Recognition of handwritten characters based on wavelet transform and SVM classifier
Joint Authors
Gaceb, Djamel
Aider, Malikah Ait
Hammush, Kamal
Source
The International Arab Journal of Information Technology
Issue
Vol. 15, Issue 6 (30 Nov. 2018)6 p.
Publisher
Publication Date
2018-11-30
Country of Publication
Jordan
No. of Pages
6
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper is devoted to the off-line handwritten character recognition based on the two dimensional wavelet transform and a single support vector machine classifier.
The wavelet transform provides a representation of the image in independent frequency bands.
It performs a local analysis to characterize images of characters in time and scale space.
The wavelet transform provides at each level of decomposition four sub-images: a smooth or approximation sub-image and three detail sub-images.
In handwritten character recognition, the wavelet transform has received more attention and its performance is related not only to the use of the type of wavelet but also to the type of a sub-image used to provide features.
Our objective here is thus to study these two previous points by conducting several tests using several wavelet families and several combinational features derived from sub-images.
They show that the symlet wavelet of order 8 is the most efficient and the features derived from the approximation sub-image allow the best discrimination between the handwritten digits
American Psychological Association (APA)
Aider, Malikah Ait& Hammush, Kamal& Gaceb, Djamel. 2018. Recognition of handwritten characters based on wavelet transform and SVM classifier. The International Arab Journal of Information Technology،Vol. 15, no. 6.
https://search.emarefa.net/detail/BIM-874002
Modern Language Association (MLA)
Aider, Malikah Ait…[et al.]. Recognition of handwritten characters based on wavelet transform and SVM classifier. The International Arab Journal of Information Technology Vol. 15, no. 6 (Nov. 2018).
https://search.emarefa.net/detail/BIM-874002
American Medical Association (AMA)
Aider, Malikah Ait& Hammush, Kamal& Gaceb, Djamel. Recognition of handwritten characters based on wavelet transform and SVM classifier. The International Arab Journal of Information Technology. 2018. Vol. 15, no. 6.
https://search.emarefa.net/detail/BIM-874002
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-874002