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检索条件"机构=Vienna University of Technology Pattern Recognition and Image Processing"

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A fast quantum mechanics based contour extraction algorithm

A fast quantum mechanics based contour extraction algorithm

引用

Medical Imaging 2009 - image processing

作者： Lan, Tian Sun, Yangguang Ding, Mingyue Institute for Pattern Recognition and Artificial Intelligence Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819475107

A fast algorithm was proposed to decrease the computational cost of the contour extraction approach based on quantum mechanics. The contour extraction approach based on quantum mechanics is a novel method proposed recently by us, which will be presented on the same conference by another paper of us titled "a statistical approach to contour extraction based on quantum mechanics". In our approach, contour extraction was modeled as the locus of a moving particle described by quantum mechanics, which is obtained by the most probable locus of the particle simulated in a large number of iterations. In quantum mechanics, the probability that a particle appears at a point is equivalent to the square amplitude of the wave function. Furthermore, the expression of the wave function can be derived from digital images, making the probability of the locus of a particle available. We employed the Markov Chain Monte Carlo (MCMC) method to estimate the square amplitude of the wave function. Finally, our fast quantum mechanics based contour extraction algorithm (referred as our fast algorithm hereafter) was evaluated by a number of different images including synthetic and medical images. It was demonstrated that our fast algorithm can achieve significant improvements in accuracy and robustness compared with the well-known state-of-the-art contour extraction techniques and dramatic reduction of time complexity compared to the statistical approach to contour extraction based on quantum mechanics. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Wave functions

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Ear segmentation using histogram based K-means clustering and Hough transformation under CVL dataset

Ear segmentation using histogram based K-means clustering an...

引用

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

作者： Liu, Heng Liu, Dekai School of Information Engineering Southwest University of Science and Technology Mianyang 621010 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9780819478061

Under CVL dataset, we provide an image segmentation approach based on adaptive histogram based K-means clustering and fast Hough transformation. This work firstly analyzes the characteristics of ear images in CVL face dataset. According to the analysis, we then use adaptive histogram based K-means clustering method to threshold ear images and then roughly segment the ear parts. After ear contour extraction, with boundary determination through vertical project, Hough transformation is utilized to locate the ear contour accurately. The experimental results and comparisons with other segmentation methods show our approach is effective. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image segmentation

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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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Recoverable image watermarking based on halftoning for content authentication

Recoverable image watermarking based on halftoning for conte...

引用

MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and pattern recognition

作者： Wang, Zuxi Zhao, Xiangyuan Wang, Wenzong Hu, Hanping Li, Li Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan 430074 China

ISBN: (纸本)9780819478092

In this paper, a semi-fragile watermark solution based on quantization index modulation in the wavelet region was proposed. The algorithm employs a compressed halftoned binary image as watermark and embeds it in the wavelet domain through quantization index modulation, which can not only identify the authenticity of the content of digital image, but also recover the tampered image approximately. Because the watermark is a low-resolution original image, which carries the original image information, so the original image is not required when authenticating, and the tampered region can be recovered according to the watermark. The method can tolerate a certain degree of compression distortion or noise. Beside, a secret key is used to select the embedded watermark bits and their embedded positions to increase the security of watermarking. Experimental results show this semi-fragile watermarking algorithm is effective and practical for content authentication. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Binary images

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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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MRI brain tumor segmentation based on improved fuzzy c-means method

MRI brain tumor segmentation based on improved fuzzy c-means...

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： Deng, Wankai Xiao, Wei Pan, Chao Liu, Jianguo Key Laboratory of Education Ministry for Image Processing and Intelligence Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei 430074 China

ISBN: (纸本)9780819478085

This paper focuses on the image segmentation, which is one of the key problems in medical image processing. A new medical image segmentation method is proposed based on fuzzy c- means algorithm and spatial information. Firstly, we classify the image into the region of interest and background using fuzzy c means algorithm. Then we use the information of the tissues' gradient and the intensity inhomogeneities of regions to improve the quality of segmentation. The sum of the mean variance in the region and the reciprocal of the mean gradient along the edge of the region are chosen as an objective function. The minimum of the sum is optimum result. The result shows that the clustering segmentation algorithm is effective. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Clustering algorithms

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RETRACTED ARTICLE: Digital fingerprinting based on synergetic

RETRACTED ARTICLE: Digital fingerprinting based on synergeti...

引用

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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Spatial and Spectral Based Segmentation of Text in Multispectral images of Ancient Documents

Spatial and Spectral Based Segmentation of Text in Multispec...

引用

International Conference on Document Analysis and recognition

作者： Martin Lettner Robert Sablatnig Pattern Recognition and Image Processing Group Institute of Computer Aided Automation University of Technology Vienna Austria

ISBN: (纸本)9781424445004

In this paper we propose a character segmentation method for multispectral images of ancient documents. Due to the low quality of the images the main idea of this study is to combine the multispectral behavior and contextual spatial information. Therefore we utilize a Markov random field model using the spectral information of the images and stroke properties to include spatial dependencies of the characters. Since the stroke properties and the Gaussian parameters for the imaging model are evaluated automatically the proposed segmentation method requires no training phase. We compared the method to state of the art character segmentation methods and demonstrate the effectiveness of combining spectral and spatial features for the segmentation of characters in multispectral images.

关键词： image segmentation Multispectral imaging image analysis Color Independent component analysis Text analysis Character recognition pattern recognition Markov random fields pattern analysis

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Color-based and context-aware skin detection for online video annotation

Color-based and context-aware skin detection for online vide...

引用

IEEE Workshop on Multimedia Signal processing

作者： Christian Liensberger Julian Stottinger Martin Kampel Institute of Computer Aided Automation Pattern Recognition and Image Processing Group University of Technology Vienna Austria

By analyzing the low level features of images only, skin detection in visual data cannot be solved. To compensate for this major drawback of many approaches, we combine a state of the art recognition algorithm with color model based skin detection. Detected faces in videos are the basis for adaptive skin-color models, which are propagated throughout the video, providing a more precise and accurate model in its recognition performance than pure color based approaches. The approach is able to run in real-time and does not need prior data-specific training. We received challenging online videos from an online service provider and use additional videos from public Web platforms covering a grand variety of different skin-colors, illumination circumstances, image quality and difficulty levels. In an extensive evaluation we estimated the best performing parameters and decide on the best model propagation techniques. We show that adaptive model propagation outperforms static low level detection.

关键词： Skin Face detection image analysis Lighting Internet Automation pattern recognition image processing image color analysis pattern analysis

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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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