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IEEE Workshop on Neural Networks for Signal processing

作者： Zhang Yankun Liu Chongqing The Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai People's Republic of China

ISBN: (纸本)0780376161

Kernel principal component analysis (KPCA) as a powerful nonlinear feature extraction method has proven as a preprocessing step for classification algorithm. A face recognition approach based on KPCA and genetic algorithms (GAs) is proposed. By the use of the polynomial functions as a kernel function in KPCA, the high order relationships can be utilized and the nonlinear principal components can be obtained. After we obtain the nonlinear principal components, we use GAs to select the optimal feature set for classification. At the recognition stage, we employed linear support vector machines (SVM) as classifier for the recognition tasks. Two face databases were used to test our algorithm and higher recognition rates were obtained which show that our algorithm is effective.

关键词： Face recognition Kernel Principal component analysis Genetic algorithms Support vector machines Support vector machine classification Feature extraction Classification algorithms Polynomials Spatial databases

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Improvement of histogram-based image retrieval and classification

Improvement of histogram-based image retrieval and classific...

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International Conference on pattern recognition

作者： S. Siggelkow H. Burkhardt Institute for Pattern Recognition and Image Processing Albert Ludwigs Universität Freiburg Freiburg im Breisgau Germany

Histogram-based techniques are commonly used in image retrieval ranging from basic color histograms to sophisticated histograms of various local feature vectors. Our approach considers multidimensional histograms of locally invariant features. In order to get rid of the discontinuous behavior of traditional histograms we develop a fuzzy histogram which does no sharp assignment of a feature vector to one bin only but performs a weighted assignment to all neighboring bins. This improvement is not restricted to the kind of feature histograms considered here but could generally improve histogram-based retrieval or classification techniques.

关键词： image retrieval Histograms Content based retrieval pattern recognition image processing Color Internet Computer vision Shape Pixel

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Hierarchical top down enhancement of robust PCA 9th

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Joint IAPR 9th International Workshop on Structural and Syntactic pattern recognition, SSPR 2002 and 4th International Workshop on Statistical Techniques in pattern recognition, SPR 2002

作者： Langs, Georg Bischof, Horst Kropatsch, Walter G. Pattern Recognition and Image Processing Group 183/2 Institute for Computer Aided Automation Vienna University of Technology Favoritenstr. 9 ViennaA-1040 Austria Institute for Computer Graphics and Vision TU Graz Inffeldgasse 16 2.OG GrazA-8010 Austria

ISBN: (纸本)3540440119

In this paper we deal with performance improvement of robust PCA algorithms by replacing regular subsampling of images by an irregular image pyramid adapted to the expected image content. The irregular pyramid is a structure built based on knowledge gained from the training set of images. It represents different regions of the image with different level of detail, depending on their importance for reconstruction. This strategy enables us to improve reconstruction results and therefore the recognition significantly. The training algorithm works on the data necessary to perform robust PCA and therefore requires no additional input. © Springer-Verlag Berlin Heidelberg 2002.

关键词： image enhancement

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Color texture-based object detection: An application to license plate localization 1st

Color texture-based object detection: An application to lice...

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1st International Workshop on pattern recognition with Support Vector Machines, SVM 2002

作者： In Kim, Kwang Jung, Keechul Kim Hyung, Jin Artificial Intelligence Lab CS Department Korea Advanced Institute of Science and Technology Taejon305-701 Korea Republic of Pattern Recognition and Image Processing Lab CS and Engineering Department Michigan State University East LansingMI48824-1226 United States

ISBN: (纸本)354044016X

This paper presents a novel color texture-based method for object detection in images. To demonstrate our technique, a vehicle license plate (LP) localization system is developed. A support vector machine (SVM) is used to analyze the color textural properties of LPs. No external feature extraction module is used, rather the color values of the raw pixels that make up the color textural pattern are fed directly to the SVM, which works well even in high-dimensional spaces. Next, LP regions are identified by applying a continuously adaptive meanshift algorithm (CAMShift) to the results of the color texture analysis. The combination of CAMShift and SVMs produces not only robust and but also efficient LP detection as time-consuming color texture analyses for less relevant pixels are restricted, leaving only a small part of the input image to be analyzed. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Object detection

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Automated segmentation of archaeological profiles for classification

Proceedings - International Conference on Pattern Recognitio...

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Proceedings - International Conference on pattern recognition 2002年第1期16卷 57-60页

作者： Kampel, Martin Sablatnig, Robert Vienna University of Technology Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Favoritenstr.9/183-2 A-1040 Vienna Austria

Classification and reconstruction of archaeological fragments is based on the profile, which is the cross-section of the fragment in the direction of the rotational axis of symmetry. In order to segment the profile into primitives like rim, wall, and base, rules based on expert knowledge are created. The input data for the estimation of the profile is a set of points produced by the acquisition system. A function fitting this set is constructed and later on processed to find the characteristic points necessary to classify the original fragment. The one we propose is based on B-splines or bell-shaped splines. © 2002 IEEE.

关键词： image segmentation

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Combining shape from silhouette and shape from structured light for volume estimation of archaeological vessels

Proceedings - International Conference on Pattern Recognitio...

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Proceedings - International Conference on pattern recognition 2002年第1期16卷 364-367页

作者： Sablatnig, Robert Tosovic, Srdan Kampel, Martin Vienna University of Technology Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Favoritenstr. 9 183-2 A-1040 Vienna Austria

An algorithm for the automatic construction of a 3d model of archaeological vessels using two different 3d algorithms is presented. In archeology the determination of the exact volume of arbitrary vessels is of importance since this provides information about the manufacturer and the usage of the vessel. To acquire the 3d shape of objects with handles is complicated, since occlusions of the object's surface are introduced by the handle and can only be resolved by taking multiple views. Therefore, the 3d reconstruction is based on a sequence of images of the object taken from different viewpoints with two different algorithms;shape from silhouette and shape from structured light. The output of both algorithms are then used to construct a single 3d model. Results of the algorithm developed are presented for both synthetic and real input images. © 2002 IEEE.

关键词： Parameter estimation

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Logarithmic tapering graph pyramid

Logarithmic tapering graph pyramid

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24th German Association for pattern recognition Symposium, DAGM 2002

作者： Haxhimusa, Yll Glantz, Roland Saib, Maamar Langs, Georg Kropatsch, Walter G. Pattern Recognition and Image Processing Group 183/2 Institute for Computer Aided Automation Vienna University of Technology Favoritenstrasse 9 ViennaA-1040 Austria Dipartimento di Informatica Università di Ca’ Foscari di Venezia Via Torino 155 MestreVE30172 Italy

ISBN: (纸本)354044209X

We present a new method to determine contraction kernels for the construction of graph pyramids. The new method works with undirected graphs and yields a reduction factor of at least 2.0. This means that with our method the number of vertices in the subgraph induced by any set of contractible edges is reduced to half or less by a single parallel contraction. Our method yields better reduction factors than the stochastic decimation algorithm, in all tests. The lower bound of the reduction factor becomes crucial with large images. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Stochastic systems

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Integer Haar wavelet for remote sensing image compression

Integer Haar wavelet for remote sensing image compression

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International Conference on Signal processing Proceedings (ICSP)

作者： Wang Zhenhua Xu Hongbo Tian Yan Tian Jinwen Liu Jian Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Image Processing and Intelligent Control Huazhong University of science and Technology Wuhan China

ISBN: (纸本)0780374886

With the development of remote sensing technique, onboard data compression has become an urgent need and a lot of study has been directed toward the development of efficient techniques. In this paper, the construction approach of integer Haar is discussed briefly, and a simple image compression scheme based on the integer Haar wavelet transform and block DPCM is proposed. The scheme can be easily designed for data processing in real-time systems of remote sensing with parallel algorithms. Simulation experimental results demonstrate that the proposed approach is a efficient image compression method.

关键词： image coding Remote sensing Wavelet transforms Frequency Data compression image reconstruction pattern recognition Artificial intelligence image processing Intelligent control

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The design and implementation of a Chinese financial invoice recognition system

The design and implementation of a Chinese financial invoice...

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IEEE Region 8 International Symposium on Video/image processing and Multimedia Communications (EURASIP)

作者： Ming Delie Liu Jian Tian Jinwen State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei China

This paper designs and implements a financial invoice recognition system based on the features of the Chinese financial invoice. By using the linear whole block moving method in each vertical segment, a new fast algorithm is put forward to detect and rectify slanted images. To distinguish the different form types (the foundation necessary for locating the form fields, filtering the form lines, etc), several representative form features are discussed and an invoice-type features library is built by using a semi-automatic machine study method. On the basis of the recognized invoice type, a real invoice form is re-oriented against the corresponding blank form according to the invoice type feature, solving the problem of adhesion of characters and form lines, as well as the problem of character segmentation and recognition. Based on the financial Chinese invoice image feature, a mutual rectification mechanism founded on the recognition results of financial Chinese characters and Arabic numerals is put forward to raise the recognition rate. Finally, experimental results and conclusions are presented.

关键词： Character recognition Optical character recognition software image recognition image segmentation image processing pattern recognition High speed optical techniques Optical filters System testing Laboratories

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Text scanner with text detection technology on image sequences

Text scanner with text detection technology on image sequenc...

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16th International Conference on pattern recognition, ICPR 2002

作者： Jung, Keechul Kim, Kwang In Kurata, Takeshi Kourogi, Masakastu Han, Junghyun Pattern Recognition and Image Processing Lab. Michigan State Univerisity United States Artificial Intelligence Lab. KAIST Korea Republic of National Institute of Advanced Industrial Science and Technology Japan School of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

ISBN: (纸本)0769516963

We propose a text scanner, which detects wide text strings in a sequence of scene images. For scene text detection, we use a multiple-CAMShift algorithm on a text probability image produced by a multi-layer perceptron. To provide enhanced resolution of the extracted text images, we perform the text detection process after generating a mosaic image in a fast and robust image registration method. © 2002 IEEE.

关键词： image enhancement

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