Offline isolated Arabic handwriting character recognition system based on SVM
Joint Authors
Salam, Mustafa
Abd al-Hasan, Alya Karim
Source
The International Arab Journal of Information Technology
Issue
Vol. 16, Issue 3 (31 May. 2019)6 p.
Publisher
Publication Date
2019-05-31
Country of Publication
Jordan
No. of Pages
6
Main Subjects
Information Technology and Computer Science
Arabic language and Literature
Topics
Abstract EN
This paper proposed a new architecture for Offline Isolated Arabic Handwriting Character Recognition System Based on SVM (OIAHCR).
An Arabic handwriting dataset also proposed for training and testing the proposed system.
Although half of the dataset used for training the SVM and the second half used for testing, the system achieved high performance with less training data.
Besides, the system achieved best recognition accuracy 99.64% based on several feature extraction methods and SVM classifier.
Experimental results show that the linear kernel of SVM is convergent and more accurate for recognition than other SVM kernels.
American Psychological Association (APA)
Salam, Mustafa& Abd al-Hasan, Alya Karim. 2019. Offline isolated Arabic handwriting character recognition system based on SVM. The International Arab Journal of Information Technology،Vol. 16, no. 3.
https://search.emarefa.net/detail/BIM-854835
Modern Language Association (MLA)
Salam, Mustafa& Abd al-Hasan, Alya Karim. Offline isolated Arabic handwriting character recognition system based on SVM. The International Arab Journal of Information Technology Vol. 16, no. 3 (May. 2019).
https://search.emarefa.net/detail/BIM-854835
American Medical Association (AMA)
Salam, Mustafa& Abd al-Hasan, Alya Karim. Offline isolated Arabic handwriting character recognition system based on SVM. The International Arab Journal of Information Technology. 2019. Vol. 16, no. 3.
https://search.emarefa.net/detail/BIM-854835
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-854835