WorldWideScience
1

LADAR object detection and tracking  

Science.gov (United States)

The paper describes an innovative LADAR system for use in detecting, acquiring and tracking high-speed ballistic such as bullets and mortar shells and rocket propelled objects such as Rocket Propelled Grenades (RPGs) and TOW missiles. This class of targets proves to be a considerable challenge for classical RADAR systems since the target areas are small, velocities are very high and target range is short. The proposed system is based on detector and illuminator technology without any moving parts. The target area is flood illuminated with one or more modulated sources and a proprietary-processing algorithm utilizing phase difference return signals generates target information. All aspects of the system utilize existing, low risk components that are readily available from optical and electronic vendors. Operating the illuminator in a continuously modulated mode permits the target range to be measured by the phase delay of the modulated beam. Target velocity is measured by the Doppler frequency shift of the returned signal.

Monaco, Sam D.

2004-10-01

2

ALLFlight: detection of moving objects in IR and ladar images  

Science.gov (United States)

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

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

2013-05-01

3

Three-dimensional material identification and hazard detection with shortwave infrared supercontinuum based spectral ladar  

Science.gov (United States)

This paper presents new experimental results from a prototype Spectral LADAR, which combines active multispectral and 3D time-of-flight point cloud imaging. The physical domain unification of these imaging modalities based on a pulse modulated supercontinuum source enables substantially higher fidelity images of obscured targets compared to the data domain fusion of passive hyperspectral cameras and conventional LADAR imagers. Spectral LADAR produces 3D spectral point clouds with unambiguously associated 3D image points and spectral vectors, promoting improved object classification performance in cluttered scenes. The 3D shape and material spectral signature of objects may be acquired in daylight or darkness, behind common glass, and behind obscurants such as foliage and camouflage. These capabilities are demonstrated by data obtained from test scenes. These scenes include plastic mine-like objects obscured by foliage, distinction of hazardous explosives inside plastic containers versus innocuous decoy materials, and 3D spectral imaging behind ordinary glass windows. These scenes, at effective ranges of approximately 40 meters, are imaged with nanosecond-regime optical pulses spanning 1.08 ?m to 1.62 ?m divided into 25 independently ranged spectral bands. The resultant point cloud is spectrally classified according to material type. In contrast to other active spectral imaging techniques, Spectral LADAR is well suited to operate at high pixel and frame rates and at considerable stand-off distances. A combination of favorable attributes, including eye safe wavelengths, relatively small apertures, and very short (single pulse) receiver integration time, bear the potential for this technique to be used on robotic platforms for on-the-move imaging and high area coverage rates.

Powers, Michael A.

2012-06-01

4

LADAR based mapping and obstacle detection system for service robots  

OpenAIRE

When travelling in unfamiliar environments, a mobile service robot needs to acquire information about his surroundings in order to detect and avoid obstacles and arrive safely at his destination. This dissertation presents a solution for the problem of mapping and obstacle detection in indoor/outdoor structured3 environments, with particular application on service robots equipped with a LADAR. Since this system was designed for structured environments, offroad terrains are o...

Gomes, Pedro Miguel Barros

2010-01-01

5

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

Science.gov (United States)

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

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

2014-10-01

6

Spectral ladar: towards active 3D multispectral imaging  

Science.gov (United States)

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.

Powers, Michael A.; Davis, Christopher C.

2010-04-01

7

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

Science.gov (United States)

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

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

2014-03-20

8

Elastic ladar modeling for synthetic imaging applications  

Science.gov (United States)

The Digital Imaging and Remote Sensing Image Generation (DIRSIG) model is a synthetic imagery generation model developed at the Center for Imaging Science (CIS) at the Rochester Institute of Technology (RIT). It is a quantitative first principle based model that calculates the sensor reaching radiance from the visible through to the long wave infrared on a spectral basis. DIRSIG generates a very accurate representation of what a sensor would see by modeling all the processes involved in the imaging chain. Currently, DIRSIG only models passive sources such as the sun and blackbody radiation due to the temperature of an object. Active systems have the benefit of the user being able to control the illumination source and tailor it for specific applications. Remote sensing Laser Detection and Ranging (LADAR) systems that utilize a laser as the active source have been in existence for over 30 years. Recent advances in tunable lasers and infrared detectors have allowed much more sophisticated and accurate work to be done, but a comprehensive spectral LADAR model has yet to be developed. In order to provide a tool to assist in LADAR development, this research incorporates a first principle based elastic LADAR model into DIRSIG. It calculates the irradiance onto the focal plane on a spectral basis for both the atmospheric and topographic return, based on the system characteristics and the assumed atmosphere. The geometrical form factor, a measure of the overlap between the sensor and receiver field-of-view, is carefully accounted for in both the monostatic and bistatic cases. The model includes the effect of multiple bounces from topographical targets. Currently, only direct detection systems will be modeled. Several sources of noise are extensively modeled, such as speckle from rough surfaces. Additionally, atmospheric turbulence effects including scintillation, beam effects, and image effects are accounted for. To allow for future growth, the model and coding are modular and anticipate the inclusion of advanced sensor modules and inelastic scattering.

Burton, Robin R.; Schott, John R.; Brown, Scott D.

2002-11-01

9

Dual Mode (MWIR AND LADAR) Seeker for Missile Defense  

Science.gov (United States)

This paper identifies the key weapon system requirements of a dual mode seeker solution that performs mission critical target discrimination, tracking and aimpoint selection during stressing conditions. System level trades made to integrate ladar into a current generation MD seeker are summarized. Proof of concept hardware was developed to both demonstrate feasibility and collect field data on simulated threats and decoys. The packaging, thermal and bore sight of separate focal planes are addressed. Operationally the seeker is cued by ground based radar to the location and direction of the threat cloud (threats and non-threats). The IR seeker tracks these objects (when separated) and provides a prioritized location map for the ladar. The ladar is used to sequentially and periodically interrogate these objects to separated CSO's and extract micro-dynamic information used for discrimination. The paper details why a Geiger mode flash ladar was selected for this application and how its output is used in discrimination. Dual mode images of threat and decoy objects are presented at various signal levels and resolutions to simulate a typical engagement timeline. This dual mode seeker will be used to gather captive carry signature data on near future MD tests.

DeFlumere, Michael E.; Fong, Michael W.; Stewart, Hamilton M.

2002-07-01

10

Recognition of tanks using laser radar (LADAR) images  

Science.gov (United States)

Three-dimensional sensors based on Laser Radar (LADAR) technology possess vast potential for the future battlefield. This work presents an algorithm for the recognition of T62 and T72 tanks from 3D imagery. The algorithm consists of several stages: a) Pre-processing of LADAR images to remove range noise and to determine ground level. b) Segmentation to extract regions that fulfill certain pre-defined conditions. c) Extraction of specific tank features from each region. d) Applying a Fuzzy Logic classifier on the feature vector to discriminate between T62 or T72 tanks and other type of targets or natural clutter. A commercial airborne LADAR sensor was used to acquire images from an area of 40 square kilometers with a measurement density of 20 pixels per square meter and a range noise of 15 cm (1 sigma). The images included more than a hundred man-made objects (tanks, armored personnel carriers, trucks, cranes)along with natural clutter (vegetation and boulders). Among the targets were 18 tanks, two of which were covered with a camouflage net. The algorithm recognized the 16 uncovered tanks with a False Alarm Rate (FAR) of 0.025 per square kilometer. This FAR value is better than the respective FAR values derived for 2D Imaging where Automatic Target Recognition (ATR) techniques are applied. These results show promise for automatic recognition of various targets employing LADAR sensors.

Garten, Haim; Tal, Yoram; Swirski, Yoram; Imber, Amir

2004-12-01

11

Research of range image on non-scanning LADAR based on APD arrays  

Science.gov (United States)

Compared to scanner imaging ladar, non-scanning LADAR plays a more prominent role in the militarily imaging scenarios. Non-scanning LADAR has many advantages, such as structure simplicity, high reliability, imaging efficiency and etc. However the range accuracy is low. This paper proposes a technique to use a designed delay line module in the APD array LADAR systems, which could significantly improve the range accuracy in all channels. A semiconductor laser is used as light source. A 5×5 APD array detector is adopted as the sensitive unit. A 25 channel parallel amplifier circuit is designed to process the signal with bandwidth 240 MHz . Field Programmable Gate Array (FPGA) is used to process these 25 signals paralleled, with a delay line module designed, to significant improve the ranging accuracy .The clock frequency of FPGA is 400MHz with accuracy 2.5ns. The delay lines module are used to measure part of pulse flying time, which is shorter than the clock cycle and could not be directly measured by the clock, and that is the cause of the ranging accuracy. Every delay cell is 46picoseconds , total timing accuracy is less than 500picoseconds. By using above technique, a short distance imaging experiment is presented and get the 5 ×5 pixels range image. The result is analyzed together with the factors, which influence the accuracy of ranging image, it shows the ranging accuracy of each pixel is 10cm. And some advanced methods are proposed to improve the accuracy of the system in the future.

Li, Baowei; Han, Shaokun; Xia, Wenze; Kang, Yanyan

2014-10-01

12

Obstacle detection in foliage with ladar and radar  

Science.gov (United States)

Autonomous off-road navigation is central to several important applications of unmanned ground vehicles. This requires the ability to detect obstacles in vegetation. We examine the prospects for doing so with scanning ladar and with a linear array of 2.2 GHz micro-impulse radar transceivers. For ladar, we summarize our work to date on algorithms for detecting obstacles in tall grass with single-axis ladar, then present a simple probabilistic model of the distance into tall grass that ladar-based obstacle detection is possible.

Matthies, Larry; Bergh, Chuck; Castano, Andres; Macedo, Jose; Manduchi, Roberto

2003-01-01

13

Fusion of hyperspectral and ladar data for autonomous target detection  

Science.gov (United States)

Robust fusion of data from disparate sensor modalities can provide improved target detection performance over those attainable with the individual sensors. In particular, detection of low-radiance manmade objects or objects under shadow obscuration in hyperspectral imagery (HSI) with acceptable false alarm rates has proven especially challenging. We have developed a fusion algorithm for the enhanced detection of difficult targets when the HSI data is simultaneously collected with LADAR data. Initial detections are obtained by applying a sub-space RX (SSRX) algorithm to the HSI data. In parallel, LADAR-derived digital elevation map (DEM) is segmented and coordinates of objects within a specific elevation range and size are returned to the HSI processor for their spectral signature extraction. Each extracted signature that has not been already detected by SSRX is used in secondary HSI detection employing the adaptive cosine estimator (ACE) algorithm. We show that spatial distribution of ACE score allows for confident discrimination between background elevations and manmade objects. Key to cross-characterization of the data is the accurate co-alignment of the image data. We have also developed an algorithm for automatic co-registration of ladar and HSI imagery, based on the maximization of mutual information, which can provide accurate, sub-pixel registration even if the case when the imaging geometries for the two sensors differ. Details of both algorithms will be presented and results from application to field data will be discussed.

Kanaev, A. V.; Walls, T. J.

2011-05-01

14

Echo signal modeling of imaging LADAR target simulator  

Science.gov (United States)

LADAR guidance technology is one of the most promising precision guidance technologies. In the aim of simulating the return waveform of the target, a 3D geometrical model of a target is built and mathematical model of target echo signal for imaging LADAR target simulator is established by using the coordinate transformation, radar equation and ranging equation. First, the 3D geometrical data of the object model is obtained by 3D geometrical modeling. Then, target coordinate system and viewpoint coordinate system are created respectively. 3D geometrical model is built in the target coordinate system. The 3D geometrical model is transformed to the viewpoint coordinate system based on the derived relationship between the two coordinate systems. Furthermore, the range information of the target could be obtained under viewpoint coordinate system. Thus, the data of the target echo signal can be obtained by using radar equation and ranging equation. Finally, the echo signal can be exported through corresponding data interface. In order to validate the method proposed in this paper, the echo signal generated by a typical target is computed and compared with the theory solutions. The signals can be applied to drive target simulator to generate a physical target LADAR image.

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

2014-11-01

15

Construction of multi-functional open modulized Matlab simulation toolbox for imaging ladar system  

Science.gov (United States)

Ladar system simulation is to simulate the ladar models using computer simulation technology in order to predict the performance of the ladar system. This paper presents the developments of laser imaging radar simulation for domestic and overseas studies and the studies of computer simulation on ladar system with different application requests. The LadarSim and FOI-LadarSIM simulation facilities of Utah State University and Swedish Defence Research Agency are introduced in details. This paper presents the low level of simulation scale, un-unified design and applications of domestic researches in imaging ladar system simulation, which are mostly to achieve simple function simulation based on ranging equations for ladar systems. Design of laser imaging radar simulation with open and modularized structure is proposed to design unified modules for ladar system, laser emitter, atmosphere models, target models, signal receiver, parameters setting and system controller. Unified Matlab toolbox and standard control modules have been built with regulated input and output of the functions, and the communication protocols between hardware modules. A simulation based on ICCD gain-modulated imaging ladar system for a space shuttle is made based on the toolbox. The simulation result shows that the models and parameter settings of the Matlab toolbox are able to simulate the actual detection process precisely. The unified control module and pre-defined parameter settings simplify the simulation of imaging ladar detection. Its open structures enable the toolbox to be modified for specialized requests. The modulization gives simulations flexibility.

Wu, Long; Zhao, Yuan; Tang, Meng; He, Jiang; Zhang, Yong

2011-06-01

16

Integration and demonstration of MEMS-scanned LADAR for robotic navigation  

Science.gov (United States)

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).

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

2014-06-01

17

Adaptive ladar receiver for multispectral imaging  

Science.gov (United States)

We are developing a novel 2D focal plane array (FPA) with read-out integrated circuit (ROIC) on a single chip for 3D laser radar imaging. The ladar will provide high-resolution range and range-resolved intensity images for detection and identification of difficult targets. The initial full imaging-camera-on-a-chip system will be a 64 by 64 element, 100-micrometers pixel-size detector array that is directly bump bonded to a low-noise 64 by 64 array silicon CMOS-based ROIC. The architecture is scalable to 256 by 256 or higher arrays depending on the system application. The system will provide all the required electronic processing at pixel level and the smart FPA enables directly producing the 3D or 4D format data to be captured with a single laser pulse. The detector arrays are made of uncooled InGaAs PIN device for SWIR imaging at 1.5 micrometers wavelength and cooled HgCdTe PIN device for MWIR imaging at 3.8 micrometers wavelength. We are also investigating concepts using multi-color detector arrays for simultaneous imaging at multiple wavelengths that would provide additional spectral dimension capability for enhanced detection and identification of deep-hide targets. The system is suited for flash ladar imaging, for combat identification of ground targets from airborne platforms, flash-ladar imaging seekers, and autonomous robotic/automotive vehicle navigation and collision avoidance applications.

Johnson, Kenneth; Vaidyanathan, Mohan; Xue, Song; Tennant, William E.; Kozlowski, Lester J.; Hughes, Gary W.; Smith, Duane D.

2001-09-01

18

Foliage discrimination using a rotating ladar  

Science.gov (United States)

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

Castano, A.; Matthies, L.

2003-01-01

19

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

Science.gov (United States)

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.

Williams, George M.; Huntington, Andrew S.

2006-05-01

20

Laboratory demonstration of Fresnel telescope imaging ladar  

Science.gov (United States)

In this paper, we present a laboratory demonstration of Fresnel telescope imaging ladar system for imaging the faraway objects with high resolution. Two concentric and coaxial quadratic wavefront with orthogonal polarization are used as scanning beams to illuminate the target. The scattered light from the target is heterodyne detected by a 90 degree 2×4 optical hybrid with two balanced receivers. The target image can be reconstructed by digital processing of the output signals of the balanced receivers. Point targets 4.3m away are reconstructed with high resolution in experiments.

Dai, Enwen; Liu, Liren; Sun, Jianfeng; Wu, Yapeng; Zhou, Yu; Yan, Aimin; Zhi, Yanan

2011-09-01

21

Optical phased-array ladar.  

Science.gov (United States)

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

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

2014-11-01

22

Doublet Pulse Coherent Laser Radar for Tracking of Resident Space Objects  

Science.gov (United States)

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

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

2014-01-01

23

Fusion of LADAR with SAR for precision strike  

Energy Technology Data Exchange (ETDEWEB)

This paper presents a concept for fusing 3-dimensional image reconnaissance data with LADAR imagery for aim point refinement. The approach is applicable to fixed or quasi-fixed targets. Quasi-fixed targets are targets that are not expected to be moved between the time of reconnaissance and the time of target engagement. The 3-dimensional image data is presumed to come from standoff reconnaissance assets tens to hundreds of kilometers from the target area or acquisitions prior to hostilities. Examples are synthetic aperture radar (SAR) or stereoprocessed satellite imagery. SAR can be used to generate a 3-dimensional map of the surface through processing of data acquired with conventional SAR acquired using two closely spaced, parallel reconnaissance paths, either airborne or satellite based. Alternatively, a specialized airborne SAR having two receiving antennas may be used for data acquisition. The data sets used in this analysis are: (1) LADAR data acquired using a Hughes-Danbury system flown over a portion of Kirtland AFB during the period September 15--16, 1993; (2) two pass interferometric SAR data flown over a terrain-dominated area of Kirtland AFB; (3) 3-dimensional mapping of an urban-dominated area of the Sandia National Laboratories and adjacent cultural area extracted from aerial photography by Vexcel Corporation; (4) LADAR data acquired at Eglin AFB under Wright Laboratory`s Advanced Technology Ladar System (ATLAS) program using a 60 {mu}J, 75 KHz Co{sub 2} laser; and (5) two pass interferometric SAR data generated by Sandia`s STRIP DCS (Data Collection System) radar corresponding to the ATLAS LADAR data. The cultural data set was used in the urban area rather than SAR because high quality interferometric SAR data were not available for the urban-type area.

Cress, D.H.; Muguira, M.R.

1995-03-01

24

Terrain classification of LADAR data over Haitian urban environments using a lower envelope follower and adaptive gradient operator  

OpenAIRE

In response to the 2010 Haiti earthquake, the ALIRT ladar system was tasked with collecting surveys to support disaster relief efforts. Standard methodologies to classify the ladar data as ground, vegetation, or man-made features failed to produce an accurate representation of the underlying terrain surface. The majority of these methods rely primarily on gradient- based operations that often perform well for areas with low topographic relief, but often fail in areas of high topographic relie...

Neuenschwander, Amy L.; Magruder, Lori A.; Crawford, Melba M.; Weed, Christopher A.; Fried, Dale G.; Knowlton, Robert C.; Heinrichs, Richard M.; Cannata, Richard

2010-01-01

25

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

Science.gov (United States)

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

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

2014-09-01

26

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

Science.gov (United States)

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

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

2014-11-01

27

Usage-based object similarity  

OpenAIRE

Recommender systems are widely used online to support users in finding relevant information. They can be based on different techniques such as content-based and collaborative filtering. In this paper, we introduce a new way of similarity calculation for item-based collaborative filtering. Thereby we focus on the usage of an object and not on the object’s users as we claim the hypothesis that similarity of usage indicates content similarity. To prove this hypothesis we use learning objects a...

Niemann, K.; Scheffel, M.; Friedrich, M.; Kirschenmann, U.; Schmitz, H. -c; Wolpers, M.

2010-01-01

28

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

Science.gov (United States)

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

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

2011-01-01

29

Sparsity based Single Object Tracking  

Directory of Open Access Journals (Sweden)

Full Text Available Object tracking has importance in various video processing applications like video surveillance, perceptual user interface driver assistance, tracking etc. This paper deals with a new tracking technique that combines the dictionary based background subtraction along with sparsity based tracking. The speed and performance challenges faced during the sparsity based tracking alone are addressed, as it is based on a background subtraction preprocessing and local compressive tracking. It also overcomes the challenges faced by the traditional techniques due to illumination variation, pose and shape change of the object. Output of the proposed technique is compared with that of compressive tracking technique.

Glincy Abraham

2013-07-01

30

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

International Nuclear Information System (INIS)

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

31

Advanced pixel design for infrared 3D LADAR imaging  

Science.gov (United States)

CEA Leti has demonstrated the good performances of its MWIR HgCdTe avalanche photodiode arrays. Gains above 20 at a moderate bias voltage of 5V have typically been measured with an excess noise factor of only 1.2. The next generation of infrared focal plane arrays will take advantage of these characteristics to address new applications, reduce system complexity and enhance performances. One of the main opportunities offered by avalanche photodiode detectors concerns long range active imaging. This paper reports the development of two novel pixel architectures for 3D active imaging based on flash LADAR technology. Both pixels have been designed in a standard 0.35?m CMOS process and perform time-of-flight measurement in addition to 2D intensity imaging with a single emitted laser pulse. The analog input circuits have been optimized to allow fast pulse detection while providing robustness to process variability. A small readout IC demonstrator has been fabricated and coupled to a 10x10 avalanche photodiode array at 40?m pixel pitch. The first test results in lab conditions show good electro-optical performances with a ranging resolution around 30cm (2ns).

Guellec, Fabrice; Tchagaspanian, Michaël; de Borniol, Eric; Castelein, Pierre; Perez, André; Rothman, Johan

2008-04-01

32

Ladar range image denoising by a nonlocal probability statistics algorithm  

Science.gov (United States)

According to the characteristic of range images of coherent ladar and the basis of nonlocal means (NLM), a nonlocal probability statistics (NLPS) algorithm is proposed in this paper. The difference is that NLM performs denoising using the mean of the conditional probability distribution function (PDF) while NLPS using the maximum of the marginal PDF. In the algorithm, similar blocks are found out by the operation of block matching and form a group. Pixels in the group are analyzed by probability statistics and the gray value with maximum probability is used as the estimated value of the current pixel. The simulated range images of coherent ladar with different carrier-to-noise ratio and real range image of coherent ladar with 8 gray-scales are denoised by this algorithm, and the results are compared with those of median filter, multitemplate order mean filter, NLM, median nonlocal mean filter and its incorporation of anatomical side information, and unsupervised information-theoretic adaptive filter. The range abnormality noise and Gaussian noise in range image of coherent ladar are effectively suppressed by NLPS.

Xia, Zhi-Wei; Li, Qi; Xiong, Zhi-Peng; Wang, Qi

2013-01-01

33

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

Science.gov (United States)

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.

Neilsen, Kevin D.; Budge, Scott E.

2013-11-01

34

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

Directory of Open Access Journals (Sweden)

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

Yong Joon Kwon

2013-07-01

35

Applications of digital IF receivers and under-sampling technique in ladar  

Science.gov (United States)

The traditional technique of phase laser range finder is mixing high frequency signals with analog circuits and filtering them to obtain the useful signal with low frequency. But the analog mixing circuits are susceptible to interference and will bring amplitude attenuation, phase jitter and offset and this way has difficulties in achieving high precision ranging and fast speed ranging at the same time. The method of this paper is based on under-sampling technique with digital synchronous detection and referring to Digital down converter technique of digital IF receiver in radar system. This method not only reduces the complexity of data processing, improves the speed and accuracy of phase detection at the same time, but also reduces requirements for ADC devices and DSP chips in the ladar system by a lower sampling rate. At the same time, the structure of electronic system is global simplified compared with traditional analog ladar system and the anti-jamming is greatly enhanced. So this method has important research value.

Song, Zhi-yuan; Zhu, Shao-lan; Dong, Li-jun; Feng, Li; He, Hao-dong

2011-06-01

36

3D-LZ helicopter ladar imaging system  

Science.gov (United States)

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.

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

2010-04-01

37

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

Science.gov (United States)

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

Barber, Zeb W; Dahl, Jason R

2014-08-20

38

Semantic Types for Class-based Objects  

OpenAIRE

We investigate semantics-based type assignment for class-based object-oriented programming. Our motivation is developing a theoretical basis for practical, expressive, type-based analysis of the functional behaviour of object-oriented programs. We focus our research using Featherweight Java, studying two notions of type assignment:- one using intersection types, the other a ‘logical’ restriction of recursive types. We extend to the object-oriented setting some existing resu...

Rowe, Reuben

2013-01-01

39

View-based 3-D object retrieval  

CERN Document Server

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

Gao, Yue

2014-01-01

40

Range accuracy of a Gated-Viewing system compared to a 3-D Flash LADAR under different turbulence conditions  

OpenAIRE

While a Gated-Viewing system primarily provides the intensity values of the captured laser radiation, it is also possible to determine range information in a static scenario by the sliding gates method. In this paper, we compare this method to a time-of-flight based 3-D Flash LADAR technique in terms of range accuracy under moderate and strong turbulence conditions. The first method requires several Gated-Viewing images (several laser pulses) with stepwise increased gate delay times. For a 3-...

Go?hler, B.; Lutzmann, P.

2010-01-01

41

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)

Full Text Available SciELO Brazil | Language: Portuguese Abstract in portuguese 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

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

2011-06-01

42

OVID: toward object-based video retrieval  

Science.gov (United States)

The current trend in content-based retrieval is the development of object-based systems. Such systems enable users to make higher level queries which are more intuitive to them than queries based on visual primitives. In this paper, we present OVID, our Object-based VIDeo retrieval system. It currently consists of a video parsing module, an annotation module, a user interface and a search mechanism. A combined multiple expert approach is at the heart of the video parsing routine for an improved performance. The annotation module extracts color and texture-based region information which will be used by the neural-network-based search routine at query tie. The iconic query paradigm on which the system is based provides users with a flexible means to define object-based queries.

Levienaise-Obadia, Barbara V.; Christmas, William J.; Kittler, Josef; Messer, Kieron; Yusoff, Yusseri

1999-12-01

43

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

DEFF Research Database (Denmark)

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

Kingo, Osman Skjold; KrØjgaard, Peter

2011-01-01

44

Speedy Object Detection based on Shape  

OpenAIRE

This study is a part of design of an audio system for in-house object detection system for visually impaired, low vision personnel by birth or by an accident or due to old age. The input of the system will be scene and output as audio. Alert facility is provided based on severity levels of the objects (snake, broke glass etc) and also during difficulties. The study proposed techniques to provide speedy detection of objects based on shapes and its scale. Features are extracti...

Jayanta Singh, Y.; Shalu Gupta

2013-01-01

45

Spatio-activity based object detection  

OpenAIRE

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 m...

Springett, Jarrad; Vendrig, Jeroen

2008-01-01

46

Time reversed photonic beamforming of arbitrary waveform ladar arrays  

Science.gov (United States)

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

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

2007-04-01

47

Characterization measurements of ASC FLASH 3D ladar  

Science.gov (United States)

As a part of the project agreement between the Swedish Defence Research Agency (FOI) and the United States of American's Air Force Research Laboratory (AFRL), a joint field trial was performed in Sweden during two weeks in January 2009. The main purpose for this trial was to characterize AFRL's latest version of the ASC (Advanced Scientific Concepts [1]) FLASH 3D LADAR sensor. The measurements were performed essentially in FOI´s optical hall whose 100 m indoor range offers measurements under controlled conditions minimizing effects such as atmospheric turbulence. Data were also acquired outdoor in both forest and urban scenarios, using vehicles and humans as targets, with the purpose of acquiring data from more dynamic platforms to assist in further algorithm development. This paper shows examples of the acquired data and presents initial results.

Larsson, Håkan; Gustafsson, Frank; Johnson, Bruce; Richmond, Richard; Armstrong, Ernest

2009-09-01

48

REBOL: Relative Expression-Based Object Language  

Science.gov (United States)

REBOL, the Relative Expression-Based Object Language, is a fascinating new scripting language developed at REBOL Technologies by Carl Sassenrath, the architect of the Amiga operating system. REBOL is intended to be used for Internet programming and, among its many features, it contains very easy-to-use networking capabilities. An example is this tiny line of REBOL code which retrieves a web page and emails it to a (fictitious) email address: "send fred@cs.wisc.edu read

Sassenrath, Carl.

49

Risk-Based Object Oriented Testing  

Science.gov (United States)

Software testing is a well-defined phase of the software development life cycle. Functional ("black box") testing and structural ("white box") testing are two methods of test case design commonly used by software developers. A lesser known testing method is risk-based testing, which takes into account the probability of failure of a portion of code as determined by its complexity. For object oriented programs, a methodology is proposed for identification of risk-prone classes. Risk-based testing is a highly effective testing technique that can be used to find and fix the most important problems as quickly as possible.

Rosenberg, Linda H.; Stapko, Ruth; Gallo, Albert

2000-01-01

50

Phase error suppression by low-pass filtering for synthetic aperture imaging ladar  

Science.gov (United States)

Compared to synthetic aperture radar (SAR), synthetic aperture imaging ladar (SAIL) is more sensitive to the phase errors induced by atmospheric turbulence, undesirable line-of-sight translation-vibration and waveform phase error, because the light wavelength is about 3-6 orders of magnitude less than that of the radio frequency. This phase errors will deteriorate the imaging results. In this paper, an algorithm based on low-pass filtering to suppress the phase error is proposed. In this algorithm, the azimuth quadratic phase history with phase error is compensated, then the fast Fourier transform (FFT) is performed in azimuth direction, after the low-pass filtering, the inverse FFT is performed, then the image is reconstructed simultaneously in the range and azimuth direction by the two-dimensional (2D) FFT. The highfrequency phase error can be effectively eliminated hence the imaging results can be optimized by this algorithm. The mathematical analysis by virtue of data-collection equation of side-looking SAIL is presented. The theoretical modeling results are also given. In addition, based on this algorithm, a principle scheme of optical processor is proposed. The verified experiment is performed employing the data obtained from a SAIL demonstrator.

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

2014-09-01

51

ROIC for gated 3D imaging LADAR receiver  

Science.gov (United States)

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%.

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

2013-09-01

52

Water Detection Based on Object Reflections  

Science.gov (United States)

Water bodies are challenging terrain hazards for terrestrial unmanned ground vehicles (UGVs) for several reasons. Traversing through deep water bodies could cause costly damage to the electronics of UGVs. Additionally, a UGV that is either broken down due to water damage or becomes stuck in a water body during an autonomous operation will require rescue, potentially drawing critical resources away from the primary operation and increasing the operation cost. Thus, robust water detection is a critical perception requirement for UGV autonomous navigation. One of the properties useful for detecting still water bodies is that their surface acts as a horizontal mirror at high incidence angles. Still water bodies in wide-open areas can be detected by geometrically locating the exact pixels in the sky that are reflecting on candidate water pixels on the ground, predicting if ground pixels are water based on color similarity to the sky and local terrain features. But in cluttered areas where reflections of objects in the background dominate the appearance of the surface of still water bodies, detection based on sky reflections is of marginal value. Specifically, this software attempts to solve the problem of detecting still water bodies on cross-country terrain in cluttered areas at low cost.

Rankin, Arturo L.; Matthies, Larry H.

2012-01-01

53

MOTION BASED OBJECT DETECTION AND CLASSIFICATION FOR NIGHT SURVEILLANCE  

OpenAIRE

This paper describes a simple technique for object detection and temporal data association of thermal image sequences. Night surveillance system using thermal imaging involves object detection, temporal data association and tracking of object. Object detection could be motion based or feature based. The temporal data association in multi-object classification involves finding the minimum distances between an object in current frame to the objects in previous frame. A performance comparison is...

Usham Dias; Milind Rane

2012-01-01

54

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

OpenAIRE

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 ...

Silva, Andrea Noreen D.; Nagalakshmi Shagoufta Taskeen

2014-01-01

55

Geodesic-based Salient Object Detection  

OpenAIRE

Saliency detection has been an intuitive way to provide useful cues for object detection and segmentation, as desired for many vision and graphics applications. In this paper, we provided a robust method for salient object detection and segmentation. Other than using various pixel-level contrast definitions, we exploited global image structures and proposed a new geodesic method dedicated for salient object detection. In the proposed approach, a new geodesic scheme, namely g...

Jiang, Richard M.

2013-01-01

56

University collections and object-based pedagogies  

Directory of Open Access Journals (Sweden)

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

Andrew Simpson

2012-10-01

57

Object-based auditory and visual attention  

OpenAIRE

Theories of visual attention argue that attention operates on perceptual objects, and thus that interactions between object formation and selective attention determine how competing sources interfere with perception. In auditory perception, theories of attention are less mature, and no comprehensive framework exists to explain how attention influences perceptual abilities. However, the same principles that govern visual perception can explain many seemingly disparate auditory phenomena. In pa...

Shinn-cunningham, Barbara G.

2008-01-01

58

Action modulates object-based selection.  

OpenAIRE

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

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

2005-01-01

59

Saliency-based object recognition in video  

OpenAIRE

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

Gonza?lez-di?az, Iva?n; Boujut, Hugo; Buso, Vincent; Benois-pineau, Jenny; Domenger, Jean-philippe

2013-01-01

60

Category vs. Object Knowledge in Category-Based Induction  

Science.gov (United States)

In one form of category-based induction, people make predictions about unknown properties of objects. There is a tension between predictions made based on the object's specific features (e.g., objects above a certain size tend not to fly) and those made by reference to category-level knowledge (e.g., birds fly). Seven experiments with artificial…

Murphy, Gregory L.; Ross, Brian H.

2010-01-01

61

Optical image reconstruction using an astigmatic lens for synthetic-aperture imaging ladar  

Science.gov (United States)

An optical processor for synthetic-aperture imaging ladar (SAIL) utilizing one astigmatic lens is proposed. The processor comprises two structures of transmitting and reflecting. The imaging process is mathematically analyzed using the unified data-collection equation of side-looking and down-looking SAILs. Results show that the astigmatic lens can be replaced with a cylindrical lens on certain conditions. To verify this concept, laboratory experiment is conducted, the imaging result of data collected from one SAIL demonstrator is given.

Sun, Zhiwei; Hou, Peipei; Zhi, Yanan; Sun, Jianfeng; Zhou, Yu; Xu, Qian; Liu, Liren

2014-11-01

62

Extraction and classification of vehicles in LADAR imagery  

Science.gov (United States)

The work presented in this paper is based on a dataset recorded with an airborne sensor. It comprises targets like M-60, M-47, M-113, bridge layers, tank retrievers, and trucks in various types of scenes. The background-object segmentation consists of first estimating the ground level everywhere in the scene, and then for each sample simply subtracting the measured height and ground level height. No assumptions concerning flat terrain etc. are made. Samples with height above ground level higher than a certain threshold are clustered by utilizing a straightforward agglomerative clustering algorithm. Around each cluster the bounding box with minimum volume is determined. Based on these bounding boxes, too small as well as too large clusters can easily be removed. However, vehicle-sized clutter will not be removed. Clutter detection is based on estimating the normal vector for a plane approximation around each sample. This approach is based on the fact that the surface normals of a vehicle is more "modulo 90°" distributed than clutter. The aim of the classification has been to classify main battle tanks (MBTs) Two types of algorithms have been studied, one based on Dempster Shafer fusion theory, and one model based. Our dataset comprises clusters of 269 vehicles (among them 131 MBTs), and 253 clutter objects (i.e. in practice vehiclesized bushes). The experiments we have carried out show that the segmentation extracts all vehicles, the clutter detection removes 90% of the clutter, and the classification finds more than 95% of the MBTs as well as removes half of the remaining clutter.

Palm, Hans C.; Haavardsholm, Trym V.; Ajer, Halvor; Jensen, Cathrine V.

2013-05-01

63

Graph-Based Approach for 3D Object Duplicate Detection  

OpenAIRE

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...

Vajda, Peter; Dufaux, Frederic; Ha M, Thien; Ebrahimi, Touradj

2009-01-01

64

Propagation of geotags based on object duplicate detection  

OpenAIRE

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

Vajda, Pe?ter; Ivanov, Ivan; Lee, Jong-seok; Goldmann, Lutz; Ebrahimi, Touradj

2010-01-01

65

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

DEFF Research Database (Denmark)

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

MØrcke, Anne Mette; Wichmann-Hansen, Gitte

2006-01-01

66

Telepresent spacecraft docking with object-based bilateral control (OBBC)  

Science.gov (United States)

The concept of object-based control is extended to the field of teleoperation, specifically to accomplish the task of spacecraft docking via a bilateral manual controller. An object-based controller with bilateral feedback controls the motion of the grasped object, not the trajectory of the manipulator. For this reason it can be designed with feedback that is intricately linked with the task kinematics. The benefits derived from anthropomorphicity and force feedback are possible without kinematically/geometrically similar master-slave systems, complex calibration and joint mapping schemes, or expensive, high degree-of-freedom force reflection. Object-based control is ideal for low-level telerobotic interfaces. A hand controller and a spacecraft docking simulation are designed and constructed to demonstrate object-based bilateral control. The dominant task objective in spacecraft docking is the approach to a target vehicle along a single axis of motion. Several methods of bilateral feedback linked with this dominant objective are proposed in addition to simple force reflection. One method involves virtual forces and another utilizes velocity reflection. Each method, practical only with object-based control, enhance the man-machine interface by providing a heuristic method of control.

Woznick, Paul

1994-12-01

67

Stereovision-Based Object Segmentation for Automotive Applications  

OpenAIRE

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...

Fu Shan; Thompson Chris; Huang Yingping

2005-01-01

68

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

Science.gov (United States)

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

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

2013-01-01

69

Content-Based Object Movie Retrieval and Relevance Feedbacks  

Directory of Open Access Journals (Sweden)

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.

Lee Greg C

2007-01-01

70

RFID and IP Based Object Identification in Ubiquitous Networking  

Directory of Open Access Journals (Sweden)

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

Nisha Vaghela

2012-10-01

71

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

Science.gov (United States)

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

Sebari, Imane; He, Dong-Chen

2013-05-01

72

A Method of Object-based De-duplication  

Directory of Open Access Journals (Sweden)

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.

Fang Yan

2011-12-01

73

Distinct Mechanisms Subserve Location- and Object-Based Visual Attention  

OpenAIRE

Visual attention can be allocated to either a location or an object, named location- or object-based attention, respectively. Despite the burgeoning evidence in support of the existence of two kinds of attention, little is known about their underlying mechanisms in terms of whether they are achieved by enhancing signal strength or excluding external noises. We adopted the noise-masking paradigm in conjunction with the double-rectangle method to probe the mechanisms of location-based attention...

Wei-LunChou; Su-LingYeh

2014-01-01

74

Autocorrelation based reconstruction of two-dimensional binary objects  

International Nuclear Information System (INIS)

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

75

A Secure and Robust Object-Based Video Authentication System  

Directory of Open Access Journals (Sweden)

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

Dajun He

2004-10-01

76

Stereovision-Based Object Segmentation for Automotive Applications  

Directory of Open Access Journals (Sweden)

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 (X-Z plane and in layered images (X-Y 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.

Chris Thompson

2005-08-01

77

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.

78

Object-based attentional selection can modulate the Stroop effect.  

Science.gov (United States)

The Stroop (1935) effect is the inability to ignore a color word when the task is to report the ink color of that word (i.e., to say "green" to the word RED in green ink). The present study investigated whether object-based processing contributes to the Stroop effect. According to this view, observers are unable to ignore irrelevant features of an attended object (Kahneman & Henik, 1981). In three experiments, participants had to name the color of one of two superimposed rectangles and to ignore words that appeared in the relevant object, in the irrelevant object, or in the background. The words were congruent, neutral, or incongruent with respect to the correct color response. Words in the irrelevant object and in the background produced significant Stroop effects, consistent with earlier findings. Importantly, however, words in the relevant object produced larger Stroop effects than did the other conditions, suggesting amplified processing of all the features of an attended object. Thus, object-based processing can modulate the Stroop effect. PMID:14651304

Wühr, Peter; Waszak, Florian

2003-09-01

79

Research on moving object detection based on frog's eyes  

Science.gov (United States)

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

Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

2008-12-01

80

Development of an Integrated Hyperspectral Imager and 3D-Flash LADAR for Terrestrial Characterization  

Science.gov (United States)

The characterization of terrestrial ecosystems using remote sensing technology has a long history with using multi-spectral imagers for vegetation classification indices, ecosystem health, and change detection. Traditional multi-band imagers are now being replaced with more advanced hyperspectral imagers, which offer finer spectral resolution and more specific characterization of terrestrial reflectances. Recently, 3- dimensional (3D) imaging technologies, such as radar interferometry and scanning laser rangers, have added a vertical dimensional to the characterization of ecosystems. The combination of hyperspectral imagery with 3D LADAR allows for detailed analysis of terrestrial biomass, health and species identification. Recognizing the need, and the technical feasibility of this type of environmental assessment, the National Research Counsel has advocated two future NASA satellite missions to measure terrestrial ecosystem health and structure, the DESDynI and HyspIRI missions. These programs will orbit synthetic aperture radar, LADAR and hyperspectral imagers. To mitigate program risk it is desirable and prudent to first demonstrate the integration of these instruments on an airborne platform. Although systems developed for separate purposes have been flown on a single aircraft, the requirements and performance of a dual sensor system has not yet been developed nor integrated as a single unit. We demonstrate a development pathway from an aircraft platform with an integrated sensor suite, using a hyperspectral imager and a laser ranger for a comprehensive remote sensing characterization of terrestrial ecology.

Swanson, A. L.; Sandor-Leahy, S.; Shepanski, J.; Wong, C.; Bracikowski, C.; Abelson, L.; Helmlinger, M.; Bauer, D.; Folkman, M.

2009-05-01

81

Model-Based Software Testing for Object-Oriented Software  

Science.gov (United States)

Model-based testing is one of the best solutions for testing object-oriented software. It has a better test coverage than other testing styles. Model-based testing takes into consideration behavioural aspects of a class, which are usually unchecked in other testing methods. An increase in the complexity of software has forced the software industry…

Biju, Soly Mathew

2008-01-01

82

A Wavelet - Based Object Watermarking System for MPEG4 Video  

Directory of Open Access Journals (Sweden)

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

F.Regragui

2010-01-01

83

A New Approach to Object Based Fuzzy Database Modeling  

Directory of Open Access Journals (Sweden)

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

Debasis Dwibedy

2013-03-01

84

Geophysics-based method of locating a stationary earth object  

Science.gov (United States)

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.

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

2008-05-20

85

A New Approach to Object Based Fuzzy Database Modeling  

OpenAIRE

The requirements in diversified application domains like Engineering, Scientific technology, Multimedia, Knowledge management in expert systems etc shift the momentum of current trends in designing database models to an innovative concept of Object Based fuzzy Database Model. The ongoing research concentrates on representing the imprecise information by taking object modelling methodology and fuzzy techniques through different levels of class hierarchy and abstractions. Still, a formal defini...

Debasis Dwibedy,; Dr. Laxman Sahoo; Sujoy Dutta,

2013-01-01

86

Detection of objects in noisy images based on percolation theory  

OpenAIRE

We propose a novel statistical method for detection of objects in noisy images. The method uses results from percolation and random graph theories. We present an algorithm that allows to detect objects of unknown shapes in the presence of nonparametric noise of unknown level. The noise density is assumed to be unknown and can be very irregular. Our procedure substantially differs from wavelets-based algorithms. The algorithm has linear complexity and exponential accuracy and...

Davies, Patrick Laurie; Langovoy, Mikhail A.; Wittich, Olaf

2011-01-01

87

Survey on model-based manipulation planning of deformable objects  

OpenAIRE

A systematic overview on the subject of model-based manipulation planning of deformable objects is presented. Existing modeling techniques of volumetric, planar and linear deformable objects are described, emphasizing the different types of deformation. Planning strategies are categorized according to the type of manipulation goal: path planning, folding/unfolding, topology modifications and assembly. Most current contributions fit naturally into these categories, and thus the presented algor...

Jime?nez Schlegl, Pablo

2012-01-01

88

CONTENT BASED IMAGE RETRIEVAL - EXTRACTION BY OBJECTS OF USER INTEREST  

OpenAIRE

Content-based image retrieval (CBIR) systems normally return the retrieval results according to the similarity between features extracted from the query and candidate images. In certain circumstances, however users are most qualified to specify the query “content” or objects(e.g., Eiffel Tower) of their interest , not the computer and only wish to retrieve images containing relevant objects, while ignoring irrelevant image areas (such as the background). Previous work on this normally req...

Kishore Kumar, D.; E.Usha sree,; K.Suneera,; Chaitanya Kumar, P. V.

2011-01-01

89

Segmentation of object-based video of gaze communication  

DEFF Research Database (Denmark)

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

Aghito, Shankar Manuel; Stegmann, Mikkel Bille

2005-01-01

90

A View-Based Approach to Three Dimensional Object Recognition  

Directory of Open Access Journals (Sweden)

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.

Xu Sheng

2009-01-01

91

Inverse treatment planning using volume-based objective functions  

International Nuclear Information System (INIS)

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

92

Multi-objective Optimization Problem Based on Genetic Algorithm  

Directory of Open Access Journals (Sweden)

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.

Li Heng

2013-01-01

93

Automatic activity estimation based on object behaviour signature  

Science.gov (United States)

Automatic estimation of human activities is a topic widely studied. However the process becomes difficult when we want to estimate activities from a video stream, because human activities are dynamic and complex. Furthermore, we have to take into account the amount of information that images provide, since it makes the modelling and estimation activities a hard work. In this paper we propose a method for activity estimation based on object behavior. Objects are located in a delimited observation area and their handling is recorded with a video camera. Activity estimation can be done automatically by analyzing the video sequences. The proposed method is called "signature recognition" because it considers a space-time signature of the behaviour of objects that are used in particular activities (e.g. patients' care in a healthcare environment for elder people with restricted mobility). A pulse is produced when an object appears in or disappears of the observation area. This means there is a change from zero to one or vice versa. These changes are produced by the identification of the objects with a bank of nonlinear correlation filters. Each object is processed independently and produces its own pulses; hence we are able to recognize several objects with different patterns at the same time. The method is applied to estimate three healthcare-related activities of elder people with restricted mobility.

Martínez-Pérez, F. E.; González-Fraga, J. A.; Tentori, M.

2010-08-01

94

Object detection with discriminatively trained part-based models.  

Science.gov (United States)

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

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

2010-09-01

95

Fuzzy-Rule-Based Object Identification Methodology for NAVI System  

Directory of Open Access Journals (Sweden)

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

Rosalyn R. Porle

2005-08-01

96

An improved template tracking method based on rigid extended object  

Science.gov (United States)

We propose an improved Lucas-Kanade template tracking method with drift correction, which can be applied in rigid extended object. Due to error accumulation, primary template tracking method leads to template drift and loses object gradually. In order to alleviate template drift, SIFT (Scale Invariant Feature Transform) feature is used to correct the template drift. SIFT feature is invariant to scale, rotation even affine transformation, so, according to matching SIFT key-points between frames, the affine parameters of object transformation can be computed, then the current template position can be obtained by affine parameters and primary template position. The experiment results prove that the improved template tracking method based on SIFT drift correction can more accurately track the rigid extended object and can alleviate the tracking position drifting effectively.

Zhang, Jianwei; Peng, Zhenming

2013-09-01

97

Rule-Based Orientation Recognition Of A Moving Object  

Science.gov (United States)

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

Gove, Robert J.

1989-03-01

98

Objectivities  

Directory of Open Access Journals (Sweden)

Full Text Available I argue that one in particular of Crispin Wright’s attempts to capture our common or intuitive concepts of objectivity, warrant, and other associated notions, relies on an ambiguity between a given constructivist reading of the concepts and at least one other, arguably more ‘ordinary’, version of the notions he tries to accommodate. I do this by focusing on one case in point, and concluding with a brief argument showing how this case generalises. I demonstrate why this ambiguity is unacceptable and also that its resolution undermines the aim it serves: to account for and accommodate our ordinary conception of (at least objectivity, warrant (or justification and truth.

Penelope A Rush

2012-07-01

99

Vector ordinal optimization based multi-objective transmission planning  

International Nuclear Information System (INIS)

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

100

Vision-based control using probabilistic geometry for objects reconstruction  

OpenAIRE

We first present a suitable object knowledge representation based on a mixture of stochastic and set membership models and consider an approximation resulting in ellipsoidal calculus by means of a normal assumption for stochastic laws and ellipsoidal over or inner bounding for uniform laws. Then we, build an efficient estimation process integrating visual data online and perform online and optimal exploratory motions for the camera. The control schemes are based on the maximization of the a p...

Flandin, Gre?gory; Chaumette, Franc?ois

2001-01-01

101

Improved Brain Tumor Detection Using Object Based Segmentation  

OpenAIRE

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...

Harneet Kaur; Sukhwinder Kaur

2014-01-01

102

Archive Design Based on Planets Inspired Logical Object Model  

DEFF Research Database (Denmark)

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.

Zierau, Eld

2008-01-01

103

Algebraic Analysis of Object-Based Key Assignment Schemes  

Directory of Open Access Journals (Sweden)

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.

Khair Eddin Sabri

2014-08-01

104

Objectivities  

OpenAIRE

I argue that one in particular of Crispin Wright’s attempts to capture our common or intuitive concepts of objectivity, warrant, and other associated notions, relies on an ambiguity between a given constructivist reading of the concepts and at least one other, arguably more ‘ordinary’, version of the notions he tries to accommodate. I do this by focusing on one case in point, and concluding with a brief argument showing how this case generalises. I demonstrate why this ambiguity is unac...

Rush, Penelope A.

2012-01-01

105

Robust Object Tracking Based on Adaptive Feature Selection  

Directory of Open Access Journals (Sweden)

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

Chen Dong-Yue

2013-01-01

106

A General Polygon-based Deformable Model for Object Recognition  

DEFF Research Database (Denmark)

We propose a general scheme for object localization and recognition based on a deformable model. The model combines shape and image properties by warping a arbitrary prototype intensity template according to the deformation in shape. The shape deformations are constrained by a probabilistic distribution, which combined with a match of the warped intensity template and the image form the final criteria used for localization and recognition of a given object. The chosen representation gives the model an ability to model an almost arbitrary object. Beside the actual model a full general scheme for applying the model is proposed. The scheme includes general methods for initialization, optimization and validation. Experimental results for real data are shown. Compared to related work the proposed meodel and the methods for initialization and validation containsa number of intersting features and improved abilities.

Jensen, Rune Fisker; Carstensen, Jens Michael

1999-01-01

107

Research on object detection based on circular polarization property  

Science.gov (United States)

It is an important subject in information scout, battlefield surveillance and automatic target recognition to detect interesting objects from complicated background. Compared with intensity detection, polarization detection has its advantage in identifying some camouflage targets. Usually, in the studies of target polarization detection, circular polarization property is usually neglected because of its small value. But in particular conditions, the circular polarization property of target will be used to accomplish object detection with their obviously different value. In this study, a single reflectance model of Mueller matrix is established, and based on Fresnel's law, circular polarization property of object is analyzed which is obvious while linear polarization property is obscure in particular condition. It is available to use the circular polarization component to detect target.

Wu, Yun-zhi; Zeng, Xian-fang; Yin, Cheng-liang; Luo, Xiao-lin

2013-09-01

108

Features Extraction for Object Detection Based on Interest Point  

Directory of Open Access Journals (Sweden)

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

Amin Mohamed Ahsan

2013-05-01

109

A VSS Algorithm Based on Multiple Features for Object Tracking  

Directory of Open Access Journals (Sweden)

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.

Bin Xu

2013-12-01

110

Nanoscale synthesis and characterization of graphene-based objects  

Directory of Open Access Journals (Sweden)

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.

Daisuke Fujita

2011-01-01

111

OBEST: The Object-Based Event Scenario Tree Methodology  

International Nuclear Information System (INIS)

Event tree analysis and Monte Carlo-based discrete event simulation have been used in risk assessment studies for many years. This report details how features of these two methods can be combined with concepts from object-oriented analysis to develop a new risk assessment methodology with some of the best features of each. The resultant Object-Based Event Scenarios Tree (OBEST) methodology enables an analyst to rapidly construct realistic models for scenarios for which an a priori discovery of event ordering is either cumbersome or impossible (especially those that exhibit inconsistent or variable event ordering, which are difficult to represent in an event tree analysis). Each scenario produced by OBEST is automatically associated with a likelihood estimate because probabilistic branching is integral to the object model definition. The OBEST method uses a recursive algorithm to solve the object model and identify all possible scenarios and their associated probabilities. Since scenario likelihoods are developed directly by the solution algorithm, they need not be computed by statistical inference based on Monte Carlo observations (as required by some discrete event simulation methods). Thus, OBEST is not only much more computationally efficient than these simulation methods, but it also discovers scenarios that have extremely low probabilities as a natural analytical result--scenarios that would likely be missed by a Monte Carlo-based method. This report documents thrlo-based method. This report documents the OBEST methodology, the demonstration software that implements it, and provides example OBEST models for several different application domains, including interactions among failing interdependent infrastructure systems, circuit analysis for fire risk evaluation in nuclear power plants, and aviation safety studies

112

Upper bound calculations of ATR performance for ladar sensors  

Science.gov (United States)

The use of robust and representative synthetic imagery data to test and evaluate automatic target recognition (ATR) systems has long been desired but generally considered beyond the current state of the art. The use of synthetic data is investigated here to calculate upper bounds on potential ATR system performance. This paper presents the use of synthetically generated imagery templates as a means of developing upper bounds of ATR performance for laser radar based seekers. This approach employs a synthetic scene generation capability and integrates it with error models that represent decrements in performance due to resolution, noise and geometric distortion resulting from the sensing process. This paper describes the modeling approach take and presents preliminary results. The model is currently undergoing testing against real imagery and is being used to select test sets to more effectively evaluate ATR's.

Diehl, Vince E.; Benedict-Hall, Geoffrey T.; Heydemann, Chris

1998-09-01

113

Likelihood-based CT reconstruction of objects containing known components  

Energy Technology Data Exchange (ETDEWEB)

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

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

2011-07-01

114

3D object recognition based on local descriptors  

Science.gov (United States)

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.

Jakab, Marek; Benesova, Wanda; Racev, Marek

2015-01-01

115

Knowledge-based simulation using object-oriented programming  

Science.gov (United States)

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

Sidoran, Karen M.

1993-01-01

116

Improved Brain Tumor Detection Using Object Based Segmentation  

Directory of Open Access Journals (Sweden)

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.

Harneet Kaur

2014-07-01

117

Object-based evaluation of hierarchical region-based representations based on information theory statistical measures  

OpenAIRE

This work presents an evaluation in terms of object representation of the hierarchical region-based representations created by a family of general statistical region merging algorithms. These merging techniques are based on different versions of information theory statistical measures; concretely, the Kullback-Leibler divergence and the Bhattacharyya coefficient. Additionally, a significance index can be defined together with these techniques to extract the most statistically meaningful parti...

Calderero Patino, Felipe; Marque?s Acosta, Fernando

2008-01-01

118

Fission-track dating using object-based image analysis  

International Nuclear Information System (INIS)

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

119

The OASE project: Object-based Analysis and Seamless prediction  

Science.gov (United States)

The research group on Object-based Analysis and SEamless prediction (OASE) is part of the Hans Ertel Centre for Weather Research (HErZ). The group consists of scientists at the Meteorological Institute, University of Bonn, the Leibniz-Institute for Tropospheric Research in Leipzig and the German Weather Service. OASE addresses seamless prediction of convective events from nowcasting to daily predictions by combining radar/satellite compositing and tracking with high-resolution model-based ensemble generation and prediction. While observation-based nowcasting provides good results for lead times between 0-1 hours, numerical weather prediction addresses lead times between 3-21 hours. Especially the discontinuity between 1-3 hours needs to be addressed. Therefore a central goal of the project is a near real-time high-resolved unprecedented data base. A radar and satellite remote sensing-driven 3D observation-microphysics composite covering Germany, currently under development, contains gridded observations and estimated microphysical quantities. Observations and microphysics are intertwined via forward operators and estimated inverse relations, which also provide uncertainties for model ensemble initialisations. The lifetime evolution of dynamics and microphysics in (severe) convective storms is analysed based on 3D scale-space tracking. An object-based analysis condenses the information contained in the dynamic 3D distributions of observables and related microphysics into descriptors, which will allow identifying governing processes leading to the formation and evolution of severe weather events. The object-based approach efficiently characterises and quantifies the process structure and life cycles of severe weather events, and facilitates nowcasting and the generation and initialisation of model prediction ensembles. Observation-based nowcasting will exploit the dual-composite based 3D feature detection and tracking to generate a set of predictions (observation-based ensemble) for severe weather events. Both the dual-composite and the observation-based ensemble will be the starting point for model-based predictions via the initialisation of high-resolution model runs for extended warnings. The poster gives an overview of the OASE project.

Troemel, Silke; Wapler, Kathrin; Bick, Theresa; Diederich, Malte; Deneke, Hartwig; Horvath, Akos; Senf, Fabian; Simmer, Clemens; Simon, Juergen

2013-04-01

120

Geographic Object-Based Image Analysis – Towards a new paradigm  

OpenAIRE

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

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

2014-01-01

121

Robust diameter-based thickness estimation of 3D objects  

OpenAIRE

We propose a robust thickness estimation approach for 3D objects based on the Shape Diameter Function (SDF). Our method first applies a modified strategy to estimate the local diameter with increased accuracy. We then compute a scale-dependent robust thickness estimate from a point cloud, constructed using this local diameter estimation and a variant of a robust distance function. The robustness of our method is benchmarked against several operations such as remeshing, geometric noise and art...

Xavier, Rolland-nevie?re; Doe?rr, Gwenae?l; Alliez, Pierre

2013-01-01

122

Image Object Detection Algorithm Based on Improved Gaussian Mixture Model  

OpenAIRE

Aiming at poor adaptability to illumination variation and single learning rate in traditional Gaussian mixture model, an improved moving object detection algorithm based on adaptive Gaussian mixture model is proposed in this paper, so as to achieve the goal of a self-adaptive background updating model. In this paper, we analyze the existed algorithms and put forward the method to make use of color histogram matching algorithm, through introduction of illumination variation factor and update-c...

Xing-liang Li; Yu-bao Wu

2014-01-01

123

Modal Logics for Reasoning about Object-based Component Composition  

OpenAIRE

Component-oriented development of software supports the adaptability and maintainability of large systems, in particular if requirements change over time and parts of a system have to be modified or replaced. The software architecture in such systems can be described by components and their composition. In order to describe larger architectures, the composition concept becomes crucial. We will present a formal framework for component composition for object-based software development. The d...

Pahl, Claus

2000-01-01

124

Cloud Aggregation and Bursting for Object Based Sharable Environment  

OpenAIRE

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

Pradeep Kumar Tripathi; Prof. Surendra Mishra; Pankaj Kawadkar

2011-01-01

125

DMD-based multi-object spectrograph on Galileo telescope  

Science.gov (United States)

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.

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

2013-03-01

126

Graph - Based High Resolution Satellite Image Segmentation for Object Recognition  

Science.gov (United States)

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

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

2014-11-01

127

Object-oriented programming of PLC based on IEC 1131  

OpenAIRE

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

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

1994-01-01

128

Salient object detection: manifold-based similarity adaptation approach  

Science.gov (United States)

A saliency detection algorithm based on manifold-based similarity adaptation is proposed. The proposed algorithm is divided into three steps. First, we segment an input image into superpixels, which are represented as the nodes in a graph. Second, a new similarity measurement is used in the proposed algorithm. The weight matrix of the graph, which indicates the similarities between the nodes, uses a similarity-based method. It also captures the manifold structure of the image patches, in which the graph edges are determined in a data adaptive manner in terms of both similarity and manifold structure. Then, we use local reconstruction method as a diffusion method to obtain the saliency maps. The objective function in the proposed method is based on local reconstruction, with which estimated weights capture the manifold structure. Experiments on four bench-mark databases demonstrate the accuracy and robustness of the proposed method.

Zhou, Jingbo; Ren, Yongfeng; Yan, Yunyang; Gao, Shangbing

2014-11-01

129

Robust object recognition based on HMAX model architecture  

Science.gov (United States)

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.

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

2012-11-01

130

Filling-Based Techniques Applied to Object Projection Feature Estimation  

CERN Document Server

3D motion tracking is a critical task in many computer vision applications. Unsupervised markerless 3D motion tracking systems determine the most relevant object in the screen and then track it by continuously estimating its projection features (center and area) from the edge image and a point inside the relevant object projection (namely, inner point), until the tracking fails. Existing object projection feature estimation techniques are based on ray-casting from the inner point. These techniques present three main drawbacks: when the inner point is surrounded by edges, rays may not reach other relevant areas; as a consequence of that issue, the estimated features may greatly vary depending on the position of the inner point relative to the object projection; and finally, increasing the number of rays being casted and the ray-casting iterations (which would make the results more accurate and stable) increases the processing time to the point the tracking cannot be performed on the fly. In this paper, we anal...

Quesada, Luis

2012-01-01

131

A detection method of moving object based on hybrid difference  

Science.gov (United States)

The detection method is based on background subtraction and inter-frame difference. To use statistical model of RGB color histograms to extracting background. In this way, the initial background image could be extracted without noise effect to a great extent. To get difference image of moving object according to the results of background subtraction and three frames difference. To get binary Image A which difference from Frame k-1 and Frame k, to get Image B which difference from Frame k and Frame k+1. Let Image A and Image B do LOR operation to get Image C for obtaining more information of the moving object. Finally, let binary image of background subtraction and Image C do LAND operation to get outline of moving object. To use self-adaption method updates background image to promise the instantaneity. If a pixel of the current frame is estimated as moving target, we set the corresponding pixel of current background image to instead of the pixel in background image, else set the corresponding pixel of current frame to update the corresponding pixel of background. To use background updating factor ? to control update rate. Moving object can be detected more accurately by mathematical morphology. This method can improve the shortcomings of background subtraction and inter-frame difference.

Wang, Chuncai; Yan, Lei; Li, Yingtao

2014-11-01

132

CONTENT BASED IMAGE RETRIEVAL - EXTRACTION BY OBJECTS OF USER INTEREST  

Directory of Open Access Journals (Sweden)

Full Text Available Content-based image retrieval (CBIR systems normally return the retrieval results according to the similarity between features extracted from the query and candidate images. In certain circumstances, however users are most qualified to specify the query “content” or objects(e.g., Eiffel Tower of their interest , not the computer and only wish to retrieve images containing relevant objects, while ignoring irrelevant image areas (such as the background. Previous work on this normally requires complicated segmentation of the object from the background. In this paper, the user can select “object of user’s interest” of different shapes, non homogenous texture containing different colors regardless of manyobjects present in the same image using varied tools like polygonal, rectangle, circle selector tools. A twostate procedure is used to query the image from the Image database. First, we integrate global color and texture feature vectors to narrow down the search space and in next state we Process using local features. We use color moments and subband statistics of wavelet decomposition as color and texture features respectively. The shape features, generated by mathematical morphology operators, are further employed to produce the final retrieval results.

Mr. D. Kishore Kumar

2011-03-01

133

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

Science.gov (United States)

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.

Campbell, Jonathan W.

2002-09-01

134

Object Recognition using Feature- and Color-Based Methods  

Science.gov (United States)

An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

Duong, Tuan; Duong, Vu; Stubberud, Allen

2008-01-01

135

Analysis of manufacturing based on object oriented discrete event simulation  

Directory of Open Access Journals (Sweden)

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.

Eirik Borgen

1990-01-01

136

An object-based methodology for knowledge representation  

Energy Technology Data Exchange (ETDEWEB)

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.

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

137

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

Directory of Open Access Journals (Sweden)

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.

Runhe Huang

2008-11-01

138

Visual-adaptation-mechanism based underwater object extraction  

Science.gov (United States)

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

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

2014-03-01

139

State-based modeling and object extraction from echocardiogram video.  

Science.gov (United States)

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

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

2008-05-01

140

OBJECT DETECTION SCHEME FOR DYNAMIC VIDEOS BASED ON LOCAL ILLUMINATION BASED TECHNIQUES?  

OpenAIRE

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

Sowrya Pratap, T.; Surendra Babu?, V.

2014-01-01

141

Object Persistence: A Framework Based On Design Patterns  

OpenAIRE

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

Kienzle, Jo?rg; Romanovsky, Alexander

2000-01-01

142

Mobile object retrieval in server-based image databases  

Science.gov (United States)

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

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

2013-05-01

143

Implementation and Comparison of Kernel and Silhouette Based Object Tracking  

OpenAIRE

Object tracking in video sequences is one of the important ongoing exploration areas in the field of computer vision. Computer vision is an arena that comprises methods for acquiring, processing, analyzing images and also covers the essential technology of automatic image analysis which is used in various fields. The aim of object tracking is to find the trajectory of the target objects through a number of frames from an image sequence. Object Tracking is identification of interesting object,...

Joshan Athanesious J, Suresh P.

2013-01-01

144

RFID and IP Based Object Identification in Ubiquitous Networking  

OpenAIRE

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...

Nisha Vaghela; Parikshit Mahalle

2012-01-01

145

The modulation of inhibition of return by object-internal structure: implications for theories of object-based attentional selection.  

Science.gov (United States)

Recently, Vecera, Behrmann, and McGoldrick (2000), using a divided-attention task, reported that targets are detected more accurately when they occur on the same structural part of an object, suggesting that attention can be directed toward object-internal features. We present converging evidence using the object-based inhibition of return (IOR) paradigm as an implicit measure of selection. The results show that IOR is attenuated when cues and targets appear on the same part of an object relative to when they are separated by a part boundary. These findings suggest that object-based mechanisms of selection can operate over shape representations that make explicit information about object-internal structure. PMID:12921430

Reppa, Irene; Leek, E Charles

2003-06-01

146

Performance Evaluation of Raster Based Shape Vectors in Object Recognition  

Directory of Open Access Journals (Sweden)

Full Text Available Object recognition is still an impediment in the field of computer vision and multimedia retrieval. Defining an object model is a critical task. Shape information of an object play a critical role in the process of object recognition. Extraction of boundary information of an object from the multimedia data and classifying this information with associated objects is the primary step towards object recognition. Rasters play an important role while computing object boundary. The trade-off lies with the dimensionality of the object versus computational cost while achieving maximum efficiency. In this treatise an attempt is made to evaluate the performance of circular and spiral raster models in terms of average retrieval efficiency and computational cost.

Akbar khan

2014-03-01

147

Experimental comparison of a Gated-Viewing system and a 3-D Flash LADAR system in terms of range precision under different turbulence conditions  

OpenAIRE

For security and military applications, long-range automatic target recognition is a very important task. Therefore, in addition to a 2-D passive or active intensity image, 3-D information of a target is desirable. Besides a LADAR system, also a Gated-Viewing (GV) system can provide depth information by simply sliding the gate through the scenery. In this paper, the GV camera LIVARÒ 500 (Intevac, 640 × 480 pixels (binning mode), EBCMOS) is compared to a 3-D Flash LADAR camera (Advanced Scie...

Go?hler, Benjamin; Lutzmann, Peter

2011-01-01

148

Object-Based Change Detection Using Georeferenced Uav Images  

Science.gov (United States)

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

Shi, J.; Wang, J.; Xu, Y.

2011-09-01

149

Object-based classification of semi-arid wetlands  

Science.gov (United States)

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.

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

2011-01-01

150

Novel technique: a pupillometer-based objective chromatic perimetry  

Science.gov (United States)

Evaluation of visual field (VF) is important for clinical diagnosis and patient monitoring. The current VF methods are subjective and require patient cooperation. Here we developed a novel objective perimetry technique based on the pupil response (PR) to multifocal chromatic stimuli in normal subjects and in patients with glaucoma and retinitis pigmentosa (RP). A computerized infrared video pupillometer was used to record PR to short- and long-wavelength stimuli (peak 485 nm and 620 nm, respectively) at light intensities of 15-100 cd-s/m2 at thirteen different points of the VF. The RP study included 30 eyes of 16 patients and 20 eyes of 12 healthy participants. The glaucoma study included 22 eyes of 11 patients and 38 eyes of 19 healthy participants. Significantly reduced PR was observed in RP patients in response to short-wavelength stimuli at 40 cd-s/m2 in nearly all perimetric locations (P retinal function and optic nerve damage in patients with retinal dystrophies and glaucoma. Furthermore, this method may be used to distinguish between the damaged cells underlying the VF defect.

Rotenstreich, Ygal; Skaat, Alon; Sher, Ifat; Kolker, Andru; Rosenfeld, Elkana; Melamed, Shlomo; Belkin, Michael

2014-02-01

151

Robust object detection based on local similar structure statistical matching  

Science.gov (United States)

We present a robust object detection method to detect generic objects with incompact, complex and changeable shapes without training. First, we build a composite template set, which contains changeful shapes, scales and viewpoints of an interested object class, extract the local structure features from the composite template set and simplify them to construct a non-similar local structure feature set of the object class. Then, we propose a matching method of local similar structure statistical matching (LSSSM) to obtain the similarity image from a test image to the local structure feature set. Finally, we use the method of non-maxima suppression in the similarity image to extract the object position and mark the object in the test image. The experimental results demonstrate that our approach performs effectively on the face and infrared human body detection.

Luo, Feiyang; Han, Jing; Qi, Wei; Zhang, Yi; Bai, Lianfa

2015-01-01

152

Partial Evaluation for Class-Based Object-Oriented Languages  

DEFF Research Database (Denmark)

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.

Schultz, Ulrik Pagh

2001-01-01

153

A Robust Object Tracking Approach based on Mean Shift Algorithm  

OpenAIRE

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

Zhang Xiaojing; Yajie Yue; Chenming Sha

2013-01-01

154

Object Tracking Approach based on Mean Shift Algorithm  

OpenAIRE

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

Xiaojing Zhang; Yajie Yue; Chenming Sha

2013-01-01

155

Feature based recognition of submerged objects in holographic imagery  

Science.gov (United States)

The ability to autonomously sense and characterize underwater objects in situ is desirable in applications of unmanned underwater vehicles (UUVs). In this work, underwater object recognition was explored using a digital holographic system. Two experiments were performed in which several objects of varying size, shape, and material were submerged in a 43,000 gallon test tank. Holograms were collected from each object at multiple distances and orientations, with the imager located either outside the tank (looking through a porthole) or submerged (looking downward). The resultant imagery from these holograms was preprocessed to improve dynamic range, mitigate speckle, and segment out the image of the object. A collection of feature descriptors were then extracted from the imagery to characterize various object properties (e.g., shape, reflectivity, texture). The features extracted from images of multiple objects, collected at different imaging geometries, were then used to train statistical models for object recognition tasks. The resulting classification models were used to perform object classification as well as estimation of various parameters of the imaging geometry. This information can then be used to inform the design of autonomous sensing algorithms for UUVs employing holographic imagers.

Ratto, Christopher R.; Beagley, Nathaniel; Baldwin, Kevin C.; Shipley, Kara R.; Sternberger, Wayne I.

2014-05-01

156

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

Science.gov (United States)

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.…

Holzinger, Andreas; Kleinberger, Thomas; Muller, Paul

157

Layer-based object detection and tracking with graph matching  

Science.gov (United States)

Automatic object detection and tracking has been widely applied in the video surveillance systems for homeland security and data fusion in the remote sensing and airborne imagery. The typical applications include human motion analysis and the vehicle detection. Here we implement object detection and tracking under shape graphs of interesting objects integrating local contextual information (corner/point features, etc) of the objects. On the top layer, shapes/sketches provide a discrimination measure to describe the global status of the interesting objects. This kind of information is very useful to improve the object tracking performance for occlusion. The shape can be modeled as a graph or hyper graph through its local geometric features. On the bottom layer, local geometric features are used to capture local properties of objects and perform correspondence estimation of high-level shapes. The local features provide a way to conquer inaccurate object segmentation and extraction. The experiments were implemented on human face tracking and vehicle detection and tracking.

He, Qiang; Chu, Chee-Hung Henry

2011-05-01

158

JTC based concealed object detection in terahertz imaging  

Science.gov (United States)

Detection of concealed objects under cloth or inside paper/lather/plastic box is a challenge for security applications. With terahertz (THz) imaging technology, it is possible to spot concealed objects inside plastic box, underneath cloths paper or similar scenarios. THz frequency domain (~100 GHz - 10 THz) shows a unique feature in the under-used domain of the electromagnetic spectrum which helps to acquire image of concealed objects. This property of THz wave makes it useful in a variety of applications. Previously millimeter wave imaging and infrared imaging were used for detection of concealed features in an image with limited success rate. THz imaging helps solving the problem to a great extent because it can transmit through substances like cloths, paper, plastic, dried food etc. THz images have poor quality and low signal-to-noise-ratio. Noises and related artifacts must be reduced for proper detection of concealed objects. In this paper, a new technique for artifact reduction and detection of concealed object is proposed by utilizing nonzero-order fringe adjusted joint transform correlation (NFJTC) technique. In the proposed NFJTC technique, the joint power spectrum (JPS) is modified to obtain the nonzero-order fringe-adjusted joint power spectrum. NFJTC is already been used for object detection but never been used to detect concealed objects in THz imagery. Test results using real life THz imagery confirm the effectiveness of the proposed technique.

Habib, M. U.; Alam, M. S.; Al-Assadi, W. K.

2013-03-01

159

3D model-based still image object categorization  

Science.gov (United States)

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%, which opens interesting perspectives in terms of semantic metadata extraction from still images/videos.

Petre, Raluca-Diana; Zaharia, Titus

2011-09-01

160

Real-time Object Detection Based on ARM9  

OpenAIRE

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 ...

Vijay Babu, M.

2013-01-01

161

Vision-based grasp tracking for planar objects  

OpenAIRE

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...

Recatala? Ballester, Gabriel; Carloni, Raffaella; Melchiorri, Claudio; Sanz Valero, Pedro Jose?; Cervera Mateu, Enric; Pobil, A?ngel Pasqual Del

2008-01-01

162

JBOOM: Java Based Object Oriented Model of Software Configuration Management  

OpenAIRE

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

Bhavya Mehta; Muttoo, S. K.

2006-01-01

163

Drifting Recovery Base Concept for GEO Derelict Object Capture  

Science.gov (United States)

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.

Bacon, John B.

2009-01-01

164

MOPSO-based multi-objective TSO planning considering uncertainties  

DEFF Research Database (Denmark)

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.

Wang, Qi; Zhang, Chunyu

2014-01-01

165

Manipulating deformable linear objects - Vision-based recognition of contact state transitions -  

OpenAIRE

A new and systematic approach to machine vision-based robot manipulation of deformable (non-rigid) linear objects is introduced. This approach reduces the computational needs by using a simple state-oriented model of the objects. These states describe the relation of the object with respect to an obstacle and are derived from the object image and its features. Therefore, the object is segmented from a standard video frame using a fast segmentation algorithm. Several object features are presen...

Abegg, Frank; Henrich, Dominik; Wo?rn, Heinz

1999-01-01

166

Ontology-Based Annotation of Learning Object Content  

Science.gov (United States)

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

Gasevic, Dragan; Jovanovic, Jelena; Devedzic, Vladan

2007-01-01

167

Objective, Way and Method of Faculty Management Based on Ergonomics  

Science.gov (United States)

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…

WANG, Hong-bin; Liu, Yu-hua

2008-01-01

168

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

Directory of Open Access Journals (Sweden)

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

Chaogai Xue

2013-05-01

169

A fuzzy rule base system for object-based feature extraction and classification  

Science.gov (United States)

In this paper, we present a fuzzy rule base system for object-based feature extraction and classification on remote sensing imagery. First, the object primitives are generated from the segmentation step. Object primitives are defined as individual regions with a set of attributes computed on the regions. The attributes computed include spectral, texture and shape measurements. Crisp rules are very intuitive to the users. They are usually represented as "GT (greater than)", "LT (less than)" and "IB (In Between)" with numerical values. The features can be manually generated by querying on the attributes using these crisp rules and monitoring the resulting selected object primitives. However, the attributes of different features are usually overlapping. The information is inexact and not suitable for traditional digital on/off decisions. Here a fuzzy rule base system is built to better model the uncertainty inherent in the data and vague human knowledge. Rather than representing attributes in linguistic terms like "Small", "Medium", "Large", we proposed a new method for automatic fuzzification of the traditional crisp concepts "GT", "LT" and "IB". Two sets of membership functions are defined to model those concepts. One is based on the piecewise linear functions, the other is based on S-type membership functions. A novel concept "fuzzy tolerance" is proposed to control the degree of fuzziness of each rule. The experimental results on classification and extracting features such as water, buildings, trees, fields and urban areas have shown that this newly designed fuzzy rule base system is intuitive and allows users to easily generate fuzzy rules.

Jin, Xiaoying; Paswaters, Scott

2007-04-01

170

Programming Model Based on Concurrent Objects for the AIBO Robot  

OpenAIRE

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

Mart N Rico, Francisco; Ca As, Jos Mar A.; Gonz Lez-careaga, Rafaela; Matell N Olivera, Vicente

2012-01-01

171

Man-made Object Detection Based on Latent Dirichlet Allocation  

OpenAIRE

With the rapid development of multimedia technologies, man-made object detection is one of the important applications. An improved LDA approach was used to learn and recognize man-made and natural scene categories. It represent the image of a scene by a collection of local regions, denoted as codewords, each region is represented as part of a “theme”. It learns the theme distributions as well as the codewords distribution over the themes. At last Suppor...

Xiaojun Xu; Yingli Lv

2013-01-01

172

Application of Object-Based Industrial Controls for Cryogenics  

CERN Document Server

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.

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

2002-01-01

173

Mobile object retrieval in server-based image databases  

OpenAIRE

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

Manger, Daniel; Pagel, Frank; Widak, Heiko

2013-01-01

174

Ensemble based multi-objective production optimization of smart wells:  

OpenAIRE

In a recent study two hierarchical multi-objective methods were suggested to include short-term targets in life-cycle production optimization. However this previous study has two limitations: 1) the adjoint formulation is used to obtain gradient information, requiring simulator source code access and an extensive implementation effort, and 2) one of the two proposed methods relies on the Hessian matrix which is obtained by a computationally expensive method. In order to overcome the first of ...

Fonseca, R. M.; Leeuwenburgh, O.; Jansen, J. D.

2012-01-01

175

Real-time Object Detection Based on ARM9  

Directory of Open Access Journals (Sweden)

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.

M.Vijay babu

2013-09-01

176

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

Science.gov (United States)

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

Logie, David S.; Kamil, Hasan

1990-01-01

177

Object based manipulation with 3D scenes in mobile environment  

OpenAIRE

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...

Slavik, Pavel; Cmolik, Ladislav; Mikovec, Zdenek

2005-01-01

178

Object Identification Using MSX-based Infrared Colors  

Science.gov (United States)

Version 1 of the MSX (Midcourse Space Experiment) Point Source Catalog has recently been released through the Infrared Processing and Analysis Center (IPAC) Infrared Science Archive (IRSA). The catalog, which contains > 300,000 Infrared sources, covers the entire Galactic plane (|b| < 5 deg.) and the areas missed by IRAS for up to six photometric bands. A majority of the sources have good measurements only in the 8.3 micron band (MSX A Band). In this paper we shall demonstrate the utility of the MSX colors in differentiating objects by type. Additionally, we shall demonstrate the utility of combining the MSX 8.3 micron survey data with near-IR surveys such as 2MASS and DENIS. The combination of J and K band data with MSX A Band allows easy discrimination of carbon stars, O-rich AGB stars, K and M giants, main sequence stars, supergiants, planetary nebulae, HII regions and T Tauri objects. We also demonstrate the utility of combining the MSX survey with ISOCAM mid-IR data.

Egan, M. P.

1999-12-01

179

An object oriented computer-based patient record reference model.  

OpenAIRE

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

Dore?, L.; Lavril, M.; Jean, F. C.; Degoulet, P.

1995-01-01

180

Video Image Object Tracking Algorithm based on Improved Principal Component Analysis  

OpenAIRE

Since the existing object tracking algorithms are very difficult to adapt the object appearance changes caused by illumination changes, large pose variations, and partial or full occlusions, an object tracking algorithm based on two-dimensional principal component analysis (2DPCA) and sparse-representation is proposed in this paper. The tracking algorithm adopts 2DPCA and sparse-representation to establish object appearance model. In order to reduce dimension of object template, incremental s...

Liping Wang

2014-01-01

181

An image retrieval system based on the feature of color differences among the edges of objects  

OpenAIRE

This paper focuses on color differences among the edges of objects in an image. The variations of colors among the objects in the image can depict the directions and simple geometric shapes of most objects in the image regardless of the influence from the shift variant of objects and scale variant in the image. Based on the feature of color differences among the edges of objects, this paper constructs an image retrieval system. Experimental results show that this system can effectively and qu...

Chan, Yung-kuan; Chen, Chih-ya

2005-01-01

182

Buried object location based on frequency-domain UWB measurements  

International Nuclear Information System (INIS)

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

183

Android Based Robot Implementation For Pick and Retain of Objects  

Directory of Open Access Journals (Sweden)

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.

Ranjith Kumar Goud

2014-10-01

184

Successes and failures in producing attentional object-based cueing effects.  

Science.gov (United States)

Over 30 years of research using Posner's spatial cueing paradigm has shown that selective attention operates on representations of spatial locations, leading to space-based theories of attention. Manipulations of stimuli and methods have shown this paradigm to be sensitive to several types of object-based representations-providing evidence for theories incorporating object-based attentional selection. This paper critically evaluates the evidence demanding object-based explanations that go beyond positing spatial representations alone, with an emphasis on identifying and interpreting successes and failures in obtaining object-based cueing effects. This overview of current evidence is used to generate hypotheses regarding critical factors in the emergence and influence of object representations-their generation, strength, and maintenance-in the modulation of object-based facilitatory and inhibitory cueing effects. PMID:22052445

Reppa, Irene; Schmidt, William C; Leek, E Charles

2012-01-01

185

Model-Based Testing of Object-Oriented Systems  

OpenAIRE

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 ...

Rumpe, Bernhard

2014-01-01

186

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

OpenAIRE

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

Chatterjee, Helen J.

2010-01-01

187

Design of Object-based Information System Prototype  

Directory of Open Access Journals (Sweden)

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

Suhyeon Yoo

2014-06-01

188

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

Directory of Open Access Journals (Sweden)

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.

Aneissha Chebolu

2013-05-01

189

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

Directory of Open Access Journals (Sweden)

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

Shahnawaz Talpur

2013-07-01

190

Activity in human visual and parietal cortex reveals object-based attention in working memory.  

Science.gov (United States)

Visual attention enables observers to select behaviorally relevant information based on spatial locations, features, or objects. Attentional selection is not limited to physically present visual information, but can also operate on internal representations maintained in working memory (WM) in service of higher-order cognition. However, only little is known about whether attention to WM contents follows the same principles as attention to sensory stimuli. To address this question, we investigated in humans whether the typically observed effects of object-based attention in perception are also evident for object-based attentional selection of internal object representations in WM. In full accordance with effects in visual perception, the key behavioral and neuronal characteristics of object-based attention were observed in WM. Specifically, we found that reaction times were shorter when shifting attention to memory positions located on the currently attended object compared with equidistant positions on a different object. Furthermore, functional magnetic resonance imaging and multivariate pattern analysis of visuotopic activity in visual (areas V1-V4) and parietal cortex revealed that directing attention to one position of an object held in WM also enhanced brain activation for other positions on the same object, suggesting that attentional selection in WM activates the entire object. This study demonstrated that all characteristic features of object-based attention are present in WM and thus follows the same principles as in perception. PMID:25716836

Peters, Benjamin; Kaiser, Jochen; Rahm, Benjamin; Bledowski, Christoph

2015-02-25

191

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)

192

A Scale Adaptive Method Based On Quaternion Correlation in Object Tracking  

Directory of Open Access Journals (Sweden)

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.

Jie Hu

2014-09-01

193

Object oriented image analysis based on multi-agent recognition system  

Science.gov (United States)

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.

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

2013-04-01

194

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

OpenAIRE

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...

Yunna Wu; Zezhong Li; Lirong Liu

2013-01-01

195

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

OpenAIRE

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

Khattab K; Dubois J; Miteran J

2009-01-01

196

Object detection and segmentation on a hierarchical region-based image representation  

OpenAIRE

In this paper we present a general framework for object detection and segmentation. Using a bottom-up unsupervised merging algorithm, a region-based hierarchy that represents the image at different resolution levels is created. Next, top-down, object class knowledge is used to select and combine regions from the hierarchy, in order to define the exact object shape. We illustrate the usefulness of the approach with four different object classes: sky, caption text, traffic ...

Vilaplana Besler, Vero?nica; Marque?s Acosta, Fernando; Leo?n Cristo?bal, Mi?riam; Gasull Llampallas, Antoni

2010-01-01

197

Learning Membership Functions in a Function-Based Object Recognition System  

OpenAIRE

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 ...

Woods, K.; Cook, D.; Hall, L.; Bowyer, K.; Stark, L.

1995-01-01

198

Analysis of the Limits of Graph-Based Object Duplicate Detection  

OpenAIRE

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...

Vajda, Peter; Goldmann, Lutz; Ebrahimi, Touradj

2009-01-01

199

A Topology-based Object Representation for Clasping, Latching and Hooking  

OpenAIRE

We present a loop-based topological object representation for objects with holes. The representation is used to model object parts suitable for grasping, e.g. handles, and it incorporates local volume information about these. Furthermore, we present a grasp synthesis framework that utilizes this representation for synthesizing caging grasps that are robust under measurement noise. The approach is complementary to a local contact-based force-closure analysis as it depends on global topological...

Stork, Johannes A.; Pokorny, Florian T.; Kragic, Danica

2013-01-01

200

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

OpenAIRE

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

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

2010-01-01

201

Object Tracking and Target Reacquisition Based on 3-D Range Data for Moving Vehicles  

OpenAIRE

In this paper, we propose an approach for tracking an object of interest based on 3-D range data. We employ particle filtering and active contours to simultaneously estimate the global motion of the object and its local deformations. The proposed algorithm takes advantage of range information to deal with the challenging (but common) situation in which the tracked object disappears from the image domain entirely and reappears later. To cope with this problem, a method based on principle compo...

Lee, Jehoon; Lankton, Shawn; Tannenbaum, Allen

2011-01-01

202

A Multi-Objective Hybrid Genetic Based Optimization for External Beam Radiation  

International Nuclear Information System (INIS)

A multi-objective hybrid genetic based optimization algorithm is proposed according to the multi-objective property of inverse planning. It is based on hybrid adaptive genetic algorithm which combines the simulated annealing, uses adaptive crossover and mutation, and adopts niched tournament selection. The result of the test calculation demonstrates that an excellent converging speed can be achieved using this approach

203

Monitoring the Progress of the Group in an Individualized Reading Program Based on Behavioral Objectives.  

Science.gov (United States)

An alternative to monitoring instruction via standardized tests is proposed for objective-based individualized instructional programs. The set of behavioral objectives upon which the procedures are based is taken from the Wisconsin Design for Reading Skill Development. Procedures that can be computerized and applied to data from…

Buchanan, Anne; And Others

204

A Color-Adaptive and Robust Visual Object Tracking Method Based on MeanShift Algorithm  

Directory of Open Access Journals (Sweden)

Full Text Available Visual object tracking is a key component in video analysis and surveillance system. In this paper we propose a novel and robust video object tracking method based on kernel tracking approach .MeanShift algorithm is a Kernel Tracking approach based on col ...

Arman Heydarian

205

Retrieving top-k prestige-based relevant spatial web objects  

DEFF Research Database (Denmark)

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.

Cao, Xin; Cong, Gao

2010-01-01

206

Video Image Object Tracking Algorithm based on Improved Principal Component Analysis  

Directory of Open Access Journals (Sweden)

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

Liping Wang

2014-05-01

207

Multiple-level patch-based object tracking using MLBP-based integral histogram  

Science.gov (United States)

This paper presents a novel multiple-level patch-based approach for object tracking using Modified Local Binary Pattern (MLBP) histograms. The initial template is divided into overlapping rectangular patches, and each of these patches is tracked independently by finding the most similar match within a search region. Every patch votes on the possible locations of the object in the current frame, by comparing its MLBP histogram with the correspondence in the target frame. To reduce the individual tracking error of a given patch due to partial occlusions, the idea of multiple-level patch partitioning is further developed. And the similarity between template and target object is compared patch-by-patch, level-by-level. The comparison starts from the highest level and progressively feeds to the lowest level through a median operation. The proposed algorithm provides additional robustness and effectiveness in several ways. First, the spatial relationship among patches is improved by this overlapping partitioning manner. Second, by introducing MLBP operator, the tracking accuracy is significantly improved. Third, the median operation utilized in the multiple-level vote-combining process provides additional robustness with respect to outliers resulting from occluded patches and pose changes. The proposed method is evaluated using both face and pedestrian sequences, and comparison is made w.r.t. several state-of-the-art tracking algorithms. Experimental results show that the proposed method significantly outperforms in case of occlusions and pose changes. Besides, the tracking in case of scale changes additionally proves the effectiveness and efficiency of the proposed method.

Yuan, Jirui; Egiazarian, Karen

2013-03-01

208

A Computational Model of Visual Attention Based on Space and Object  

Directory of Open Access Journals (Sweden)

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

Shuhong Li

2014-01-01

209

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

International Nuclear Information System (INIS)

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

210

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

Science.gov (United States)

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

2015-01-01

211

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

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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.

J. Fernandez Galarreta

2014-09-01

212

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

Science.gov (United States)

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.

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

2014-09-01

213

The timecourse of space- and object-based attentional prioritization with varying degrees of certainty  

OpenAIRE

The relative contributions of surfaces (i.e., object-based) and underlying spatial representations (i.e., space-based) to attentional prioritization and selection remain unclear. In most experimental circumstances, the two representations overlap thus their respective contributions cannot be evaluated. Here, a dynamic version of the two-rectangle paradigm allowed for a successful de-coupling of spatial and object representations. Space-based (cued spatial location), cued surface (cued locatio...

SarahShomstein

2013-01-01

214

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

OpenAIRE

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...

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

2008-01-01

215

Object-based approaches to image classification for hyperspatial and hyperspectral data  

Science.gov (United States)

The prime objective of this research is to develop a suitable object based classifier for detailed land use/land cover classification (LULC) of remote sensing data with high spatial and spectral resolution. Owing to technical limitations, remote sensing data were available either at high spatial resolution (4 bands) but not with combination of both until recently. Processing of the high spectral resolution imagery for LULC classification was predominantly pixel based due to the lack of sufficient spatial resolution for identifying individual objects. For high spatial resolution imagery, object based analysis was devised that performed classification at individual object level. But detailed object classification was restricted due to the limitations in the spectral resolution. Recently, the advancements in remote sensing technology have made hyperspectral imagery with high spatial resolution available that permits object-based processing of these datasets for a detailed LULC classification. However, currently available object-based classifiers are only modifications of the pixel based classifiers developed for multispectral data. They are either parametric in nature with the assumption of Gaussian distribution and/or do not completely exploit the rich spectral information available in the hyperspectral imagery. This research proposes a supervised non-parametric fuzzy classifier that performs classification based on the object-level distribution of reflectance values. A fuzzy Kolmogorov-Smirnov based classifier is proposed that performs an object-to-object matching of the empirical distribution of the reflectance values of each object and derives a fuzzy membership grade for each class without any distributional assumptions. This object based classification procedure was tested for its robustness on three different sensors with varying combinations of spectral and spatial resolutions. General land use/land cover classifications as well as detailed urban forest tree species classifications were performed to test the performance of the classifier. The results for the two study areas show that the proposed classifier consistently achieves high accuracies, irrespective of the sensor, and also demonstrates superior performance in comparison to other popular object and pixel-based classifiers.

Sridharan, Harini

216

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

Directory of Open Access Journals (Sweden)

Full Text Available Based on the research status of objective control theory of new energy power projects, analysed the system components of power projects, proposed the subsystem reliability control theory directed at four objectives, gave reliability control standards and calculation methods of four objectives, obtained the objective integrated method of subsystem reliability, used disjoint minimal path sets method to deal with the minimal path sets in the project construction process, proposed system reliability control theory of new energy power projects, then combined the known reliability control standards to assess project reliability, finally established objective integrated control model of new energy power projects based on reliability theory. Finally an simple example proves that the proposed objective integrated control model is simple and practical.  

Yunna Wu

2013-08-01

217

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

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

Yuan Tian

2010-03-01

218

Reusability Evaluation of Learning Objects Stored in Open Repositories Based on Their Metadata  

Science.gov (United States)

Reusability is considered to be the key property of learning objects residing in open repositories. In consecuence, measurement instruments for learning object reusability should be developed. In this preliminary research we propose to evaluate the reusability of learning objects by a priori reusability analysis based on their metadata records. A set of reusability metrics extracted from metadata records are defined and a quality assessment of the metadata application profiles defined in repositories eLera and Merlot is exposed.

Sanz, Javier; Sánchez-Alonso, Salvador; Dodero, Juan Manuel

219

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

OpenAIRE

Detecting static objects in video sequences has a high relevance in many surveillance applications, such as the detection of abandoned objects in public areas. In this paper, we present a system for the detection of static objects in crowded scenes. Based on the detection of two background models learning at different rates, pixels are classified with the help of a finite-state machine. The background is modelled by two mixtures of Gaussians with identical parameters except for the learning ...

Thomas Sikora; Heras Evangelio, Rub Amp N.

2011-01-01

220

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)

221

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

OpenAIRE

A modified object-tracking algorithm that uses the flexible Metric Distance Transform kernel and multiple features for the Mean shift procedure is proposed and tested. The Faithful target separation based on RGB joint pdf of the target region and that of a neighborhood surrounding the object is obtained. The non-linear log-likelihood function maps the multimodal object/background distribution as positive values for colors associated with foreground, while negative values are marked for backgr...

Amir Aliabadian; Esmaeil Akbarpour; Mohammad Yosefi

2012-01-01

222

Moving Object Classification Method Based on SOM and K-means  

OpenAIRE

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 ...

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

2011-01-01

223

Shaping Attention with Reward: Effects of Reward on Space- and Object-Based Selection  

OpenAIRE

The contribution of rewarded actions to automatic attentional selection remains obscure. We hypothesized that some forms of automatic orienting, such as object-based selection, can be completely abandoned in lieu of reward maximizing strategy. While presenting identical visual stimuli to the observer, in a set of two experiments, we manipulate what is being rewarded (different object targets or random object locations) and the type of reward received (money or points). It was observed that re...

Shomstein, Sarah; Johnson, Jacoba

2013-01-01

224

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

Directory of Open Access Journals (Sweden)

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

Slamet Widodo

2013-04-01

225

Principal Objects Detection Using Graph-Based Segmentation and Normalized Histogram  

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

Pham The Bao

2012-01-01

226

Multi-view Object Detection Based on Spatial Consistency in a Low Dimensional Space  

Science.gov (United States)

This paper describes a new approach for detecting objects based on measuring the spatial consistency between different parts of an object. These parts are pre-defined on a set of training images and then located in any arbitrary image. Each part is represented by a group of densely sampled SIFT features. Supervised Locally Linear Embedding is then used to describe the appearance of each part in a low dimensional space. The novelty of this approach is that linear embedding techniques are used to model each object part and the background in the same coordinate space. This permits the detection algorithm to explicitly label test features as belonging to an object part or background. A spatial consistency algorithm is then employed to find object parts that together provide evidence for the location of object(s) in the image. Experiments on the 3D and PASCAL VOC datasets yield results comparable and often superior to those found in the literature.

Gill, Gurman; Levine, Martin

227

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

Science.gov (United States)

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

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

2015-01-01

228

Object tracking system using a VSW algorithm based on color and point features  

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Full Text Available Abstract An object tracking system using a variable search window (VSW algorithm based on color and feature points is proposed. A meanshift algorithm is an object tracking technique that works according to color probability distributions. An advantage of this algorithm based on color is that it is robust to specific color objects; however, a disadvantage is that it is sensitive to non-specific color objects due to illumination and noise. Therefore, to offset this weakness, it presents the VSW algorithm based on robust feature points for the accurate tracking of moving objects. The proposed method extracts the feature points of a detected object which is the region of interest (ROI, and generates a VSW using the given information which is the positions of extracted feature points. The goal of this paper is to achieve an efficient and effective object tracking system that meets the accurate tracking of moving objects. Through experiments, the object tracking system is implemented that it performs more precisely than existing techniques.

Lim Hye-Youn

2011-01-01

229

Object tracking system using a VSW algorithm based on color and point features  

Science.gov (United States)

An object tracking system using a variable search window (VSW) algorithm based on color and feature points is proposed. A meanshift algorithm is an object tracking technique that works according to color probability distributions. An advantage of this algorithm based on color is that it is robust to specific color objects; however, a disadvantage is that it is sensitive to non-specific color objects due to illumination and noise. Therefore, to offset this weakness, it presents the VSW algorithm based on robust feature points for the accurate tracking of moving objects. The proposed method extracts the feature points of a detected object which is the region of interest (ROI), and generates a VSW using the given information which is the positions of extracted feature points. The goal of this paper is to achieve an efficient and effective object tracking system that meets the accurate tracking of moving objects. Through experiments, the object tracking system is implemented that it performs more precisely than existing techniques.

Lim, Hye-Youn; Kang, Dae-Seong

2011-12-01

230

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

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

Masayasu Atsumi

2013-05-01

231

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

Science.gov (United States)

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…

Cho, Dongbin; Proctor, Robert W.

2010-01-01

232

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

Science.gov (United States)

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

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

2013-01-01

233

The Timecourse of Space- and Object-based Attentional Prioritization with Varying Degrees of Certainty  

Directory of Open Access Journals (Sweden)

Full Text Available The relative contributions of surfaces (i.e., object-based and underlying spatial representations (i.e., space-based to attentional prioritization and selection remain unclear. In most experimental circumstances, the two representations overlap thus their respective contributions cannot be evaluated. Here, a dynamic version of the two-rectangle paradigm allowed for a successful de-coupling of spatial and object representations. Space-based (cued spatial location, cued surface (cued location on an object, and object-based (locations within the cued object effects were sampled at several timepoints following the cue with high or low certainty as to target location. In the high uncertainty condition spatial benefits prevailed throughout most of the timecourse, as evidenced by facilitatory and inhibitory effects. Additionally, the cued surface, rather than a whole object, received the attentional benefit. When target location was predictable (low uncertainty manipulation, only probabilities guided selection (i.e., biased location received the benefit. These results suggest that with high uncertainty as to the location of the upcoming target, all available information present within the stimulus display is used for the purposes of attentional selection (e.g., spatial locations, surfaces albeit to varying degrees and at different time points. However, as certainty increases, only spatial certainty guides selection (i.e., surfaces and objects are filtered out. Taken together, these results further elucidate the contributing role of space- and object-representations to attentional guidance.

SarahShomstein

2013-12-01

234

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

Directory of Open Access Journals (Sweden)

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.

Helen J. Chatterjee

2010-01-01

235

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)

236

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

Science.gov (United States)

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

Sun, Zhaolei; Hui, Bin

2014-11-01

237

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

OpenAIRE

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 e...

Weiqi Zhou; Cadenasso, Mary L.; Kirsten Schwarz; Pickett, Steward T. A.

2014-01-01

238

DEVS-Based Modeling and Simulation of the CORBA Portable Object Adapter  

OpenAIRE

We present in this paper our approach for the modeling and the simulation of distributed architectures based upon Common Object Request Broker Architecture (CORBA). We point out a global methodology for the modeling of algorithmic functions using a DEVS?based approach, and we apply it to a function of the CORBA Portable Object Adapter: find_POA(). We will expose the methodology we defined, which allows the taking into account of all the computer control structures, and then will introduce t...

Gentili, Emmanuelle; Bernardi, Fabrice; Santucci, Jean-franc?ois

2001-01-01

239

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

OpenAIRE

Object-based image coding is drawing a great attention for the many opportunities it offers to high-level applications. In terms of rate-distortion performance, however, its value is still uncertain, because the gains provided by an accurate image segmentation are balanced by the inefficiency of coding objects of arbitrary shape, with losses that depend on both the coding scheme and the object geometry. This work aims at measuring rate-distortion costs and gains for a wavelet-based shape-ada...

Cagnazzo Marco; Parrilli Sara; Poggi Giovanni; Verdoliva Luisa

2007-01-01

240

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

Directory of Open Access Journals (Sweden)

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.

Qian Zhang

2009-04-01

241

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

Directory of Open Access Journals (Sweden)

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.

L. DJEROU,

2012-01-01

242

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

Scientific Electronic Library Online (English)

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

José Eduardo Mendonça, Xavier; Hansjörg Andreas, Schneebeli.

1998-04-01

243

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

OpenAIRE

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

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

2014-01-01

244

User-assisted Object Detection by Segment Based Similarity Measures in Mobile Laser Scanner Data  

Science.gov (United States)

This paper describes a method that aims to find all instances of a certain object in Mobile Laser Scanner (MLS) data. In a userassisted approach, a sample segment of an object is selected, and all similar objects are to be found. By selecting samples from multiple classes, a classification can be performed. Key assumption in this approach is that a one-to-one relationship exists between segments and objects. In this paper the focus is twofold: (1) to explain how to get proper segments, and (2) to describe how to find similar objects. Point attributes that help separating neighbouring objects are presented. These point attributes are used in an attributed connected component algorithm where segments are grown, based on proximity and attribute values. Per component, a feature vector is proposed that consists of two parts. The first is a height histogram, containing information on the height distribution of points within a component. The second contains size and shape information, based on the components' bounding box. A simple correlation function is used to find similarities between samples, as selected by a user, and other components. Our approach is tested on a MLS dataset, containing over 300 objects in 13 classes. Detection accuracies heavily depend on the success of the segmentation, and the number of selected samples in combination with the variety of object types in the scene.

Oude Elberink, S.; Kemboi, B.

2014-08-01

245

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

Science.gov (United States)

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.

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

2015-01-01

246

An Object-Oriented Architecture for a Web-Based CAI System.  

Science.gov (United States)

This paper describes the design and implementation of an object-oriented World Wide Web-based CAI (Computer-Assisted Instruction) system. The goal of the design is to provide a flexible CAI/ITS (Intelligent Tutoring System) framework with full extendibility and reusability, as well as to exploit Web-based software technologies such as JAVA, ASP (a…

Nakabayashi, Kiyoshi; Hoshide, Takahide; Seshimo, Hitoshi; Fukuhara, Yoshimi

247

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

International Nuclear Information System (INIS)

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

248

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

Science.gov (United States)

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

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

2015-03-01

249

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

Directory of Open Access Journals (Sweden)

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

Hui-bin Wang

2013-01-01

250

An object oriented framework of EPICS for MicroTCA based control system  

International Nuclear Information System (INIS)

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

251

Key Object Discovery and Tracking Based on Context-Aware Saliency  

Directory of Open Access Journals (Sweden)

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.

Geng Zhang

2013-01-01

252

3D-modeling of deformed halite hopper crystals by Object Based Image Analysis  

Science.gov (United States)

Object Based Image Analysis (OBIA) is an established method for analyzing multiscale and multidimensional imagery in a range of disciplines. In the present study this method was used for the 3D reconstruction of halite hopper crystals in a mudrock sample, based on Computed Tomography data. To quantitatively assess the reliability of OBIA results, they were benchmarked against a corresponding "gold standard", a reference 3D model of the halite crystals that was derived by manual expert digitization of the CT images. For accuracy assessment, classical per-scene statistics were extended to per-object statistics. The strength of OBIA was to recognize all objects similar to halite hopper crystals and in particular to eliminate cracks. Using a support vector machine (SVM) classifier on top of OBIA, unsuitable objects like halite crystal clusters, polyhalite-coated crystals and spherical halite crystals were effectively dismissed, but simultaneously the number of well-shaped halites was reduced.

Leitner, Christoph; Hofmann, Peter; Marschallinger, Robert

2014-12-01

253

The study of high-resolution imaging of astronomical object based on phase-diversity method  

Science.gov (United States)

The high resolution imaging of astronomical object based on phase-diversity method is a technique for obtaining estimates of both the object and the distribution of wavefront induced by atmospheric turbulence,by exploiting the simultaneous collection of one or more pairs of short-exposure images. One of the pair images is the conventional focal-plane image and another is formed by further blurring the focal-image by defocus.The telescopic optical system and image collection system of phase-diversity method are simulated by using computer in this paper. Based on signal estimation theory and optimization theory, the objective function is derived under additive Gaussian noise model. The resulting large scale unconstrained optimization problem is solved numerically using a limited memory BFGS method. The restoring results demonstrate that the phase-diversity method is remarkably efficient for removing the effect of atmospheric turbulence and solving the image restoration problem of astronomical extended object.

Li, Q.; Shen, M. Z.

2007-01-01

254

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

Science.gov (United States)

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

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

2006-08-01

255

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

OpenAIRE

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

Monika Moskal, L.; Jakubauskas, Mark E.

2013-01-01

256

Object modelling data base of geographical information system of transmissions pipelines  

OpenAIRE

: 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...

Levic?nik, Toni

2008-01-01

257

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

OpenAIRE

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

Borges, Ana Rosa; Antunes, Carlos Henggeler

2003-01-01

258

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

OpenAIRE

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

Edmund TRolls

2012-01-01

259

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

OpenAIRE

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...

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

2009-01-01

260

Video segmentation based on the presence and/or absence of moving objects  

Science.gov (United States)

Video clip is the dominant component of multimedia system. However, video data are voluminous. An effective and efficient visual data management system is highly desired. Recent technology in digital video processing has moved to 'content-based' storage and retrieval. To detect meaningful area/region, using only production and camera operation- based detection is not enough. The contents of a video also have to be considered. The basic idea of this scheme is that if we can distinguish individual objects in the whole video sequence, we would be able to capture the changes in content throughout the sequences. Among many object features, motion content has been widely used as an important key in video storage and retrieval systems. Therefore, through motion- based representation, this paper will investigate an algorithm for sub-shot extraction and key-frame selection. From a given video sequence, first we segment the sequence into shots by using some of the production and camera operation-based detection techniques. Then, from the beginning of each shot, we calculate optical flow vectors by using complex wavelet phase-matching-based method on a pair of successive frames. Next, we segment each moving object based on these vectors using clustering in a competitive agglomeration scheme and represent them into a number of layers. After separating moving object(s) from each other for every frame in this shot, we extract sub-shots and select key-frames by using information about the presence and absence of moving object in each layer. Finally, these key-frames and sub-shots have been used to represent the whole video in panoramic mosaic-based representation form. Experimental results showing the significance of the proposed method are also provided.

Nitsuwat, Supot; Jin, Jesse S.; Hudson, M. B.

1999-08-01

261

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

Science.gov (United States)

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

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

2012-01-01

262

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

Science.gov (United States)

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

LIPPITT, CHRISTOPHER D.; COULTER, LLOYD L.; FREEMAN, MARY; LAMANTIA-BISHOP, JEFFREY; PANG, WYSON; STOW, DOUGLAS A.

2011-01-01

263

An Objects Detecting and Tracking method based on MSPF and SVM  

OpenAIRE

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

Wei Sun 1; Xu Zhang 2; Yunyi Yan 3

2012-01-01

264

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

Directory of Open Access Journals (Sweden)

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.

Sunil T. D

2014-06-01

265

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

Science.gov (United States)

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

Chi, Jeong Hee; Kim, Sang Ho

266

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

Science.gov (United States)

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

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

2014-12-01

267

Object shape-based optical sensing methodology and system for condition monitoring of contaminated engine lubricants  

Science.gov (United States)

Presence of contaminants, such as gasoline, moisture, and coolant in the engine lubricant indicates mechanical failure within the engine and significantly reduces lubricant quality. This paper describes a novel sensing system, its methodology and experimental verifications for analysis of the presence of contaminants in the engine lubricants. The sensing methodology is based on the statistical shape analysis methodology utilizing optical analysis of the distortion effect when an object image is obtained through a thin random optical medium. The novelty of the proposed sensing system lies within the employed methodology which an object with a known periodic shape is introduced behind a thin film of the contaminated lubricant. In this case, an acquired image represents a combined lubricant-object optical appearance, where an a priori known periodical structure of the object is distorted by a contaminated lubricant. The object, e.g. a stainless steel woven wire cloth with a mesh size of 65×65 µm2 and a circular wire diameter of 33 µm was placed behind a microfluidic channel, containing engine lubricant and optical images of flowing lubricant with stationary object were acquired and analyzed. Several parameters of acquired optical images, such as, color of lubricant and object, object shape width at object and lubricant levels, object relative color, and object width non-uniformity coefficient, were proposed. Measured on-line parameters were used for optical analysis of fresh and contaminated lubricants. Estimation of contaminant presence and lubricant condition was performed by comparison of parameters for fresh and contaminated lubricants. Developed methodology was verified experimentally showing ability to distinguish lubricants with 1%, 4%, 7%, and 10% coolant, gasoline and water contamination individually and in a combination form of coolant (0%-5%) and gasoline (0%-5%).

Bordatchev, Evgueni; Aghayan, Hamid; Yang, Jun

2014-03-01

268

Vision-based object detection and recognition system for intelligent vehicles  

Science.gov (United States)

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

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

1999-01-01

269

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

Directory of Open Access Journals (Sweden)

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

Muhammad Kamal

2011-10-01

270

Applications of custom developed object based analysis tool: Precipitation in Pacific, Tropical cyclones precipitation, Hail areas  

Science.gov (United States)

In the last few years an object-based analysis software tool was developed at University of Ljubljana in collaboration with National Center for Atmospheric Research (NCAR). The tool was originally based on ideas of the Method for Object-Based Diagnostic Evaluation (MODE) developed by NCAR but has since evolved and changed considerably and is now available as a separate free software package. The software is called the Forward in Time object analysis tool (FiT tool). The software was used to analyze numerous datasets - mainly focusing on precipitation. Climatology of satellite and model precipitation in the low-and-mid latitude Pacific Ocean was performed by identifying and tracking of individual perception systems and estimating their lifespan, movement and size. A global climatology of tropical cyclone precipitation was performed using satellite data and tracking and analysis of areas with hail in Slovenia was performed using radar data. The tool will be presented along with some results of applications.

Skok, Gregor; Rakovec, Jože; Strajnar, Benedikt; Bacmeister, Julio; Tribbia, Joe

2014-05-01

271

Key Object Discovery and Tracking Based on Context-Aware Saliency  

OpenAIRE

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 c...

Geng Zhang; Zejian Yuan; Nanning Zheng

2013-01-01

272

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

OpenAIRE

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 coe...

Anastasia Polychronaki; Sander Veraverbeke; Gitas, Ioannis Z.; Annekatrien Debien

2013-01-01

273

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

Directory of Open Access Journals (Sweden)

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

Harini Nagendra

2013-03-01

274

A fast three-dimensional object recognition based on modulation analysis  

Science.gov (United States)

A novel method of the 3-D object recognition based on modulation analysis is proposed. Two orthogonal gratings with a small interval are vertically projected on an object surface and the recognized object is placed between the imaging planes of the two gratings. Then the image of the object surface modulated by the orthogonal gratings can be obtained by a CCD camera from the same direction, and the object height information is encoded in the image. The image is processed by the operations consisting of performing the Fourier transform and spatial spectrum analysis. The fundamental frequency can be obtained in two different directions. Then we calculated the recognition parameter RP (the normalized energy of each fundamental frequency). According to the RP values, we can determine the object position in the 2-D orthogonal co-ordinate system. The RP values will vary for different objects, so the different objects will be shown in different positions of the co-ordinate system. The expressions of the recognition parameter in the space and spectrum region have been given in this work. There are some advantages of our method. Firstly, it can recognize the 3-D object by the fundamental frequency energy analysis in two directions of the frequency domain, which cannot be almost discerned from their 2-D intensity images. Secondly, it has the advantages of shift-invariance and rotation-invariance, and can avoid the influence of shadow on 3-D object recognition. Finally the method has noise resistance ability. Both the computer simulation and the experimental results are presented in support of the proposed idea.

Wang, Ying; Su, Xianyu; Dou, Yunfu

2010-10-01

275

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

Science.gov (United States)

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

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

2014-09-20

276

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

Science.gov (United States)

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.

Ding, Hao; Li, Xudong; Zhao, Huijie

2013-03-01

277

Design and Evaluation of Perceptual-based Object Group Selection Techniques  

Science.gov (United States)

Selecting groups of objects is a frequent task in graphical user interfaces. It is required prior to many standard operations such as deletion, movement, or modification. Conventional selection techniques are lasso, rectangle selection, and the selection and de-selection of items through the use of modifier keys. These techniques may become time-consuming and error-prone when target objects are densely distributed or when the distances between target objects are large. Perceptual-based selection techniques can considerably improve selection tasks when targets have a perceptual structure, for example when arranged along a line. Current methods to detect such groups use ad hoc grouping algorithms that are not based on results from perception science. Moreover, these techniques do not allow selecting groups with arbitrary arrangements or permit modifying a selection. This dissertation presents two domain-independent perceptual-based systems that address these issues. Based on established group detection models from perception research, the proposed systems detect perceptual groups formed by the Gestalt principles of good continuation and proximity. The new systems provide gesture-based or click-based interaction techniques for selecting groups with curvilinear or arbitrary structures as well as clusters. Moreover, the gesture-based system is adapted for the graph domain to facilitate path selection. This dissertation includes several user studies that show the proposed systems outperform conventional selection techniques when targets form salient perceptual groups and are still competitive when targets are semi-structured.

Dehmeshki, Hoda

278

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

Science.gov (United States)

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

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

2014-09-01

279

Feature-based inattentional blindness: loss of awareness to featural information in fully attended objects.  

Science.gov (United States)

In two experiments, we investigated the impact of feature-based attention on observers' awareness of object appearance. Participants were shown a sequence of two displays, each containing eight objects (rectangles), and were asked to detect changes in the orientation of a cued rectangle. A set of baseline trials preceded probe trials in which half of the rectangles in each display were unexpectedly distorted by 70 %. Participants in both Experiment 1 (100-ms display duration) and Experiment 2 (100- and 400-ms display durations) were unaware of these modifications in the task-irrelevant feature (texture), even when they were asked to select the viewed object in a forced choice procedure. A control experiment showed that participants could identify the physical distortion when they were made aware of its presence. The results demonstrate that feature-based attention moderates the appearance of objects, even when those objects are fully expected and fully attended, implying a distinct form of unawareness that we term feature-based inattentional blindness. PMID:24935808

Persuh, Marjan; Gomez, Mabel; Bauer, Lisa; Melara, Robert D

2014-11-01

280

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

Science.gov (United States)

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

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

2012-10-01

281

[Location selection for Shenyang urban parks based on GIS and multi-objective location allocation model].  

Science.gov (United States)

Based on geographic information system (GIS) technology and multi-objective location-allocation (LA) model, and in considering of four relatively independent objective factors (population density level, air pollution level, urban heat island effect level, and urban land use pattern), an optimized location selection for the urban parks within the Third Ring of Shenyang was conducted, and the selection results were compared with the spatial distribution of existing parks, aimed to evaluate the rationality of the spatial distribution of urban green spaces. In the location selection of urban green spaces in the study area, the factor air pollution was most important, and, compared with single objective factor, the weighted analysis results of multi-objective factors could provide optimized spatial location selection of new urban green spaces. The combination of GIS technology with LA model would be a new approach for the spatial optimizing of urban green spaces. PMID:22384602

Zhou, Yuan; Shi, Tie-Mao; Hu, Yuan-Man; Gao, Chang; Liu, Miao; Song, Lin-Qi

2011-12-01

282

Moving Object Classification Method Based on SOM and K-means  

Directory of Open Access Journals (Sweden)

Full Text Available 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 on bidirectional comparison of centroid to do tracking, and an improved method to obtain initial background when using background subtraction method to detect motion of moving objects. Experimental results show the effectiveness and robustness of the proposed approach.

Jian Wu

2011-08-01

283

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

284

A New Merging Algorithm Based on Semantic Relationships of Learning Objects  

Directory of Open Access Journals (Sweden)

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

Elio Rivas-Sanchez

2013-12-01

285

A model-based approach for detection of objects in low resolution passive millimeter wave images  

Science.gov (United States)

A model-based vision system to assist the pilots in landing maneuvers under restricted visibility conditions is described. The system was designed to analyze image sequences obtained from a Passive Millimeter Wave (PMMW) imaging system mounted on the aircraft to delineate runways/taxiways, buildings, and other objects on or near runways. PMMW sensors have good response in a foggy atmosphere, but their spatial resolution is very low. However, additional data such as airport model and approximate position and orientation of aircraft are available. These data are exploited to guide our model-based system to locate objects in the low resolution image and generate warning signals to alert the pilots. Also analytical expressions were derived from the accuracy of the camera position estimate obtained by detecting the position of known objects in the image.

Kasturi, Rangachar; Tang, Yuan-Liang; Devadiga, Sadashiva

1993-01-01

286

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

Directory of Open Access Journals (Sweden)

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

Cagnazzo Marco

2007-01-01

287

Object tracking and target reacquisition based on 3-D range data for moving vehicles.  

Science.gov (United States)

In this paper, we propose an approach for tracking an object of interest based on 3-D range data. We employ particle filtering and active contours to simultaneously estimate the global motion of the object and its local deformations. The proposed algorithm takes advantage of range information to deal with the challenging (but common) situation in which the tracked object disappears from the image domain entirely and reappears later. To cope with this problem, a method based on principle component analysis (PCA) of shape information is proposed. In the proposed method, if the target disappears out of frame, shape similarity energy is used to detect target candidates that match a template shape learned online from previously observed frames. Thus, we require no a priori knowledge of the target's shape. Experimental results show the practical applicability and robustness of the proposed algorithm in realistic tracking scenarios. PMID:21486717

Lee, Jehoon; Lankton, Shawn; Tannenbaum, Allen

2011-10-01

288

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

International Nuclear Information System (INIS)

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

289

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

OpenAIRE

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

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

2014-01-01

290

Identifying optimal classification rules for geographic object-based image analysis  

OpenAIRE

In Geographic Object-based Image Analysis (GEOBIA), remote sensing experts benefit from a large spectrum of characteristics to interpret images (spectral information, texture, geometry, spatial relations, etc). However, the quality of a classification is not always increased by considering a higher number of features. The experts are then used to define classification rules based on a laborious "trial-and-error" process. In this paper, we test a methodology to automatically determine an optim...

Arvor, D.; Saint-geours, N.; Dupuy, S.; Andre?s, S.; Durieux, L.

2013-01-01

291

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

OpenAIRE

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

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

1996-01-01

292

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

OpenAIRE

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...

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

2010-01-01

293

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

OpenAIRE

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...

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

2011-01-01

294

ARTIFICIAL NEURAL NETWORK BASED DISCRIMINATION OF MINELIKE OBJECTS IN INFRARED IMAGES  

OpenAIRE

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...

Suganthi, G.; Reeba Korah; Seetharaman, N.

2014-01-01

295

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

DEFF Research Database (Denmark)

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.

Gu, Tao; Chen, Shaxun

2010-01-01

296

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

Directory of Open Access Journals (Sweden)

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

Weihong Wang

2012-01-01

297

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

OpenAIRE

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

Weihong Wang; Yanye Du; Qu Li; Zhaolin Fang

2012-01-01

298

Ground-based follow-up of Solar System objects detected by Gaia  

Science.gov (United States)

In the frame of the DPAC consortium preparing the Gaia mission, a specific follow-up activity has been set up in order to ensure best scientific return related to solar-system-object (SSO) science. This activity encompasses a system of alerts for newly detected objects provided by CNES, the French data center in charge of the Solar System data processing, and IMCCE, to organize and publish the alerts, and to retrieve the objects astrometry and feed the Minor Planet Center database. We are expecting in particular the detection of new near-Earth objects (NEO) at low solar elongation, or even inner-Earth objects. Owing to its observing mode, the satellite will not be able to monitor these objects after discovery and they could be lost. It is thus important to consolidate and improve their orbital parameters. This is the objective of the SSO ground-based follow-up. Once the objective is reached, it is possible to update the auxiliary database of orbital elements used within the Gaia data reduction pipeline for identifying the known SSOs and to allow Gaia to subsequently identify these objects properly during its mission. In order to reach these goals we have carried out two main activities: -- We have developed a pipeline for processing the Gaia raw data that will be received, and for disseminating only the topocentric data useful for observers in an automatized way -- We have set up a worldwide network of observing stations, the Gaia-FUN-SSO network (shortly described at https://www.imcce.fr/gaia-fun-sso/). At this date, 55 observing sites have registered and many participants have already contributed to several training campaigns for NEO observations. We will describe both activities and we will give preliminary results regarding the Gaia Solar System alerts, depending on the status of the triggering system during this early stage of the mission.

Thuillot, W.; Carry, B.; Berthier, J.; David, P.; Devillepoix, H.; Hestroffer, D.

2014-07-01

299

Modeling and efficient optimization for object-based scalability and some related problems.  

Science.gov (United States)

MPEG-4 is the first visual coding standard that allows coding of scenes as a collection of individual audio-visual objects. We present mathematical formulations for modeling object-based scalability and some functionalities that it brings with it. Our goal is to study algorithms that aid in semi-automating the authoring and subsequent selective addition/dropping of objects from a scene to provide content scalability. We start with a simplistic model for object-based scalability using the "knapsack problem"--a problem for which the optimal object set can be found using known schemes such as dynamic programming, the branch and bound method and approximation algorithms. The above formulation is then generalized to model authoring or multiplexing of scalable objects (e.g., objects encoded at various target bit-rates) using the "multiple choice knapsack problem." We relate this model to several problems that arise in video coding, the most prominent of these being the bit allocation problem. Unlike previous approaches to solve the operational bit allocation problem using Lagrangean relaxation, we discuss an algorithm that solves linear programming (LP) relaxation of this problem. We show that for this problem the duality gap for Lagrange and LP relaxations is exactly the same. The LP relaxation is solved using strong duality with dual descent--a procedure that can be completed in "linear" time. We show that there can be at most two fractional variables in the optimal primal solution and therefore this relaxation can be justified for many practical applications. This work reduces problem complexity, guarantees similar performance, is slightly more generic, and provides an alternate LP-duality based proof for earlier work by Shoham and Gersho (1988). In addition, we show how additional constraints may be added to impose inter-dependencies among objects in a presentation and discuss how object aggregation can be exploited in reducing problem complexity. The marginal analysis approach of Fox (1966) is suggested as a method of re-allocation with incremental inputs. It helps in efficiently re-optimizing the allocation when a system has user interactivity, appearing or disappearing objects, time driven events, etc. Finally, we suggest that approximation algorithms for the multiple choice knapsack problem, which can be used to quantify complexity vs. quality tradeoff at the encoder in a tunable and universal way. PMID:18262907

Batra, P

2000-01-01

300

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

OpenAIRE

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

Surbhi Maggo; Chetna Gupta

2014-01-01

301

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

Directory of Open Access Journals (Sweden)

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.

Shiyan Pang

2014-11-01

302

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

Science.gov (United States)

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.

Suh, Woonsuk; Lee, Eunseok

303

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

Directory of Open Access Journals (Sweden)

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.

Chandra Mani Sharma

2012-01-01

304

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

Science.gov (United States)

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

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

2014-12-01

305

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

Science.gov (United States)

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.

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

2014-12-01

306

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

Directory of Open Access Journals (Sweden)

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

Debasis Dwibedy, Dr. Laxman Sahoo, Sujoy Dutta

2013-04-01

307

A New Design Method based on Cooperative Data Mining from Multi-Objective Design Space  

Science.gov (United States)

We propose a new multi-objective parameter design method that uses the combination of the following data mining techniques: analysis of variance, self-organizing map, decision tree analysis, rough set theory, and association rule. This method first aims to improve multiple objective functions simultaneously using as much predominant main effects of different design variables as possible. Then it resolves the remaining conflictions between the objective functions using predominant interaction effects of design variables. The key to realizing this method is the obtaining of various design rules that quantitatively relate levels of design variables to levels of objective functions. Based on comparative studies of data mining techniques, the systematic processes for obtaining these design rules have been clarified, and the points of combining data mining techniques have also been summarized. This method has been applied to a multi-objective robust optimization problem of an industrial fan, and the results show its superior capabilities for controlling parameters to traditional single-objective parameter design methods like the Taguchi method.

Sugimura, Kazuyuki; Obayashi, Shigeru; Jeong, Shinkyu

308

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

Science.gov (United States)

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.

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

2014-11-01

309

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

Directory of Open Access Journals (Sweden)

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.

S.N. Qasem

2010-01-01

310

Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance  

Directory of Open Access Journals (Sweden)

Full Text Available We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences.

Lei Qin

2014-05-01

311

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

Directory of Open Access Journals (Sweden)

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.

R K Jena

2014-05-01

312

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

DEFF Research Database (Denmark)

A number of emerging applications of data management technology involve the monitoring and querying of large quantities of continuous variables, e.g., the positions of mobile service users, termed moving objects. In such applications, large quantities of state samples obtained via sensors are streamed to a database. Indexes for moving objects must support queries efficiently, but must also support frequent updates. Indexes based on minimum bounding regions (MBRs) such as the R-tree exhibit high concurrency overheads during node splitting, and each individual update is known to be quite costly. This motivates the design of a solution that enables the B+-tree to manage moving objects. We represent moving-object locations as vectors that are timestamped based on their update time. By applying a novel linearization technique to these values, it is possible to index the resulting values using a single B+-tree that partitions values according to their timestamp and otherwise preserves spatial proximity. We develop algorithms for range and k nearest neighbor queries, as well as continuous queries. The proposal can be grafted into existing database systems cost effectively. An extensive experimental study explores the performance characteristics of the proposal and also shows that it is capable of substantially outperforming the R-tree based TPR-tree for both single and concurrent access scenarios.

Jensen, Christian SØndergaard; Lin, Dan

2004-01-01

313

Depth image based rendering for multiview stereoscopic displays: role of information at object boundaries  

Science.gov (United States)

Depth image based rendering (DIBR) is useful for multiview autostereoscopic systems because it can produce a set of new images with different camera viewpoints, based on a single two-dimensional (2D) image and its corresponding depth map. In this study we investigated the role of object boundaries in depth maps for DIBR. Using a standard subjective assessment method, we asked viewers to evaluate the depth and the image quality of stereoscopic images in which the view for the right eye was rendered using (a) full depth maps, (b) partial depth maps containing full depth information but that was only located at object boundaries and edges, and (c) partial depth maps containing binary depth information at object boundaries and edges. Results indicate that depth quality was enhanced and image quality was slightly reduced for all test conditions, compared to a reference condition consisting of 2D images. The present results confirm previous observations indicating that depth information at object boundaries is sufficient in DIBR to create new views such as to produce a stereoscopic effect. However, depth ratings for the partial depth maps tended to be slightly lower than those generated with the full depth maps. The present study also indicates that more research is needed to increase the depth and image quality of the rendered stereoscopic images based on DIBR before the technique can be of wide and practical use.

Tam, Wa James; Speranza, Filippo; Zhang, Liang; Renaud, Ron; Chan, Jason; Vazquez, Carlos

2005-11-01

314

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

DEFF Research Database (Denmark)

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

Civilis, Alminas; Jensen, Christian SØndergaard

2005-01-01

315

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

DEFF Research Database (Denmark)

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

Civilis, A.; Jensen, Christian SØndergaard

2005-01-01

316

Context based Coding of Binary Shapes by Object Boundary Straightness Analysis  

OpenAIRE

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%...

Aghito, Shankar Manuel; Forchhammer, Søren

2007-01-01

317

A Robust Approach to Segment Desired Object Based on Salient Colors  

Directory of Open Access Journals (Sweden)

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

Jérôme Da Rugna

2008-01-01

318

Fuzzy preference based interactive fuzzy physical programming and its application in multi-objective optimization  

International Nuclear Information System (INIS)

Interactive Fuzzy Physical Programming (IFPP) developed in this paper is a new efficient multi-objective optimization method, which retains the advantages of physical programming while considering the fuzziness of the designer's preferences. The fuzzy preference function is introduced based on the model of linear physical programming, which is used to guide the search for improved solutions by interactive decision analysis. The example of multi-objective optimization design of the spindle of internal grinder demonstrates that the improved preference conforms to the subjective desires of the designer

319

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

OpenAIRE

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

Zhu Lei; Yang Jing

2011-01-01

320

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

OpenAIRE

Visual image interpretation and digital image classification have been used to map and monitor mangrove extent and composition for decades. The presence of a high-spatial resolution hyperspectral sensor can potentially improve our ability to differentiate mangrove species. However, little research has explored the use of pixel-based and object-based approaches on high-spatial hyperspectral datasets for this purpose. This study assessed the ability of CASI-2 data for mangrove species mapping ...

Muhammad Kamal; Stuart Phinn

2011-01-01

321

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

Directory of Open Access Journals (Sweden)

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

Heras Evangelio Rubén

2011-01-01

322

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

Directory of Open Access Journals (Sweden)

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

Amir Aliabadian

2012-03-01

323

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

Science.gov (United States)

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.

Zhang, Shuqun; Furia, Bryan

2014-09-01

324

Reflection-mode optical-resolution photoacoustic microscopy based on a reflective objective.  

Science.gov (United States)

We developed a new reflection-mode optical-resolution photoacoustic microscopy (OR-PAM) based on the cooperation of a reflective objective and an ultrasonic transducer. The reflective objective is used to produce nearly diffraction-limited optical focusing, and the excited ultrasound waves are then directly detected by an ultrasonic transducer that was placed in the central cone of the objective. This new design avoids the coupling between optical focusing and ultrasound transmission in the reflection mode. Moreover, the proposed system is able to provide lateral resolution of 1.2 ?m at 580 nm, penetration depth of 0.9 mm in biological tissues, and a work distance of 6.0 mm. We present in vivo imaging of the microvasculature in mouse ears and in vitro imaging of red blood cells (RBCs), which demonstrate the capability of the system to study microcirculation. PMID:24104331

Wang, Hui; Yang, Xiaoquan; Liu, Yanyan; Jiang, Bowen; Luo, Qingming

2013-10-01

325

An object-oriented based daytime over land fog detection approach using EOS/MODIS data  

Science.gov (United States)

A new algorithm is presented for land fog detection from daytime image of Earth Observation System Moderate Resolution Imaging Spectroradiometer (EOS/MODIS) data. Due to its outstanding spatial and spectral resolutions, this image is an ideal data source for fog detection. The algorithm utilizes an object-oriented technique to separate fog from other cloud types. In this paper, MOD35 product is first introduced to exclude cloud-free areas, and high clouds are removed with MODIS 26 band, and then a parameter named Normalized Difference Fog Index (NDFI) is proposed based on Streamer radiative model and MODIS data for fog detection. Through segmenting NDFI image into regions of pixels, and computing attributes (e.g. mean value of brightness temperature) for each region to create objects, each object could be identified based on the attributes selected to determine whether belongs to fog or cloud. Algorithm's performance is evaluated against ground-based measurements over China in winter. The algorithm is proved to be effective in detecting fog accurately based on two different test cases.

Wen, Xiongfei; Liu, Liangming; Li, Wei; Dong, Pei

2009-09-01

326

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

Directory of Open Access Journals (Sweden)

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.

Jaewoon Lee

2015-02-01

327

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

Science.gov (United States)

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

Wang, Ping; Wu, Guangqiang

2013-03-01

328

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

Science.gov (United States)

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

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

2014-04-01

329

Image Coding Scheme Based on Object Extraction and Hybrid Transformation Technique  

Directory of Open Access Journals (Sweden)

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

Usama S. Mohammed

2010-05-01

330

Research and development of infrared object detection system based on FPGA  

Science.gov (United States)

Infrared object detection is an important technique of digital image processing. It is widely used in automatic navigation, intelligent video surveillance systems, traffic detection, medical image processing etc. Infrared object detection system requires large storage and high speed processing technology. The current development trend is the system which can be achieved by hardware in real-time with fewer operations and higher performance. As a main large-scale programmable specific integrated circuit, field programmable gate array (FPGA) can meet all the requirements of high speed image processing, with the characteristics of simple algorithm realization, easy programming, good portability and inheritability. So it could get better result by using FPGA to infrared object detection system. According to the requirements, the infrared object detection system is designed on FPGA. By analyzing some of the main algorithms of object detection, two new object detection algorithms called integral compare algorithm (ICA) and gradual approach centroid algorithm (GACA) are presented. The system design applying FPGA in hardware can implement high speed processing technology, which brings the advantage of both performance and flexibility. ICA is a new type of denoising algorithm with advantage of lower computation complexity and less execution time. What is more important is that this algorithm can be implemented in FPGA expediently. Base on image preprocessing of ICA, GACA brings high positioning precision with advantage of insensitivity to the initial value and fewer times of convergence iteration. The experiments indicate that the infrared object detection system can implement high speed infrared object detecting in real-time, with high antijamming ability and high precision. The progress of Verilog-HDL and its architecture are introduced in this paper. Considering the engineering application, this paper gives the particular design idea and the flow of this method's realization in FPGA device. And we also discuss the problems on how to describe the hardware system in Verilog-HDL. Based on the hardware architecture of infrared object detection system, the component units of the system are discussed in detail, such as image data acquisition unit, data pre-processing unit and logical control unit etc. The design of the FPGA function and its implementation are carried on Verilog-HDL with TOP-DOWN method. The ending is the prospect of the project.

Zhao, Jianhui; He, Jianwei; Wang, Pengpeng; Li, Fan

2009-07-01

331

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

OpenAIRE

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

Andrea Baraldi; Luigi Boschetti

2012-01-01

332

Data-driven hierarchical structure kernel for multiscale part-based object recognition.  

Science.gov (United States)

Detecting generic object categories in images and videos are a fundamental issue in computer vision. However, it faces the challenges from inter and intraclass diversity, as well as distortions caused by viewpoints, poses, deformations, and so on. To solve object variations, this paper constructs a structure kernel and proposes a multiscale part-based model incorporating the discriminative power of kernels. The structure kernel would measure the resemblance of part-based objects in three aspects: 1) the global similarity term to measure the resemblance of the global visual appearance of relevant objects; 2) the part similarity term to measure the resemblance of the visual appearance of distinctive parts; and 3) the spatial similarity term to measure the resemblance of the spatial layout of parts. In essence, the deformation of parts in the structure kernel is penalized in a multiscale space with respect to horizontal displacement, vertical displacement, and scale difference. Part similarities are combined with different weights, which are optimized efficiently to maximize the intraclass similarities and minimize the interclass similarities by the normalized stochastic gradient ascent algorithm. In addition, the parameters of the structure kernel are learned during the training process with regard to the distribution of the data in a more discriminative way. With flexible part sizes on scale and displacement, it can be more robust to the intraclass variations, poses, and viewpoints. Theoretical analysis and experimental evaluations demonstrate that the proposed multiscale part-based representation model with structure kernel exhibits accurate and robust performance, and outperforms state-of-the-art object classification approaches. PMID:24808345

Botao Wang; Hongkai Xiong; Xiaoqian Jiang; Zheng, Yuan F

2014-04-01

333

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

Directory of Open Access Journals (Sweden)

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

DR.P.SUBASHINI

2011-08-01

334

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.)

335

Electro-holography display using computer generated hologram of 3D objects based on projection spectra  

Science.gov (United States)

A new method of synthesizing computer-generated hologram of three-dimensional (3D) objects is proposed from their projection images. A series of projection images of 3D objects are recorded with one-dimensional azimuth scanning. According to the principles of paraboloid of revolution in 3D Fourier space and 3D central slice theorem, spectra information of 3D objects can be gathered from their projection images. Considering quantization error of horizontal and vertical directions, the spectrum information from each projection image is efficiently extracted in double circle and four circles shape, to enhance the utilization of projection spectra. Then spectra information of 3D objects from all projection images is encoded into computer-generated hologram based on Fourier transform using conjugate-symmetric extension. The hologram includes 3D information of objects. Experimental results for numerical reconstruction of the CGH at different distance validate the proposed methods and show its good performance. Electro-holographic reconstruction can be realized by using an electronic addressing reflective liquid-crystal display (LCD) spatial light modulator. The CGH from the computer is loaded onto the LCD. By illuminating a reference light from a laser source to the LCD, the amplitude and phase information included in the CGH will be reconstructed due to the diffraction of the light modulated by the LCD.

Huang, Sujuan; Wang, Duocheng; He, Chao

2012-11-01

336

Bionics-Based Approach for Object Tracking to Implementin Robot Applications  

Directory of Open Access Journals (Sweden)

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

Hussam K. Abdul-Ameer

2010-01-01

337

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

Science.gov (United States)

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

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

2013-06-01

338

Histogram Curve Matching Approaches for Object-based Image Classification of Land Cover and Land Use.  

Science.gov (United States)

The classification of image-objects is usually done using parametric statistical measures of central tendency and/or dispersion (e.g., mean or standard deviation). The objectives of this study were to analyze digital number histograms of image objects and evaluate classifications measures exploiting characteristic signatures of such histograms. Two histograms matching classifiers were evaluated and compared to the standard nearest neighbor to mean classifier. An ADS40 airborne multispectral image of San Diego, California was used for assessing the utility of curve matching classifiers in a geographic object-based image analysis (GEOBIA) approach. The classifications were performed with data sets having 0.5 m, 2.5 m, and 5 m spatial resolutions. Results show that histograms are reliable features for characterizing classes. Also, both histogram matching classifiers consistently performed better than the one based on the standard nearest neighbor to mean rule. The highest classification accuracies were produced with images having 2.5 m spatial resolution. PMID:24403648

Toure, Sory I; Stow, Douglas A; Weeks, John R; Kumar, Sunil

2013-05-01

339

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

Directory of Open Access Journals (Sweden)

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.

Anastasia Polychronaki

2013-11-01

340

Three-dimensional model-based object recognition and segmentation in cluttered scenes.  

Science.gov (United States)

Viewpoint independent recognition of free-form objects and their segmentation in the presence of clutter and occlusions is a challenging task. We present a novel 3D model-based algorithm which performs this task automatically and efficiently. A 3D model of an object is automatically constructed offline from its multiple unordered range images (views). These views are converted into multidimensional table representations (which we refer to as tensors). Correspondences are automatically established between these views by simultaneously matching the tensors of a view with those of the remaining views using a hash table-based voting scheme. This results in a graph of relative transformations used to register the views before they are integrated into a seamless 3D model. These models and their tensor representations constitute the model library. During online recognition, a tensor from the scene is simultaneously matched with those in the library by casting votes. Similarity measures are calculated for the model tensors which receive the most votes. The model with the highest similarity is transformed to the scene and, if it aligns accurately with an object in the scene, that object is declared as recognized and is segmented. This process is repeated until the scene is completely segmented. Experiments were performed on real and synthetic data comprised of 55 models and 610 scenes and an overall recognition rate of 95 percent was achieved. Comparison with the spin images revealed that our algorithm is superior in terms of recognition rate and efficiency. PMID:16986541

Mian, Ajmal S; Bennamoun, Mohammed; Owens, Robyn

2006-10-01

341

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

Science.gov (United States)

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

Sertel, Elif; Yay, Irmak

2014-01-01

342

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

Directory of Open Access Journals (Sweden)

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

Claudia T. Pereira

2012-07-01

343

Personalised Learning Object System Based on Self-Regulated Learning Theories  

Directory of Open Access Journals (Sweden)

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

Ali Alharbi

2014-06-01

344

Object detection and tracking method of AUV based on acoustic vision  

Science.gov (United States)

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

Zhang, Tie-dong; Wan, Lei; Zeng, Wen-jing; Xu, Yu-ru

2012-12-01

345

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

CERN Document Server

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...

Trunfio, Paolo

2014-01-01

346

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

Directory of Open Access Journals (Sweden)

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.

Stéphanie Jehan-Besson

2002-06-01

347

Object-based depth image-based rendering for a three-dimensional video system by color-correction optimization  

Science.gov (United States)

Three-dimensional (3-D) video technologies are becoming increasingly popular because they can provide high quality and immersive experience to end users. Depth image-based rendering (DIBR) is a key technology in 3-D video systems due to its low bandwidth cost as well as the arbitrary rendering viewpoint. We propose an object-based DIBR method by color-correction optimization. The proposed method first performs temporal consistent rendering to reduce the rendering complexity. Then, by segmenting the depth map into foreground and background, the object-based scalable rendering is performed to improve the rendering quality and reduce the rendering complexity. Finally, the rendered virtual view is further optimized by color-correction operation. Experimental results show that, compared to the results without the above optimization operations, the proposed method can reduce >40% computational complexity while maintaining high rendering quality.

Shao, Feng; Jiang, Gang-Yi; Yu, Mei; Zhang, Yun

2011-04-01

348

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

OpenAIRE

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

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

2013-01-01

349

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

Energy Technology Data Exchange (ETDEWEB)

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

Qiang, J. (Ji); Ryne, Robert

2001-01-01

350

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

Science.gov (United States)

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

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

351

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

Directory of Open Access Journals (Sweden)

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.

Jing Liu

2013-01-01

352

A Dynamic Interval Based Circular Safe Region Algorithm for Continuous Queries on Moving Objects  

Directory of Open Access Journals (Sweden)

Full Text Available Moving object database (MOD engine is the foundation of Location-Based Service (LBS information systems. Continuous queries are important in spatial-temporal reasoning of a MOD. The communication costs were the bottleneck for improving query efficiency until the rectangular safe region algorithm partly solved this problem. However, this algorithm can be further improved, as we demonstrate with the dynamic interval based continuous queries algorithm on moving objects. Two components, circular safe region and dynamic intervals were adopted by our algorithm. Theoretical proof and experimental results show that our algorithm substantially outperforms the traditional periodic monitoring and the rectangular safe region algorithm in terms of monitoring accuracy, reducing communication costs and server CPU time. Moreover, in our algorithm, the mobile terminals do not need to have any computational ability.

Chen Zhang

2011-05-01

353

Empirical analysis of web-based user-object bipartite networks  

Science.gov (United States)

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.

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

2010-05-01

354

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

International Nuclear Information System (INIS)

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

355

Empirical analysis of web-based user-object bipartite networks  

CERN Document Server

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.

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

2009-01-01

356

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

OpenAIRE

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

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

2011-01-01

357

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

OpenAIRE

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-ob...

Lai, M. Z.; Duan, Z. M.; Zhang, G. Y.; B.D

2013-01-01

358

Evaluation of regional bulbar redness using an image-based objective method  

OpenAIRE

AIM: To develop an image-based objective method to precisely evaluate regional ocular bulbar injection.METHODS:Six healthy adult volunteers were photographed in four orientations (superior, inferior, nasal and temporal sides) with and without stimulating eye drops. Six line segments (covering 30°) were drawn 4mm away from the limbus on each image using ImageJ software. The graph peaks, which were derived from the areas under the line segments and corresponded to the cross-sectional grey-leve...

Wen-Juan Zhao; Fang Duan; Zhong-Ting Li; Hua-Jun Yang; Qiang Huang; Kai-Li Wu

2014-01-01

359

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

OpenAIRE

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

Pop, Adrian

2008-01-01

360

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

OpenAIRE

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

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

2012-01-01

361

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

OpenAIRE

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...

Broega, A. C.; Silva, Maria Elisabete

2008-01-01

362

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

OpenAIRE

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...

Acker, Ju?rgen; Henrich, Dominik

2003-01-01

363

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

OpenAIRE

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...

Aronsson, Peter; Fritzson, Peter

2001-01-01

364

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

OpenAIRE

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 gen...

Shiyan Pang; Xiangyun Hu; Zizheng Wang; Yihui Lu

2014-01-01

365

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

CERN Document Server

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

Wang, Hui

2009-01-01

366

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

OpenAIRE

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 (...

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

2013-01-01

367

The role of object-based learning in transferable skills development  

Directory of Open Access Journals (Sweden)

Full Text Available This paper considers how object-based learning (OBL can be used to complement reflective skills development systems, which are commonplace in UK universities. It describes how some UCL students had difficulty understanding the concept of such a system and in choosing skills to develop. We therefore began developing a series of OBL activities, which could be used to help students understand how the system should be used and to identify their skill strengths and weaknesses.

Jenny Marie

2010-01-01

368

An IPM-APSO based hybrid method for multiple objective minimizations using TCPS  

OpenAIRE

This paper presents an Interior Pont Method (IPM) and variant of Particle Swarm Optimization (APSO) based hybrid method to solve optimal power flow in power system incorporating Flexible AC Transmission Systems (FACTS) such as Thyristor Controlled Phase Shifter (TCPS) for minimization of multiple objectives. The proposed IPM-APSO algorithm identifies the optimal values of generator active-power output and the adjustment of reactive power control devices. The proposed optimization process with...

Balasubba Reddy, M.; Obulesh, Dr Y. P.; Sivanaga Raju, Dr S.

2012-01-01

369

Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis  

OpenAIRE

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...

Jane Southworth; Youliang Qiu; Luke Rostant; Sanchayeeta Adhikari; Cerian Gibbes

2010-01-01

370

An object-based approach to weather analysis and its applications  

Science.gov (United States)

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

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

2013-04-01

371

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

Science.gov (United States)

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.

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

2015-01-01

372

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

Directory of Open Access Journals (Sweden)

Full Text Available Multi-objective image segmentation is a frequently encountered problem. The classical C-V algorithm has the shortage about multi-iterative operations and the computational time is too long to segment the large size image. On the base of analysis upon the relationship between the image size and the number of iterations and time to get the right result, the article proposes a fast image segmentation algorithm based on local C-V active contour model which are based on threshold segmentation and the connected component labeling to segment the large size image with multiple objectives. In the first step, a coarse segmentation is obtained by using the OTSU method, then label and cut the image with the fast non-recursion pixel marking algorithm of connected domains. The segmentation is used as an initial solution in the C-V model. The analysis and experimental results indicate that the improved C-V algorithm can get the right result quickly compared with classical C-V algorithm. It is fast and effective to segment the large size image with multiple objectives.

Zhu Lei

2011-02-01

373

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

Directory of Open Access Journals (Sweden)

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.

Maggi Kelly

2011-11-01

374

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

Directory of Open Access Journals (Sweden)

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

José M. Peña

2014-05-01

375

Multimodal saliency-based attention for object-based scene analysis  

OpenAIRE

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

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

2011-01-01

376

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

OpenAIRE

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 (UAV...

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

2014-01-01

377

Reconstruction and 3D visualisation based on objective real 3D based documentation.  

Science.gov (United States)

Reconstructions based directly upon forensic evidence alone are called primary information. Historically this consists of documentation of findings by verbal protocols, photographs and other visual means. Currently modern imaging techniques such as 3D surface scanning and radiological methods (computer tomography, magnetic resonance imaging) are also applied. Secondary interpretation is based on facts and the examiner's experience. Usually such reconstructive expertises are given in written form, and are often enhanced by sketches. However, narrative interpretations can, especially in complex courses of action, be difficult to present and can be misunderstood. In this report we demonstrate the use of graphic reconstruction of secondary interpretation with supporting pictorial evidence, applying digital visualisation (using 'Poser') or scientific animation (using '3D Studio Max', 'Maya') and present methods of clearly distinguishing between factual documentation and examiners' interpretation based on three cases. The first case involved a pedestrian who was initially struck by a car on a motorway and was then run over by a second car. The second case involved a suicidal gunshot to the head with a rifle, in which the trigger was pushed with a rod. The third case dealt with a collision between two motorcycles. Pictorial reconstruction of the secondary interpretation of these cases has several advantages. The images enable an immediate overview, give rise to enhanced clarity, and compel the examiner to look at all details if he or she is to create a complete image. PMID:21979427

Bolliger, Michael J; Buck, Ursula; Thali, Michael J; Bolliger, Stephan A

2012-09-01

378

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

OpenAIRE

The devastating series of fire events that occurred during the summers of 2007 and 2009 in Greece made evident the need for an operational mechanism to map burned areas in an accurate and timely fashion to be developed. In this work, Système pour l’Observation de la Terre (SPOT)-4 HRVIR images are introduced in an object-based classification environment in order to develop a classification procedure for burned area mapping. The development of the procedure was based on two images and then ...

Anastasia Polychronaki; Gitas, Ioannis Z.

2012-01-01

379

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

OpenAIRE

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

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

2012-01-01

380

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

Energy Technology Data Exchange (ETDEWEB)

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

Zhu, Zhiwei; Zhou, Xiaoqin; Liu, Qiang; Zhao, Shaoxin [Jilin University, Changchun (China)

2011-12-15

381

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

International Nuclear Information System (INIS)

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

382

Objective evaluation method of steering comfort based on movement quality evaluation of driver steering maneuver  

Science.gov (United States)

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

Yang, Yiyong; Liu, Yahui; Wang, Man; Ji, Run; Ji, Xuewu

2014-09-01

383

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

Science.gov (United States)

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

Huang, Shih-Chia; Chen, Bo-Hao

2013-12-01

384

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)

385

A new multi-object image thresholding method based on correlation between object class uncertainty and intensity gradient  

OpenAIRE

Purpose: Image thresholding and gradient analysis have remained popular image preprocessing tools for several decades due to the simplicity and straight-forwardness of their definitions. Also, optimum selection of threshold and gradient strength values are hidden steps in many advanced medical imaging algorithms. A reliable method for threshold optimization may be a crucial step toward automation of several medical image based applications. Most automatic thresholding and gradient selection m...

Liu, Yinxiao; Liang, Guoyuan; Saha, Punam K.

2012-01-01

386

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

387

An Objects Detecting and Tracking method based on MSPF and SVM  

Directory of Open Access Journals (Sweden)

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

Wei Sun 1

2012-02-01

388

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

Directory of Open Access Journals (Sweden)

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.

Kang Ling

2009-02-01

389

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

International Nuclear Information System (INIS)

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

390

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

CERN Document Server

Many image watermarking schemes have been proposed in recent years, but they usually involve embedding a watermark to the entire image without considering only a particular object in the image, which the image owner may be interested in. This paper proposes a watermarking scheme that can embed a watermark to an arbitrarily shaped object in an image. Before embedding, the image owner specifies an object of arbitrary shape that is of a concern to him. Then the object is transformed into the wavelet domain using in place lifting shape adaptive DWT(SADWT) and a watermark is embedded by modifying the wavelet coefficients. In order to make the watermark robust and transparent, the watermark is embedded in the average of wavelet blocks using the visual model based on the human visual system. Wavelet coefficients n least significant bits (LSBs) are adjusted in concert with the average. Simulation results shows that the proposed watermarking scheme is perceptually invisible and robust against many attacks such as loss...

Essaouabi, A; Fegragui, F

2009-01-01

391

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

Directory of Open Access Journals (Sweden)

Full Text Available Many image watermarking schemes have been proposed in recent years, but they usually involve embedding a watermark to the entire image without considering only a particular object in the image, which the image owner may be interested in. This paper proposes a watermarking scheme that can embed a watermark to an arbitrarily shaped object in an image. Before embedding, the image owner specifies an object of arbitrary shape that is of a concern to him. Then the object is transformed into the wavelet domain using in place lifting shape adaptive DWT(SADWT and a watermark is embedded by modifying the wavelet coefficients. In order to make the watermark robust and transparent, the watermark is embedded in the average of wavelet blocks using the visual model based on the human visual system. Wavelet coefficients n least significant bits (LSBs are adjusted in concert with the average. Simulation results shows that the proposed watermarking scheme is perceptually invisible and robust against many attacks such as lossy compression (e.g. JPEG, JPEG2000, scaling, adding noise, filtering, etc.

F. Regragui

2009-10-01

392

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

393

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

Science.gov (United States)

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

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

2015-02-01

394

Multi-objective scheduling in an agent based Holonic manufacturing system  

Directory of Open Access Journals (Sweden)

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.

T. K. Jana

2014-01-01

395

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

Directory of Open Access Journals (Sweden)

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.

Quoc Tuan Vo

2013-01-01

396

Image analysis based grading of bladder carcinoma. Comparison of object, texture and graph based methods and their reproducibility.  

Science.gov (United States)

The possibility that computerized image analysis could increase the reproducibility of grading of bladder carcinoma as compared to conventional subjective grading made by pathologists was investigated. Object, texture and graph based analysis were carried out from Feulgen stained histological tissue sections. The object based features were extracted from gray scale images, binary images obtained by thresholding the nuclei and several other images derived through image processing operations. The textural features were based on the spatial gray-tone co-occurrence probability matrices and the graph based features were extracted from the minimum spanning trees connecting all nuclei. The large numbers of extracted features were evaluated in relation to subjective grading and to factors related to prognosis using multivariate statistical methods and multilayer backpropagation neural networks. All the methods were originally developed and tested on material from one patient and then tested for reproducibility on entirely different patient material. The results indicate reasonably good reproducibility for the best sets of features. In addition, image analysis based grading showed almost identical correlation to mitotic density and expression of p53 protein as subjective grading. It should thus be possible to use this kind of image analysis as a prognostic tool for bladder carcinoma. PMID:9373709

Choi, H K; Jarkrans, T; Bengtsson, E; Vasko, J; Wester, K; Malmström, P U; Busch, C

1997-01-01

397

Linear stereo vision based objects detection and tracking using spectral clustering  

Science.gov (United States)

Objects detection and tracking is a key function for many applications like video surveillance, robotic, intelligent transportation systems,...etc. This problem is widely treated in the literature in terms of sensors (video cameras, laser range finder, Radar) and methodologies. This paper proposes a new approach for detecting and tracking objects using stereo vision with linear cameras. After the matching process applied to edge points extracted from the images, the reconstructed points in the scene are clustered using spectral analysis. The obtained clusters are then tracked throughout their center of gravity using a Kalman filter and a Nearest Neighbour (NN) based data association algorithm. The approach is tested and evaluated on real data to demonstrate its effectiveness for obstacle detection and tracking in front of a vehicle. This work is a part of a project that aims to develop advanced driving aid systems, supported by the CPER, STIC and Volubilis programs.

Moqqaddem, Safaa; Ruichek, Y.; Touahni, R.; Sbihi, A.

2011-01-01

398

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

Directory of Open Access Journals (Sweden)

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%.

Elias David Nino Ruiz

2013-05-01

399

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

Energy Technology Data Exchange (ETDEWEB)

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.

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

2004-06-01

400

A new method for feature selection based on fuzzy similarity measures using multi objective genetic algorithm  

Directory of Open Access Journals (Sweden)

Full Text Available Feature selection (FS is considered to be an important preprocessing step in machine learning and pattern recognition, and feature evaluation is the key issue for constructing a feature selection algorithm. Feature selection process can also reduce noise and this way enhance the classification accuracy. In this article, feature selection method based on fuzzy similarity measures by multi objective genetic algorithm (FSFSM - MOGA is introduced and performance of the proposed method on published data sets from UCI was evaluated. The results show the efficiency of the method is compared with the conventional version. When this method multi-objective genetic algorithms and fuzzy similarity measures used in CFS method can improve it.

Hassan Nosrati Nahook

2014-06-01

401

Context based Coding of Binary Shapes by Object Boundary Straightness Analysis  

DEFF Research Database (Denmark)

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

Aghito, Shankar Manuel; Forchhammer, SØren

2004-01-01

402

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

Directory of Open Access Journals (Sweden)

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.

Jinchang Ren

2010-04-01

403

A Moving Objects Detection Algorithm Based on Three-Frame Difference and Sparse Optical Flow  

Directory of Open Access Journals (Sweden)

Full Text Available Moving objects detection is an important research of computer vision. Optical flow method is a main way, but it is limited to use because of its complexity. A moving objects detection algorithm based on three-frame difference and optical flow is proposed. The calculation of optical flow is simplified. Harris corners are detected and then only the corners are selected to compute optical flow information, which reduce the algorithm’s complexity. Because the detected moving target area is not complete, three-frame difference method is introduced as a supplement. The experimental results show that the algorithm can achieve real-time and has better results than anyone of these two separate algorithms.

Guo-Wu Yuan

2014-01-01

404

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

Science.gov (United States)

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

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

2014-07-01

405

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

CERN Document Server

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

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

2010-01-01

406

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

Science.gov (United States)

Many teaching centers have now adopted objective structured clinical examination (OSCE) as an assessment method for undergraduate dermatology courses. A modification of the standard OSCE in dermatology is computer based or electronic OSCE (eOSCE). We attempted to validate the use of a computer-based OSCE in dermatology in a group of fifth year medical students. The scores of the students in the computer-based OSCE showed a strong positive correlation with the scores on the clinical presentation (Pearson's co-efficient - 0.923, P value <0.000, significant at the 0.01 level) and a good correlation with overall scores of the student (Pearson's co-efficient - 0.728, P value <0.000, significant at the 0.01 level), indicating that this is a reliable method for assessment in dermatology. Generally, the students' feedback regarding the methods was positive. PMID:24685849

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

2014-01-01

407

Fast object reconstruction in block-based compressive low-light-level imaging  

Science.gov (United States)

In this paper we propose a simply yet effective and efficient method for long-term object tracking. Different from traditional visual tracking method which mainly depends on frame-to-frame correspondence, we combine high-level semantic information with low-level correspondences. Our framework is formulated in a confidence selection framework, which allows our system to recover from drift and partly deal with occlusion problem. To summarize, our algorithm can be roughly decomposed in a initialization stage and a tracking stage. In the initialization stage, an offline classifier is trained to get the object appearance information in category level. When the video stream is coming, the pre-trained offline classifier is used for detecting the potential target and initializing the tracking stage. In the tracking stage, it consists of three parts which are online tracking part, offline tracking part and confidence judgment part. Online tracking part captures the specific target appearance information while detection part localizes the object based on the pre-trained offline classifier. Since there is no data dependence between online tracking and offline detection, these two parts are running in parallel to significantly improve the processing speed. A confidence selection mechanism is proposed to optimize the object location. Besides, we also propose a simple mechanism to judge the absence of the object. If the target is lost, the pre-trained offline classifier is utilized to re-initialize the whole algorithm as long as the target is re-located. During experiment, we evaluate our method on several challenging video sequences and demonstrate competitive results.

Ke, Jun; Sui, Dong; Wei, Ping

2014-11-01

408

Target Object Identification and Location Based on Multi-sensor Fusion  

Directory of Open Access Journals (Sweden)

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.

Yong Jiang

2013-03-01

409

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

Science.gov (United States)

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

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

2010-06-01

410

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

Science.gov (United States)

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.

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

2014-07-01

411

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

Directory of Open Access Journals (Sweden)

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.

Xiaolong Liu

2015-01-01

412

A comparison of the accuracy of pixel based and object based classifications of integrated optical and LiDAR data  

Science.gov (United States)

A comparison of the accuracy of pixel based and object based classifications of integrated optical and LiDAR data Land cover maps are generally produced on the basis of high resolution imagery. Recently, LiDAR (Light Detection and Ranging) data have been brought into use in diverse applications including land cover mapping. In this study we attempted to assess the accuracy of land cover classification using both high resolution aerial imagery and LiDAR data (airborne laser scanning, ALS), testing two classification approaches: a pixel-based classification and object-oriented image analysis (OBIA). The study was conducted on three test areas (3 km2 each) in the administrative area of Kraków, Poland, along the course of the Vistula River. They represent three different dominating land cover types of the Vistula River valley. Test site 1 had a semi-natural vegetation, with riparian forests and shrubs, test site 2 represented a densely built-up area, and test site 3 was an industrial site. Point clouds from ALS and ortophotomaps were both captured in November 2007. Point cloud density was on average 16 pt/m2 and it contained additional information about intensity and encoded RGB values. Ortophotomaps had a spatial resolution of 10 cm. From point clouds two raster maps were generated: intensity (1) and (2) normalised Digital Surface Model (nDSM), both with the spatial resolution of 50 cm. To classify the aerial data, a supervised classification approach was selected. Pixel based classification was carried out in ERDAS Imagine software. Ortophotomaps and intensity and nDSM rasters were used in classification. 15 homogenous training areas representing each cover class were chosen. Classified pixels were clumped to avoid salt and pepper effect. Object oriented image object classification was carried out in eCognition software, which implements both the optical and ALS data. Elevation layers (intensity, firs/last reflection, etc.) were used at segmentation stage due to proper wages usage. Thus a more precise and unambiguous boundaries of segments (objects) were received. As a results of the classification 5 classes of land cover (buildings, water, high and low vegetation and others) were extracted. Both pixel-based image analysis and OBIA were conducted with a minimum mapping unit of 10m2. Results were validated on the basis on manual classification and random points (80 per test area), reference data set was manually interpreted using ortophotomaps and expert knowledge of the test site areas.

Gajda, Agnieszka; Wójtowicz-Nowakowska, Anna

2013-04-01

413

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

International Nuclear Information System (INIS)

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

414

THE EFFECTS OF OPERATIONAL OBJECTIVES-BASED TRAINING PROGRAM ON JUNIOR II MALE HANDBALL PLAYERS  

Directory of Open Access Journals (Sweden)

Full Text Available This paper aims to prove the effectiveness of the operational objectives-based sports training program in the junior II male handball players from the Bacau School Sports Club, during the technical-tactical drills. The aim of this research was to test the subjects throughout the competition season by applying a series of technical-tactical tests. We presumed that after applying the operational objective-based athletic training program in the junior II male handball players, the progress in the technical-tactical drills will be ascending, recording superior final results, these being conditioned by an optimal programing of the training.The goal of this study was to prove that the progress of the Bacau School Sports Club junior II male handball players in the technical-tactical drills was correlated with the operational objective-based program.The research subjects consisted of an experimental group from the Bacau School Sports Club and a witness group from School 3 - the Adjud School Sports Club Both groups comprised 19 junior II male players. In order to emphasize the progress recorded in the technical-tactical training, we gathered data from three control drills and from the assessment of the players' actions during the game. The progress was conditioned by the programing of the athletic training; during the training sessions, we intervened each time through the operational objectives, for improving the training process.The more prominent progress during the first part of the competition season is due to the technical training, while the sufficiently prominent progress in the last part of the season is due to the tactical training, a fact that results from the programing of the operational objectives - the ones for the technical training are more in the first part of the season, while the ones for the tactical training are in larger number in the second part of the season.The effectiveness of the programs gained them a first place in the Junior II National Championship.

Sufaru Constantin

2014-06-01

415

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

Science.gov (United States)

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

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

2007-01-01

416

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

Science.gov (United States)

Next-generation infrared astronomical instrumentation for ground-based and space telescopes could be based on MOEMS programmable slit masks for multi-object spectroscopy (MOS). This astronomical technique is used extensively to investigate the formation and evolution of galaxies. We are developing a 2048x1080 Digital-Micromirror-Device-based (DMD) MOS instrument to be mounted on the Galileo telescope and called BATMAN. A two-arm instrument has been designed for providing in parallel imaging and spectroscopic capabilities. The field of view (FOV) is 6.8 arcmin x 3.6 arcmin with a plate scale of 0.2 arcsec per micromirror. The wavelength range is in the visible and the spectral resolution is R=560 for 1 arcsec object (typical slit size). The two arms will have 2k x 4k CCD detectors. ROBIN, a BATMAN demonstrator, has been designed, realized and integrated. It permits to determine the instrument integration procedure, including optics and mechanics integration, alignment procedure and optical quality. First images and spectra have been obtained and measured: typical spot diameters are within 1.5 detector pixels, and spectra generated by one micro-mirror slits are displayed with this optical quality over the whole visible wavelength range. Observation strategies are studied and demonstrated for the scientific optimization strategy over the whole FOV. BATMAN on the sky is of prime importance for characterizing the actual performance of this new family of MOS instruments, as well as investigating the operational procedures on astronomical objects. This instrument will be placed on the Telescopio Nazionale Galileo mid-2015.

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

2014-07-01

417

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

Science.gov (United States)

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

Zhu, Shiping; Li, Liyun; Wang, Zaikuo

2012-12-01

418

Neural activity associated with self, other, and object-based counterfactual thinking.  

Science.gov (United States)

Previous research has shown that autobiographical episodic counterfactual thinking-i.e., mental simulations about alternative ways in which one's life experiences could have occurred-engages the brain's default network (DN). However, it remains unknown whether or not the DN is also engaged during impersonal counterfactual thoughts, specifically those involving other people or objects. The current study compares brain activity during counterfactual simulations involving the self, others and objects. In addition, counterfactual thoughts involving others were manipulated in terms of similarity and familiarity with the simulated characters. The results indicate greater involvement of DN during person-based (i.e., self and other) as opposed to object-based counterfactual simulations. However, the involvement of different regions of the DN during other-based counterfactual simulations was modulated by how close and/or similar the simulated character was perceived to be by the participant. Simulations involving unfamiliar characters preferentially recruited dorsomedial prefrontal cortex. Simulations involving unfamiliar similar characters, characters with whom participants identified personality traits, recruited lateral temporal gyrus. Finally, our results also revealed differential coupling of right hippocampus with lateral prefrontal and temporal cortex during counterfactual simulations involving familiar similar others, but with left transverse temporal gyrus and medial frontal and inferior temporal gyri during counterfactual simulations involving either oneself or unfamiliar dissimilar others. These results suggest that different brain mechanisms are involved in the simulation of personal and impersonal counterfactual thoughts, and that the extent to which regions associated with autobiographical memory are recruited during the simulation of counterfactuals involving others depends on the perceived similarity and familiarity with the simulated individuals. PMID:25579447

De Brigard, Felipe; Nathan Spreng, R; Mitchell, Jason P; Schacter, Daniel L

2015-04-01

419

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

DEFF Research Database (Denmark)

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.

Juel, Anders

420

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

Directory of Open Access Journals (Sweden)

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.

A.I. De Castro

2014-06-01

421

Dynamic Verification of an Object-Rule Knowledge Base Using Colored Petri Nets  

Directory of Open Access Journals (Sweden)

Full Text Available In this paper, we propose a formal description for the dynamic verification of an Object-Rule Hybrid Knowledge-based System (HKBS, capitalizing on the work carried out within the verification framework of Frame-Rule Hybrid Expert Systems. The main idea is to model an HKBS by means of a Colored Petri Network (CPN. In this way, method invocations, state class changes, rules and productions will be modeled as components of the CPN. Detection and analysis of the HKBS will be carried out by the construction and analysis of the markings graph, which results from the inference process.

Chakib Tadj

2006-06-01

422

Multi-Objective PSO- and NPSO-based Algorithms for Robot Path Planning  

OpenAIRE

In this paper two novel Particle Swarm Optimization (PSO)-based algorithms are presented for robot path planning with respect to two objectives, the shortest and smoothest path criteria. The first algorithm is a hybrid of the PSO and the Probabilistic Roadmap (PRM) methods, in which the PSO serves as the global planner whereas the PRM performs the local planning task. The second algorithm is a combination of the New or Negative PSO (NPSO) and the PRM methods. Contrary to the basic PSO in w...

Sedighizadeh, D.; Masehian, E.

2010-01-01

423

Effective Scanned-Certification Image Retrieval Based on Local Object and Block Matching  

Directory of Open Access Journals (Sweden)

Full Text Available Scanned certifications are widely used in China as proof of past achievements. To avoid repetitive usage of the same certification in various awards or funding applications, we design and implement a scanned-certification image retrieval system based on local object and block matching. The seal is used as a salient feature and a modified Hough round detection method is applied for extraction. And local round seals are combined with blocks attributes of the seals to build image indexes. Experimental results will demonstrate the effectiveness of the system. Additionally, we conduct experiments on single color histogram, which further demonstrates the effectiveness of the proposed image retrieval method.

Hao Zhang

2014-03-01

424

An IPM-APSO based hybrid method for multiple objective minimizations using TCPS  

Directory of Open Access Journals (Sweden)

Full Text Available This paper presents an Interior Pont Method (IPM and variant of Particle Swarm Optimization (APSO based hybrid method to solve optimal power flow in power system incorporating Flexible AC Transmission Systems (FACTS such as Thyristor Controlled Phase Shifter (TCPS for minimization of multiple objectives. The proposed IPM-APSO algorithm identifies the optimal values of generator active-power output and the adjustment of reactive power control devices. The proposed optimization process with IPM-APSO is presented with case study example using IEEE 30-bus test system to demonstrate its applicability. The results are presented to show the feasibility and potential of this new approach.

M.Balasubba Reddy

2012-08-01