Affiliations: [a] Signal and Image Processing Laboratory, Electronics and Computer Science Faculty, University of Science and Technology of Houari Boumedienne, Algiers, Algeria | [b] School of Computing, Engineering and Information Sciences, Northumbria University, Newcastle upon Tyne, UK | [c] Department of Computer Science, King Saud University, Riyadh, Saudi Arabia
Correspondence:
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Corresponding author: Professor Salim Chitroub, Signal and Image Processing Laboratory, Electronics and Computer Science Faculty, U.S.T.H.B, P.O. Box 32, El – Alia, Bab – Ezzouar, 16111, Algiers, Algeria. Tel.: +213 21 24 71 87; Fax: +213 21 24 71 87; E-mail: [email protected]; [email protected]
Abstract: This paper is concerned with an application of ICA for a possible improvement of iris recognition by replying to the question: does ICA perform well for such purpose? To achieve this, the hypotheses and the theoretical concepts of ICA methods used are handled so that coherence with iris authentication application is guaranteed. Our contribution is not in the development of new theoretical concepts of ICA but it is in adapting its basic ideas for our application. Also, it consists of deploying its powerful and its efficiency for iris recognition, and consequently; it's potential to embed it on smart cards for increasing application domains of secure biometric-based individual identification systems. We have developed a comparative study between the implemented ICA algorithms and other recent and popular methods of iris recognition. We have demonstrated our experimental results using some mathematical criteria. Three different subsets of international certified CASIA iris image databases are used for testing the different implemented methods. The conclusion of such comparative study is that the ICA-based approaches are more effective and more practical than other existing methods.
Keywords: Data analysis, independent component analysis (ICA), relative Newton method, feature extraction, iris recognition, biometrics, security systems
