Mohammed Cheriet, Nawwaf Kharma, Cheng-Lin Liu, Ching Suen

Character Recognition Systems (eBook, PDF)

A Guide for Students and Practitioners

• Format: PDF

Produktbeschreibung

"Much of pattern recognition theory and practice, including methods such as Support Vector Machines, has emerged in an attempt to solve the character recognition problem. This book is written by very well-known academics who have worked in the field for many years and have made significant and lasting contributions. The book will no doubt be of value to students and practitioners." -Sargur N. Srihari, SUNY Distinguished Professor, Department of Computer Science and Engineering, and Director, Center of Excellence for Document Analysis and Recognition (CEDAR), University at Buffalo, The State University of New York "The disciplines of optical character recognition and document image analysis have a history of more than forty years. In the last decade, the importance and popularity of these areas have grown enormously. Surprisingly, however, the field is not well covered by any textbook. This book has been written by prominent leaders in the field. It includes all important topics in optical character recognition and document analysis, and is written in a very coherent and comprehensive style. This book satisfies an urgent need. It is a volume the community has been awaiting for a long time, and I can enthusiastically recommend it to everybody working in the area." -Horst Bunke, Professor, Institute of Computer Science and Applied Mathematics (IAM), University of Bern, Switzerland In Character Recognition Systems, the authors provide practitioners and students with the fundamental principles and state-of-the-art computational methods of reading printed texts and handwritten materials. The information presented is analogous to the stages of a computer recognition system, helping readers master the theory and latest methodologies used in character recognition in a meaningful way. This book covers: * Perspectives on the history, applications, and evolution of Optical Character Recognition (OCR) * The most widely used pre-processing techniques, as well as methods for extracting character contours and skeletons * Evaluating extracted features, both structural and statistical * Modern classification methods that are successful in character recognition, including statistical methods, Artificial Neural Networks (ANN), Support Vector Machines (SVM), structural methods, and multi-classifier methods * An overview 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 at-hand. Researchers and graduate students in computer science and engineering will find this book useful for designing a concrete system in OCR technology, while practitioners will rely on it as a valuable resource for the latest advances and modern technologies that aren't covered elsewhere in a single book.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 352
• Erscheinungstermin: 28. Juni 2008
• Englisch
• ISBN-13: 9780470176528
• Artikelnr.: 37290779

Autorenporträt

Professor Mohamed Cheriet is currently Professor of Computer and Electrical Engineering at the University of Concordia. He has published extensively on the subjects of pattern and character recognition, and machine intelligence. Professor Nawwaf Kharma has been an assistant professor for the Department of Electrical and Computer Engineering at Concordia University since 2000. Dr. Cheng-Lin Liu worked for Hitachi until the beginning of 2005, and then joined the Institute of Automation at the Chinese Academy of Sciences in Beijing. He is also a member of the IEEE. Professor Ching Suen is Director for the Center for Pattern Recognition, working under the fields of artificial intelligence, human-computer communications, and pattern recognition.

Inhaltsangabe

Figures. List of Tables. Preface. Acknowledgments. Acronyms. 1.
Introduction: Character Recognition, Evolution and Development. 1.1
Generation and Recognition of Characters. 1.2 History of OCR. 1.3
Development of New Techniques. 1.4 Recent Trends and Movements. 1.5
Organization of the Remaining Chapters. References. 2. Tools for Image
Pre-Processing. 2.1 Generic Form Processing System. 2.2 A Stroke Model for
Complex Background Elimination. 2.3 A Scale-Space Approach for Visual Data
Extraction. 2.4 Data Pre-Processing. 2.5 Chapter Summary. References 72. 3.
Feature Extraction, Selection and Creation. 3.1 Feature Extraction. 3.2
Feature Selection for Pattern Classification. 3.3 Feature Creation for
Pattern Classification. 3.4 Chapter Summary. References. 4. Pattern
Classification Methods. 4.1 Overview of Classification Methods. 4.2
Statistical Methods. 4.3 Artificial Neural Networks. 4.4 Support Vector
Machines. 4.5 Structural Pattern Recognition. 4.6 Combining Multiple
Classifiers. 4.7 A Concrete Example. 4.8 Chapter Summary. References. 5.
Word and String Recognition. 5.1 Introduction. 5.2 Character Segmentation.
5.3 Classification-Based String Recognition. 5.4 HMM-Based Recognition. 5.5
Holistic Methods For Handwritten Word Recognition. 5.6 Chapter Summary.
References. 6. Case Studies. 6.1 Automatically Generating Pattern
Recognizers with Evolutionary Computation. 6.2 Offline Handwritten Chinese
Character Recognition. 6.3 Segmentation and Recognition of Handwritten
Dates on Canadian Bank Cheques. References.

Rezensionen

"In the words of Horst Bunke (also from the back cover), it is a volume the community has been awaiting for a long time, and I can enthusiastically recommend it to everybody working in the area. I concur and recommend the book to readers interested either in the general field of OCR, or in a more in-depth treatment of the constituent techniques." ( Computing Reviews , March 12, 2008)
"Researchers and graduate students...[and] practitioners might find it a valuable resource for the latest advances and modern technologies..." ( IEEE Computer Magazine , December 2007)