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The Handbook of Document Image Processing and Recognition is a comprehensive resource on the latest methods and techniques in document image processing and recognition. Each chapter provides a clear overview of the topic followed by the state of the art of techniques used - including elements of comparison between them - along with supporting references to archival publications, for those interested in delving deeper into topics addressed. Rather than favor a particular approach, the text enables the reader to make an informed decision for their specific problems.
List of contents
A Brief History of Documents and Writing Systems.- Machine-printed Character Recognition.- Handprinted Character and Word Recognition.- Continuous Handwritten Script Recognition.- Middle Eastern Character Recognition.- Asian Character Recognition.- Graphics Recognition Techniques.- An Overview of Symbol Recognition.- Analysis and Interpretation of Graphical Documents.- Logo and Trademark Recognition.- Recognition of Tables and Forms.- Document Creation, Image Acquisition and Document Quality.- Processing Mathematical Notation.- Document Analysis in Postal Applications and Check Processing.- Analysis and Recognition of Music Scores.- Analysis of Documents Born Digital.- Image Based Retrieval and Keyword.- Spotting in Documents.- Text Localization and Recognition in Images and Video.- Online Handwriting Recognition.- Online Signature Verification.- Sketching Interfaces.- Datasets and Annotations for Document Analysis and Recognition.- The Evolution of Document Image Analysis.- Tools and Metrics for Document Analysis Systems Evaluation.- Imaging Techniques in Document Analysis Processes.- Page Segmentation Techniques in Document Analysis.- Analysis of the Logical Layout of Documents.- Page Similarity and Classification.- Text Segmentation for Document Recognition.- Language, Script and Font Recognition.- Part A, Introduction, Background and Fundamentals.- Part B, Page Analysis.- Part C, Text Recognition.- Part D, Processing of Non-textual Information.- Part E, Applications.- Part F, Analysis of Online Data.- Part G, Evaluation and Benchmarking.
About the author
Dr. David Doermann is Senior Research Scientist and Director of the Laboratory for Language and Media Processing at the University of Maryland Institute for Advanced Computer Studies, College Park, MD, USA. He is also President and co-founder of Applied Media Analysis, Inc., and Editor-in-Chief of the International Journal on Document Analysis and Recognition.
Dr. Karl Tombre is Professor at École des Mines de Nancy (Institut National Polytechnique de Lorraine), Villers-lès-Nancy, France, and on secondment to Institut National de Recherche en Informatique et an Automatique (INRIA), where he is Director of the INRIA Nancy - Grand Est research center. He is also Editor-in-chief of the International Journal on Document Analysis and Recognition.
Report
From the book reviews:
"This edited compendium of chapters represents the largest effort to date to bring together the breadth and depth of image processing research for document text extraction, segmentation of document image into picture and text zones, and general optical character recognition (OCR) of the international family of foreign languages. ... will appeal to the widest audience possible, including academicians, practitioners, library science and legal professionals, and all who are interested in the efficient storage and retrieval of vast numbers of documents." (R. Goldberg, Computing Reviews, October, 2014)
