Optical Character Recognition Systems for Different Languages with Soft Computing

Arindam Chaudhuri

ISBN 10: 3319502514 / ISBN 13: 9783319502519

Published by Springer International Publishing, Springer International Publishing, 2017

About this Item

Druck auf Anfrage Neuware - Printed after ordering - 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.

Seller Inventory # 9783319502519

Bibliographic Details

• Title: Optical Character Recognition Systems for Different Languages with Soft Computing
• Publisher: Springer International Publishing, Springer International Publishing
• Publication Date: 2017
• Language: English
• ISBN 10: 3319502514
• ISBN 13: 9783319502519
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 21D millimeters 241 millimeters width by 160 millimeters height by 21 millimeters depth
• Weight: 571 grams

About this title

Synopsis

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.