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