Performance evaluation of different color models used in color iris authentication

This paper presents an iris authentication system using different color models. This method is able to cope with different noises of color iris images. The experiments reveal that HSV and YIQ color spaces are optimal models as compared to other color spaces on iris authentication. The proposed method is validated on UBIRIS noisy iris database available in the public domain. This method using color histogram processing and fusion at the matching score achieves classification accuracy of 92.1%, equal error rate of 0.072 and computational time is 0.039 Sec. It has better accuracy as compared to related works and performs well in noisy conditions.