Arabic font recognition based on a texture analysis

Faten Jaiem Kallel Slim Kanoun Véronique Eglin 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : Existing works on the font recognition and based on texture analysis often used Gray Level Cooccurence Matrix (GLCM), Gabor Filters (GF) and wavelet. In this paper, we use Steerable Pyramid (SP) for texture analysis of arabic homogeneous and normalized text block in order to font recognition. In this frameworks, we use K Nearest Neighbors (KNN) and Back-propagation Artificial Neural Network (BpANN) for classification. The Obtained experimental results on the APTID/MF database (Arabic Printed Text Image/ Multi- Font) are encouragents.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01313191
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Submitted on : Monday, May 9, 2016 - 4:11:59 PM
Last modification on : Friday, January 11, 2019 - 5:08:45 PM

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Faten Jaiem Kallel, Slim Kanoun, Véronique Eglin. Arabic font recognition based on a texture analysis. ICFHR, International Conference on Frontiers in Handwriting Recognition, Sep 2014, Heraklion, Crète, Greece. pp.673-677, ⟨10.1109/ICFHR.2014.118⟩. ⟨hal-01313191⟩

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