proposed methodology wants to semi-automate some geographic objects clustering operation...

  10. Complex object tracking by visual servoing based on 2D image motion

    OpenAIRE

    Crétual, A.; Chaumette, François; Bouthemy, Patrick

    1998-01-01

    Efficient real-time robotic tasks using a monocular vision system were previously developed with simple objects (e.g. white points on a black background), within a visual servoing context. Due to recent developments, it is now possible to design real-time visual tasks exploiting motion information in the image, estimated by robust algorithms. This paper proposes such an approach to track complex objects, such as a pedestrian. It consists in integrating the measured 2D motion of the object to ...

  11. Distribution Network Expansion Planning Based on Multi-objective PSO Algorithm

    DEFF Research Database (Denmark)

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

    2013-01-01

    This paper presents a novel approach for electrical distribution network expansion planning using multi-objective particle swarm optimization (PSO). The optimization objectives are: investment and operation cost, energy losses cost, and power congestion cost. A two-phase multi-objective PSO algorithm was proposed to solve this optimization problem, which can accelerate the convergence and guarantee the diversity of Pareto-optimal front set as well. The feasibility and effectiveness of both the p...

  12. A combined object-tracking algorithm for omni-directional vision-based AGV navigation

    Science.gov (United States)

    Yuan, Wei; Sun, Jie; Cao, Zuo-Liang; Tian, Jing; Yang, Ming

    2010-03-01

    A combined object-tracking algorithm that realizes the realtime tracking of the selected object through the omni-directional vision with a fisheye lens is presented. The new method combines the modified continuously adaptive mean shift algorithm with the Kalman filter method. With the proposed method, the object-tracking problem when the object reappears after being sheltered completely or moving out of the field of view is solved. The experimental results perform well, and the algorithm proposed here improves the robustness and accuracy of the tracking in the omni-directional vision.

  13. A wavelet-based Bayesian framework for 3D object segmentation in microscopy

    OpenAIRE

    KOKARAM, ANIL CHRISTOPHER; PAN, KANGYU; Ramaswami, Mani; CORRIGAN, DAVID

    2012-01-01

    In confocal microscopy, target objects are labeled with fluorescent markers in the living specimen, and usually appear with irregular brightness in the observed images. Also, due to the existence of out-of-focus objects in the image, the segmentation of 3-D objects in the stack of image slices captured at different depth levels of the specimen is still heavily relied on manual analysis. In this paper, a novel Bayesian model is proposed for segmenting 3-D synaptic objects from given image stac...

  14. An object-based interaction framework for the operation of multiple field robots

    Science.gov (United States)

    Jones, Henry Lee, II

    Today's field robots, such as the Sojourner Mars rover or the Predator unmanned aerial vehicle, work alone to accomplish dirty, dull, or dangerous missions. Plans for the next generation of robotic systems call for multiple field robots to conduct these missions cooperatively under the direction of a single operator. This research examines the role of the operator in multiple-robot missions and creates a human-robot interaction framework that supports this role---a vital step toward the successful deployment of these future robots. In a typical user-centered approach to the development of a human-robot interaction framework, the work practices of the robot operator would be observed, characterized, and integrated into the design. Unfortunately, there are no settings where one can study the operator of multiple robots at work because no such systems have been deployed. As an alternative, this research incorporated a surrogate setting that could be used to inform the early interaction design of multiple-robot systems. Police Special Weapons and Tactics (SWAT) teams were chosen as this setting, and an ethnographic study of SWAT commanders was conducted. Concepts from the interdisciplinary study of geographically distributed work, including common ground, shared mental models, and information sharing, were used to understand and characterize the ethnographic observations. Using lessons learned from the surrogate setting, an implementation of a new human-robot interaction framework was demonstrated on the Micro Autonomous Rovers (MAR) platform in the Aerospace Robotics Laboratory at Stanford University. This interaction framework, which is based on the sensing and manipulation of physical objects by the robots, was derived from the finding that references to physical objects serve as an essential communication and coordination tool for SWAT commanders. A human-computer interface that utilizes direct manipulation techniques and three-dimensional computer graphics was created to test the new interaction paradigm. Using this interface, a single operator can coordinate the actions of multiple robots. Operators with many different levels of experience with robot operation were able to conduct a variety of complex missions using the MAR robots.

  15. An efficient hybrid evolutionary algorithm based on PSO and HBMO algorithms for multi-objective Distribution Feeder Reconfiguration

    International Nuclear Information System (INIS)

    This paper introduces a robust searching hybrid evolutionary algorithm to solve the multi-objective Distribution Feeder Reconfiguration (DFR). The main objective of the DFR is to minimize the real power loss, deviation of the nodes' voltage, the number of switching operations, and balance the loads on the feeders. Because of the fact that the objectives are different and no commensurable, it is difficult to solve the problem by conventional approaches that may optimize a single objective. This paper presents a new approach based on norm3 for the DFR problem. In the proposed method, the objective functions are considered as a vector and the aim is to maximize the distance (norm2) between the objective function vector and the worst objective function vector while the constraints are met. Since the proposed DFR is a multi objective and non-differentiable optimization problem, a new hybrid evolutionary algorithm (EA) based on the combination of the Honey Bee Mating Optimization (HBMO) and the Discrete Particle Swarm Optimization (DPSO), called DPSO-HBMO, is implied to solve it. The results of the proposed reconfiguration method are compared with the solutions obtained by other approaches, the original DPSO and HBMO over different distribution test systems.

  16. An Assistant for Loading Learning Object Metadata: An Ontology Based Approach

    Science.gov (United States)

    Casali, Ana; Deco, Claudia; Romano, Agustín; Tomé, Guillermo

    2013-01-01

    In the last years, the development of different Repositories of Learning Objects has been increased. Users can retrieve these resources for reuse and personalization through searches in web repositories. The importance of high quality metadata is key for a successful retrieval. Learning Objects are described with metadata usually in the standard…

  17. A Study of Video Object Tracking based on Automatic Background Segmentation and updating using Different Technique

    Directory of Open Access Journals (Sweden)

    Pushpender Prasad Chaturvedi

    2013-06-01

    Full Text Available Video object tracking play an important role insecuritysurveillance in current scenario. Theexplosion of successful digital device, the ease ofuse of high quality and economical video cameras,and the increasing need for computerized videoanalysis has generated a great deal of interest invideo tracking methods. There are three techniquesfor video analysis: exposure of interesting movingtarget, tracking of such target from frame to frame,and analysis of target tracks to identify theiractivities. The successful video object trackingsystem faced a problem of false detection of movingvideo object. The false video object detection arisesdue to drastic change of background of movingvideo. For the maintenance of background updatingvarious authors proposed a method for automaticbackground updating. In this paper we study ofdifferent video object tracking method usingbackground updating factor

  18. A Study of Video Object Tracking based on Automatic Background Segmentation and updating using Different Technique

    Directory of Open Access Journals (Sweden)

    Pushpender Prasad Chaturvedi

    2013-06-01

    Full Text Available Video object tracking play an important role in security surveillance in current scenario. The explosion of successful digital device, the ease of use of high quality and economical video cameras, and the increasing need for computerized video analysis has generated a great deal of interest in video tracking methods. There are three techniques for video analysis: exposure of interesting moving target, tracking of such target from frame to frame, and analysis of target tracks to identify their activities. The successful video object tracking system faced a problem of false detection of moving video object. The false video object detection arises due to drastic change of background of moving video. For the maintenance of background updating various authors proposed a method for automatic background updating. In this paper we study of different video object tracking method using background updating factor.

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

    Directory of Open Access Journals (Sweden)

    Andrea Baraldi

    2012-09-01

    Full Text Available According to existing literature and despite their commercial success, state-of-the-art two-stage non-iterative geographic object-based image analysis (GEOBIA systems and three-stage iterative geographic object-oriented image analysis (GEOOIA systems, where GEOOIA/GEOBIA, remain affected by a lack of productivity, general consensus and research. To outperform the degree of automation, accuracy, efficiency, robustness, scalability and timeliness of existing GEOBIA/GEOOIA systems in compliance with the Quality Assurance Framework for Earth Observation (QA4EO guidelines, this methodological work is split into two parts. The present first paper provides a multi-disciplinary Strengths, Weaknesses, Opportunities and Threats (SWOT analysis of the GEOBIA/GEOOIA approaches that augments similar analyses proposed in recent years. In line with constraints stemming from human vision, this SWOT analysis promotes a shift of learning paradigm in the pre-attentive vision first stage of a remote sensing (RS image understanding system (RS-IUS, from sub-symbolic statistical model-based (inductive image segmentation to symbolic physical model-based (deductive image preliminary classification. Hence, a symbolic deductive pre-attentive vision first stage accomplishes image sub-symbolic segmentation and image symbolic pre-classification simultaneously. In the second part of this work a novel hybrid (combined deductive and inductive RS-IUS architecture featuring a symbolic deductive pre-attentive vision first stage is proposed and discussed in terms of: (a computational theory (system design; (b information/knowledge representation; (c algorithm design; and (d implementation. As proof-of-concept of symbolic physical model-based pre-attentive vision first stage, the spectral knowledge-based, operational, near real-time Satellite Image Automatic Mapper™ (SIAM™ is selected from existing literature. To the best of these authors’ knowledge, this is the first time a symbolic syntactic inference system, like SIAM™, is made available to the RS community for operational use in a RS-IUS pre-attentive vision first stage, to accomplish multi-scale image segmentation and multi-granularity image pre-classification simultaneously, automatically and in near real-time.

  20. Prediction based collaborative trackers (PCT): a robust and accurate approach toward 3D medical object tracking.

    Science.gov (United States)

    Yang, Lin; Georgescu, Bogdan; Zheng, Yefeng; Wang, Yang; Meer, Peter; Comaniciu, Dorin

    2011-11-01

    Robust and fast 3D tracking of deformable objects, such as heart, is a challenging task because of the relatively low image contrast and speed requirement. Many existing 2D algorithms might not be directly applied on the 3D tracking problem. The 3D tracking performance is limited due to dramatically increased data size, landmarks ambiguity, signal drop-out or complex nonrigid deformation. In this paper, we present a robust, fast, and accurate 3D tracking algorithm: prediction based collaborative trackers (PCT). A novel one-step forward prediction is introduced to generate the motion prior using motion manifold learning. Collaborative trackers are introduced to achieve both temporal consistency and failure recovery. Compared with tracking by detection and 3D optical flow, PCT provides the best results. The new tracking algorithm is completely automatic and computationally efficient. It requires less than 1.5 s to process a 3D volume which contains millions of voxels. In order to demonstrate the generality of PCT, the tracker is fully tested on three large clinical datasets for three 3D heart tracking problems with two different imaging modalities: endocardium tracking of the left ventricle (67 sequences, 1134 3D volumetric echocardiography data), dense tracking in the myocardial regions between the epicardium and endocardium of the left ventricle (503 sequences, roughly 9000 3D volumetric echocardiography data), and whole heart four chambers tracking (20 sequences, 200 cardiac 3D volumetric CT data). Our datasets are much larger than most studies reported in the literature and we achieve very accurate tracking results compared with human experts' annotations and recent literature. PMID:21642040

  1. Visual Perception Based Objective Stereo Image Quality Assessment for 3D Video Communication

    Directory of Open Access Journals (Sweden)

    Gangyi Jiang

    2014-04-01

    Full Text Available Stereo image quality assessment is a crucial and challenging issue in 3D video communication. One of major difficulties is how to weigh binocular masking effect. In order to establish the assessment mode more in line with the human visual system, Watson model is adopted, which defines visibility threshold under no distortion composed of contrast sensitivity, masking effect and error in this study. As a result, we propose an Objective Stereo Image Quality Assessment method (OSIQA, organically combining a new Left-Right view Image Quality Assessment (LR-IQA metric and Depth Perception Image Quality Assessment (DP-IQA metric. The new LR-IQA metric is first given to calculate the changes of perception coefficients in each sub-band utilizing Watson model and human visual system after wavelet decomposition of left and right images in stereo image pair, respectively. Then, a concept of absolute difference map is defined to describe abstract differential value between the left and right view images and the DP-IQA metric is presented to measure structure distortion of the original and distorted abstract difference maps through luminance function, error sensitivity and contrast function. Finally, an OSIQA metric is generated by using multiplicative fitting of the LR-IQA and DP-IQA metrics based on weighting. Experimental results shows that the proposed method are highly correlated with human visual judgments (Mean Opinion Score and the correlation coefficient and monotony are more than 0.92 under five types of distortions such as Gaussian blur, Gaussian noise, JP2K compression, JPEG compression and H.264 compression.

  2. Object-Based Mapping of the Circumpolar Taiga-Tundra Ecotone with MODIS Tree Cover

    Science.gov (United States)

    Ranson, K. J.; Montesano, P. M.; Nelson, R.

    2011-01-01

    The circumpolar taiga tundra ecotone was delineated using an image-segmentation-based mapping approach with multi-annual MODIS Vegetation Continuous Fields (VCF) tree cover data. Circumpolar tree canopy cover (TCC) throughout the ecotone was derived by averaging MODIS VCF data from 2000 to 2005 and adjusting the averaged values using linear equations relating MODIS TCC to Quickbird-derived tree cover estimates. The adjustment helped mitigate VCF's overestimation of tree cover in lightly forested regions. An image segmentation procedure was used to group pixels representing similar tree cover into polygonal features (segmentation objects) that form the map of the transition zone. Each polygon represents an area much larger than the 500 m MODIS pixel and characterizes the patterns of sparse forest patches on a regional scale. Those polygons near the boreal/tundra interface with either (1) mean adjusted TCC values from5 to 20%, or (2) mean adjusted TCC values greater than 5% but with a standard deviation less than 5% were used to identify the ecotone. Comparisons of the adjusted average tree cover data were made with (1) two existing tree line definitions aggregated for each 1 degree longitudinal interval in North America and Eurasia, (2) Landsat-derived Canadian proportion of forest cover for Canada, and (3) with canopy cover estimates extracted from airborne profiling lidar data that transected 1238 of the TCC polygons. The adjusted TCC from MODIS VCF shows, on average, less than 12% TCC for all but one regional zone at the intersection with independently delineated tree lines. Adjusted values track closely with Canadian proportion of forest cover data in areas of low tree cover. A comparison of the 1238 TCC polygons with profiling lidar measurements yielded an overall accuracy of 67.7%.

  3. Mapping temporal changes in connectivity using high-resolution aerial data and object based image analysis

    Science.gov (United States)

    Masselink, Rens; Anders, Niels; Keesstra, Saskia; Seeger, Manuel

    2014-05-01

    Within the field of geomorphology mapping has always been an important tool to interpret spatial and temporal distributions of phenomena and processes at the surface. In the field of connectivity however, although throughout the past decade many articles have been published, there are only very few that go into the mapping of connectivity. This study aimed at developing a new, automated method for mapping connectivity within agricultural catchments. The method, which is a combination of Object-Based Image Analysis (OBIA) and traditional geomorphological field mapping, was applied to two agricultural catchments in Navarre, Spain, both with an area of approximately 2 sq.km. An unmanned aerial vehicle (UAV) was used to take aerial photographs with a resolution of 6 cm, of which a DEM with a 12 cm resolution was created using structure-from-motion photogrammetry. Connectivity was mapped within the study areas using OBIA using a top down method, meaning that connectivity was mapped at different scale levels, starting at the largest scale. Firstly sub-catchments were automatically delineated, after which several characteristics and features that affect connectivity within the sub-catchments were classified, e.g. landuse, landslides, rills, gullies, riparian vegetation, changes in slope, ploughing direction etc. In two consecutive years (2013-2014) photographs were taken and connectivity of both catchments of both years will be compared. Future work will include a quantification of the mapped connectivity (highly connected years vs. low connected years), causes and consequences of these differences in connectivity, comparison to existing connectivity indices and comparison of mapped connectivity in sub-catchments and measured discharge.

  4. A multi-objective optimization approach based on simulated annealing and its application to nuclear fuel management

    International Nuclear Information System (INIS)

    As far as stochastic optimization methods are concerned, Simulated Annealing (SA) and Genetic Algorithms (GA) have been successfully applied to fuel management, when using a single objective function. Recent work has shown that it is possible to use a true multi-objective approach (e.g. fresh fuel enrichment minimization and cycle length maximization,...) based on GA. In that approach, ranking the individuals of the population is based on the non-dominance principle. It is shown that a similar approach can be applied to SA, which is traditionally single objective. In this approach, every time a solution using is accepted, it is compared to other archived solutions using the non-dominance principle. At the end of the optimization search, one ends up with an archived population which actually represents the trade-off surface between all the objective functions of interest, among which the expert will then choose the best solution according to his priorities. (author)

  5. A robust mean-shift tracking through occlusion and scale based on object trajectory for surveillance camera

    Science.gov (United States)

    Labidi, Hocine; Luo, Sen-Lin; Boubekeur, Mohamed Bachir

    2015-03-01

    Object tracking is an important part in surveillance systems, One of the algorithms used for this task is the meanshift algorithm due to the robustness, computational efficiency and implementation ease. However the traditional meanshift cannot effectively track the moving object when the scale changes, because of the fixed size of the tracking window, and can lose the target while an occlusion, In this study a method based on the trajectory direction of the moving object is presented to deal with the problem of scale change. Furthermore a histogram similarity metric is used to detect when target occlusion occurs, and a method based on multi kernel is proposed, to estimate which part is not in occlusion and this part will be used to extrapolate the motion of the object and gives an estimation of its position, Experimental results show that the improved methods have a good adaptability to the scale and occlusion of the target.

  6. Risk functions for human and porcine eye rupture based on projectile characteristics of blunt objects.

    Science.gov (United States)

    Kennedy, Eric A; Ng, Tracy P; McNally, Craig; Stitzel, Joel D; Duma, Stephan M

    2006-11-01

    Eye ruptures are among the most devastating eye injuries and can occur in automobile crashes, sporting impacts, and military events, where blunt projectile impacts to the eye can be encountered. The purpose of this study was to develop injury risk functions for globe rupture of both human and porcine eyes from blunt projectile impacts. This study was completed in two parts by combining published eye experiments with new test data. In the first part, data from 57 eye impact tests that were reported in the literature were analyzed. Projectile characteristics such as mass, cross-sectional area, and velocity, as well as injury outcome were noted for all tests. Data were sorted by species type and areas were identified where a paucity of data existed, based on the kinetic and normalized energy of assaulting objects. For the second part, a total of 126 projectile tests were performed on human and porcine eyes. Projectiles used for these tests included blunt aluminum projectiles, BBs, foam pellets, Airsoft pellets, and paintballs. Data for each projectile were recorded prior to testing and high-speed video was used to determine projectile velocity prior to striking the eye. In part three the data were pooled for a total of 183 eye impact tests, 83 human and 100 porcine, and were analyzed to develop the injury risk criteria. Binary logistic regression was used to develop injury risk functions based on kinetic and normalized energy. Probit analysis was used to estimate confidence intervals for the injury risk functions. Porcine eyes were found to be significantly stronger than human eyes in resisting globe rupture (p=0.01). For porcine eyes a 50% risk of globe rupture was found to be 71,145 J/m2, with a confidence interval of 63,245 J/m2 to 80,390 J/m2. Human eyes were found to have a 50% risk of globe rupture at a lower, 35,519 J/m2, with confidence intervals of 32,018 J/m2 to 40,641 J/m2. The results presented in this paper are useful in estimating the risk of globe rupture when projectile parameters are known, or can be used to validate computational eye models. PMID:17311182

  7. Weed Mapping in Early-Season Maize Fields Using Object-Based Analysis of Unmanned Aerial Vehicle (UAV) Images

    OpenAIRE

    Peña, José Manuel; Torres-Sánchez, Jorge; de Castro, Ana Isabel; Kelly, Maggi; López-Granados, Francisca

    2013-01-01

    The use of remote imagery captured by unmanned aerial vehicles (UAV) has tremendous potential for designing detailed site-specific weed control treatments in early post-emergence, which have not possible previously with conventional airborne or satellite images. A robust and entirely automatic object-based image analysis (OBIA) procedure was developed on a series of UAV images using a six-band multispectral camera (visible and near-infrared range) with the ultimate objective of generating a w...

  8. Recording digital holograms of optically transparent objects in arbitrary spectral intervals based on acousto-optic filtration of radiation

    Science.gov (United States)

    Machikhin, A. S.; Polschikova, O. V.; Ramazanova, A. G.; Pozhar, V. E.

    2015-10-01

    The problem of obtaining digital holographic images of optically transparent objects in arbitrary spectral intervals is considered. A Mach-Zehnder interferometer based optical scheme with acousto-optic spectral filtration of the broadband radiation is presented. The spectral selection allows one to increase the informativeness of digital holograms due to the choice of spectral channels in which elements with different physico-chemical properties have a sufficient contrast. Examples of recorded spectral holographic images of a test object and real objects are presented.

  9. An Effort Prediction Framework for Software Code Quality Measurement Based on Quantifiable Constructs for Object Oriented Design

    Directory of Open Access Journals (Sweden)

    Prof. Waweru Mwangi

    2014-04-01

    Full Text Available As the Object Oriented Technology enters into software organizations, it has created new challenges for the companies which used only Product Metrics as a tool for monitoring, controlling and maintaining the software product. The structural architecture focus of this research paper is to prove that the mechanisms of Object Oriented Design constructs, namely Inheritance, Encapsulation and Polymorphism are the keys to foster reuse and achieve easier maintainability and less complex software codes. This research paper proposes an effort prediction automated framework for software code quality measurement; based on quantifiable constructs for object oriented design, the framework measures the effort of maintaining and reusing the three constructs of Object Oriented Design that is; Encapsulation, Inheritance and Polymorphism. The adoption of the Object Oriented Design constructs in this paper is to calculatedly produce easy to maintain, reusable, better and cheaper software in the market. This research paper proceeds to automate the proposed framework system that will be able to predict the effort of measuring the constructs of Object Oriented Design. In order to achieve this, we have utilized one predictor which has been extremely studied: software metrics. The final outcome of this paper is an effort prediction automated tool for software code quality assessment, which predicts effort of maintaining and reusing Object Oriented Programming Languages based on the three OOD constructs. The results acquired are beneficial to be used by software developers, software engineers and software project managers for aligning and orienting their design with common industry practices.

  10. Contactless Measurement Of Rectilinearity Of An Elongated Object Based On The Example A Crane Rail

    Directory of Open Access Journals (Sweden)

    ?mielewski Kazimierz

    2015-07-01

    Full Text Available The common aim of engineering surveys is to determine deviations from rectilinearity for elongated objects. We have developed a number of methods for measuring points that represent an elongated object. These are the constant straight (optical, laser, mechanical-string method, the trigonometric method, geometric levelling method, photogrammetric methods and terrestrial laser scanning. When taking these measurements, it is crucial to have a direct access to the survey points of the measured object. Factors impeding the measurements include: adverse lighting conditions, vibration, dust, refractory effects, lack of direct access to the survey points, etc.

  11. A Vision-Based System for Object Identification and Information Retrieval in a Smart Home

    Science.gov (United States)

    Grech, Raphael; Monekosso, Dorothy; de Jager, Deon; Remagnino, Paolo

    This paper describes a hand held device developed to assist people to locate and retrieve information about objects in a home. The system developed is a standalone device to assist persons with memory impairments such as people suffering from Alzheimer's disease. A second application is object detection and localization for a mobile robot operating in an ambient assisted living environment. The device relies on computer vision techniques to locate a tagged object situated in the environment. The tag is a 2D color printed pattern with a detection range and a field of view such that the user may point from a distance of over 1 meter.

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

    DEFF Research Database (Denmark)

    Mahalle, Parikshit N.; Prasad, Neeli R.; Prasad, Ramjee

    2013-01-01

    As computing technology is becoming more tightly coupled into dynamic and mobile world of the Internet of Things (IoT), security mechanism is more stringent, flexible and less intrusive. Scalability issue in IoT makes identity management (IdM) of ubiquitous objects more challenging, and there is a need of context-aware access control solution for IdM. Confronting uncertainty of different types of objects in IoT is not easy. This paper presents the logical framework for object classification in c...

  13. Intermediary object for participative design processes based on the ergonomic work analysis

    DEFF Research Database (Denmark)

    Souza da Conceição, Carolina; Duarte, F.

    2012-01-01

    The objective of this paper is to present and discuss the use of an intermediary object, built from the ergonomic work analysis, in a participative design process. The object was a zoning pattern, developed as a visual representation ‘mapping’ of the interrelations among the functional units of the offshore accommodations module. The ergonomic work analysis is a method that favors the identification of everyday problems, so having direct link to participatory structures. And the developed zoning pattern tool seemed to be an appropriate way of transferring the use experience into the design process.

  14. Multi-objective dynamic economic emission dispatch of electric power generation integrated with game theory based demand response programs

    International Nuclear Information System (INIS)

    Highlights: • In this work, a game theory based DR program is integrated into the DEED problem. • Objectives are to minimize fuel and emissions costs and maximize the DR benefit. • Optimal generator output, customer load and customer incentive are determined. • Developed model is tested with two different scenarios. • Model provides superior results than independent optimization of DR or DEED. - Abstract: The dynamic economic emission dispatch (DEED) of electric power generation is a multi-objective mathematical optimization problem with two objective functions. The first objective is to minimize all the fuel costs of the generators in the power system, whilst the second objective seeks to minimize the emissions cost. Both objective functions are subject to constraints such as load demand constraint, ramp rate constraint, amongst other constraints. In this work, we integrate a game theory based demand response program into the DEED problem. The game theory based demand response program determines the optimal hourly incentive to be offered to customers who sign up for load curtailment. The game theory model has in built mechanisms to ensure that the incentive offered the customers is greater than the cost of interruption while simultaneously being beneficial to the utility. The combined DEED and game theoretic demand response model presented in this work, minimizes fuel and emissions costs and simultaneously determines the optimal incentive and load curtailment customers have to perform for maximal power system relief. The developed model is tested on two test systems with industrial customers and obtained results indicate the practical benefits of the proposed model

  15. Neural Classifier for Object Classification with Cluttered Background Using Spectral Texture Based Features

    Directory of Open Access Journals (Sweden)

    B. Nagarajan

    2008-01-01

    Full Text Available The goal of this study is to build a system that detects and classifies the car objects amidst background clutter and mild occlusion. This study addresses the issues to classify objects of real-world images containing side views of cars with cluttered background with that of non-car images with natural scenes. The threshold technique with background subtraction is used to segment the background region to extract the object of interest. The background-segmented image with region of interest is divided into equal sized blocks of sub-images. The spectral texture features are extracted from each sub-block. The features of the objects are fed to the back-propagation neural classifier. Thus the performance of the neural classifier is compared with various categories of block size. Quantitative evaluation shows improved results of 85.5%. A critical evaluation of present approach under the proposed standards is presented.

  16. Tracking 3D Moving Objects Based on GPS/IMU Navigation Solution, Laser Scanner Point Cloud and GIS Data

    Directory of Open Access Journals (Sweden)

    Siavash Hosseinyalamdary

    2015-07-01

    Full Text Available Monitoring vehicular road traffic is a key component of any autonomous driving platform. Detecting moving objects, and tracking them, is crucial to navigating around objects and predicting their locations and trajectories. Laser sensors provide an excellent observation of the area around vehicles, but the point cloud of objects may be noisy, occluded, and prone to different errors. Consequently, object tracking is an open problem, especially for low-quality point clouds. This paper describes a pipeline to integrate various sensor data and prior information, such as a Geospatial Information System (GIS map, to segment and track moving objects in a scene. We show that even a low-quality GIS map, such as OpenStreetMap (OSM, can improve the tracking accuracy, as well as decrease processing time. A bank of Kalman filters is used to track moving objects in a scene. In addition, we apply non-holonomic constraint to provide a better orientation estimation of moving objects. The results show that moving objects can be correctly detected, and accurately tracked, over time, based on modest quality Light Detection And Ranging (LiDAR data, a coarse GIS map, and a fairly accurate Global Positioning System (GPS and Inertial Measurement Unit (IMU navigation solution.

  17. Local object-based super-resolution mosaicing from low-resolution video

    OpenAIRE

    Krämer, Petra; Benois-Pineau, Jenny; Domenger, Jean-Philippe

    2011-01-01

    Many efficient super-resolution methods have been presented in the past for improving resolution of images degraded by global blurs. Unfortunately, in video, more complex situations can be observed where local blurs appear in each frame which are mainly caused by object motions. To address this problem, we propose in this article a local super-resolution method which allows the restoration of such local blurs. Moreover, the motion of objects in video sequences may be very complex and particul...

  18. An Energy Efficient Localization Strategy for Outdoor Objects based on Intelligent Light-Intensity Sampling

    OpenAIRE

    Sandnes, Frode Eika

    2010-01-01

    A simple and low cost strategy for implementing pervasive objects that identify and track their own geographical location is proposed. The strategy, which is not reliant on any GIS infrastructure such as GPS, is realized using an electronic artifact with a built in clock, a light sensor, or low-cost digital camera, persistent storage such as flash and sufficient computational circuitry to make elementary trigonometric computations. The object monitors the lighting conditions and thereby detec...

  19. Dynamic process based on multi- creteria Constraints to personalize multimedia-learning objects

    OpenAIRE

    Aouag, Sofiane

    2006-01-01

    Abstract: Individualized learning is the most important process that need to use individualization constraints to ensure adaptive systems able to support flexible solutions dynamically adapt content as well as interface and the scenario of multimedia learning object to fit pedagogical intentions. Therefore, this various aspect of multimedia learning object have to be supported in a highly personalized manner by the system. Though, tracking and grasping the user behavior remains the most chall...

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

    OpenAIRE

    Reza Oji

    2012-01-01

    Object recognition is an important task in image processing and computer vision. This paper presents a perfect method for object recognition with full boundary detection by combining affine scale invariant feature transform (ASIFT) and a region merging algorithm. ASIFT is a fully affine invariant algorithm that means features are invariant to six affine parameters namely translation (2 parameters), zoom, rotation and two camera axis orientations. The features are very reliab...

  1. New Design Objective and Human Intent-based Management of Changes for Product Modeling

    OpenAIRE

    László Horváth

    2007-01-01

    This paper is concerned with the evaluation of effects of modeled object changesat development of product in virtual space. Modeling of engineering objects such aselements and structures of products, results of analyses and tests, processes for production,and customer services has reached the level where sophisticated descriptions and modelingprocedures serve lifecycle management of product information (PLM). However, effectiveutilization of highly associative product models is impossible in ...

  2. Evaluation of three vision based object perception methods for a mobile robot

    OpenAIRE

    Ramisa, Arnau; Aldavert, David; Vasudevan, Shrihari; Toledo, Ricardo; Lopez De Mantaras, Ramon

    2012-01-01

    This paper addresses visual object perception applied to mobile robotics. Being able to perceive household objects in unstructured environments is a key capability in order to make robots suitable to perform complex tasks in home environments. However, finding a solution for this task is daunting: it requires the ability to handle the variability in image formation in a moving camera with tight time constraints. The paper brings to attention some of the issues with applying three state of the...

  3. A Time-Based Account of the Perception of Odor Objects and Valences

    OpenAIRE

    Olofsson, Jonas K.; Bowman, Nicholas E.; Khatibi, Katherine; Gottfried, Jay A.

    2012-01-01

    Is human odor perception guided by memory or emotion? Object-centered accounts predict that recognition of unique odor qualities precedes valence decoding. Valence-centered accounts predict the opposite: that stimulus-driven valence responses precede and guide identification. In a speeded response time study, participants smelled paired odors, presented sequentially, and indicated whether the second odor in each pair belonged to the same category as the first (object evaluation task) or wheth...

  4. RANSAC based three points algorithm for ellipse fitting of spherical object's projection

    OpenAIRE

    Xu, Shenghui

    2015-01-01

    As the spherical object can be seen everywhere, we should extract the ellipse image accurately and fit it by implicit algebraic curve in order to finish the 3D reconstruction. In this paper, we propose a new ellipse fitting algorithm which only needs three points to fit the projection of spherical object and is different from the traditional algorithms that need at least five point. The fitting procedure is just similar as the estimation of Fundamental Matrix estimation by s...

  5. A Trajectory and Orientation Reconstruction Method for Moving Objects Based on a Moving Monocular Camera

    Directory of Open Access Journals (Sweden)

    Jian Zhou

    2015-03-01

    Full Text Available We propose a monocular trajectory intersection method to solve the problem that a monocular moving camera cannot be used for three-dimensional reconstruction of a moving object point. The necessary and sufficient condition of when this method has the unique solution is provided. An extended application of the method is to not only achieve the reconstruction of the 3D trajectory, but also to capture the orientation of the moving object, which would not be obtained by PnP problem methods due to lack of features. It is a breakthrough improvement that develops the intersection measurement from the traditional “point intersection” to “trajectory intersection” in videometrics. The trajectory of the object point can be obtained by using only linear equations without any initial value or iteration; the orientation of the object with poor conditions can also be calculated. The required condition for the existence of definite solution of this method is derived from equivalence relations of the orders of the moving trajectory equations of the object, which specifies the applicable conditions of the method. Simulation and experimental results show that it not only applies to objects moving along a straight line, or a conic and another simple trajectory, but also provides good result for more complicated trajectories, making it widely applicable.

  6. A trajectory and orientation reconstruction method for moving objects based on a moving monocular camera.

    Science.gov (United States)

    Zhou, Jian; Shang, Yang; Zhang, Xiaohu; Yu, Wenxian

    2015-01-01

    We propose a monocular trajectory intersection method to solve the problem that a monocular moving camera cannot be used for three-dimensional reconstruction of a moving object point. The necessary and sufficient condition of when this method has the unique solution is provided. An extended application of the method is to not only achieve the reconstruction of the 3D trajectory, but also to capture the orientation of the moving object, which would not be obtained by PnP problem methods due to lack of features. It is a breakthrough improvement that develops the intersection measurement from the traditional "point intersection" to "trajectory intersection" in videometrics. The trajectory of the object point can be obtained by using only linear equations without any initial value or iteration; the orientation of the object with poor conditions can also be calculated. The required condition for the existence of definite solution of this method is derived from equivalence relations of the orders of the moving trajectory equations of the object, which specifies the applicable conditions of the method. Simulation and experimental results show that it not only applies to objects moving along a straight line, or a conic and another simple trajectory, but also provides good result for more complicated trajectories, making it widely applicable. PMID:25760053

  7. MEASURING OBJECT-ORIENTED SYSTEMS BASED ON THE EXPERIMENTAL ANALYSIS OF THE COMPLEXITY METRICS

    Directory of Open Access Journals (Sweden)

    J.S.V.R.S.SASTRY,

    2011-05-01

    Full Text Available Metrics are used to help a software engineer in quantitative analysis to assess the quality of the design before a system is built. The focus of Object-Oriented metrics is on the class which is the fundamental building block of the Object-Oriented architecture. These metrics are focused on internal object structure and external object structure. Internal object structure reflects the complexity of each individual entity such as methods and classes. External complexity measures the interaction among entities such as Coupling and Inheritance. This paper mainly focuses on a set of object oriented metrics that can be used to measure the quality of an object oriented design. Two types of complexity metrics in Object-Oriented paradigm namely Mood metrics and Lorenz & Kidd metrics. Mood metrics consist of Method inheritance factor(MIF, Coupling factor(CF, Attribute inheritance factor(AIF, Method hiding factor(MHF, Attribute hiding factor(AHF, and polymorphism factor(PF. Lorenz & Kidd metrics consist of Number of operations overridden (NOO, Number operations added (NOA, Specialization index(SI. Mood metrics and Lorenz & Kidd metrics measurements are used mainly by designers and testers. Designers uses these metrics to access the software early in process,making changes that will reduce complexity and improve the continuing capability of the design. Testers use to test the software for finding the complexity, performance of the system, quality of the software. This paper reviews Mood metrics and Lorenz & Kidd metrics are validates theoretically and empirically methods. In thispaper, work has been done to explore the quality of design of software components using object oriented paradigm. A number of object oriented metrics have been proposed in the literature for measuring the design attributes such as inheritance, coupling, polymorphism etc. This paper, metrics have been used to analyzevarious features of software component. Complexity of methods involved is a predictor of how much time, effort, Cost is required to develop and maintain the class. If a large number of methods can be invoked in response to a message, the testing and debugging of the class becomes more complicated since it requires a greater level of understanding on the part of the tester.

  8. MULTIPLE OBJECTS

    Directory of Open Access Journals (Sweden)

    A. A. Bosov

    2015-04-01

    Full Text Available Purpose. The development of complicated techniques of production and management processes, information systems, computer science, applied objects of systems theory and others requires improvement of mathematical methods, new approaches for researches of application systems. And the variety and diversity of subject systems makes necessary the development of a model that generalizes the classical sets and their development – sets of sets. Multiple objects unlike sets are constructed by multiple structures and represented by the structure and content. The aim of the work is the analysis of multiple structures, generating multiple objects, the further development of operations on these objects in application systems. Methodology. To achieve the objectives of the researches, the structure of multiple objects represents as constructive trio, consisting of media, signatures and axiomatic. Multiple object is determined by the structure and content, as well as represented by hybrid superposition, composed of sets, multi-sets, ordered sets (lists and heterogeneous sets (sequences, corteges. Findings. In this paper we study the properties and characteristics of the components of hybrid multiple objects of complex systems, proposed assessments of their complexity, shown the rules of internal and external operations on objects of implementation. We introduce the relation of arbitrary order over multiple objects, we define the description of functions and display on objects of multiple structures. Originality.In this paper we consider the development of multiple structures, generating multiple objects.Practical value. The transition from the abstract to the subject of multiple structures requires the transformation of the system and multiple objects. Transformation involves three successive stages: specification (binding to the domain, interpretation (multiple sites and particularization (goals. The proposed describe systems approach based on hybrid sets can be used in many application systems for structural and content analysis. An example of the use the hybrid sets for logistics systems modeling is shown.

  9. Motion object tracking based on the low-rank matrix representation

    Science.gov (United States)

    Kong, Xiaofang; Chen, Qian; Xu, Fuyuan; Gu, Guohua; Ren, Kan; Qian, Weixian

    2015-10-01

    Motion object tracking is one of the most important research directions in computer vision. Challenges in designing a tracking method are usually caused by occlusions, noise, or illumination changes. In this paper, a robust visual tracking algorithm is proposed in order to cope with the occlusion by introducing the motion object tracking issue as a low-rank matrix representation problem. First, being the main contribution of this paper, the observation matrix composed by image sequences is decomposed into a low-rank matrix and a sparse matrix. The motion object in the image sequence forms the low-rank matrix and the occlusion on the motion object forms the sparse matrix. Then the motion object tracking is carried out using a Bayesian state under the particle filter framework. Finally, an effective alternating algorithm is utilized to solve the proposed optimization formulation. The proposed algorithm has been examined throughout several challenging image sequences, and experiment results show that it works effectively and efficiently in different situations.

  10. Motion object tracking based on the low-rank matrix representation

    Science.gov (United States)

    Kong, Xiaofang; Chen, Qian; Xu, Fuyuan; Gu, Guohua; Ren, Kan; Qian, Weixian

    2015-08-01

    Motion object tracking is one of the most important research directions in computer vision. Challenges in designing a tracking method are usually caused by occlusions, noise, or illumination changes. In this paper, a robust visual tracking algorithm is proposed in order to cope with the occlusion by introducing the motion object tracking issue as a low-rank matrix representation problem. First, being the main contribution of this paper, the observation matrix composed by image sequences is decomposed into a low-rank matrix and a sparse matrix. The motion object in the image sequence forms the low-rank matrix and the occlusion on the motion object forms the sparse matrix. Then the motion object tracking is carried out using a Bayesian state under the particle filter framework. Finally, an effective alternating algorithm is utilized to solve the proposed optimization formulation. The proposed algorithm has been examined throughout several challenging image sequences, and experiment results show that it works effectively and efficiently in different situations.

  11. Multi-Objective Optimization Based Collision Avoidance Algorithm for an Intelligence Marine Navigation

    Directory of Open Access Journals (Sweden)

    H. Faroqi

    2015-01-01

    Full Text Available Currently, the collision avoidance algorithm is considered as an essential part of the marine navigation systems. The collision avoidance algorithm determines and decides to change the speed and direction of a ship in the presence of obstacles. Avoidance of collision problem can be considered as a spatial multi objective problem due to it needs to handle with different objectives by searching a space of possible routes and find a set of optimal routes. Solving collision avoidance problem in ship’s routing is a complicated problem because of different objectives, inconsistency between them and presence of dynamic and static obstacles in sea. In this study, the Multi-Objective Evolutionary Algorithm (MOEA as an optimization technique has been used for solving the problem in the context of GIS. Two objectives, highest safety and lowest deviation from main route, have been considered for simulating and solving the problem. The proposed algorithm has been implemented for solving the problem in five simulated situations, including various modes of dynamic and static obstacles. The results have been analytically and numerically evaluated. Determination of the optimal routes set, suitable rapidity of the algorithm (about 40 sec, efficient convergence trend and repeatability of results (80% are the positive and promising consequences of evaluating the algorithm’s results.

  12. New Design Objective and Human Intent-based Management of Changes for Product Modeling

    Directory of Open Access Journals (Sweden)

    László Horváth

    2007-03-01

    Full Text Available This paper is concerned with the evaluation of effects of modeled object changesat development of product in virtual space. Modeling of engineering objects such aselements and structures of products, results of analyses and tests, processes for production,and customer services has reached the level where sophisticated descriptions and modelingprocedures serve lifecycle management of product information (PLM. However, effectiveutilization of highly associative product models is impossible in current modeling becausetechniques are not available for tracking and evaluation of high number of associativerelationships in large product model. The author analyzed the above problem andconsidered inappropriate organization of product information as its main cause. In orderto gain a solution in current modeling systems, a new method is proposed in this paper forchange management. In this method, joint modeling of design objectives and human intentis applied for shape-centered products. As background information for the proposedmodeling, paper discusses research results in change management for product developmentin modeling environments. Following this, integrated modeling of closely relatedengineering objects is proposed as extension to current industrial PLM systems. Next,design objective driven product change management is detailed. Finally, virtual space isoutlined as a possible advanced application of the proposed change management with thecapability of representation of human intent.

  13. Chaotic improved PSO-based multi-objective optimization for minimization of power losses and L index in power systems

    International Nuclear Information System (INIS)

    Highlights: • New method for MOORPD problem using MOCIPSO and MOIPSO approaches. • Constrain-prior Pareto-dominance method is proposed to meet the constraints. • The limits of the apparent power flow of transmission line are considered. • MOORPD model is built up for MOORPD problem. • The achieved results by MOCIPSO and MOIPSO approaches are better than MOPSO method. - Abstract: Multi-objective optimal reactive power dispatch (MOORPD) seeks to not only minimize power losses, but also improve the stability of power system simultaneously. In this paper, the static voltage stability enhancement is achieved through incorporating L index in MOORPD problem. Chaotic improved PSO-based multi-objective optimization (MOCIPSO) and improved PSO-based multi-objective optimization (MOIPSO) approaches are proposed for solving complex multi-objective, mixed integer nonlinear problems such as minimization of power losses and L index in power systems simultaneously. In MOCIPSO and MOIPSO based optimization approaches, crossover operator is proposed to enhance PSO diversity and improve their global searching capability, and for MOCIPSO based optimization approach, chaotic sequences based on logistic map instead of random sequences is introduced to PSO for enhancing exploitation capability. In the two approaches, constrain-prior Pareto-dominance method (CPM) is proposed to meet the inequality constraints on state variables, the sorting and crowding distance methods are considered to maintain a well distributed Pareto optimal solutions, and moreover, fuzzy set theory is employed to extract the best compromise solution over the Pareto optimal curve. The proposed approaches have been examined and tested in the IEEE 30 bus and the IEEE 57 bus power systems. The performances of MOCIPSO, MOIPSO, and multi-objective PSO (MOPSO) approaches are compared with respect to multi-objective performance measures. The simulation results are promising and confirm the ability of MOCIPSO and MOIPSO approaches for generating lower power losses and smaller L index than MOPSO method

  14. A mobile ground-based radar sensor for detection and tracking of moving objects

    Science.gov (United States)

    Vivet, Damien; Checchin, Paul; Chapuis, Roland; Faure, Patrice; Rouveure, Raphaël; Monod, Marie-Odile

    2012-12-01

    The detection and tracking of moving objects (DATMO) in an outdoor environment from a mobile robot are difficult tasks because of the wide variety of dynamic objects. A reliable discrimination of mobile and static detections without any prior knowledge is often conditioned by a good position estimation obtained using Global Positionning System/Differential Global Positioning System (GPS/DGPS), proprioceptive sensors, inertial sensors or even the use of Simultaneous Localization and Mapping (SLAM) algorithms. In this article a solution of the DATMO problem is presented to perform this task using only a microwave radar sensor. Indeed, this sensor provides images of the environment from which Doppler information can be extracted and interpreted in order to obtain not only velocities of detected objects but also the robot's own velocity.

  15. Multi-objective analysis of a component-based representation within an interactive evolutionary design system

    Science.gov (United States)

    Machwe, A. T.; Parmee, I. C.

    2007-07-01

    This article describes research relating to a user-centered evolutionary design system that evaluates both engineering and aesthetic aspects of design solutions during early-stage conceptual design. The experimental system comprises several components relating to user interaction, problem representation, evolutionary search and exploration and online learning. The main focus of the article is the evolutionary aspect of the system when using a single quantitative objective function plus subjective judgment of the user. Additionally, the manner in which the user-interaction aspect affects system output is assessed by comparing Pareto frontiers generated with and without user interaction via a multi-objective evolutionary algorithm (MOEA). A solution clustering component is also introduced and it is shown how this can improve the level of support to the designer when dealing with a complex design problem involving multiple objectives. Supporting results are from the application of the system to the design of urban furniture which, in this case, largely relates to seating design.

  16. Can state-of-the-art HVS-based objective image quality criteria be used for image reconstruction techniques based on ROI analysis?

    Science.gov (United States)

    Dostal, P.; Krasula, L.; Klima, M.

    2012-06-01

    Various image processing techniques in multimedia technology are optimized using visual attention feature of the human visual system. Spatial non-uniformity causes that different locations in an image are of different importance in terms of perception of the image. In other words, the perceived image quality depends mainly on the quality of important locations known as regions of interest. The performance of such techniques is measured by subjective evaluation or objective image quality criteria. Many state-of-the-art objective metrics are based on HVS properties; SSIM, MS-SSIM based on image structural information, VIF based on the information that human brain can ideally gain from the reference image or FSIM utilizing the low-level features to assign the different importance to each location in the image. But still none of these objective metrics utilize the analysis of regions of interest. We solve the question if these objective metrics can be used for effective evaluation of images reconstructed by processing techniques based on ROI analysis utilizing high-level features. In this paper authors show that the state-of-the-art objective metrics do not correlate well with subjective evaluation while the demosaicing based on ROI analysis is used for reconstruction. The ROI were computed from "ground truth" visual attention data. The algorithm combining two known demosaicing techniques on the basis of ROI location is proposed to reconstruct the ROI in fine quality while the rest of image is reconstructed with low quality. The color image reconstructed by this ROI approach was compared with selected demosaicing techniques by objective criteria and subjective testing. The qualitative comparison of the objective and subjective results indicates that the state-of-the-art objective metrics are still not suitable for evaluation image processing techniques based on ROI analysis and new criteria is demanded.

  17. Identification of Mine-Shaped Objects based on an Efficient Phase Stepped-Frequency Radar Approach

    DEFF Research Database (Denmark)

    Sørensen, Helge Bjarup Dissing; Jakobsen, Kaj Bjarne; Nymann, Ole

    1997-01-01

    A computational efficient approach to identify very small mine-shaped plastic objects, e.g. M56 Anti-Personnel (AP) mines buried in the ground, is presented. The size of the objects equals the smallest AP-mines in use today, i.e., the most difficult mines to detect with respect to humanitarian mine clearance. Our approach consists of three stages, the phase stepped-frequency radar method, generation of a quarternary image and template crosscorrelation. The phase stepped-frequency radar method be...

  18. Dynamic Linking of Smart Digital Objects Based on User Navigation Patterns

    CERN Document Server

    Elango, A; Nelson, M L; Elango, Aravind; Bollen, Johan; Nelson, Michael L.

    2004-01-01

    We discuss a methodology to dynamically generate links among digital objects by means of an unsupervised learning mechanism which analyzes user link traversal patterns. We performed an experiment with a test bed of 150 complex data objects, referred to as buckets. Each bucket manages its own content, provides methods to interact with users and individually maintains a set of links to other buckets. We demonstrate that buckets were capable of dynamically adjusting their links to other buckets according to user link selections, thereby generating a meaningful network of bucket relations. Our results indicate such adaptive networks of linked buckets approximate the collective link preferences of a community of user

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

    DEFF Research Database (Denmark)

    Henriksen, Lars

    1994-01-01

    The paper describes an approach to real time detection and tracking of underwater objects, using image sequences from an electrically scanned high-resolution sonar. The use of a high resolution sonar provides a good estimate of the location of the objects, but strains the computers on board, because of the high rate of raw data. The amount of data can be cut down by decreasing the scanned area, but this reduces the possibility of planning an optimal path. In the paper methods are described, that...

  20. Multi Objective Optimization Using Biogeography Based Optimization and Differentional Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Samira Abdi

    2012-11-01

    The proposed algorithm (MOBBO/DE makes the use of nondominated sorting approach improve the convergence ability efficiently and hence it can generate the promising candidate solutions. It also combines crowding distance to guarantee the diversity of Pareto optimal solutions. The proposed approach is validated using several test functions and some metrics taken from the standard literature on evolutionary multi-objective optimization. Results indicate that the approach is highly competitive and that can be considered a viable alternative to solve multi-objective optimization problems.