95 articles 

inria-00108307, version 1

HMM-Based On-Line Recognition of Handwritten Whiteboard Notes

Marcus Liwicki () 1, Horst Bunke () 1

Tenth International Workshop on Frontiers in Handwriting Recognition (2006)

Abstract: In this paper we present an on-line recognition system for handwritten texts acquired from a whiteboard. This input modality has received relatively little attention in the handwriting recognition community in the past. The system proposed in this paper uses state-of-the-art normalization and feature extraction strategies to transform a handwritten text line into a sequence of feature vectors. Additional preprocessing techniques are introduced, which significantly increase the word recognition rate. For classification, Hidden Markov Models are used together with a statistical language model. In writer independent experiments we achieved word recognition rates of 67.3% on the test set when no language model is used, and 70.8% by including a language model.

  • 1:  Institute of Computer Science and Applied Mathematics (IAM)
  • University of Bern
  • Domain : Computer Science/Document and Text Processing
    Computer Science/Computer Vision and Pattern Recognition
  • Keywords : Handwritten Text Recognition – HMM – On-line – Writer-Independend
  • Comment : http://www.suvisoft.com
  • inria-00108307, version 1
  • oai:hal.inria.fr:inria-00108307
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  • Submitted on: Friday, 20 October 2006 13:35:57
  • Updated on: Friday, 20 October 2006 13:37:18