Mohammed Cheriet & Nawwaf Kharma 
Character Recognition Systems 
A Guide for Students and Practitioners

‘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.

Sobre o autor

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.