Combination of Local and Global Vision Modelling for Arabic Handwritten Words Recognition

Samia Snoussi-Maddouri Hamidi Amiri Abdel Belaïd 1 Christophe Choisy 1
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LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
Abstract : We propose in this paper a recognition system of Arabic hand-written words issued from literal amounts of Arabic checks. This system is based on the concept of PERCEPTRO developed by M. Côté for Latin word recognition. It is a specific NN, named Transparent Neural Network (TNN), combining a global and a local vision modelling (GVM - LVM) of the word. In the forward propagation movement, the former (GVM) proposes a list of structural features characterising the presence of some letters in the word. GVM proposes a list of possible letters and words containing these characteristics. Then, in the back-propagation movement, these letters are confirmed or not according to their proximity with corresponding printed letters. The correspondence between the letter shapes and the corresponding printed letters is performed by LVM using the correspondence of their Fourier descriptors, playing the role of a letter shape normalizer.
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Communication dans un congrès
Eighth International Workshop on Frontiers in Handwriting Recognition - IWFHR'02, 2002, Ontario, Canada, 2002
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Soumis le : jeudi 19 octobre 2006 - 09:02:07
Dernière modification le : jeudi 11 janvier 2018 - 06:19:59
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  • HAL Id : inria-00107580, version 1

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Samia Snoussi-Maddouri, Hamidi Amiri, Abdel Belaïd, Christophe Choisy. Combination of Local and Global Vision Modelling for Arabic Handwritten Words Recognition. Eighth International Workshop on Frontiers in Handwriting Recognition - IWFHR'02, 2002, Ontario, Canada, 2002. 〈inria-00107580〉

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