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

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