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This paper presents a comparative study for window-based descriptors on theapplication of Arabic handwritten alphabet recognition. We show a detailedexperimental evaluation of different descriptors with several classifiers. Theobjective of the paper is to evaluate different window-based descriptors on theproblem of Arabic letter recognition. Our experiments clearly show that theyperform very well. Moreover, we introduce a novel spatial pyramid partitioningscheme that enhances the recognition accuracy for most descriptors. Inaddition, we introduce a novel dataset for Arabic handwritten isolated alphabetletters, which can serve as a benchmark for future research.

Window-Based Descriptors for Arabic Handwritten Alphabet Recognition: A Comparative Study on a Novel Dataset