Handwritten word verification by SVM-based hypotheses re-scoring and multiple thresholds rejection

Laurent Guichard 1 Alejandro Toselli 2 Bertrand Coüasnon 1
1 IMADOC - Interprétation et Reconnaissance d’Images et de Documents
UR1 - Université de Rennes 1, INSA Rennes - Institut National des Sciences Appliquées - Rennes, CNRS - Centre National de la Recherche Scientifique : UMR6074
Abstract : In the field of isolated handwritten word recognition, the development of verification systems that optimize the trade-off between performance and reliability is still an active research topic. To minimize the recognition errors, usually, a verification system is used to accept or reject the hypotheses produced by an existing recognition system. In this paper, a novel verification architecture is presented. In essence, the recognition hypotheses, re-scored by a set of the support vector machines, are validated by a verification mechanism based on multiple rejection thresholds. In order to tune these (class-dependent) rejection thresholds, an algorithm based on dynamic programming is proposed which focus on maximizing the recognition rate for a given prefixed error rate.
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Laurent Guichard, Alejandro Toselli, Bertrand Coüasnon. Handwritten word verification by SVM-based hypotheses re-scoring and multiple thresholds rejection. International Conference on Frontiers in Handwriting Recognition, Nov 2010, Kolkata, India. ⟨inria-00542856⟩

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