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inria-00104760, version 1

Fuzzy Relative Positioning for On-Line Handwritten Stroke Analysis

François Bouteruche () a1, Sébastien Macé () a1, Eric Anquetil () a1

Tenth International Workshop on Frontiers in Handwriting Recognition (2006)

Abstract: This paper deals with the qualitative and robust modelling of the relative positioning of on-line handwritten strokes. We exploit the fuzzy approach to take the imprecision of such relations into account. We first transpose a well-formalized method which proved itself in the domain of image analysis to the on-line case; it aims at evaluating the relation “to be in a given direction” relatively to a reference. Our first contribution is a solution to deal with the particular nature of on-line strokes, which are constituted of non-connected points. Our second and main contribution is a method to learn automatically fuzzy relative position relationships. It aims at evaluating the relation “to be in a given position” relatively to a reference using jointly the direction and the distance. We test the impact of this new fuzzy positioning approach on one possible application: the recognition of handwritten graphic gestures, which requires spatial context information to be discriminated. Whereas the recognition rate is 52.95% without any spatial information, we obtain a maximum of 95.75% when we use learnt relative position relationships.

  • a –  Institut National des Sciences Appliquées de Rennes
  • 1:  IMADOC (IRISA)
  • Institut National des Sciences Appliquées (INSA) - Rennes – CNRS : UMR6074 – Université de Rennes 1
  • Domain : Computer Science/Computer Vision and Pattern Recognition
    Computer Science/Document and Text Processing
  • Keywords : On-line interpretation – Handwritten stroke analysis – Fuzzy positioning – Learning
  • Comment : http://www.suvisoft.com
 
  • inria-00104760, version 1
  • oai:hal.inria.fr:inria-00104760
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  • Submitted on: Monday, 9 October 2006 12:33:50
  • Updated on: Wednesday, 14 March 2007 08:55:30