Earticle

초록

영어

Automatic off-line Arabic handwriting recognition still faces a big challenges. Due to the cursive nature of the Arabic language, most of published works are based on recognition of a whole word without segmentation. This paper presents a new framework for the recognition of handwritten Arabic words based on segmentation. This framework involves two phases (training phase and testing phase). In the training phase, Arabic handwritten characters were trained to be recognized, while in the testing phase, words were segmented into characters for recognition. Classification is achieved in two steps (classification of the segmented characters and classification of the word). A dictionary is constructed and used to correct any errors occurring during the previous stages of the recognition process. This work has been tested with IFN/ENIT database and a comparison made against some existing methods and promising results have been obtained.

목차

Abstract
 1. Introduction
 2. Challenges and Motivation
 3. A Framework based on Segmentation
  3.1. Training Phase
  3.2. Testing Phase
 4. Experimental Results
  4.1. Segmentation of the Word into Characters
  4.2. Classification of the Segmented Characters
  4.3. Classification of Words
 5. Conclusion and Future Work
 References

키워드

저자

• A. Lawgali [ University of Benghazi, Libya ]
• M. Angelova [ Northumbria University,Newcastle upon Tyne, UK ]
• A. Bouridane [ Northumbria University,Newcastle upon Tyne, UK ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605