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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
LITIS - Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes
Abstract : 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
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Conference papers
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https://hal-normandie-univ.archives-ouvertes.fr/hal-02087617
Contributor : Thierry Paquet <>
Submitted on : Tuesday, April 2, 2019 - 11:33:07 AM
Last modification on : Tuesday, November 24, 2020 - 9:38:03 AM

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COMUE-NORMANDIE | LITIS | INSA-ROUEN | UNIROUEN | UNILEHAVRE | INSA-GROUPE

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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⟩

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