Arabic and Chinese handwriting recognition : SACH 2006 summit, College Park, MD, USA, September 27-28, 2006 : selected papers / David Doermann, Stefan Jaeger (eds.)

The book constitutes the refereed proceedings of the Summit on Arabic and Chinese Handwriting Recognition, SACH 2006, held in College Park, USA, September 27-28, 2006. The 16 revised full papers presented were carefully reviewed and selected from a total of over 60 submissions. The first six papers...

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Bibliographic Details
Online Access: Full Text (via Springer)
Corporate Author: SACH 2006 College Park, Md.
Other Authors: Doermann, David S. (David Scott), Jäger, Stefan, Dr
Other title:SACH 2006.
Format: Conference Proceeding eBook
Language:English
Published: Berlin ; New York : Springer, ©2008.
Series:Lecture notes in computer science ; 4768.
LNCS sublibrary. Image processing, computer vision, pattern recognition, and graphics.
Subjects:
Table of Contents:
  • Visual Recognition of Arabic Handwriting: Challenges and New Directions
  • A Review on Persian Script and Recognition Techniques
  • Human Reading Based Strategies for Off-Line Arabic Word Recognition
  • Versatile Search of Scanned Arabic Handwriting
  • A Two-Tier Arabic Offline Handwriting Recognition Based on Conditional Joining Rules
  • Databases and Competitions: Strategies to Improve Arabic Recognition Systems
  • Handwritten Chinese Character Recognition: Effects of Shape Normalization and Feature Extraction
  • How to Deal with Uncertainty and Variability: Experience and Solutions
  • An Efficient Candidate Set Size Reduction Method for Coarse-Classification in Chinese Handwriting Recognition
  • Techniques for Solving the Large-Scale Classification Problem in Chinese Handwriting Recognition
  • Recent Results of Online Japanese Handwriting Recognition and Its Applications
  • Segmentation-Driven Offline Handwritten Chinese and Arabic Script Recognition
  • Multi-character Field Recognition for Arabic and Chinese Handwriting
  • Multi-lingual Offline Handwriting Recognition Using Hidden Markov Models: A Script-Independent Approach
  • Handwritten Character Recognition of Popular South Indian Scripts
  • Ensemble Methods to Improve the Performance of an English Handwritten Text Line Recognizer.