Guide to OCR for Indic Scripts

Document Recognition and Retrieval

  • Venu Govindaraju
  • Srirangaraj (Ranga) Setlur

Part of the Advances in Pattern Recognition book series (ACVPR)

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Section: Recognition of Indic scripts

    1. Front Matter
      Pages 1-1
    2. C.V. Jawahar, Anand Kumar, A. Phaneendra, K.J. Jinesh
      Pages 3-25
    3. Jignesh Dholakia, Atul Negi, S. Rama Mohan
      Pages 73-95
    4. R.S. Umesh, Peeta Basa Pati, A.G. Ramakrishnan
      Pages 97-124
    5. N.V. Neeba, Anoop Namboodiri, C.V. Jawahar, P.J. Narayanan
      Pages 125-146
    6. Aparna Kokku, Srinivasa Chakravarthy
      Pages 147-162
    7. Omar Mukhtar, Srirangaraj Setlur, Venu Govindaraju
      Pages 163-171
    8. Prem Natarajan, Ehry MacRostie, Michael Decerbo
      Pages 173-180
    9. Mudit Agrawal, Huanfeng Ma, David Doermann
      Pages 181-207
    10. A. Bharath, Sriganesh Madhvanath
      Pages 209-234
  3. Section: Retrieval of Indic documents

    1. Front Matter
      Pages 235-235
    2. Peter M. Scharf, Malcolm Hyman
      Pages 237-247
    3. Zhixin Shi, Srirangaraj Setlur, Venu Govindaraju
      Pages 249-267
    4. Gaurav Harit, Santanu Chaudhury, Ritu Garg
      Pages 269-284
    5. Anurag Bhardwaj, Srirangaraj Setlur, Venu Govindaraju
      Pages 285-299
    6. Prasenjit Majumder, Mandar Mitra
      Pages 301-314
  4. Back Matter
    Pages 315-325

About this book

Introduction

Optical Character Recognition (OCR) is a key enabling technology critical to creating indexed, digital library content, and it is especially valuable for Indic scripts, for which there has been very little digital access.

Indic scripts, the ancient Brahmi scripts prevalent in the Indian subcontinent, present some challenges for OCR that are different from those faced with Latin and Oriental scripts. But properly utilized, OCR will help to make Indic digital archives practically accessible to researchers and lay users alike by creating searchable indexes and machine-readable text repositories.

This unique guide/reference is the very first comprehensive book on the subject of OCR for Indic scripts, providing an overview of the state-of-the-art research in this field as well as other issues related to facilitating query and retrieval of Indic documents from digital libraries. All major research groups working in this area are represented in this book, which is divided into sections on recognition of Indic scripts and retrieval of Indic documents.

Topics and features:

  • Contains contributions from the leading researchers in the field
  • Discusses data set creation for OCR development
  • Describes OCR systems that cover eight different scripts: Bangla, Devanagari, Gurmukhi, Gujarati, Kannada, Malayalam, Tamil, and Urdu (Perso-Arabic)
  • Explores the challenges of Indic script handwriting recognition in the online domain
  • Examines the development of handwriting-based text input systems
  • Describes ongoing work to increase access to Indian cultural heritage materials
  • Provides a section on the enhancement of text and images obtained from historical Indic palm leaf manuscripts
  • Investigates different techniques for word spotting in Indic scripts
  • Reviews mono-lingual and cross-lingual information retrieval in Indic languages

This is an excellent reference for researchers and graduate students studying OCR technology and methodologies. This volume will contribute to opening up the rich Indian cultural heritage embodied in millions of ancient and contemporary documents spanning topics such as science, literature, medicine, astronomy, mathematics and philosophy.

Venu Govindaraju FIEEE FIAPR, is a Distinguished Professor of Computer Science and Engineering at the University at Buffalo. He has over 20 years of research experience in pattern recognition, information retrieval and biometrics. His seminal work on handwriting recognition was at the core of the first handwritten address interpretation system used by the U.S. Postal Service.

Srirangaraj Setlur SMIEEE, is a Principal Research Scientist at the University at Buffalo. He has over 15 years of research experience in pattern recognition that includes NSF sponsored work on multilingual OCR technologies for digital libraries and other applications. His work on postal automation has led to technology adopted by the U.S. Postal Service, and Royal Mail in the U.K.

Keywords

Digital Libraries Document Retrieval Indic Scripts OCR Text Recognition handwriting recognition

Editors and affiliations

  • Venu Govindaraju
    • 1
  • Srirangaraj (Ranga) Setlur
    • 2
  1. 1.Analysis & Recognition (CEDAR)Center of Excellence for DocumentAmherstU.S.A.
  2. 2.Analysis & Recognition (CEDAR)Center of Excellence for DocumentAmherstU.S.A.

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-84800-330-9
  • Copyright Information Springer-Verlag London 2010
  • Publisher Name Springer, London
  • eBook Packages Computer Science
  • Print ISBN 978-1-84800-329-3
  • Online ISBN 978-1-84800-330-9
  • Series Print ISSN 1617-7916
  • About this book