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Arabic and Chinese Handwriting Recognition

SACH 2006 Summit College Park, MD, USA, September 27-28, 2006 Selected Papers

  • Editors
  • David Doermann
  • Stefan Jaeger
Conference proceedings SACH 2006

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4768)

Table of contents

  1. Front Matter
  2. Sara Izadi, Javad Sadri, Farshid Solimanpour, Ching Y. Suen
    Pages 22-35
  3. Abdel Belaïd, Christophe Choisy
    Pages 36-56
  4. Sargur N. Srihari, Gregory R. Ball, Harish Srinivasan
    Pages 57-69
  5. Masaki Nakagawa, Junko Tokuno, Bilan Zhu, Motoki Onuma, Hideto Oda, Akihito Kitadai
    Pages 170-195
  6. Daniel Lopresti, George Nagy, Sharad Seth, Xiaoli Zhang
    Pages 218-230
  7. Prem Natarajan, Shirin Saleem, Rohit Prasad, Ehry MacRostie, Krishna Subramanian
    Pages 231-250
  8. Umapada Pal, Nabin Sharma, Tetsushi Wakabayashi, Fumitaka Kimura
    Pages 251-264
  9. Back Matter

About these proceedings

Introduction

In the fall of 2006, the University of Maryland, along with various government and industrial sponsors, invited leading researchers from all over the world to a two-day Summit on Arabic and Chinese Handwriting Recognition (SACH 2006). The event acted as a complement to the biennial Symposium on Document Image Understanding Technology (SDIUT), providing a focused glimpse into the state of the art in Arabic and Chinese handwriting recognition. It offered a forum for interaction with prominent researchers at the forefront of the scientific community and provided an opportunity for participants to help explore possible directions of the field. This book is a result of the expansion, peer review, and revision of selected papers presented at this meeting. Handwriting recognition remains the Holy Grail of document analysis, and Arabic and Chinese scripts embrace many of the most significant challenges. We are pleased to have 16 scientific papers covering the original topics of handwritten Arabic and Chinese, as well as 2 papers covering other handwritten scripts. We asked each author to not only describe the techniques used in addressing the problem, but to attempt to identify the key research challenges and problems that the community faces. The result is an impressive collection of manuscripts that provide various detailed views of the state of research. In this book, six articles deal directly with Arabic handwriting. • Cheriet provides an overview of the problems of Arabic recognition and how systems can use natural language processing techniques to correct errors in lexicon-based systems.

Keywords

Biometric Applications Commercial Systems Databases Feature Extraction Handwriting Models Handwritten OCR Information Retrieval Language Identification Linguistic Processing Performance Preprocessing and Segmentation classification cognition language uncertainty

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-78199-8
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-78198-1
  • Online ISBN 978-3-540-78199-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site