Offline Arabic Handwriting Recognition Using Deep Learning: Comparative Study

Abstract

By virtue of advances in machine learning, handwriting recognition is considered as one of the main research topics in this field. Many studies have been proposed to improve this recognition of handwritten texts for different languages such as Latin and Chinese. Yet, the processing of Arabic texts remains a particularly distinctive problem due to the complicated nature of the Arabic script compared to other scripts. In this work, we display a study and an evaluation of relevant articles recently published in conferences and indexed journals. The core of the problem is to relatively find out an efficient method capable of recognizing the handwritten text by any user via digital devices. In this article, we study the various works interested in the recognition of handwritten Arabic script implemented by deep learning. We thouroughly discuss different classification approaches like CNN, RNN and DBN. The pros and cons of each approach will be presented, as well as their different results.