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  • Conference proceedings
  • © 2008

Arabic and Chinese Handwriting Recognition

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

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

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Conference series link(s): SACH: Summit on Arabic and Chinese Handwriting Recognition

Conference proceedings info: SACH 2006.

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Table of contents (16 papers)

  1. Front Matter

  2. A Review on Persian Script and Recognition Techniques

    • Sara Izadi, Javad Sadri, Farshid Solimanpour, Ching Y. Suen
    Pages 22-35
  3. Human Reading Based Strategies for Off-Line Arabic Word Recognition

    • Abdel Belaïd, Christophe Choisy
    Pages 36-56
  4. Versatile Search of Scanned Arabic Handwriting

    • Sargur N. Srihari, Gregory R. Ball, Harish Srinivasan
    Pages 57-69
  5. Recent Results of Online Japanese Handwriting Recognition and Its Applications

    • Masaki Nakagawa, Junko Tokuno, Bilan Zhu, Motoki Onuma, Hideto Oda, Akihito Kitadai
    Pages 170-195
  6. Multi-character Field Recognition for Arabic and Chinese Handwriting

    • Daniel Lopresti, George Nagy, Sharad Seth, Xiaoli Zhang
    Pages 218-230
  7. Multi-lingual Offline Handwriting Recognition Using Hidden Markov Models: A Script-Independent Approach

    • Prem Natarajan, Shirin Saleem, Rohit Prasad, Ehry MacRostie, Krishna Subramanian
    Pages 231-250
  8. Handwritten Character Recognition of Popular South Indian Scripts

    • Umapada Pal, Nabin Sharma, Tetsushi Wakabayashi, Fumitaka Kimura
    Pages 251-264
  9. Back Matter

Other Volumes

  1. Arabic and Chinese Handwriting Recognition

About this book

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

Buying options

eBook USD 39.99
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (Canada)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions