Mohamed E Hussein

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

TitleWindow-Based Descriptors for Arabic Handwritten Alphabet Recognition: A Comparative Study on a Novel Dataset
Publication TypeJournal Article
Year of Publication2014
AuthorsM. Torki, M. E. Hussein, A. Elsallamy, M. Fayyaz, and S. Yaser
Abstract

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.

URLhttp://arxiv.org/abs/1411.3519
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