Does independent component analysis perform well for iris recognition?

Imen Bouraoui, Salim Chitroub, Ahmed Bouridane

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)409-426
JournalIntelligent Data Analysis
Volume16
Issue number3
DOIs
Publication statusPublished - 9 May 2012

Keywords

  • biometrics
  • Data analysis
  • feature extraction
  • independent component analysis (ICA)
  • iris recognition
  • relative Newton method
  • security systems

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