Arabic font recognition based on a texture analysis - Archive ouverte HAL
Communication Dans Un Congrès Année : 2014

Arabic font recognition based on a texture analysis

Faten Jaiem Kallel
  • Fonction : Auteur
Slim Kanoun
  • Fonction : Auteur

Résumé

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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Dates et versions

hal-01313191 , version 1 (09-05-2016)

Identifiants

Citer

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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