Fundamentals In Handwriting Recognition

For many years researchers in the field of Handwriting Recognition were considered to be working in an area of minor importance in Pattern Recog nition. They had only the possibility to present the results of their research at general conferences such as the ICPR or publish their papers in journals such as some of the IEEE series or PR, together with many other papers generally oriented to the more promising areas of Pattern Recognition. The series of International Workshops on Frontiers in Handwriting Recog nition and International Conferences on Document Analysis and Recognition together with some special issues of several journals are now fulfilling the expectations of many researchers who have been attracted to this area and are involving many academic institutions and industrial companies. But in order to facilitate the introduction of young researchers into the field and give them both theoretically and practically powerful tools, it is now time that some high level teaching schools in handwriting recognition be held, also in order to unite the foundations of the field. Therefore it was my pleasure to organize the NATO Advanced Study Institute on Fundamentals in Handwriting Recognition that had its origin in many exchanges among the most important specialists in the field, during the International Workshops on Frontiers in Handwriting Recognition.

What Is Handwriting Recognition Handwriting recognition (HWR) is the ability of a computer to accept and interpret comprehensible handwritten input from sources such as paper documents, pictures, touch-screens, and other devices. Handwritten text recognition (HTR) is another name for handwriting recognition. Handwriting recognition (HWR) is also known as handwritten text recognition (HTR). By using optical scanning or intelligent word recognition, the image of the written text can be sensed "off line" from a piece of paper. This can be done in a number of different ways. A different option is for the movements of the pen tip to be sensed "on line," for instance by a pen-based computer screen surface. This is a task that is typically simpler because there are more hints available. Formatting, accurate character segmentation, and the identification of words that are most likely to be written are all taken care of by a handwriting recognition system. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Handwriting Recognition Chapter 2: Artificial Neural Network Chapter 3: Optical Character Recognition Chapter 4: Recurrent Neural Network Chapter 5: Long Short-term Memory Chapter 6: Deep Learning Chapter 7: Signature Recognition Chapter 8: Handwritten Biometric Recognition Chapter 9: MNIST Database Chapter 10: History of Artificial Neural Networks (II) Answering the public top questions about handwriting recognition. (III) Real world examples for the usage of handwriting recognition in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of handwriting recognition' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of handwriting recognition.

Handwriting Recognition has become a very important research area which is attracting more and more scientists. In fact, the extraordinary advances in the field of data acquisition technology and the promising results of the research, nowadays make possible the development of commercial systems for processing and recognition of handwritten documents.This book contains the results of the activity of the most important academic and industrial research groups working in this area. The new issues arising in the field are focused and involve both theoretical and practical aspects related to handwriting recognition and document processing systems. The contributions of eminent experts point out the more interesting challenges for the scientific community ranging from acquisition and preprocessing of handwritten documents, to recognition of handwritten digits and words, to the design of multi-expert systems and the exploitation of the contextual knowledge to improve system performance.

Character and handwriting recognition by computers is attracting much attention particularly because of its potential for application in many areas such as office automation, bank check processing, recognition of postal addresses and ZIP Codes, signature verification, and document and text recognition. Over the past four decades, many methods have been proposed, developed and tested for computers to recognize characters, and they have been reported in a variety of publications. The present volume is a coherent and integrated publication containing papers which give new research results in this increasingly active field. It is a boon to researchers, scientists and engineers who need to keep abreast of new developments in character and handwriting methodologies and applications. Contents: Foreword (C Y Suen)OCR and Off-Line Character Recognition:Optical Character Recognition — A Survey (S Impedovo et al.)Transformation-Ring-Projection (TRP) Algorithm and its VLSI Implementation (Y Y Tang et al.)Regularities and Singularities in Line Pictures (J C Simon & O Baret)On-Line Character Recognition:Speed, Accuracy, and Flexibility Trade-Offs in On-Line Character Recognition (C C Tappert)Chinese and Japanese Character Recognition: Some Research Achievements on Chinese Character Recognition in China (J-W Tai)Applications:Understanding Handwritten Text in a Structured Environment: Determining ZIP Codes from Addresses (E Cohen et al.)A Structural Approach to On-Line Character Recognition: System Design and Applications (F Nouboud & R Plamondon)Progress in Verification of Skillfully Simulated Handwritten Signatures (M Ammar)and other papers Readership: Computer scientists, engineers, researchers and industrialists.

A collection of articles representing progress in the major areas of fundamental and applied handwriting research. Areas covered are: behavioural and cognitive science; development, education and neuroscience; computer analysis and recognition; and forensic document examination.

"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.

Knowledge-Based Intelligent Techniques in Character Recognition presents research results on intelligent character recognition techniques, reflecting the tremendous worldwide interest in the applications of knowledge-based techniques in this challenging field. This resource will interest anyone involved in computer science, computer engineering, applied mathematics, or related fields. It will also be of use to researchers, application engineers and students who wish to develop successful character recognition systems such as those used in reading addresses in a postal routing system or processing bank checks. Features

"Forensic document examination is the study of physical evidence and physical evidence cannot lie. Only its interpretation can err. Only the failure to find it, or to hear its true testimony can deprive it of its value."—Roy Huber This is a comprehensive update of Huber and Headrick's seminal work on handwriting examination. New coverage includes a review of forensic handwriting examination research, handwriting analysis training and proficiency, revised methods and procedures, an updated listing and clarification of terminology and electronic signatures, the analysis of digitized handwriting, and other related technological advances. The book includes updated photographs, several added illustrations, and advances in techniques based on the scientific research conducted in the area over the last 20 years. Features of the new edition include: The latest on electronic signatures, digital handwriting, automated handwriting verification, and the many advances in technology and research over the last two decades An overview of the fundamentals of handwriting examination with updated discussion of the intrinsic and extrinsic variables associated with handwriting identification A review of the criticism of handwriting expert opinions and methodology, addressing both the strengths and scientific limitations of the area Fully revised while remaining true to the spirit and approach of original authors Roy Huber and A. M. Headrick Addition of nearly 200 new references and new glossary terms representing advances in research and methods. With extensive photographs to help clearly illustrate concepts, Huber and Headrick’s Handwriting Identification: Facts and Fundamentals, Second Edition serves as an invaluable reference to law libraries, practicing document examiners, forensic and criminal justice students, and every lawyer handling cases in which the authenticity of handwriting and documents might be disputed.