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6th International Conference on Signal processing, ICSP 2002

作者： Tao, Wen-Bing Tian, Jin-Wen Liu, Jian State Key Laboratory for Image Processing and Intelligence Control Hubei Wuhan430074 China Institute for Pattern Recognition and Artificial Intelligence HUST Hubei Wuhan430074 China

ISBN: (纸本)0780374886

In this paper, we proposed a new Primitive-Structure- Based approach for extracting rectangle building from aerial urban images. We obtain all kinds of primitive-structure that compose rectangle by analysing geometrical primitive structure from the straight-line-graph that has been produced by edge- Detection and contour-tracking and straight-line-splitting, then merge these primitive structure to rectangle through the merging arithmetic. The experimental results show that the approach is times computationally faster than the previous methods. The results of performance assessment also support the robustness and precision of the approach developed. © 2002 IEEE.

关键词： Merging

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Recoverable image watermarking based on halftoning for content authentication

Recoverable image watermarking based on halftoning for conte...

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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： 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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An accurately located method and secure scheme for image authentication

An accurately located method and secure scheme for image aut...

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International Conference on Multimedia Technology

作者： Wang, Zuxi Wang, Wenzong Dong, Liefeng Ye, Peng Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Wuhan China Ningbo Polytechnic Ningbo China

ISBN: (纸本)9781424478743

A novel authentication watermarking scheme for images is proposed in this paper, which holds accuracy location and high security at the same time. In the scheme, different keys are selected for different host data, and the generation and insertion of watermark is dependent on the selected key. Analyzing different pieces of watermarked data in order to launch an attack becomes impossible because of the lack of common characteristics in these pieces. Beside, to increase the security of system, the chaos technology is used to encrypt the watermark and shuffle the location of embedding. A method for tamper detecting based on the running window is proposed in the scheme. Not only can it distinguish malicious attacks from unintentional attacks, but also it can locate the tampered area accurately. Experimental results show this semi-fragile watermarking algorithm is effective and practical for content authentication. ©2010 IEEE.

关键词： Authentication

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image Stitching with single-hidden layer feedforward Neural Networks

Image Stitching with single-hidden layer feedforward Neural ...

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International Joint Conference on Neural Networks

作者： Min Yan Qian Yin Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University

ISBN: (纸本)9781509006212

In this paper, a novel image stitching method is proposed, which utilizes scale-invariant feature transform (SIFT) feature and single-hidden layer feedforward neural network (SLFN) to get higher precision of parameter estimation. In this method, features are extracted from the image sets by the SIFT descriptor and form into the input vector of the SLFN. The output of the SLFN is those translation, rotation and scaling parameters with respect to reference and registered image sets. We also apply a fast learning scheme, called pseudoinverse learning, to train SLFN to get higher training efficiency. Comparative experiments are performed between our proposed method and the traditional random sample consensus (RANSAC) based method. The results show that our method has the advantage not only at accuracy but also remarkably at fast speed.

关键词： SIFT descriptor Feedforward neural network image registration image stitching feedforward neural nets image stitching image registration Parameter estimation fast speed

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Gait period detection based on layered coding of depth information

Gait period detection based on layered coding of depth infor...

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International Conference on Machine Tool Technology and Mechatronics Engineering, ICMTTME 2014

作者： Zhang, Hao Lin Ben, Xian Ye Zhang, Peng Liu, Tian Jiao Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang China School of Information Science and Engineering Shandong University Jinan China

ISBN: (纸本)9783038352464

Gait period detection, serving as a preprocessor for gait recognition, is commonly studied in the recent past. In this paper, we proposed a novel gait period detection method for depth gait video stream. The method introduces the concept of layered coding for depth images which decreases computational complexity. Furthermore, the extreme value of the sum of layered codes for gait sequence is utilized to judge the period endpoint, which is in accord with the naked-eye observation. In addition, gait recognition experiments on the TUM GAID database are conducted with the description of gait features of one single detected period by the proposed scheme using tensor representation. The high recognition accuracy verifies the effectiveness of the proposed depth gait period detection method. © (2014) Trans Tech Publications, Switzerland.

关键词： Codes (symbols)

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Learning Multiple Pooling Combination for image Classification

Learning Multiple Pooling Combination for Image Classificati...

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International Joint Conference on Neural Networks

作者： Junlin Hu Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University

ISBN: (纸本)9781467314886

Recently sparse coding with spatial pyramid matching method has shown its excellent performance in image classification. Inspired by this technique, we present an image classification approach by learning the optimal Multiple Pooling Combination strategy based on Non-Negative Sparse Coding (MPC-NNSC) in this paper. First, non-negative sparse coding with three different pooling methods as well as spatial pyramid matching method are utilized to encode local descriptors for image representation, respectively. Then a promising weight learning approach is employed to find a set of optimal weights for best fusing all these pooling methods in different scales. Lastly, support vector machine classifier with linear and histogram intersection kernel is employed for the final classification task. Experiments on two popular benchmark datasets are presented and they demonstrate the better performance of the proposed scheme compared to the state-of-the-art methods.

关键词： image classification pooling Sparse coding image representation Nonnegative Pyramid

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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...

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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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基于目标区域特性的海面小目标检测快速算法

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自动化学报 2005年第3期31卷 427-433页

作者：邹玉兰汪国有张磊 Institute for Pattern Recognition and Artificial Intelligence State Education Commission Key Laboratory for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan 430074

A fast object detection method based on object region dissimilarity and 1-D AGADM(one dimensional average gray absolute difference maximum) between object and background isproposed for real-time defection of small offshore targets. Then computational complexity, antinoiseperformance, the signal-to-noise ratio (SNR) gain between original images and their results as afunction of SNR of original images and receiver operating characteristic (ROC) curve are analyzed andcompared with those existing methods of small target detection such as two dimensional average grayabsolute difference maximum (2-D AGADM), median contrast filter algorithm and multi-level filteralgorithm. Experimental results and theoretical analysis have shown that the proposed method hasfaster speed and more adaptability to small object shape and also yields improved SNR performance.

关键词：小目标检测快速算法区域特性海面

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RETRACTED ARTICLE: Digital fingerprinting based on synergetic

RETRACTED ARTICLE: Digital fingerprinting based on synergeti...

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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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Kernel Selection with Evolutionary Algorithm for Multiple Kernel Independent Component Analysis

Kernel Selection with Evolutionary Algorithm for Multiple Ke...

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International Joint Conference on Neural Networks

作者： Peng Wu Qian Yin Ping Guo Image Processing and Pattern Recognition Laboratory Beijing Normal University

ISBN: (纸本)9781509006212

Kernel independent component analysis (KICA) has an important application in blind source separation, in which how to select the optimal kernel, including the kernel functional form and its parameters, is the key issue for obtaining the optimal performance. In practices, a single kernel is usually chosen as the kernel model of KICA in light of experience. However, selecting a suitable kernel model is a more difficult problem if one has not sufficient experience. To deal with this problem, an evolution based method to select the kernel model of KICA is proposed in this paper. There are two main features of the proposed method: one is that using a multiple kernel model, a convex combination of several single kernels, replaces the single kernel model;another is that particle swarm optimization (PSO) algorithm is utilized to find the combination weights of the composite kernel. Experiments conducted on separating one-dimensional mixed signals, nature images, and spectroscopic CCD images showed that using multiple kernels model with PSO kernel selection algorithm can enhance the performance of KICA.

关键词： Seeds Kernel evolutionary algorithm Independent component analysis

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