Combination of Local and Global Vision Modelling for Arabic Handwritten Words RecognitionReport as inadecuate




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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.

Mots-clés : transparent neural network arabic handwriting recognition fourier descriptors réseau transparent reconnaissance de l-écriture arabe





Author: Samia Snoussi-Maddouri Hamidi Amiri Abdel Belaïd - Christophe Choisy -

Source: https://hal.archives-ouvertes.fr/



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