Feature correlation evaluation approach for iris feature quality measure
Signal Processing
Sparsity inspired selection and recognition of iris images
BTAS'09 Proceedings of the 3rd IEEE international conference on Biometrics: Theory, applications and systems
Estimating and fusing quality factors for iris biometric images
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on recent advances in biometrics
Measurement of defocus level in iris images using different convolution kernel methods
MCPR'10 Proceedings of the 2nd Mexican conference on Pattern recognition: Advances in pattern recognition
Iris image evaluation for non-cooperative biometric iris recognition system
MICAI'11 Proceedings of the 10th international conference on Artificial Intelligence: advances in Soft Computing - Volume Part II
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In this paper, a kind of analysis method using the wavelet coefficient in "region of interest (ROI)" is presented to evaluate the iris images sequence automatically. By use of Canny operator and Fast Hough transform, the outer edge of the iris section is fast and accurately located. The ROI is determined according to human visual system property, at the same time, the image with acquisition deformation is filtered. Consequently, the quality evaluation factor is computed by means of the wavelet coefficient in corresponded ROI, then the iris images sequence quality is evaluated combining with the factors, such as the area of iris section and its ratio to the one of pupil section, and the experiment results indicate the correctness and validity of the method.