On-line writer adaptation for handwriting recognition using fuzzy inference systems

Harold Mouchère 1 Eric Anquetil 1 Nicolas Ragot 1
1 IMADOC - Interprétation et Reconnaissance d’Images et de Documents
UR1 - Université de Rennes 1, INSA Rennes - Institut National des Sciences Appliquées - Rennes, CNRS - Centre National de la Recherche Scientifique : UMR6074
Abstract : We present an automatic on-line adaptation mechanism to the writer's handwriting style for the recognition of isolated handwritten characters. The classifier is based on a fuzzy inference system (FIS). This FIS is composed of fuzzy prototypes which represent the intrinsic properties of the classes and it uses numeric conclusions. The proposed adaptation mechanism affects both the conclusions of the rules and the fuzzy prototypes of the premises by re-centering and re-shaping them. Doing so, the FIS is automatically fitted to the handwriting style of the writer that is currently using the system. This adaptation mechanism has been tested with 8 different writers. The results show the adaptation mechanism is able to improve the recognition rate from 88% to 98.2% in average for the 26 Latin letters.
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Submitted on : Wednesday, April 12, 2006 - 11:29:46 AM
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Harold Mouchère, Eric Anquetil, Nicolas Ragot. On-line writer adaptation for handwriting recognition using fuzzy inference systems. 8th International Conference on Document Analysis and Recognition - ICDAR'05, Aug 2005, Seoul/Korea. ⟨inria-00001246⟩

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