Anca Ignat, Ioan Pavaloi
16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2021)
In this paper we study the problem of the recognition process for iris images with missing information. Our approach uses keypoints related features for solving this problem. We present our recognition results obtained using SURF (Speeded-Up Robust Features) features extracted from occluded iris images. We tested the influence on the recognition rate of two threshold parameters, one linked with the SURF extraction process and the other with the keypoint matching scheme. The proposed method was tested on UPOL iris database using eleven levels of occlusion. The experiments show that the method we describe in this paper produces better results than Daugman procedure on all considered datasets and the results we previously obtained using SIFT features. Comparisons were also performed with iris recognition results that use colour for iris characterization, computed on the same databases of irises with different levels of missing information.
You can find the whole article here: https://www.semanticscholar.org/paper/Occluded-Iris-Recognition-using-SURF-Features-Ignat-Pavaloi/b479c8b783235cebdc8cac8d1b3d8dd1059e3a20