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2012 International Conference on Mechatronic Systems and Automation Systems, MSAS 2012

作者： Wang, Gaihua Li, Dehua Zhao, Tongzhou Institute for pattern recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China The College of Physics and Information Science of Xinjiang Normal University Urumqi 830053 China Hubei Province Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan 430073 China

ISBN: (纸本)9783037854921

New impulse detection and filtering algorithm is proposed in color images. Based on fast peer group filter, the proposed filtering algorithm uses different iteration times to complete filter according to different impulse noise density. The extensive experimental results show that the proposed scheme provides better performance than many of the existing vector filters. Meanwhile, the proposed approach is simple and practical for real-time application. © (2012) Trans Tech Publications, Switzerland.

关键词： Impulse noise

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The first nontrivial three color upper domination Ramsey number is 13

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Journal of Combinatorial Mathematics and Combinatorial Computing 2012年 83卷 161-165页

作者： Su, Changming Lang, Fangnian Shao, Zehui School of Information Science and Technology Chengdu University Chengdu 610106 China University Key Laboratory of Pattern Recognition and Intelligent Information Processing Sichuan Province China School of Electronic Engineering University of Electronic Science and Technology of China Chengdu 610054 China

The upper domination Ramsey number u(3, 3, 3) is the smallest integer n such that every 3-coloring of the edges of complete graph Kn contains a monochromatic graph G with T(G) ≥ 3, where T(G) is the maximum order over all the minimal dominating sets of the complement of G. In this note, with the help of computers, we determine that U(3, 3, 3) = 13, which improves the results that 13 ≤ U(3, 3, 3) ≤ 14 provided by Michael A. Henning and Ortrud R. Oellermann.

关键词： Graph theory

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Computation of the folkman number Fv(3,5;6)

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Journal of Combinatorial Mathematics and Combinatorial Computing 2012年 81卷 11-17页

作者： Shao, Zehui Liang, Meilian Pan, Linqiang Xu, Xiaodong School of Information Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing China School of Mathematics and Information Science Guangxi University Nanning 530004 China Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China Guangxi Academy of Sciences Nanning Guangxi 530007 China

We prove that Fv(3,5;6) = 16, which solves the smallest open case of vertex Folkman numbers of the form Fv(3,k;k + 1). The proof uses computer algorithms.

关键词： Mathematical techniques

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Target recognition method based on template matching in downward-looking infrared image

Target recognition method based on template matching in down...

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2012 3rd IEEE/IET International Conference on Audio, Language and Image processing, ICALIP 2012

作者： Zhu, Hu Deng, Lizhen Zhou, Gang Bai, Xiaodong Wang, Gaihua National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China College of Electrical and Electronic Engineering Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China

ISBN: (纸本)9781467301718

Automatic ground target recognition technology in downward-looking infrared imagery is challenging problems due to the complexity of real-world. A robust ground target recognition method is proposed for downward-looking infrared (DLIR) image sequences in this paper. A complete model of the proposed method is designed firstly and the principles of some key technologies are introduced as following. Perspective transformation is used to solve the projective problems of landmark translation, rotation and scale variance in real-time image sequence. The size of landmark is estimated real-timely by using flight parameters and imaging parameters for getting the model with an appropriate scale. Based on the matching results of landmark and flight parameters, target position technology is proposed to identify the position of target by using the position relation between landmark and target. Experimental results using real-world image data with complicated background showed that the proposed method not only causes high precisely locating results, but also has good robustness for target occlusion. © 2012 IEEE.

关键词： Template matching

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Fast ground target detection method in infrared image sequences

Fast ground target detection method in infrared image sequen...

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2012 3rd IEEE/IET International Conference on Audio, Language and Image processing, ICALIP 2012

作者： Zhu, Hu Deng, Lizhen Wang, Gaihua Zhou, Gang Bai, Xiaodong National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China College of Electrical and Electronic Engineering Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China

ISBN: (纸本)9781467301718

Automatic target detection (ATD) in infrared (IR) imagery is a fundamental and challenging task in computer vision. A fast automatic target detection method in IR image sequence is proposed in this paper. Since the position and scale of target change real-timely, we can predict the target position in real-time image by using the history position of target and flight parameters information of previous and current frames, and then estimate the scale of target depending on flight parameters and imaging parameters for getting the model with the appropriate scale. In order to make the template matching more robust for target rotation, the template matching method based on parametric template vector is used to recognize the position of target. The detection result is identified by using multiframe integration based on recognition information of history and currant frames. Some experimental results using real-world images with complicated background validate the effectiveness and robustness of the proposed method under rotation and scale variance condition. © 2012 IEEE.

关键词： Template matching

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Integrating Segmentation and Classification Accuracy for Accuracy Assessment in Object-based Image Analysis

Integrating Segmentation and Classification Accuracy for Acc...

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International Conference on Audio, Language and Image processing

作者： Nan Li Hong Huo Tao Fang Institute of Image Processing and Pattern Recognition Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education Institute of Image Processing and PatternRecognition Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education

ISBN: (纸本)9781467301732

An accuracy assessment method that integrates segmentation and classification accuracy is proposed to meet the requirements of object-based image analysis. Segmentation errors are measured by establishing the relationship between pixels and their corresponding segments according to the overlaps of segments and reference polygons. Then, two improved confusion matrices that take the segmentation errors into consideration are used: one for pixel-level classification results, and the other for object-level classification results. A final accuracy assessment combines the statistics of these two confusion matrices. The proposed method can be applied to segmentation scale selection in the hierarchical interpretation system. An experiment on a SPOT5 image demonstrates the effectiveness of this method for segmentation scale selection, which can guide the fusion of objects of different scales to obtain a higher accuracy.

关键词： segmentation image analysis Segmentation object orientation confusion matrix pixel

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One-Class SVM assisted accurate tracking

One-Class SVM assisted accurate tracking

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ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC

作者： Keren Fu Chen Gong Yu Qiao Jie Yang Irene Guy Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai China Chalmers tekniska hogskola Goteborg SE

Recently, tracking is regarded as a binary classification problem by discriminative tracking methods. However, such binary classification may not fully handle the outliers, which may cause drifting. In this paper, we argue that tracking may be regarded as one-class problem, which avoids gathering limited negative samples for background description. Inspired by the fact the positive feature space generated by One-Class SVM is bounded by a closed sphere, we propose a novel tracking method utilizing One-Class SVMs that adopt HOG and 2bit-BP as features, called One-Class SVM Tracker (OCST). Simultaneously an efficient initialization and online updating scheme is also proposed. Extensive experimental results prove that OCST outperforms some state-of-the-art discriminative tracking methods on providing accurate tracking and alleviating serious drifting.

关键词： Target tracking Support vector machines Training Feature extraction Face Boosting Semisupervised learning

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Lower bounds on some van der waerden numbers based on quadratic residues

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Journal of Combinatorial Mathematics and Combinatorial Computing 2012年 83卷 23-31页

作者： Liang, Meilian Xu, Xiaodong Shao, Zehui Xiu, Baoxin School of Mathematics and Information Science Guangxi University Nanning 530004 China Guangxi Academy of Sciences Nanning 530007 China Key Laboratory of Pattern Recognition and Intelligent Information Processing School of Information Science and Technology Chengdu University Chengdu 610106 China College of Information System and Management National University of Defense Technology Changsha 410073 China

The van der Waerden number W(r, k) is the least integer N such that every r-coloring of {1,2, • • •, N} contains a monochromatic arithmetic progression of length at least k. Rabung gave a method to obtain lower bounds on W(2,k) based on quadratic residues, and performed computations on all primes no greater than 20117. By improving the efficiency of the algorithm of Rabung, we perform the computation for all primes up to 6 x 107, and obtain lower bounds on W(2, k) for k between 11 and 23.

关键词： Computational efficiency

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Ship detection in polarimetric SAR based on support vector machine

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Research Journal of Applied Sciences, Engineering and Technology 2012年第16期4卷 2844-2850页

作者： Su, Xuwu Yang, Guangyou Sang, Hongshi State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China School of Mechanical Engineering Hubei University of Science and Technology Wuhan 430068 China

A Support Vector Machine (SVM) based method for ship detection in Polarimetric SAR (POLSAR) is proposed in this study. Because of similarities of ship and man-made structures on land in scattering mechanisms, land and sea are first segmented by SVM according to polarimetric features and texture features;The SVM-based Recursive Feature Elimination (RFE-SVM) approach is adopted to improve the performance of the segmentation algorithm. Then ship targets are extracted from sea by SVM classifier;Threshold-based rules and SVM-based rules are established for discriminating ship from non-ship target at last. The experiments are carried out on POLSAR data from Radarsat-2. For the available SAR images, the average accuracy of ship detection is over 95%. © Maxwell Scientific Organization, 2012.

关键词： Support vector machines

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Fast Ground Target Detection Method in Infrared Image Sequences

Fast Ground Target Detection Method in Infrared Image Sequen...

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International Conference on Audio, Language and Image processing

作者： Hu Zhu Lizhen Deng Gaihua Wang Gang Zhou Xiaodong Bai National Key Laboratory of Science and Technology on Multi-spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology College of Electrical & Electronic Engineering Huazhong University of Science and Technology

ISBN: (纸本)9781467301732

Automatic target detection (ATD) in infrared (IR) imagery is a fundamental and challenging task in computer vision. A fast automatic target detection method in IR image sequence is proposed in this paper. Since the position and scale of target change real-timely, we can predict the target position in real-time image by using the history position of target and flight parameters information of previous and current frames, and then estimate the scale of target depending on flight parameters and imaging parameters for getting the model with the appropriate scale. In order to make the template matching more robust for target rotation, the template matching method based on parametric template vector is used to recognize the position of target. The detection result is identified by using multi-frame integration based on recognition information of history and currant frames. Some experimental results using real-world images with complicated background validate the effectiveness and robustness of the proposed method under rotation and scale variance condition.

关键词： Infrared imaging images Targets flight parameter computer vision real image fast ground infrared imagery automatic target currant Object detection TEMPLATE MATCHING Scale formation

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