Noise detection of iris image based on texture analysis

Noise detection is very important in an iris recognition system. A novel noise detection method for iris images is presented in this paper. According to the texture feature of different noises, a 2-D circular Gabor Filter is designed to detect specular reflection and estimate pupil's location, then, a 1-D peak Gabor Filter is proposed to detect eyelid boundary and eyelashes. Furthermore, eyelid is localized on eyelid boundary image by parabolic Integrodifferential operator. In terms of the experiment on the CASIA-IrisV3-Lamp iris database, which contains 16214 iris images, the correct rate of pupil estimation is 100% and eyelid localization is 99.4% respectively. The results show that the proposed method is quite effective.

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