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2009 International Conference on Computational Intelligence and Software Engineering, CiSE 2009

作者： Wang, Zuxi Ge, Qiang Wang, Wenzong Hu, Hanping Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan China

ISBN: (纸本)9781424445073

Owing to the weaknesses of existing correlation detection methods in digital fingerprint matching, such as difficult to determine the threshold and low matching accuracy rate, a method proposed in digital fingerprint matching based on synergetic, which was applied in pattern recognition. Then, the experimental result indicated that the method proposed in the paper has a high matching rate. ©2009 IEEE.

关键词： Copyrights

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A comparative study of radial basis function neural networks in dynamic clustering algorithm

A comparative study of radial basis function neural networks...

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MIPPR 2009 - pattern recognition and Computer Vision: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Zhou, Peng Li, Dehua Wu, Hong Zeng, Jun Chen, Feng State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

This paper developed two learning procedure, respectively, based on the orthogonal least squares (OLS) method and the "Innovation- Contribution" criterion (ICc) proposed newly. The orthogonal use of the stepwise-regression algorithm of the ICc mages the model structure independent of the selected term sequence and reduces the cluster region further as compared with orthogonal least squares (OLS). as the Bayesian information criteria (BIC) method is incorporate into the clustering process of the ICc, except for the widths of Gaussian functions, it has no other parameter that need tuning ,but the user is required to specify the tolerance ρ, which is relevant to noises and will be difficult to implement in the real system, for the OLS algorithm. The two algorithms are employed to the Radial Basis Function Neural Networks (RBFNN) to compare its performance for different noise nonlinear dynamic systems. Experimental results show that they provide an efficient approximation to the required results for fitting models, but the clustering procedures of the ICc is substantially better solutions than does the OLS. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Radial basis function networks

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Curve reconstruction from a set of dense scattered points using A* algorithm

Curve reconstruction from a set of dense scattered points us...

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MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Sun, Yangguang Zhou, Chengping Cai, Chao Ding, Mingyue Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies HUST Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China HUST Wuhan 430074 China

ISBN: (纸本)9780819478061

In this paper, a novel curve reconstruction method based on A* algorithm from a set of dense scattered points was proposed. Our method can not only reconstruct dense scattered points with single connected complicated form, but also solve the problem building the curve from the scattered points with close form and multiply connected form. Moreover, the influence of noise points on reconstructed curves is farther decreased, and the shape of dense scattered points will be well hold. Experimental results have demonstrated that the proposed method has the feasibility and robustness. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： pattern recognition

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Pulsar/CNS integrated navigation based on federated UKF

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Chinese Journal of Systems Engineering and Electronics 2010年第4期000卷

作者： Jin Liu Jie Ma Jinwen Tian State Key Laboratory for Multi-spectral Information Processing Technologies Institue for Pattern Recognition and artifical IntelligenceHuazhnng University of Science and TechnologyWuhan 430074P.R.China

In order to improve the autonomous navigation capability of satellite,a pulsar/CNS(celestial navigation system)integrated navigation method based on federated unscented Kalman filter(UKF)is *** celestial navigation is a mature and stable navigation ***,its position determination performance is not satisfied due to the low accuracy of horizon *** pulsar navigation is a new navigation method,which can provide highly accurate range *** major drawback of single pulsar navigation is that the system is completely *** two methods are complementary to each other,the federated UKF is used here for fusing the navigation data from single pulsar navigation and *** to the traditional celestial navigation method and single pulsar navigation,the integrated navigation method can provide better navigation *** simulation results demonstrate the feasibility and effectiveness of the navigation method.

关键词： autonomous navigation celestial navigation system(CNS) pulsar federated unscented Kalman filter(UKF)

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Adaptive synthetic aperture radar image enhancement

Adaptive synthetic aperture radar image enhancement

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MIPPR 2009 - Multispectral image Acquisition and processing: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Cheng, Hua Tian, Jinwen Huazhong University of Science and Technology Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies China

ISBN: (纸本)9780819478054

An adaptive SAR image enhancement method is presented for reducing the speckle noise and increasing the contrast of synthetic aperture radar (SAR) images. First, a fuzzy logic based filter, employing fuzzy edge to weight the contributions of pixel values in filter window, is used to filter the speckles. Second, the original SAR image is decomposed into lowfrequency component and high-frequency component. The fuzzy filtered image is viewed as the low-frequency component, and the contrast limited adaptive histogram equalization algorithm is used to increase its contrast. The highfrequency component is obtained by subtracting the low-frequency component from the original image, and its gain is controlled by fuzzy structural which employed to express the degree of a pixel belonging to structures. After processed one after the other, the two components are added together to form the final enhanced SAR image. Experimental results show the excellent effect of the proposed method by visual observation and numerical measurement. Many fine structures and little speckle noise can be seen from the enhanced SAR images. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image enhancement

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Adaptive tracking method for ground target of FLIR imaging

Adaptive tracking method for ground target of FLIR imaging

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MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Li, Yun Zhang, Tianxu Zuo, Zhengrong Wan, Meijun State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478061

An adaptive tracking method for ground target in FLIR image including centric and eccentric tracking is presented in this paper. The eccentric tracking is adopted to assist ATR or manual target acquisition by stabilizing the light axis of the seeker. The tracking adaptability detection at the start of centric tracking avoids tracking bad locked point and decreases the shift, slide and jump in the subsequent tracking. Combination of periodic template-updating based on scale variance rate and interruptive template-updating based on supervision of tracking point enhances the adaptability of tracking template. Supervision, modification of current tracking point and the combination of direct and indirect tracking increase the stability of tracking system. The multi-scale and size-variable template is adopted to fit the variable target scale. The detection and adoption of occlusion mask increase the accuracy of the tracking system. The hardware system based on multi-DSP takes a real-time parallel processing. The trial results show that this method is efficient to reduce the possibility of shift, slide, and jump in ground target tracking comparing with the traditional correlation tracking method. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Target tracking

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Airborne target tracking algorithm against oppressive decoys in infrared imagery

Airborne target tracking algorithm against oppressive decoys...

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MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Sun, Xiechang Zhang, Tianxu State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478061

This paper presents an approach for tracking airborne target against oppressive infrared decoys. Oppressive decoy lures infrared guided missile by its high infrared radiation. Traditional tracking algorithms have degraded stability even come to tracking failure when airborne target continuously throw out many decoys. The proposed approach first determines an adaptive tracking window. The center of the tracking window is set at a predicted target position which is computed based on uniform motion model. Different strategies are applied for determination of tracking window size according to target state. The image within tracking window is segmented and multi features of candidate targets are extracted. The most similar candidate target is associated to the tracking target by using a decision function, which calculates a weighted sum of normalized feature differences between two comparable targets. Integrated intensity ratio of association target and tracking target, and target centroid are examined to estimate target state in the presence of decoys. The tracking ability and robustness of proposed approach has been validated by processing available real-world and simulated infrared image sequences containing airborne targets and oppressive decoys. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Target tracking

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Classifier-based feature fusion for texture discrimination

Classifier-based feature fusion for texture discrimination

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2009 International Conference on Information Engineering and Computer Science, ICIECS 2009

作者： Ma, Jianglin Zhang, Zhouwei Wang, Chengyi Chen, Zhong Remote Sensing Image Processing Laboratory Institute of Remote Sensing Applications CAS Beijing China Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781424449941

A classifier-based method to select and fuse grey level co-occurrence matrix (GLCM), Gaussian Markov random field (GMRF) and discrete wavelet transform (DWT) features to improve texture discrimination is presented. Feature selection via wrapper approaches is applied to find the optimal combination of texture features. The fused features have obtained higher discrimination accuracy compared with individual features. The curse of dimensionality is shown to affect discrimination accuracy, and feature selection and reduction helps obtain higher accuracy. Overall our proposed classifier-based method obtains the highest discrimination accuracy compared to other feature reduction methods such as principal component analysis (PCA) and linear discriminant analysis (LDA). Meanwhile GLCM features are found to produce higher discrimination accuracy than GMRF and DWT, and LDA is demonstrated to obtain higher discrimination accuracy than PCA. ©2009 IEEE.

关键词： Discrete wavelet transforms

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Acquisition and tracking landmarks for navigation of aircraft

Acquisition and tracking landmarks for navigation of aircraf...

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MIPPR 2009 - Automatic Target recognition and image Analysis: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Yang, Xiaoyu Zhang, Tianxu Yan, Luxin Wang, Dengwei Wang, Xiaoping State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478061

In this paper, we proposed a method is used to estimate an aircraft's own position in flight depending on acquisition and tracking an enlarged landmark in an image sequence. Acquisition operation is based on matching 2D template with a 2D scene of the landmark area generated by the aircraft seeker. After the landmark location is acquired, tracking the center point of the landmark maintains the slant range estimate between the sensor and the landmark which is calculated depending on data of three successive positions from the measured IMU/ GPS information. Then, we obtain the absolute position of the aircraft in the world coordinate system (WCS) with the transformation from the landmark coordinate system (LCS) into the WCS. Finally, bias errors of the Inertial Navigation are corrected for navigation of the aircraft. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Aircraft

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A novel search coding method for generic object recognition based on shared features

A novel search coding method for generic object recognition ...

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MIPPR 2009 - pattern recognition and Computer Vision: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Zheng, Ping Sang, Nong State Key Laboratory for Multispectral Information Processing Technologies Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

In this paper, we consider the combined problem of distinguishing classes from the background and from each other, and propose an improved framework based on the previous state-of-the-art approaches. In the process of building ECOC (Error Correcting Output Coding) matrix (also called as sharing matrix), we adopt an encoding rule of one-versus-all, and maximize Hamming distance in categories as far as possible through heuristic search in sharing-code maps (i.e., layer joint boosting). Then the final classifier is responsible for detection, and ECOC matrix for recognition. In order to make full use of the output of the final classifier and its corresponding ECOC matrix, the following measures are worth considering: Firstly, a logistic function of the output mentioned above is used for a posterior probability of each codeword. Therefore the identified class label is the one corresponding to the codeword of Maximum a posteriori (MAP). Secondly, a similarity measurement utilizing the confusion matrix is advanced to focus on the similarities between classes. Thirdly, for the purpose of adaptive adjustment in Hamming distance, we change the subsequent search coding method according to the confusion matrix until the training errors are convergent. The experimental results illustrate the effectiveness of the proposed approach. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Hamming distance

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