Arabic handwritten script recognition system based on HOG and Gabor features
Joint Authors
Uwashi, Muhammad
Hani, Ansar
Khayr Allah, Munji
Source
The International Arab Journal of Information Technology
Issue
Vol. 14, Issue 4A (s) (31 Jul. 2017), pp.639-646, 8 p.
Publisher
Publication Date
2017-07-31
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Considered as among the most thriving applications in the pattern recognition field, handwriting recognition, despite being quite matured, it still raises so many research questions which are a challenge for the Arabic Handwritten Script.
In this paper, we investigate Support Vector Machines (SVM) for Arabic Handwritten Script recognition.
The proposed method takes the handcrafted feature as input and proceeds with a supervised learning algorithm.
As designed feature, Histogram of Oriented Gradients (HOG) is used to extract feature vectors from textual images.
The Multi-class SVM with an RBF kernel was chosen and tested on Arabic Handwritten Database named IFN/ENIT.
Performances of the feature extraction method are compared with Gabor filter, showing the effectiveness of the HOG descriptor.
We present simulation results so that we will be able to prove that the good functioning on the suggested system based-SVM classifier.
American Psychological Association (APA)
Uwashi, Muhammad& Hani, Ansar& Khayr Allah, Munji. 2017. Arabic handwritten script recognition system based on HOG and Gabor features. The International Arab Journal of Information Technology،Vol. 14, no. 4A (s), pp.639-646.
https://search.emarefa.net/detail/BIM-902991
Modern Language Association (MLA)
Uwashi, Muhammad…[et al.]. Arabic handwritten script recognition system based on HOG and Gabor features. The International Arab Journal of Information Technology Vol. 14, no. 4A (Special issue) (2017), pp.639-646.
https://search.emarefa.net/detail/BIM-902991
American Medical Association (AMA)
Uwashi, Muhammad& Hani, Ansar& Khayr Allah, Munji. Arabic handwritten script recognition system based on HOG and Gabor features. The International Arab Journal of Information Technology. 2017. Vol. 14, no. 4A (s), pp.639-646.
https://search.emarefa.net/detail/BIM-902991
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 644-646
Record ID
BIM-902991