Items related to Handbook of Document Image Processing and Recognition
Synopsis
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.
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From the Back Cover
The Handbook of Document Image Processing and Recognition provides a consistent, comprehensive resource on the available methods and techniques in document image processing and recognition. It includes unified comparison and contrast analysis of algorithms in standard table formats. Thus, it educates the reader in order to help them to make informed decisions on their particular problems.
The handbook is divided into several parts. Each part starts with an introduction written by the two editors. These introductions set the general framework for the main topic of each part and introduces the contribution of each chapter within the framework. The introductions are followed by several chapters written by established experts of the field.
Each chapter provides the reader with a clear overview of the topic and of the state of the art in techniques used (including elements of comparison between them). Each chapter is structured in the same way: It starts with an introductory text, concludes with a summary of the main points addressed in the chapter and ends with a comprehensive list of references. Whenever appropriate, the authors include specific sections describing and pointing to consolidated software and/or reference datasets. Numerous cross-references between the chapters ensure this is a truly integrated work, without unnecessary duplications and overlaps between chapters.
This reference work is intended for the use by a wide audience of readers from around the world such as graduate students, researchers, librarians, lecturers, professionals, and many other people.
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 Université de Lorraine, France, one of the lagest French universities, where he currently is vice-president in charge of partnerships and international affairs. He was one of the founders, and for many years an editor-in-chief of the International Journal on Document Analysis and Recognition. From 2007 to 2012 he was director of the Inria Nancy - Grand Est research center, a large public research center in computer science and applied mathematics. From 2006 to 2008 he was President of the International Association for Pattern Recognition (IAPR).
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