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Kokubunji, Tokyo, Japan
Oct. 26, 2004 to Oct. 29, 2004
ISBN: 0-7695-2187-8
pp: 9-13
Lionel Prevost , Laboratoire des Instruments et Systèmes déIle de France
Loïc Oudot , Laboratoire des Instruments et Systèmes déIle de France
ABSTRACT
We recently developed a handwritten text recognizer for on-line text written on a touch-terminal. This system based on the activation-verification cognitive model. It composed of three experts dedicated respectively to signal segmentation in symbols, symbol classification and lexical analysis of the classification results. The baseline system is writer-independent. We present in this paper several strategies of self-supervised writer-adaptation that we compare to the supervised adaptation scheme. The best strategy called "prototype dynamic management" modify the recognizer parameters allowing to get results close to the supervised methods. Results, are presented on a 90 texts (5 400 words) database written by 38 different writers.
INDEX TERMS
handwriting recognition, self-supervised adaptation, model-based classifier
CITATION
Lionel Prevost, Loïc Oudot, "Self-Supervised Adaptation for On-Line Text Recognition", IWFHR, 2004, Proceedings. Ninth International Workshop on Frontiers in Handwriting Recognition, Proceedings. Ninth International Workshop on Frontiers in Handwriting Recognition 2004, pp. 9-13, doi:10.1109/IWFHR.2004.93
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