Dealing with precise and imprecise decisions with a Dempster-Shafer Theory based algorithm in the context of handwriting recognition

Thomas Burger (1) , Yousri Kessentini (2) , Thierry Paquet (3)

1 Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (UMR 3192)
2 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes
3 DocApp - LITIS - Equipe Apprentissage

The classification process in handwriting recognition is designed to provide lists of results rather than single results, so that context models can be used as post-processing. Most of the time, the length of the list is determined once and for all the items to classify. Here, we present a method based on Dempster-Shafer theory that allows a different length list for each item, depending on the precision of the information involved in the decision process. As it is difficult to compare the results of such an algorithm to classical accuracy rates, we also propose a generic evaluation methodology. Finally, this algorithm is evaluated on Latin and Arabic handwritten isolated word datasets.

Domaines: Traitement du texte et du document

Thomas Burger, Yousri Kessentini, Thierry Paquet. Dealing with precise and imprecise decisions with a Dempster-Shafer Theory based algorithm in the context of handwriting recognition. ICFHR 2010, 2010, Kolkata, India. ⟨10.1109/ICFHR.2010.64⟩. ⟨hal-00493829⟩