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检索条件"机构=Image Processing and pattern Recognition Laboratory"

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A new method for ship classification and recognition

A new method for ship classification and recognition

引用

MIPPR 2005: image Analysis Techniques

作者： Zhao, Guangzhou Wang, Fei Zhang, Tianxu Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China State Key Laboratory for Image Processing and Intelligent Control Wuhan 430074 China

This paper proposes a fast and robust algorithm for classification and recognition of ships based on the Principal Component Analysis (PCA) method. The three-dimensional ship models are achieved by modeling software of MultiGen, and then they are projected by Vega simulating software for two-dimensional ship silhouettes. The PCA method as against the Back-Propagation (BP) neural network method for simulated ship recognition using training and testing experiments, we can see that there is a sharp contrast between them. Some recognition results from simulated data are presented, the correct recognition rate of PCA method improved rapidly for each of the five ship types than that of neural network method, the number of times a ship type is recognized as one of the other ships is reduced greatly.

关键词： Classification (of information)

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Improved PSO algorithm with harmony search for complicated function optimization problems

Improved PSO algorithm with harmony search for complicated f...

引用

9th International Symposium on Neural Networks, ISNN 2012

作者： Yu, Jian Guo, Ping Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 China College of Mathematics and Information Technology Hanshan Normal University Chaozhou Guangdong 521041 China

ISBN: (纸本)9783642313455

Improved particle swarm optimization algorithm with harmony search (IHPSO) is proposed in this paper. This algorithm takes particle swarm search direction estimation mechanism and harmony search (HS) approach to particle swarm optimization (PSO) algorithm, which increases the search capability of PSO algorithm considerably. The proposed algorithm initializes a new search with harmony pitch adjusting or random selection when PSO search direction is estimated incorrectly. This can provide further opportunities of finding better solutions for the particle swarm by guiding the entire particle swarm to promising new regions of the search space and accelerating the search. PSO, HPSO and IHPSO, as well as other advanced PSO procedures from the literature were compared on several benchmark test functions extensively. Statistical analyses of the experimental results indicate that the performance of IHPSO is better than the performance of PSO and HPSO. © 2012 Springer-Verlag.

关键词： Particle swarm optimization (PSO)

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Study of point spread function of astronomical object imaging

引用

International Conference on Information Science and Applications, ICISA 2016

作者： Yu, Jian Yin, Qian Guo, Ping College of Computer and Information Engineering Hanshan Normal University ChaozhouGuangdong521041 China Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing100875 China

ISBN: (纸本)9789811005565

The research of point spread function (PSF) of astronomical object imaging is very important to the astronomical image restoration. In this paper, the simulated atmospheric turbulent phase screen, the short exposure PSF and longexposure PSF during the astronomical object imaging are studied. One novel Gaussian process move-and-superposition model for representing the final astronomical object long exposure PSF formation is proposed. The proposed model obtains more accurate final PSF of astronomical object imaging. © Springer Science+Business Media Singapore 2016.

关键词： Optical transfer function

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Robust visual tracking based on online learning of joint sparse dictionary

Robust visual tracking based on online learning of joint spa...

引用

6th International Conference on Machine Vision, ICMV 2013

作者： Li, Qiaozhe Qiao, Yu Yang, Jie Bai, Li Key Laboratory of Ministry of Education for System Control and Information Processing Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China School of Computer Science University of Nottingham Nottingham United Kingdom

ISBN: (纸本)9780819499967

In this paper, we propose a robust visual tracking algorithm based on online learning of a joint sparse dictionary. The joint sparse dictionary consists of positive and negative sub-dictionaries, which model foreground and background objects respectively. An online dictionary learning method is developed to update the joint sparse dictionary by selecting both positive and negative bases from bags of positive and negative image patches/templates during tracking. A linear classifier is trained with sparse coefficients of image patches in the current frame, which are calculated using the joint sparse dictionary. This classifier is then used to locate the target in the next frame. Experimental results show that our tracking method is robust against object variation, occlusion and illumination change. © 2013 SPIE.

关键词： E-learning

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Unified restoration method for different degraded images

Unified restoration method for different degraded images

引用

2010 International Conference on Optoelectronics and image processing, ICOIP 2010

作者： Hong, Hanyu Li, Liangcheng Yan, Luxin Zhang, Tianxu Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430074 China Institute for Pattern Recognition and AI Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780769542522

Blurred images are caused by many factors such as defocus, motion, and atmospheric turbulence. Due to the unknown various factors that cannot be distinguished in the blurred image, it is necessary to propose a unified method for image restoration. In order to solve this problem, a unified restoration method for different degraded images is presented, in which we use edge information of blurred image to predict the blur mode. It operates by locally predicting a sharp image using edge information of blurred image and establishes a nonlinear and spatial anisotropic regularization function from the prediction sharp image and the blurred image. Then we can estimate the point spread function (PSF) and recover the blurred image quickly. A series of restoration experiments for different blured images have been performed to verify the effectiveness of the proposed method. © 2010 IEEE.

关键词： Restoration

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MULTISPECTRAL REMOTE SENSING image CLASSIFICATION WITH MULTIPLE FEATURES

MULTISPECTRAL REMOTE SENSING IMAGE CLASSIFICATION WITH MULTI...

引用

2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

作者： QIAN YIN PING GUO Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 Chin Image Processing and Pattern Recognition Laboratory Beijing Normal University Beijing 100875 Chin

In this paper, we propose to combine the spectral and texture features to compose the multi-feature vectors for the classification of multispectral remote sensing *** usually is difficult to obtain the higher classification accuracy if only considers one kind feature, especially for the case of different geographical objects have the same spectrum or texture specialty for a multispectral remote sensing *** spectral feature and the texture feature are composed together to form a new feature vector, which can represent the most effective features of the given remote sensing *** this way we can overcome shortcomings of only using the single feature and raise the classification *** system classification performance with composed feature vector is investigated by *** analysis of results we can learn how to combine the multi-feature vector can obtain a higher classification rate, and experiments proved that the proposed method is feasible and useful in multispectral remote sensing image classification study.

关键词： Spectrum feature Texture feature Multispectral remote sensing image Feature combination Classification.

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Classifier-based feature fusion for texture discrimination

Classifier-based feature fusion for texture discrimination

引用

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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An effective document image deblurring algorithm

An effective document image deblurring algorithm

引用

作者： Chen, Xiaogang He, Xiangjian Yang, Jie Wu, Qiang Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Centre for Innovation in IT Services and Applications University of Technology Sydney Australia Key Laboratory of System Control and Information Processing Ministry of Education China

ISBN: (纸本)9781457703942

Deblurring camera-based document image is an important task in digital document processing, since it can improve both the accuracy of optical character recognition systems and the visual quality of document images. Traditional deblurring algorithms have been proposed to work for natural-scene images. However the natural-scene images are not consistent with document images. In this paper, the distinct characteristics of document images are investigated. We propose a content-aware prior for document image deblurring. It is based on document image foreground segmentation. Besides, an upper-bound constraint combined with total variation based method is proposed to suppress the rings in the deblurred image. Comparing with the traditional general purpose deblurring methods, the proposed deblurring algorithm can produce more pleasing results on document images. Encouraging experimental results demonstrate the efficacy of the proposed method. © 2011 IEEE.

关键词： image enhancement

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Restoration of rotational motion blurred image based on chebyshev polynomial interpolations

Restoration of rotational motion blurred image based on cheb...

引用

MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Zhang, Tianxu Hong, Hanyu Yan, Luxin Zhang, Xiuhua Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Laboratory of Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430074 China

ISBN: (纸本)9780819478085

The restoration of rotational motion blurred image involves a lot of interpolations operators in rectangular-to-polar transformation and its inversion of polar-to-rectangular. The technique of interpolation determines the quality of restoration and computational complexity. In this paper, we incorporate orthogonal chebyshev polynomials interpolations into the processing of restoration of rotational motion blurred image, in which the space-variant blurs are decomposed into a series of space-invariant blurs along the blurring paths, and the blurred gray-values of the discrete pixels of the blurring paths are calculated by using of orthogonal chebyshev polynomials' interpolations and the space-variant blurs can be removed along the blurring paths in the polar system. At same way, we use orthogonal chebyshev polynomials' interpolations to perform polar-to-rectangular transformation to put the restored image back to its original rectangular format. In order to overcome the interference of noise, an optimization restoration algorithm based on regularizations is presented, in which non-negative and edge-preserving smoothing are incorporated into the process of restoration. A series of experiments have been performed to test the proposed interpolation method, which show that the proposed interpolations are effective to preserve edges. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Chebyshev polynomials

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New method for laser parameter detection

New method for laser parameter detection

引用

4th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Optical Test and Measurement Technology and Equipment

作者： Hong, Hanyu Zhang, Huimin Wan, Xiang Zhang, Xiuhua Laboratory of Image Processing and Intelligent Control Wuhan Institute of Technology Wuhan 430074 China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of science and technology Wuhan 430074 China

ISBN: (纸本)9780819475435

A new method to detect laser parameter is proposed in this paper. The improved Michelson Interferometer is used as experiment system to detect parameter. In the proposed detection method, the interference images in variant atmosphere visibility by regulating the polarizer in the system simulate the transmissibility of laser. Experimental results show that the proposed scheme can simulate laser parameter in true atmosphere environment and has good application value. © 2009 SPIE.

关键词： Michelson interferometers

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