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检索条件"主题词=image segmentation algorithm"

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A real-time parallel combination segmentation method for aluminum surface defect images

A real-time parallel combination segmentation method for alu...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Xiu-Qin Huang Xin-Bin Luo Ren-Zhong Wang Suzhou Non-ferrous Metals Research Institute Suzhou Jiangsu China School of Aeronautics and Astronautics Shanghai Jiaotong University China

ISBN: (纸本)9781467372220

A single defect image segmentation algorithm cannot obtain the desired segmentation results for all images because of the defect diversity. A parallel combination segmentation method is proposed to integrate multiple results of the different segmentation algorithms to obtain the desired defect segmentation map for high-speed aluminum surface defect detection. Two types of segmentation algorithms are designed in this combination framework, namely, the automatic threshold segmentation based on the image statistical model and adaptive entropy-based segmentation. The automatic threshold segmentation algorithm detects defects rapidly using the threshold parameters obtained by modeling the image effectively, and the adaptive entropy-based segmentation algorithm effectively detects defects using ID information entropy. These two types of segmentation algorithms run in parallel, and their segmentation results are fused by an "and" operation. Thus, an improved image segmentation map with higher accuracy is obtained. Many experimental results and field applications show that the parallel combination segmentation algorithm is a stable and efficient segmentation algorithm, which improves the accuracy of the original segmentation algorithm that it contains.

关键词： Combination segmentation Defect extraction Edge detection Entropy Surface defect detection Surface defect detection segmentation segmentation Edge detection entropy image segmentation algorithm Parallel Connection defect image aluminium surface

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Research and Application of Moving Target Tracking algorithm Based on Computer Vision

Research and Application of Moving Target Tracking Algorithm...

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2019 7th International Conference on Machinery,Materials and Computing Technology(ICMMCT 2019)

作者： Dong Fei Shaanxi Railway Institute

Computer vision technology has developed rapidly in the current computer world,and the processing methods for video images have also been significantly *** on the computer theory based on Marr,this paper discusses and studies the tracking of moving objects in *** the motion change of the monitored vehicle as an example,the Robert algorithm is used to track the changes of the vehicle during driving,and the multi-association template matching method is used to improve the accuracy of the *** is proved in the experiment that the algorithm in this paper has better precision in the tracking of the vehicle and can meet the current needs for tracking the moving target.

关键词： tracking algorithm image segmentation algorithm machine vision

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Experimental evaluation of segmentation algorithms for corner detection in sonar images

Experimental evaluation of segmentation algorithms for corne...

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OCEANS

作者： Pedro L. Oliveira Bruno M. Ferreira Nuno A. Cruz Faculty of Engineering University of Porto Portugal INESC TEC Porto Portugal

ISBN: (纸本)9781728114521

Corners usually appear very distinct from the rest of the scene in a mechanical scanning imaging sonar (MSIS) image, generally characterized by sharp intensities. The detection of corners is particularly useful in human-structured environments such as tanks because the knowledge on their location provides a way to compute the vehicle position. The combination of some basic operations typically used for image segmentation have great potential to detect and localize corners in sonar images automatically. This article proposes and evaluates with experimental data a set of image segmentation algorithms for corner detection in sonar scans. The developed algorithms are evaluated with ground truth, and their performance is analyzed following a few relevant metrics for autonomous navigation.

关键词： Sonar imaging Mechanical scanning imaging sonar (MSIS) Corner detection Experimental evaluation image segmentation Corner detection image segmentation sonar image segmentation algorithm corners sonar imaging autonomous navigation

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Triangle Meshes segmentation and Its Application to Region of Interest in 3D Model

Triangle Meshes Segmentation and Its Application to Region o...

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International conference on audio, language and image processing

作者： Xiao Cheng Yu Wan Longcun Jin Chenglin Shi Xiang Zou Xiaoqing Yu School of Communication and Information Engineering Shanghai University China Department of Electronic Engineering City University of Hong Kong Hong Kong

ISBN: (纸本)9781424458653

This paper applies a mesh segmentation algorithm to extract the region of interest (RoI) of a 3D model. While studied in image and video processing, RoI is a totally new research area in geometry processing. Mesh segmentation is one of the most important area in 3D geometry processing and also works as the preprocess to several other applications in computer graphics. In this paper, we are trying to utilize the mesh segmentation algorithm to realize the RoI effects in 3D Model rendering. The proposed algorithm extends the current curvature-based method and integrates the hierarchical clustering. Firstly, our algorithm extracts the geometric features of 3D models and take advantage of these geometrical hints to cluster the triangle faces by Fitting pertinent primitives. Lastly, we evaluate the centeroid of each region of 3D model that is about to be the focus point in RoI rendering which is realized by GPU-based depth of field technique.

关键词： three-dimensional displays COMPUTER GRAPHICS image segmentation algorithm region of interest Triangle algorithms Three Dimensions Medical Subject Headings Meshes

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Robot football RGB and the combination of HIS adaptive threshold method

Robot football RGB and the combination of HIS adaptive thres...

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International Conference on Computer Science and Network Technology (ICCSNT)

作者： Wanming Liu Lihua Wang Wenying Tian Professional technical institute Hebei Normal Shijiazhuang China Department of Computer Shijiazhuang Vocational Technology Institute Shijiazhuang China

ISBN: (纸本)9781467329637

This paper introduces the principle of vision subsystem design, image processing technology of the target identification, binary image are introduced, according to the original soccer robot vision subsystem existing error identification, missing target of these problems, advances some modification. Using zoning thought RGB and HIS combination of color image segmentation algorithm to identify and missing target by mistake. This paper puts forward in maintaining a basic without changing its hardware, improve its digital image processing software design solutions, and program design and commissioning.

关键词： Robot football Target identification Binary image formatting Target recognition THRESHOLDING METHOD Error identification home information system image segmentation algorithm red-green-blue colour model Program Design Software design adaptive thresholding COMMISSIONING Footballs image processing SUB-SYSTEM

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REMOTE SENSING image REPRESENTATION BASED ON HIERARCHICAL HISTOGRAM PROPAGATION

REMOTE SENSING IMAGE REPRESENTATION BASED ON HIERARCHICAL HI...

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IEEE International Geoscience and Remote Sensing Symposium

作者： Jefersson A. dos Santos Otavio A. B. Penatti Ricardo da S. Torres Philippe-H. Gosselin Sylvie Philipp-Foliguet Alexandre X. Falcao RECOD Lab - Institute of Computing University of Campinas ETIS CNRS ENSEA University of Cergy-Pontoise

ISBN: (纸本)9781479911127

Many methods have been recently proposed to deal with the large amount of data provided by high-resolution remote sensing technologies. Several of these methods rely on the use of image segmentation algorithms for delineating target objects. However, a common issue in geographic object-based applications is the definition of the appropriate data representation scale, a problem that can be addressed by exploiting multiscale segmentation. The use of multiple scales, however, raises new challenges related to the definition of effective and efficient mechanisms for extracting features. In this paper, we address the problem of extracting histogram-based features from a hierarchy of regions for multiscale classification. The strategy, called H-Propagation, exploits the existing relationships among regions in a hierarchy to iteratively propagate features along multiple scales. The proposed method speeds up the feature extraction process and yields good results when compared with global low-level extraction approaches.

关键词： Histogram propagation image representation Multiscale analysis GEOBIA image representation Multiscale analysis image segmentation algorithm remote sensing Social Hierarchy images Extraction processes

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Cardiac parameters analysis for zebrafish heart regeneration based on high frequency ultrasound imaging

Cardiac parameters analysis for zebrafish heart regeneration...

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2010 IEEE International Ultrasonics Symposium

作者： Yanyan Yu Ching-Ling Lien K. Kirk Shung Lei Sun Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong SAR China Department of Cardiothoracic Surgery Children's Hospital Los Angeles and University of Southern California Los Angeles CA USA Department of Biomedical Engineering University of Southern California Los Angeles CA USA

ISBN: (纸本)9781457703829

Zebrafish can fully regenerate their myocardium after up to 20percent ventricular resection within 2 months without evidence of scar tissues. The extraordinary regenerative abilities provide a significant model system to study the activation of the regenerative potential of human heart tissue. In order to characterize cardiac functions of zebrafish during heart regeneration, we used high-frame-rate high-frequency ultrasound system with the capabilities of 75 MHz B-mode imaging to monitor real-time cardiac parameters. Longitudinal in vivo experiments was carried out to capture echocardiographic images from individual fishes. A pilot study on 6 fish over 30 days post amputation (dpa) was performed using this technique. A total of over 400 videos were captured. To process the large video data, an automatic image segmentation algorithm was developed. By using information obtained from temporal decorrelation of the B-mode image sequence, the epicardium is determined in a region-based level set framework combined with shape priors and Kalman filtering. Afterwards, the size of the heart was estimated frame by frame using the outlined epicardium to obtain its dynamic variation. Subsequently, the maximum and minimum of the heart size was used to calculate ejection fraction (EF). The time course of the mean EF (n(velence)6) with a "V" shape indicates the strong ability of zebrafish to recovery cardiac functions along its morphological regeneration.

关键词： high frequency ultrasound zebrafish heart regeneration automatic segmentation ejection fraction Zebrafish Heart cardiac functions heart morphology Pericardium Visceral Pericardium image segmentation algorithm heart tissues Pilot Studies video data Cicatrix Ultrasonography Regeneration

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Segment an image by Looking into an image Corpus

Segment an Image by Looking into an Image Corpus

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IEEE Conference on Computer Vision and Pattern Recognition

作者： Xiaobai Liu Jiashi Feng Shuicheng Yan Liang Lin Hai Jin Huazhong University of Science and Technology National University of Singapore Sun Yat-Sen University

ISBN: (纸本)9781457703942

This paper investigates how to segment an image into semantic regions by harnessing an unlabeled image corpus. First, the image segmentation task is recast as a small-size patch grouping problem. Then, we discover two novel patch-pair priors, namely the first-order patch-pair density prior and the second-order patch-pair co-occurrence prior, founded on two statistical observations from the natural image corpus. The underlying rationalities are: 1) a patch-pair falling within the same object region generally has higher density than a patch-pair falling on different objects, and 2) two patch-pairs with high co-occurrence frequency are likely to bear similar semantic consistence confidences (SCCs), i.e. the confidence of the consisted two patches belonging to the same semantic concept. These two discriminative priors are further integrated into a unified objective function in order to augment the intrinsic patch-pair similarities, originally calculated using patch-level visual features, into the semantic consistence confidences. Nonnegative constraint is also imposed over the output variables and an efficient iterative procedure is provided to seek the optimal solution. The ultimate patch grouping is conducted by first building a similarity graph, which takes the atomic patches as vertices and the augmented patch-pair SCCs as edge weights, and then employing the popular Normalized Cut approach to group patches into semantic clusters. Extensive image segmentation experiments on two public databases clearly demonstrate the superiority of the proposed approach over various state-of-the-arts unsupervised image segmentation algorithms.

关键词： images image imagery (Psychotherapy) image segmentation Semantics image segmentation algorithm Two patches Iterative Process output variable Objective function

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TRACKING ARTICULATED HUMAN MOVEMENTS WITH A COMPONENT BASED APPROACH TO BOOSTED MULTIPLE INSTANCE LEARNING

TRACKING ARTICULATED HUMAN MOVEMENTS WITH A COMPONENT BASED ...

引用

IEEE International Conference on image Processing

作者： Kyuseo Han Johnny Park Avinash C. Kak School of Electrical and Computer Engineering Purdue University

ISBN: (纸本)9781479923427

Our work is about a new class of object trackers that are based on a boosted Multiple Instance Learning (MIL) algorithm to track an object in a video sequence. We show how the scope of such trackers can be expanded to the tracking of articulated movements by humans that frequently result in large frame-to-frame variations in the appearance of what needs to be tracked. To deal with the problems caused by such variations, our paper presents a component based version of the boosted MIL algorithm. Components are the output of an image segmentation algorithm applied to the pixels in the bounding box encapsulating the object to be tracked. The components give the boosted MIL the additional degrees of freedom that it needs in order to deal with the large frame-to-frame variations associated with articulated movements.

关键词： Articulated human tracking Multiple instance learning Online boosting ARTICULATED image segmentation algorithm Degree of freedom tracking bounding boxes pixel New classes Learning

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Active human visual segmentation in polar space by using segmentation by weighted aggregation method

Active human visual segmentation in polar space by using seg...

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IET Chennai Fourth International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2013)

作者： S. Pavithra A. Rengarajan St. Peter's University Chennai Veltech Multitech Engineering College Chennai

ISBN: (纸本)9781510804524

This paper presents a new idea in image segmentation algorithm driven by human visual system segmentation techniques and has been widely studied in the visual attention. The human eyes fixate at important locations in the scene, and every fixation point lies inside a particular region of arbitrary shape and size. we propose a method to segment the object of interest by finding the optimal closed contour around the fixation point in the polar space, The human visual system has two types of attention: overt attention (eye movements) and covert attention (without eye movement). For evaluating the segmentation result, from both region-based and boundary-based perspectives, are integrated into an objective function .Our approach can be complemented in a variety of ways, An interesting avenue has to do with learning models of the world. For example, if we had a model of a “squirrel,” we could segment the “squirrel,” more correctly in the region.

关键词： Object segmentation Polar space image segmentation Human visual system Visual attention SWA Visual Attention Object segmentation ITSN2 gene Visual System Eye Movements image segmentation algorithm Visualization Squirrels

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