Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances

Ahmed, Rami; Dashtipour, Kia; Gogate, Mandar; Raza, Ali; Zhang, Rui; Huang, Kaizhu; Hawalah, Ahmad; Adeel, Ahsan; Hussain, Amir

Abstract

In pattern recognition, automatic handwriting recognition (AHWR) is an area of research that has developed rapidly in the last few years. It can play a significant role in broad-spectrum of applications rending from, bank cheque processing, application forms processing, postal address processing, to text-to-speech conversion. However, most research efforts are devoted to English-language only. This work focuses on developing Offline Arabic Handwriting Recognition (OAHR). The OAHR is a very challenging task due to some unique characteristics of the Arabic script such as cursive nature, ligatures, overlapping, and diacritical marks. In the recent literature, several effective Deep Learning (DL) approaches have been proposed to develop efficient AHWR systems. In this paper, we commission a survey on emerging AHWR technologies with some insight on OAHR background, challenges, opportunities, and future research trends.

Citation

Ahmed, R., Dashtipour, K., Gogate, M., Raza, A., Zhang, R., Huang, K., Hawalah, A., Adeel, A., & Hussain, A. (2019, July). Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances. Presented at 10th International Conference, BICS 2019, Guangzhou, China

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 10th International Conference, BICS 2019
• Start Date: Jul 13, 2019
• End Date: Jul 14, 2019
• Online Publication Date: Feb 1, 2020
• Publication Date: 2020
• Deposit Date: Apr 26, 2022
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Pages: 457-468
• Series Title: Lecture Notes in Computer Science
• Series Number: 11691
• Series ISSN: 0302-9743
• Book Title: Advances in Brain Inspired Cognitive Systems: 10th International Conference, BICS 2019, Guangzhou, China, July 13–14, 2019, Proceedings
• ISBN: 978-3-030-39430-1
• DOI: https://doi.org/10.1007/978-3-030-39431-8_44
• Keywords: Offline Arabic Handwritten Recognition, Offline Arabic database, Deep Learning
• Public URL: http://researchrepository.napier.ac.uk/Output/2867038