A robust iris segmentation with fuzzy supports

Authors:
C. C. Teo;H. F. Neo;G. K. O. Michael;C. Tee;K. S. Sim
Affiliations:
FIST;FIST;FIST;FIST;FET, Multimedia University, Jalan Ayer Keroh Lama, Malacca, Malaysia
Venue:
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: theory and algorithms - Volume Part I
Year:
2010

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Abstract

Today, iris recognition is reported as one of the most reliable biometric approaches. With the strength of contactless, the hygienic issue is therefore minimized and the possibility of disease infection through the device as a medium is low. In this paper, a MMU2 iris database with such consideration is created for this study. Moreover, the proposed iris segmentation method has shown its robustness with intelligent fuzzy supports. Furthermore, it has been tested with 18414 iris images across different databases available in the public without changing any threshold values and parameters. The experiment results show a total of 17915 or 97.30%.of correct iris segmentation.