A Brief History of Documents and Writing Systems.- Document Creation, Image Acquisition and Document Quality.- 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.- Font, Script, and Language Recognition.- Handprinted Character and Word Recognition.- Continuous Handwritten Script Recognition.- Middle Eastern Character Recognition.- Asian Character Recognition.- Post-processing of OCR-ed text.- Graphics Recognition Techniques.- An Overview of Symbol Recognition.- Analysis and Interpretation of Graphical Documents.- Logo and Trademark Recognition.- Recognition of Tables and Forms.- Processing Mathematical Notation.- Document Analysis in Postal Applications and Check Processing.- Digital Library Projects and Historical Documents.- Analysis and Recognition of Music Scores.- Document Analysis for Biometrics and Forensics.- Analysis of Documents Born Digital.- Image Based Retrieval and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.- Tools and Metrics for Document Analysis Systems Evaluation.

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.

A comprehensive reference on the methods and techniques used in document image processing and recognition, for both experienced and novice researchers Integrates and summarizes work on closely related tasks that are treated separately in the field Includes unified comparison and contrast analyses of algorithms in standard table formats Includes supplementary material: sn.pub/extras

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