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检索条件"任意字段=MIPPR 2011: Pattern Recognition and Computer Vision"

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mippr 2009 - Automatic Target recognition and Image Analysis

MIPPR 2009 - Automatic Target Recognition and Image Analysis

引用

mippr 2009 - Automatic Target recognition and Image Analysis: 6th International Symposium on Multispectral Image Processing and pattern recognition

ISBN: (纸本)9780819478061

The proceedings contain 186 papers. The topics discussed include: removing shift-variant motion blur from an image using Poisson interpolation;online real AdaBoost with co-training for object tracking;object detection based on multiscale discrete points sampling and grouping;real-time detection of removed objects based on multi-cue fusion;tabletop interaction system using plate position recognition by computer vision;transfer network learning based remote sensing target recognition;optimum selection of common master image for multitemporal InSAR;real-time object detection based on the improved boosted features;an automated detection method of permanent scatterers in radar interferometry based on ICA;the small infrared target detection in complicated background based on adaptive morphological filter;a fuzzy-logic-based context model for multiscale segmentation fusion;and recognition of sand dredges in the Changjiang River based on ASAR remote sensing data.

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Fruit shape detection by optimizing Chan-Vese model

Fruit shape detection by optimizing Chan-Vese model

引用

mippr 2009 - Automatic Target recognition and Image Analysis: 6th International Symposium on Multispectral Image Processing and pattern recognition

作者： Shou, Zhouxiang Wang, Qihui Gui, Jiangsheng Wang, Yuhuai Hangzhou Normal University Hangzhou 310012 China Dept. of Information and Electronic Zhejiang Sci.-Tech. University Hangzhou 310018 China

ISBN: (纸本)9780819478061

Applications of machine vision for automated inspection and sorting of fruits have been widely studied by scientists and engineers. In these applications, edge detection, segmentation, and shape recovery are difficult problem. Previous studies have usually adopted some preprocessing such as noise removal and motion deblurring before using a threshold method to detect shape boundary. In many cases, however, this manner is troubled and not unified and does not work well. This research proposes a novel approach for fruit shape detection in RGB spaces based on a fast level set method and the Chan-Vese model. We called it optimizing Chan-Vese model (OCV). This new algorithm is fast because it needs no re-initialization procedure and thus is suitable for fruit sorting. OCV has three advantages compared to traditional methods. First, it provides a unified framework for detection fruit shape boundary, requiring no preprocessing and even if the raw image is noisy or blurred. Second, it can detect boundaries for images of fruit with multi-colored edges, which traditional methods fail to deal with. Third, it is processed directly in colour space without any transformations that can lose much information. The proposed method has been applied to fruit shape detection with promising results. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： computer vision

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X-ray image denoising with directional support value transform

X-ray image denoising with directional support value transfo...

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mippr 2009 - Medical Imaging, Parallel Processing of Images, and Optimization Techniques: 6th International Symposium on Multispectral Image Processing and pattern recognition

作者： Zheng, Sheng Hendriks, Emile A. Lei, Bangjun Hao, Wei Institute of Intelligent Vision and Image Information China Three Gorges University Yichang 443002 China Information and Communication Theory Group Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology 2628CD Delft Netherlands

ISBN: (纸本)9780819478085

Under the support vector machine framework, the support value analysis-based image fusion has been studied, where the salient features of the original images are represented by their support values. The support value transform (SVT)-based image fusion approach have demonstrated some advantages over the existing methods in multisource image fusion. In this paper, the directional support value transform (DSVT) is applied to the denoising of some standard images embedded in white noise and the X-ray images. This directional transform is not norm-preserving and, therefore, the variance of the noisy support values will depend on the scales. And then we use the hard-thresholding rule for estimating the unknown support values in different scales and the thresholding is scale-dependent. The peak signal noise ratio (PSNR) is used as an "objective" measure of performance, and our own visual capabilities are used to identify artifacts whose effects may not be well-quantified by the PSNR value. The experimental results demonstrate that simple thresholding of the support values in the proposed method is very competitive with techniques based on wavelets, including thresholding of decimated or undecimated wavelet transforms. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Image fusion

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Proceedings of SPIE - mippr 2007: pattern recognition and computer vision

Proceedings of SPIE - MIPPR 2007: Pattern Recognition and Co...

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mippr 2007: pattern recognition and computer vision

ISBN: (纸本)9780819469526

The proceedings contain 101 papers. The topics discussed include: rotation invariant texture classification based on Gabor wavelets;group clustering and its visualization in group support systems;scene classification using low-level feature and intermediate feature;new method of 3D point reconstruction from monocular camera;probability output modeling for support vector machines;binocular stereo vision system design for lunar rover;shape classification using hidden Markov model and structural feature;research on target recognition techniques of radar networking based on fuzzy mathematics;novel cross correlation method for redshift determination of galaxy spectra;research on the city's water affairs dispatchment system based on rough sets theory;texture classification of aerial image based on Bayesian networks;and recognizing license plate character based on simplified PCNN.

关键词： computer vision

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Audio-visual gender recognition

Audio-visual gender recognition

引用

Conference on pattern recognition and computer vision

作者： Liu, Ming Xu, Xun Huang, Thomas S. Univ Illinois Beckman Inst Image Format Grp Urbana IL 61801 USA

ISBN: (纸本)9780819469526

Combining different modalities for pattern recognition task is a very promising field. Basically, human always fuse information from different modalities to recognize object and perform inference, etc. Audio-Visual gender recognition is one of the most common task in human social communication. Human can identify the gender by facial appearance, by speech and also by body gait. Indeed, human gender recognition is a multi-modal data acquisition and processing procedure. However, computational multimodal gender recognition has not been extensively investigated in the literature. In this paper, speech and facial image are fused to perform a mutli-modal gender recognition for exploring the improvement of combining different modalities.

关键词： Visualization Acoustics Binary data Databases pattern recognition Neural networks computer vision technology Data acquisition Gait analysis Machine vision

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Face recognition under variable lighting using local qualitative representations

Face recognition under variable lighting using local qualita...

引用

mippr 2007: pattern recognition and computer vision

作者： Zhang, Yi Chu, Ying Mou, Xingang Zhang, Guilin State Education Commission Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819469526

In this paper, a face recognition method using local qualitative representations is proposed to solve the problem of face recognition in varying lighting. Based on the observation that the ordinal relationship between the average brightness of image regions pair is invariant under lighting changes, Local Binary Mapping is defined as an illumination invariant for face recognition based on Local Binary pattern descriptor, which extracts the local variance features of an image. For the 'symbol' feature vector, hamming distance is used as similarity measurement. It has been proved that the proposed method can provide the accuracy of 100 percent for subset 2, 3, 4 and 98.89 percent for subset 5 of the Yale facial database B when all images in subset 1 are used as gallery.

关键词： Face recognition

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Group clustering and its visualization in group support systems

Group clustering and its visualization in group support syst...

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mippr 2007: pattern recognition and computer vision

作者： Caiquan, Xiong Dehua, Li Lianghai, Jin Xianbin, Sun Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China School of Computer Science Hubei University of Technology Wuhan 430068 China

ISBN: (纸本)9780819469526

Consensus building in group support systems relies on the mutual-question and mutual-elicitation of experts, so a feedback mechanism is required to conduct experts to converge their thinking by visualizing the individual opinion and the consistent state of the group. This paper proposes a new feedback mechanism, which first clusters the experts' preferences into a set of subgroups, and then uses different line-types or line-colors to display the clustered opinions in parallel coordinate. By using this mechanism, the group consistency is analyzed and the group discussion is conducted efficiently. One of the characteristics of the proposed method is that it can protect the minority views automatically. An example is presented to illustrate the application of the method.

关键词： Cluster analysis

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Classification of lunar soil from reflectance spectrum by PCA and SVM

Classification of lunar soil from reflectance spectrum by PC...

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Conference on pattern recognition and computer vision

作者： Zhang, Xiaoyu Huang, Maohai Chu, Jun Li, Chunlai Chinese Acad Sci Applicat Ctr Lunar & Deep Space Explorat Natl Astron Observ Beijing 100012 Peoples R China

ISBN: (纸本)9780819469526

Scientists on the ground need understand the environment around the unmanned lunar rover in lunar exploration through analyzing data obtained by various payloads. There are two main material on the moon, high land material and mare material on the moon. We use reflectance spectrums of lunar soils from Apollo mission measured by LSCC to classify the two kinds of materials. Principal component analysis is applied to reduce and select the feature of the reflectance spectrums. These features input support vector machine, which base on statistical learning theory and is used widely to classify in modem pattern recognition. Our work shows that the reflectance spectrums of lunar soils are strong link with the material which they represent.

关键词： lunar exploration lunar soils reflectance spectrum pattern recognition PCA SVM

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Object matching using weight hausdorff distance matrix combined with genetic algorithm

Object matching using weight hausdorff distance matrix combi...

引用

Conference on pattern recognition and computer vision

作者： Yu, Qiuze Yang, Bing Liu, Jian Tian, Jinwen Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intelligence Key Lab Multispectral Informat Technol Wuhan 430074 Peoples R China

ISBN: (纸本)9780819469526

A new similarity measure based on Hausdorff Distance Matrix Frobenius Norm for object matching is proposed in this paper. This measure is more reliable and can achieve higher location accuracy compared with other measures based on classic and modified Hausdorff Distance under the condition of high level noise and high ratio occlusion of template. The search strategy based on genetic algorithms is employed to make algorithm faster. Experimental results under noise of different level demonstrate high performance of the matching algorithm.

关键词： object matching weight hausdorff distance matrix genetic algorithms (GA)

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Binocular stereo vision system design for lunar rover

Binocular stereo vision system design for lunar rover

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Conference on pattern recognition and computer vision

作者： Chu, Jun Jiao, Chunlin Guo, Hang Zhang, Xiaoyu Nanchang Univ Aeronaut Dept Aeronaut & Mech Engn Nanchang 330034 Jiangxi Peoples R China Chinese Acad Sci Lumar & Deep Space Explorat Ctr Natl Observ Beijing 100110 Peoples R China Northwestern Polytech Univ Instb Mech & Elect Engn Xian 710072 Peoples R China Nanchang Univ Beijing Acad Nanchang Univ Beijing 100101 Peoples R China

ISBN: (纸本)9780819469526

In this paper. we integrate a pair of CCD cameras and a digital pan/title of two degrees of freedom into a binocular stereo vision system, which simulates the panoramic cameras system of the lunar rover. The constraints for placement and parameters choice of the stereo cameras pair are proposed based on science objective of Chang'e-Ilmission. And then these constraints are applied to our binocular stereo vision system and analyzed the location precise of it. Simulation and experimental result confirm the constraints proposed and the analysis of the location precise.

关键词： stereo vision parameters choice location error analysis science objection

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