Deep learning algorithms for arabic handwriting recognition: A review

Ahmed AL-Saffar, Suryanti Awang, Wafaa Al-Saiagh, Sabrina Tiun, A. S. Al-khaleefa

Research output: Contribution to journalArticle

Abstract

Computer vision (CV) refers to the study of the computer simulation of human visual science. Major task of CV is to collect images (or video) so that they could be used for analysis, gathering information, and making decisions or judgements. CV has greatly progressed and developed in the past few decades. In recent years, deep learning (DL) approaches have won several contests in pattern recognition and machine learning. (DL) dramatically improved the state-of-the-art in visual object recognition, object detection, handwritten recognition and many other domains. Handwritten recognition technique is one of this tasks that targeted to extract the text from documents or another images type. In contrast to the English domain, there are a limited works on the Arabic language that achieved satisfactory results, Due to the Arabic language cursive nature that induces many technical difficulties. This paper highlighted the pre-processing and binarization methods that have been used in the literature along with proposed numerous directions for developing. We review the various current deep learning approaches and tools used for Arabic handwritten recognition (AHWR), identified challenges along this line of this research, and gives several recommendations including a framework based (DL) that is particularly applicable for dealing with cursive nature languages.

Original languageEnglish
Pages (from-to)344-353
Number of pages10
JournalInternational Journal of Engineering and Technology(UAE)
Volume7
Issue number3.20 Special Issue 20
DOIs
Publication statusPublished - 1 Jan 2018

Fingerprint

Handwriting
Learning algorithms
Learning
Computer vision
Language
Information analysis
Object recognition
Pattern recognition
Learning systems
Computer Simulation
Decision making
Decision Making
Deep learning
Recognition (Psychology)
Computer simulation
Processing
Research

Keywords

  • Arabic OCR
  • Deep convolutional neural networks
  • Image processing
  • Pattern recognition
  • Text recognition

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science (miscellaneous)
  • Environmental Engineering
  • Chemical Engineering(all)
  • Engineering(all)
  • Hardware and Architecture

Cite this

Deep learning algorithms for arabic handwriting recognition : A review. / AL-Saffar, Ahmed; Awang, Suryanti; Al-Saiagh, Wafaa; Tiun, Sabrina; Al-khaleefa, A. S.

In: International Journal of Engineering and Technology(UAE), Vol. 7, No. 3.20 Special Issue 20, 01.01.2018, p. 344-353.

Research output: Contribution to journalArticle

AL-Saffar, Ahmed ; Awang, Suryanti ; Al-Saiagh, Wafaa ; Tiun, Sabrina ; Al-khaleefa, A. S. / Deep learning algorithms for arabic handwriting recognition : A review. In: International Journal of Engineering and Technology(UAE). 2018 ; Vol. 7, No. 3.20 Special Issue 20. pp. 344-353.
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