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Comparison of Gabor-Based Features for Writer Identification of Farsi/Arabic Handwriting

Abstract : Writer identification recently has been studied and it has a wide variety of applications. Most studies are based on English documents with the assumption that the written text is fixed (text-dependent methods) and no research has been reported on Farsi or Arabic documents. In this paper, we have proposed a method for off-line writer identification based on Farsi handwriting, which is text-independent. Based on idea that has been presented in previous studies, in this paper we assume handwriting as texture image and a set of features which are based on multi-channel Gabor filtering and co-occurrence matrix features, are extracted from preprocessed image of documents. Experimental results demonstrate that the best result, 92% correct identification in a hit list with size 3 and 88% in a hit list with size 1, is acquired by using Gaborenergy features on Farsi handwritten documents from 25 peoples.
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Contributor : Anne Jaigu <>
Submitted on : Friday, October 6, 2006 - 3:45:53 PM
Last modification on : Friday, March 2, 2018 - 3:04:02 PM
Long-term archiving on: : Tuesday, April 6, 2010 - 6:52:00 PM


  • HAL Id : inria-00104466, version 1



F. Shahabi, M. Rahmati. Comparison of Gabor-Based Features for Writer Identification of Farsi/Arabic Handwriting. Tenth International Workshop on Frontiers in Handwriting Recognition, Université de Rennes 1, Oct 2006, La Baule (France). ⟨inria-00104466⟩



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