Keyword spotting in handwritten documents based on a generic text line HMM and a SVM verification

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

1 MIRACL - Multimedia, InfoRmation systems and Advanced Computing Laboratory
2 LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes
3 DocApp - LITIS - Equipe Apprentissage

In this paper, we propose a novel system for keyword spotting in handwritten documents. Our approach proceeds in two steps: first a generic text line HMM provides a simple and flexible tool to localize the keyword and its character boundaries. In the second step, a SVM based verification system estimates and combines the character probabilities to provide keyword confidence scores which are further combined with the HMM score. The system has been evaluated on a public handwritten document database used for the 2011 ICDAR handwriting recognition competitions and shows that the verification stage improves the performance and outperforms some other state-of-the-art approaches.

Keywords: Hidden Markov models; Handwriting recognition; Image recognition

Domains: Computer Science [cs]; Computer Vision and Pattern Recognition [cs.CV]

Yousri Kessentini, Thierry Paquet. Keyword spotting in handwritten documents based on a generic text line HMM and a SVM verification. 2015 13th International Conference on Document Analysis and Recognition (ICDAR), Aug 2015, Tunis, France. pp.41-45, ⟨10.1109/ICDAR.2015.7333722⟩. ⟨hal-02087617⟩