Spatial and Textural Aspects for Arabic Handwritten Characters Recognition

Author
Keywords
Abstract
The purpose of the present paper is the recognition of handwritten Arabic characters in their isolated form. The specificity of Arabic characters is taken into consideration, each of the proposed feature extraction method integrates one of the two aspects: spatial and textural. In the first step, a modified Bitmap Sampling method is proposed, which converts the character’s images into a binary Matrix and then constructs a Mask for each class. A matching rate is used between the input binary matrix and the masks to determinate the corresponding class. In the second step we investigate the use of an Artificial Neural Network as classifier with the binary matrices as features and then the histograms of Local Binary Patterns to capture the texture aspect of the characters. Finally, the results of these two methods are combined to take into consideration both aspects at the same time. Tested on the Arabic set of the Isolated Farsi Handwritten Character Database, the proposed method has 2.82% error rate.
Year of Publication
2018
Journal
International Journal of Interactive Multimedia and Artificial Intelligence
Volume
5
Issue
Regular Issue
Number
1
Number of Pages
86-91
Date Published
06/2018
ISSN Number
1989-1660
Citation Key
URL
http://www.ijimai.org/journal/sites/default/files/files/2017/12/ijimai_5_1_11_pdf_70968.pdf
DOI
10.9781/ijimai.2017.12.002
Attachment