Dempster-Shafer based rejection strategy for handwritten word recognition

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

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

In this paper, a novel rejection strategy is proposed to optimize the reliability of a handwritten word recognition system. The proposed approach is based on several steps. First, we combine the outputs of several HMM classifiers using the Dempster-Shafer theory (DST). Then, we take advantage of the expressivity of mass functions (the counter part of probability distributions in DST) to characterize the quality/reliability of the classification. Finally, we use this characterization to decide whether a test word is rejected or not. Experiments carried out on RIMES and IFN/ENIT datasets show that the proposed approach outperforms other state-of-the-art rejection methods.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Thomas Burger, Yousri Kessentini, Thierry Paquet. Dempster-Shafer based rejection strategy for handwritten word recognition. he Eleventh International Conference on Document Analysis and Recognition, 2011, Beijing, China. ⟨10.1109/ICDAR.2011.112⟩. ⟨hal-00599672⟩