Optical character recognition systems for different languages with soft computing
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Bibliographic Information
Optical character recognition systems for different languages with soft computing
（Studies in fuzziness and soft computing, v. 352）
Springer, c2017
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Includes bibliographical references and index
Description and Table of Contents
Description
The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.
Table of Contents
1 Introduction.-2 Optical Character Recognition Systems.-3 Soft Computing Techniques for Optical Character Recognition Systems.-4 Optical Character Recognition Systems for English language.-5 Optical Character Recognition Systems for French language.-6 Optical Character Recognition Systems for German language.-7 Optical Character Recognition Systems for Latin language.-8 Optical Character Recognition Systems for Hindi language.-9 Optical Character Recognition Systems for Gujrati language.-10 Summary and Future Research.-Index.
by "Nielsen BookData"