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IEEE International Conference on Systems, Man and Cybernetics

作者： Huaiying Xia Rukun Hu Bingxin Xu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

In classification of multi-source remote sensing image, it is usually difficult to obtain higher classification accuracy. In the previous work, the modeling technique for the remote sensing image classification based on the minimum description length (MDL) principle with mixture model is analyzed theoretically. In this work, experimental studies are performed for investigating the modeling technique. With intensive experiments and sophisticated analysis, it is found that the developed modeling technique can build a robust classification system, which can avoid classifier over-fitting training data and make the learning process trade-off between bias and variance. Meanwhile, designed mixture model is more efficient to represent real multi-source remote sensing images compared to single model.

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Graph-Based Text Segmentation Using a Selected Channel image

Graph-Based Text Segmentation Using a Selected Channel Image

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Proceedings of the Digital image Computing: Technqiues and Applications (DICTA)

作者： Chao Zeng Wenjing Jia Xiangjian He Jie Yang INEXT FEIT University of Technology Sydney Australia Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

This paper proposes a graph-based method for segmentation of a text image using a selected colour-channel image. The text colour information usually presents a two polarity trend. According to the observation that the histogram distributions of the respective colour channel images are usually different from each other, we select the colour channel image with the histogram having the biggest distance between the two main peaks, which represents the main foreground colour strength and background colour strength respectively. The peak distance is estimated by the mean-shift procedure performed on each individual channel image. Then, a graph model is constructed on a selected channel image to segment the text image into foreground and background. The proposed method is tested on a public database, and its effectiveness is demonstrated by the experimental results.

关键词： Pixel image color analysis image segmentation Histograms Lighting Text recognition Kernel

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Contour extraction of gait recognition

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Procedia Engineering 2010年 7卷 275-279页

作者： Fan Zhang Rui Li Shuai Liu College of Computer and Information Engineering Henan University Kaifeng 475001 China Institute of Image Processing and Pattern Recognition Henan University Kaifeng 475001 China

Gait recognition is a new biometric identification technology. Its aim is to recognize people and detect physiological, pathological and mental characters by their walk style. The feature extraction of gait is the key step in gait recognition. This paper combines the background subtraction method with symmetric differential method to segment the motion human image, and then extracts the contour of motion human with improved GVF (gradient vector flow) Snake model. The experimental results show that the proposed method can extract contour features effectively for the gait recognition.

关键词： GVF snake models Gait recognition Motion segmentation Contour extraction

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The method of image restoration in the environments of dust

The method of image restoration in the environments of dust

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International Conference on Mechatronics and Automation

作者： Wang, Yuanyu Li, Yuanzong Zhang, Tianxu Department of Computer Fundamental Education TaiYuan University of Technology TaiYuan CO 030024 China College of Mechanical Engineering TaiYuan University of Technology TaiYuan CO 030024 China Institute for Pattern Recognition and A.I. State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology WuHan CO 430074 China

ISBN: (纸本)9781424451418

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, a particle swarm optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with dual threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments. © 2010 IEEE.

关键词： Dust

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Design of distributed warehouse management system based on ***

Design of distributed warehouse management system based on *...

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Pacific-Asia Conference on Circuits, Communications and Systems, PACCS

作者： Fan Zhang Yanbin Cui Institute of Image Processing and Pattern Recognition Henan University Kaifeng China College of Computer and Information Engineering Henan University Kaifeng China

ISBN: (纸本)9781424479689

A distributed warehouse management system is design based on the *** framework. Unlike many frameworks which focus on the database data operation or construct flexible user interface, the proposed project mainly focus on the business logic. According to the ***, the system can easily construct object-oriented business logic layers. This system can be easily configured N layers logical structure running on one to four physical layers. System environment expanded from the traditional local area network to wide area networks, and can meet the requirements of distributed applications. The system uses contact less deployment technology in the distributed environment and can be remotely updated automatically.

关键词： Logistics Security Workstations

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Tensor error correction for corrupted values in visual data

Tensor error correction for corrupted values in visual data

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IEEE International Conference on image processing

作者： Yin Li Yue Zhou Junchi Yan Jie Yang Xiangjian He Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University China Faculty of Engineering and Information Technology Sydney University of Technology Australia

The multi-channel image or the video clip has the natural form of tensor. The values of the tensor can be corrupted due to noise in the acquisition process. We consider the problem of recovering a tensor L of visual data from its corrupted observations X = L + S, where the corrupted entries S are unknown and unbounded, but are assumed to be sparse. Our work is built on the recent studies about the recovery of corrupted low-rank matrix via trace norm minimization. We extend the matrix case to the tensor case by the definition of tensor trace norm in. Furthermore, the problem of tensor is formulated as a convex optimization, which is much harder than its matrix form. Thus, we develop a high quality algorithm to efficiently solve the problem. Our experiments show potential applications of our method and indicate a robust and reliable solution.

关键词： Tensile stress Sparse matrices Nickel Matrix decomposition Optimization Visualization Minimization

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An image-sequence compressing algorithm based on homography transformation for unmanned aerial vehicle

An image-sequence compressing algorithm based on homography ...

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International Symposium on Intelligence Information processing and Trusted Computing

作者： Gong, Junbin Zheng, Chenlin Tian, Jinwen Wu, Dingxue Institute for Pattern Recognition and Artificial Intelligence National Key Laboratory of Science and Technology on Multi-spectral Information Processing Huazhong University of Science and Technology Wuhan 430074 China College of Computer Science and Technology Huanggang Normal University Huanggang 438000 China

ISBN: (纸本)9780769541969

Focus on the image compressing problem of unmanned aerial vehicle with high compression ratio, fixed compressing ratio and low computational complexity requirement, a low-complexity image-sequence compressing algorithm based on homography transformation was proposed. The image sequences were dynamically divided into framegroups according the data from airborne inertial navigation systems, and the intermediate frames in the same frame-group was bi-directionally predicted by the first-frame and the end-frame with homography transformation. The homography matrix was got approximately by the airborne inertial navigation systems firstly and then was accurately computed by fast multiple sub-areas template matching. At the end the first frame and the residual images of the intermediate frames of the same frame-group was merged into a big image and coded by JPEG2000 to generate fixed-size code streams. The experiment results show that the proposed algorithm was with high compression performance, low computational complexity and excellent capacity for code-size control and will has good prospect in engineer. © 2010 IEEE.

关键词： image compression

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Design and implementation of knowledge base for target recognition in remote sensing images

Design and implementation of knowledge base for target recog...

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2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

作者： Chen, Shaobin Cai, Chao Li, Erlang Ding, Mingyue Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology State Key Laboratory for Multi-spectral Information Processing Technologies Wuhan 430074 China School of Life Science and Technology of Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424459346

In this paper, the knowledge modeling, architecture design and detailed implementation of an ontology-based knowledge base for target recognition in remote sensing images is presented. Knowledge base is a critical component of a large ground target recognition system which is a hybrid system that combines knowledge base with remote sensing image processing module. The knowledge base provides necessary knowledge for remote sensing image processing module, and remote sensing image processing module can perform multiple tasks with the support of the knowledge base. The existence of the knowledge base makes the whole recognition system more flexible and more generic than those systems without knowledge base. The effectiveness of the presented knowledge base shows the good prospect of the application of knowledge base in remote sensing image processing domain. ©2010 IEEE.

关键词： Knowledge based systems

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Istree Digital Watermarking Algorithm Based on Contourlet Transform

Istree Digital Watermarking Algorithm Based on Contourlet Tr...

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International Conference on Machine Vision and Human-Machine Interface (MVHI)

作者： Fan Zhang Yuli Xu Rui Li Institute of Image Processing and Pattern Recognition Henan University Kaifeng China College of Computer and Information Engineering Henan University Kaifeng China

In order to protect the copyright of the image, in this paper proposed a novel important sub-tree (Istree) digital watermarking algorithm based on contourlet transform. First, Shuffling is applied by watermarking image for increasing robustness. Second, the original image are decomposed three levels by contourlet transform, and then analysis sub-bands in all directions, according to various levels sub-bands in all direction structure like tree. And find important sub-tree, then Scrambling after the watermark image sequence is embedded in important sub-tree. The experimental results show that the algorithm has a certain degree of robustness and can resistance attack.

关键词： Watermarking Discrete wavelet transforms Discrete transforms Wavelet transforms Discrete Fourier transforms Fourier transforms Robustness Wavelet domain image processing image analysis

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Motion blur detection based on lowest directional high-frequency energy

Motion blur detection based on lowest directional high-frequ...

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IEEE International Conference on image processing

作者： Xiaogang Chen Jie Yang Qiang Wu Jiajia Zhao Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University China Centre of Innovation in IT Services and Applications Sydney University of Technology Sydney Australia

Motion blur detection and the relevant blurring parameter estimation are important for many computer vision tasks. The contribution of this paper is in two folds. First, we propose a closed-form solution for motion direction estimation on blurred image. Secondly, a novel method is proposed for motion blurred region detection. The proposed direction estimation is based on measurement of lowest directional high-frequency energy. Compared with traditional methods, it will improve accuracy with less computational cost. Moreover, the proposed motion blurred region detection can efficiently estimate blurred regions without Point Spread Function estimation. Encouraging results are shown by experiments.

关键词： Estimation Pixel image segmentation image restoration Transforms Deconvolution Closed-form solution

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