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Artificial Immune Recognition System for Arabic writer identification

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2 Author(s)
Chawki Djeddi ; Mathematics and Computer science department, Cheikh Larbi Tebessi University, Tebessa, Algeria ; Labiba Souici-Meslati

Artificial Immune Systems (AIS) is an emerging bio-inspired computer science technique which embody the principles of biological immune systems for tackling complex real-world problems such as pattern recognition. Among the several immune-computing models, Artificial Immune Recognition System (AIRS) is one of the widely used for classification problems. Meanwhile, the issues related to writer identification are currently at the heart of numerous concerns in our modern day's society. Writer identification for Arabic text is receiving a renewed attention. Many popular machine learning techniques have been used in writer identification systems but only one limited attempt has been done with AIS. In this paper, we apply AIRS to perform Arabic writer identification based on a set of features extracted from Grey Level Co-occurrence Matrices. Some feature selection techniques are applied to improve computation time and accuracy results. Three traditional classifiers have also been used in our experiments for performance comparison. The obtained results show the promising ability of AIRS in Writer identification.

Published in:

Innovation in Information & Communication Technology (ISIICT), 2011 Fourth International Symposium on

Date of Conference:

Nov. 29 2011-Dec. 1 2011