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5th International Conference on Document Analysis and recognition, ICDAR 1999

作者： Lu, Yue Shi, Pengfei Wu, Jianzhong Rui, Jianming Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai200030 China Third Research Institute Ministry of Post and Telecommunication Shanghai200062 China

ISBN: (纸本)0769503187

In this paper, a practical postal numeral segmentation and recognition system for Chinese business letters is presented. Line information for the address blocks is gained from the envelope image by projection, then the sub-image of the postal numerals is segmented. The numerals are recognized by three independent classifiers, and their results are combined to form final results. An improved voting principle based on a priori knowledge of each classifier is utilized to combine multiple classifiers in order to achieve perfect performance for high recognition rate and low error rate. The recognition ability of each classifier, acting with the voting principle, is obtained by statistics for a large set of samples. Different thresholds gained by training are employed for different classes, which can yield better results. A parallel structure hardware is designed to implement a real-time image processing system. The performance of the system is shown to be satisfactory, sufficient for the requirements of practical use. © 1999 IEEE.

关键词： Real time systems

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On estimating the position of fragments on rotational symmetric pottery 2

On estimating the position of fragments on rotational symmet...

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2nd International Conference on 3-D Digital Imaging and Modeling, 3DIM 1999

作者： Sablatnig, Robert Menard, Christian Vienna University of Technology Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Treitlstr. 3 183-2 WienA-1040 Austria

ISBN: (纸本)0769500625

The activation of ancient vessel-fragments is a time consuming but important task for archaeologists. The basis for classification and reconstruction is the profile which is the cross-section of the fragment in the direction of the rotational axis of symmetry. Hence the position of a fragment (orientation) on a vessel is important. In this work the estimation of the axis of rotation out of range data by using a Hough inspired method is proposed. In order to avoid outliers a robust method for estimation of the axis is used. Classification and reconstruction are performed in a bottom-up manner using a description language, which holds all features of the fragment as primitives and all properties among features as relations. Classification of newly found fragments of unknown type is performed by comparing the description of the new fragment with the description of already classified fragments by completing graph similarity. The sub-graph with the highest similarity is then used to reconstruct the complete vessel out of the fragment. © 1999 IEEE.

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Texture Segmentation Based on image Model and Neural Network

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Journal of Earth Science 1999年第4期18卷 333-335页

作者： Chen Zhenyu Sheng Wen Wang Guangjun Li Dehua(State Education Commission Laboratory for image processing and Intelligence Control, institute for pattern recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wu han 430074) State Education Commission Laboratory for Image Processing and Intelligence Control Institute for Pattern Recognition and Artificial IntelligenceHuazhong University of Science and TechnologyWuhan 430074

This paper presents a texture segmentation approach which is based on the Markov random field model (MRF) and feed forward neural *** texture is modeled by the second order Gauss MRF model, and the least square error estimation is employed for the solution of model parameters. To perform texture segmentation, we introduced an improved BP algorithm to get faster learning speed. Experiment shows that better segmentation results can be obtained than the traditional Euclidean distance method.

关键词： texture analysis Markov random field neural network

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Unconstrained handwritten numeral recognition using Hausdorff distance and multi-layer neural network classifier

Unconstrained handwritten numeral recognition using Hausdorf...

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International Conference on Document Analysis and recognition

作者： Xuejing Wu Pengfei Shi Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)0769503187

A method for zip code recognition is presented. 2D binary images are input to HAVNET, a neural network which employs the Hausdorff distance as a similarity metric to train the weights which are required to represent the patterns learned by the network. A new learning rule for HAVNET is also introduced. In this approach, HAVNET is combined with a multilayer neural network. The Hausdorff distance acts as a zip code filter. Only the confusing digits are input into the multilayer network for training or recognition. Experimental results show that the correct-recognition rate with zero rejection is more than 97% for a database used by the Chinese mail sorting system.

关键词： Handwriting recognition Neural networks Multi-layer neural network pattern recognition Shape Optical character recognition software Euclidean distance image recognition Optical filters Postal services

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On estimating the position of fragments on rotational symmetric pottery

On estimating the position of fragments on rotational symmet...

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International Conference on 3D Imaging, Modeling, processing, Visualization and Transmission (3DIMPVT)

作者： R. Sablatnig C. Menard Institute of Computer Aided Automation Pattern Recognition and Image Processing Group University of Technology Vienna Wien Austria

关键词： image reconstruction Ceramics Automation pattern recognition image processing Cultural differences Global communication Shape Production Consumer behavior

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An implementation of postal numerals segmentation and recognition system for Chinese business letters

An implementation of postal numerals segmentation and recogn...

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International Conference on Document Analysis and recognition

作者： Yue Lu Pengfei Shi Jianzhong Wu Jianming Rui Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China The Third Research Institute Ministry of Posts and Telecommunications Shanghai China

ISBN: (纸本)0769503187

A practical postal numeral segmentation and recognition system for Chinese business letters is presented. Line information for the address blocks is gained from the envelope image by projection, then the sub-image of the postal numerals is segmented. The numerals are recognized by three independent classifiers, and their results are combined to form final results. An improved voting principle based on a priori knowledge of each classifier is utilized to combine multiple classifiers in order to achieve perfect performance for high recognition rate and low error rate. The recognition ability of each classifier, acting with the voting principle, is obtained by statistics for a large set of samples. Different thresholds gained by training are employed for different classes, which can yield better results. A parallel structure hardware is designed to implement a real-time image processing system. The performance of the system is shown to be satisfactory, sufficient for the requirements of practical use.

关键词： image segmentation image processing image recognition Voting Real time systems Character recognition pattern recognition Error analysis Sorting Electronic mail

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A fast decomposition of banded symmetric Toeplitz matrices for parallel processing

A fast decomposition of banded symmetric Toeplitz matrices f...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： W. Xiong J. Li R.M.M. Chen S. Qian Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Department of Electronic Engineering City University Hong Kong China

The eigendecomposition of banded symmetric matrices Is important in regularized signal restoration. In this paper a new fast decomposition algorithm is developed by using FFT and rank-one update. In this way the split of the matrix becomes more direct and the cost of the initial decomposition decreases. The algorithm is especially useful for parallel processing. Two numerical examples are given, which show that the new method can achieve comparable results to the classical methods.

关键词： Matrix decomposition Symmetric matrices Parallel processing Signal restoration Eigenvalues and eigenfunctions image processing pattern recognition Computer science Costs Concurrent computing

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An Evolutionary Algorithm for Optimizing Handwritten Numeral Templates Represented by Rational B-Spline Surfaces

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Journal of Advanced Computational Intelligence and Intelligent Informatics 1999年第6期3卷 462-466页

作者： Chi, Zheru Lu, Zhongkang Siu, Wan-Chi Shi, Peng-Fei Centre of Digital Signal Processing for Multimedia Applications Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hung Horn Kowloon Hong Kong Institute of Image Processing and Pattern Recognition Shanghai Jiaolong University Shanghai200030 China

To improve the reliability of a template-matching classifier for recognizing connected handwritten characters, we present an evolutionary algorithm to optimize handwritten numeral templates represented by rational B-spline surfaces of character pixel-boundary distance maps (PBDMs). Initial templates are extracted by training a feed-forward neural network. In simulation, 1, 000 handwritten numeral templates (100 templates for each class) were extracted and optimized using 10, 426 training samples (isolated numerals from NIST Special Database 3). A tern plate-matching classifier using these 1, 000 optimized templates rejected 90.7% of nonnumeral patterns (not included in the training set) while achieving a correct classification rate of 96.4% on independent isolated numerals. © Fuji Technology Press Ltd. Creative Commons CC BY-ND: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NoDerivatives 4.0 International License (http://***/licenses/by-nd/4.0/).

关键词： Template matching

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Impulse noise removal using linear prediction model

Impulse noise removal using linear prediction model

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4th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, ITELSIKS 1999

作者： Prudyus, Ivan Voloshynovskiy, Sviatoslav Rytsar, Yuriy Holotyak, Taras Radio Engineering Faculty State University Lvivska Polytechnika 12 S.Bandery Str. Lviv 290646 Ukraine Coordinated Science Laboratory University of Illinois College of Engineering 1308 West Main Street Urbana IL 61801-2307 United States Department of Image Processing and Pattern Recognition Institute of Physics and Mechanics National Academy of Science of Ukraine 5 Naukova str. Lviv Ukraine

ISBN: (纸本)078035768X

Noise removal is an important problem in many applications. In this paper a new two-step scheme of the decision-based impulse noise removal method by means of contaminated pixel detection is proposed and comparison with direct order statistic filtering is given. The proposed methods satisfy both objective and subjective image quality. © 1999 IEEE.

关键词： Impulse noise

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Impulse noise removal using linear prediction model

Impulse noise removal using linear prediction model

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International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Service (TELSIKS)

作者： I. Prudyus S. Voloshynovskiy Y. Rytsar T. Holotyak National University Lvivska Politechnika Lviv Ukraine Coordinated Science Laboratory College of Engineering University of Illinois Urbana IL USA Department of Image Processing and Pattern Recognition Institute of Physics and Mechanics National Academy of Sciences Lviv Ukraine

关键词： Predictive models Statistics Noise reduction Pixel Electronic mail image quality Nonlinear filters Filtering algorithms Data analysis Statistical analysis

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