Abstract

The purpose of fake iris detection is to discriminate between real and fake iris images and to defeat fake (forged) iris images. A robust fake iris detection method should be able to detect various types of fake iris images obtained from a fake printed iris, an artificial eye, or a fake contact lens, correctly and nonintrusively. To solve the problem, we propose a new fake iris detection method. We measure distinctive physiological multifeatures [the first and second features refer to the reflectance ratios of the iris to the sclera (RRIS) at 750 and 850 nm, respectively, and the third feature refers to the thickness of the corneoscleral limbus], and classify those features extracted from live irises and fake irises using a support vector machine (SVM). Using the proposed method, we can discriminate various types of fake iris images without inconveniencing users by shining visible light. To measure the performance of the method, three types of fake irises are made: a printed iris, an artificial eye, and a fake contact lens. Our experimental results show that it is possible to detect those fake iris images with high accuracy.

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