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International Conference on Modelling, Identification and control (ICMIC)

作者： Songtao Chang Mao Su Da Zhang Yongji Wang Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

It is difficult to guide the entry vehicle to prescribed area due to the disperse of environment and kinematics. Through predicted residual range at the current state based on drag acceleration, we developed a predictor-corrector guidance law which doesn't need iteration to figure out the reference trajectory. Then using extended state observer based controller to track the reference trajectory. We use several missions(under various disperse conditions) to test the guidance law. Simulation results demonstrated that the guidance law is able to achieve the prescribed terminal conditions under various perturbations in the aerodynamic coefficients, the density of the atmosphere and the mass of the vehicle.

关键词： Acceleration Trajectory Vehicles Observers Vehicle dynamics Planning Earth

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An application of circumscribed circle filter in the multi-stencils fast marching method 12

An application of circumscribed circle filter in the multi-s...

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27th Annual ACM Symposium on Applied Computing, SAC 2012

作者： Liu, Hong Hung, Chih-Cheng Hu, Huaifei Yu, Mali Song, Enmin School of Computer Science Huazhong University of Science and Technology Wuhan China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Wuhan Hubei 430074 China School of Computing and Software Engineering Southern Polytechnic State University Marietta GA 30060 United States

ISBN: (纸本)9781450308571

We develop an effective method for improving the segmentation result based on the Multi-Stencils Fast Marching method (MSFM). In MSFM, the gradient information of the image plays a vital role for calculating edges. It is straightforward to obtain the edge of good quality images;however, MSFM may not have robust edge maps available for images with spurious edges. Thus, a special multi-direction circumscribed circle filter is proposed to calculate the image gradient information which is then used in the MSFM. Using the new gradient information, better image contours can be obtained with MSFM. The size of the radius used in our circle filter is constant even the standard deviation of zero-mean Gaussian noise changes while the parameters of mean filter and Canny filter for gradient computation have to be correctly selected according to different noisy images. Our proposed method shows that it is effective through the experiments of image segmentation. © 2012 ACM.

关键词： image segmentation

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Textural fabric defect detection using adaptive quantized Gray-level Co-occurrence Matrix and Support Vector Description Data

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Information Technology Journal 2012年第6期11卷 673-685页

作者： Bi, Mingde Sun, Zhigang Li, Yesong Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology 1037 Luoyu Road Hubei 430074 Wuhan China

A new defect detection algorithm base on Support Vector Data Description (SVDD) is proposed. A fabric texture model is built on the gray-level histogram of textural fabric image. Two Gray-level Co-occurrence Matrix (GLCM) features are used to characterize the fabric texture. And an adaptive quantization scheme base on the texture mode is proposed to reduce the size of GLCM and reduce the computational complexity of feature extraction. Besides, twonew features are proposed to characterize the continuous property of the fabric defects. The SVDD classifier is used as a detector for defect detection. Experimental results of real fabric defects are provided to validate the effectiveness and robustness of the proposed detection algorithm. And a prototyped detection system is built to evaluate the real-time performance of the detection algorithm. © 2012 Asian Network for Scientific Information.

关键词： Data description

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Adaptive flocking of multi-agent systems with locally Lipschitz nonlinearity

Adaptive flocking of multi-agent systems with locally Lipsch...

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31st Chinese control Conference, CCC 2012

作者： Ningzi, Zhang Housheng, Su Chen, Michael Z. Q. Xiaofan, Wang Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China Department of Mechanical Engineering University of Hong Kong Hong Kong Hong Kong Department of Automation Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9789881563811

This paper investigates adaptive flocking of multi-agent systems (MASs) with a virtual leader. All agents and the virtual leader share the same intrinsic nonlinear dynamics, which satisfies a locally Lipschitz condition and depends on both position and velocity information of the agent itself. Under the assumption that the initial network is connected, an approach to preserving the connectivity of the network is proposed. Based on the Lyapunov stability theory, an adaptive flocking control law is derived to make the MASs track the virtual leader without collision. Finally, a numerical example is presented to illustrate the effectiveness of the theoretical results. © 2012 Chinese Assoc of Automati.

关键词： Multi agent systems

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Person re-identification across multi-camera system based on local descriptors

Person re-identification across multi-camera system based on...

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ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC

作者： Qiao Huang Jie Yang Yu Qiao Institute of Image Processing and Pattern Recognition and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai China

Tracking the same person across multiple cameras is an important task in multi-camera systems. It is also desirable to re-identify the individuals who have been previously seen with a single-camera. This paper addresses this problem by the re-identification of the same individual in two different datasets, which are both challenging situations from video surveillance system. In this paper, local descriptors are introduced for image description, and support vector machines are employed for high classification performance and so an efficient Bag of Features approach for image presentation. In this way, robustness against low resolution, occlusion and pose, viewpoint and illumination changes is achieved in a very fast way. We get promising results from the evaluation with situations where a number of individuals vary continuously from a multi-camera system.

关键词： Vocabulary Cameras Histograms Feature extraction image color analysis Support vector machine classification Kernel

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Displacement prediction model of landslide based on ensemble of extreme learning machine

Displacement prediction model of landslide based on ensemble...

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19th International Conference on Neural Information processing, ICONIP 2012

作者： Lian, Cheng Zeng, Zhigang Yao, Wei Tang, Huiming Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan Hubei China School of Computer Science South-Central University for Nationalities Wuhan Hubei China Faculty of Engineering China University of Geosciences Wuhan Hubei China

ISBN: (纸本)9783642344770

Based on time series analysis, total accumulative displacement of landslide is divided into the trend component displacement and the periodic component displacement according to the response relation between dynamic changes of landslide displacement and inducing factors. In this paper, a novel neural network technique called the ensemble of extreme learning machine (E-ELM) is proposed to investigate the interactions of different inducing factors affecting the evolution of landslide. Trend component displacement and periodic component displacement are forecasted respectively, then total predictive displacement is obtained by adding the calculated predictive displacement value of each sub. A case study of Baishuihe landslide in the Three Gorges reservoir area is presented to illustrate the capability and merit of our model. © 2012 Springer-Verlag.

关键词： Landslides

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$H_{\infty}$ Filtering for Neutral Systems With Mixed Delays and Multiplicative Noises

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IEEE Transactions on Circuits and Systems II: Express Briefs 2012年第11期59卷 820-824页

作者： Shiping Wen Zhigang Zeng Tingwen Huang Department of Control Science and Engineering Huazhong University of Science and Technology and Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China Texas A & M University at Qatar Doha Qatar

This brief investigates the H ∞ filtering problem for a class of neutral systems with mixed delays and multiplicative noises. The mixed delays comprise both discrete time-varying and distributed delays. Moreover, the multiplicative disturbances are in the form of a scalar Gaussian white noise with unit variance. In the presence of mixed delays and multiplicative noises, sufficient conditions for the existence of an H ∞ filter are derived, such that the filtering error dynamics is asymptotically mean-square stable and also achieves a guaranteed H ∞ performance level. Then, a linear matrix inequality approach for designing such an H ∞ filter is presented. Finally, a numerical example is provided to illustrate the effectiveness of the developed theoretical results.

关键词： Delay Noise Robustness control systems Stochastic systems Linear matrix inequalities

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A novel segmentation method for convex lesions based on dynamic programming with local intra-class variance 12

A novel segmentation method for convex lesions based on dyna...

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27th Annual ACM Symposium on Applied Computing, SAC 2012

作者： Yu, Mali Huang, Qiliang Jin, Renchao Song, Enmin Liu, Hong Hung, Chih-Cheng School of Computer Science Huazhong University of Science and Technology Wuhan China Key Laboratory of Education Ministry for Image Processing and Intelligent Control Wuhan Hubei China Radiology Department Second People's Hospital of Nanning Nanning China School of Computing and Software Engineering Southern Polytechnic State University GA United States

ISBN: (纸本)9781450308571

Lesion segmentation plays an important role in medical image processing and analysis. There exist several successful dynamic programming (DP) based segmentation methods for general images. In those methods, the gradient is used as an important factor in the cost function to attract the contours to the boundaries. Since medical images have their characteristics such as low contrast, blurred edges and high noises, the gradient operator cannot work well enough to achieve a satisfactory performance for boundary detection. We define the local intra-class variance and combine it with the dynamic programming method to replace the traditional gradient operation. Experiments on synthetic and X-ray images are carried out and the results are compared with Canny and fast multilevel fuzzy edge detection (FMFED) algorithms. It is demonstrated that the proposed method performs better on medical images with low contrast, blurred edges and high noises. In addition, 483 regions of interest of mammograms randomly extracted from DDSM of the University of South Florida are used to compare our proposed method with the plane-fitting and dynamic programming method (PFDP), and the normalized cut segmentation method (Ncut). The results demonstrate that our method is more accurate and robust than PFDP and Ncut. © 2012 ACM.

关键词： Dynamic programming

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A hybrid method to segment common carotid arteries from 3D ultrasound images

A hybrid method to segment common carotid arteries from 3D u...

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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Xin Yang Wanji He Jiaoying Jin Xuming Zhang Ming Yuchi Mingyue Ding State Key Laboratory for Multi-spectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence (IPRAI) Huazhong University of Science and Technology Wuhan Hubei China Image Processing and Intelligence Control Key Laboratory of Education Ministry of China S School of Life Science and Technology Huazhong University of Science and Technology Wuhan Hubei China

A hybrid method is used to evaluate atherosclerosis through a mathematical morphology approach and GVF-Snake method. Common carotid artery (CCA) segmentation requires outlining the intima and adventitia contours on the transverse view of B-mode ultrasound (US) images. The lumen and adventitia contours are segmented using a morphology and GVF-Snake methods, respectively. Upon analyzing ten separate patient data sets demonstrate that a comparison between the proposed method and the traditional approach (manual contouring) on 110 transverse images of the CCA showed a mean absolute distance (MAD) of 0.67±0.17mm for lumen and 0.64 ± 0.19mm for adventitia. Their Dice Similarity Coefficient (DSC) values are 92.7%±2.3% and 90.3%±3.5% for lumen and adventitia segmentation, respectively. These values are in good agreement with clinical standards.

关键词： image segmentation Three dimensional displays Measurement Biomedical imaging Ultrasonic imaging Sun

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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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