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检索条件"机构=Laboratory of Image and Signal Processing of the Institute of Science and Technology"

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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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Needle segmentation in 3D ultrasound images based on phase-grouping

Needle segmentation in 3D ultrasound images based on phase-g...

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： Zhao, Siying Qiu, Wu Ming, Yuchi Ding, Mingyue Institute of Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China Institute of Pattern Recognition and Artificial Intelligence Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Hubei 10086 China School of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074 China School of Life Science and Technology Huazhong University of Science and Technology Hubei 10086 China

ISBN: (纸本)9780819478085

Three Dimensional (3D) ultrasound images can provide spatial information to help doctors locate the needle position precisely in ultrasound-guided surgery. In this paper, we present a method called "3D Phase-grouping" to segment the needle inside the patient. The method is an extension from 2D phase-grouping to the 3D case via a new mathematic model-the outer products of adjacent orientation vectors. Firstly, the voxels with the same outer products of the gradient orientation vectors of the adjacent points are divided into Line Support Regions (LSR). Then, the needle is extracted with the 3D Least-Squares line fitting method in the maximal LSR. Synthetic and 3D ultrasound phantom data were tested. The segmentation results were evaluated by the angular deviation, position deviation and computational time. Compared with the 3D Hough transform, 3D Phase-Grouping is more accurate and faster without using pre-information. The computational complexity and robustness of the algorithm remain to be our future research topics. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Needles

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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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Despeckling SAR images using bayes-shrink in bandelet domain

Despeckling SAR images using bayes-shrink in bandelet domain

引用

2009 2nd International Congress on image and signal processing, CISP'09

作者： Yanan, Xu Qingwei, Gao Yixiang, Lu Weinian, Zhong Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China Institute of Electronic Science and Technology Anhui University Hefei 230039 China

ISBN: (纸本)9781424441310

Synthetic aperture radar (SAR) images are inherently affected by multiplicative speckle noise, which is due to the coherent nature of scattering phenomena. This paper presents a despeckling method for SAR images based on adaptive bandelets thresholding. This threshold is derived in a Bayesian framework. The proposed threshold is simple and closed form, and it is applied to adaptive bandelets coefficients to achieve more satisfying results. The performances of adaptive bandelets Bayesshrink soft-thresholding and wavelet thresholding for despeckling SAR images are compared through an experiment. Experiment results clearly demonstrated the capability of the proposed scheme in SAR image speckle reduction especially for SAR images possessing detailed textures. ©2009 IEEE.

关键词： Synthetic aperture radar

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Path Integral Based Contour Extraction Method Using Multilevel Metropolis Sampling

Path Integral Based Contour Extraction Method Using Multilev...

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7th International Conference on Photonics and Imaging in Biology and Medicine

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

ISBN: (纸本)9780819475398

In this paper we proposed a novel path integral method using multilevel Metropolis sampling to extract the contours of interested objects of medical images, which is a quantum statistical approach inspired by the essential characteristics of quantum. The implemented multilevel Metropolis sampling is a fast approach to the sampling problem and can be used to sample any distribution function and calculate all actions for the movements of quantum particle towards the position with high probability density likely to be accepted. Comparing with traditional deformable models based on classical mechanics which are sensitive to the initialization of contour and difficult to adapt topology changes of the contour, our work has the capability to break through the limitations of deformable models and makes the boundary extraction in high noise and low contrast of medical images possible. Experiments were performed with synthetic and medical images and the feasibility and potential of our method was demonstrated. © 2009 SPIE.

关键词： Distribution functions

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A statistical approach to contour extraction based on quantum mechanics

A statistical approach to contour extraction based on quantu...

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Medical Imaging 2009 - image processing

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

ISBN: (纸本)9780819475107

Contour extraction is a key issue in many medical applications. A novel statistical approach based on quantum mechanics to extract contour of the interested object of medical images was proposed in this paper. The natures of quantum statistical concepts such as the quantum discontinuity and the wave function correspond to the discrete and gray possibility of an image respectively. Contour extraction will be performed by the quantum particle movement, where the particle will be moved forward to the position with high probability density edges in image potential field. Experimental results with medical images demonstrated that the proposed approach has the capability to extract contours with arbitrary initialization and handle topology changes as well as both the inner and outer contours by a single initialization. Keywords: Statistical approach, contour extraction, path integral, quantum mechanics. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Medical applications

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Skeleton-based fast path planning for UAV

Skeleton-based fast path planning for UAV

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

作者： Liu, Xin Zhou, Chengping Ding, Mingyue Cai, Chao Institute for Pattern Recognition and Artificial Intelligence National Lab. for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478092

A new path planning method for UAV in static workspace is presented. The method can find a nearly optimal path in short time which satisfies the UAV kinematic constraints. The method makes use of the skeletons to construct the graph of the planning space considering the configuration of the obstacles and utilizes the graph to find a shortest collision-free path, and a novel technique is utilized to convert the free path into a feasible path. The method can be applied to different applications and easy to be implemented. Experimental results showed that the path planning can be done in a fraction of second on a contemporary workstation (2-3 seconds) under the condition of satisfying the kinematic constraints. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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Kernel-based nonlinear independent component analysis for underdetermined blind source separation

Kernel-based nonlinear independent component analysis for un...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Shigeki Miyabe Biing-Hwang Juang Hiroshi Saruwatari Kiyohiro Shikano Graduate School of Information Science Nara Institute of Science and Technology Japan Center of Signal & Image Processing Georgia Institute of Technology USA

In this paper we propose a new unsupervised training method for nonlinear spatial filter using a new independent component analysis based on kernel infomax. The nonlinearity of the spatial filter used in this paper is equivalent to the integration of beamforming and spectral subtraction, and the whole structure is optimized by independent component analysis in the reproducing kernel Hilbert space. The optimized filter is shown to be capable of achieving better quality output than the conventional method based on time-frequency binary masking.

关键词： Independent component analysis Blind source separation Kernel Source separation Array signal processing Hilbert space Time frequency analysis signal processing Spatial filters Optimization methods

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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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