"A lot of pattern recognition theory and practice, including methods such as Support Vector Machines, has emerged in an attempt to solve the problem of character recognition Srihari,. SUNY Distinguished Professor, Department of Computer Science and Engineering, and Director, Center for Excellence for Document Analysis and Recognition (CEDAR ), University at Buffalo, State University of New York "The disciplines of optical character recognition and document analysis of imagery has a history of more than forty years it covers. All the important topics in optical character recognition and document analysis, and written in a style that is very coherent and-komprehensif. Horst Bunke, Professor, Institute of Sciences Computer and Applied Mathematics (IAM), University of Bern, Switzerland In Character Recognition Systems, the authors provide practitioners and students with the basic principles and methods of computation of state-of-the-art reading printed texts and handwritten materials. The information presented is analogous to the gradual introduction of computer systems, helps readers master the theory and latest methodologies used in character recognition in a meaningful way. This book includes: * Perspectives on the history, applications, and evolution of Optical Character Recognition (OCR) * Pre-process the most widely used techniques, and methods for extracting character contours and framework * Evaluating extracted features, both structural and statistical * Modern classification methods are successful in character recognition, including statistical methods, Artificial Neural Network (ANN), Support Vector Machines (SVM), structural methods, and multi-classifier methods * Review of word and string recognition methods and techniques * Case studies that illustrate practical applications, with descriptions of the methods and theories behind the experimental results Each chapter contains major steps and tricks to handle the tasks described in the hand.