A biometric iris matching system for reliable person identification using an adaptive Gabor filter

One of the biometric authentications is iris recognition using template matching. There are many methods proposed for iris template matching such as Local Binary Pattern (LBP) and Histogram of Oriented Gradients (HOG). In this paper, the iris matching is performed from the templates generated using the adaptive Gabor extraction feature. The comparison is made among the same eye side of the same person, different eye sides of the same person, and the eyes of the different person for better authentication. The Gabor feature extraction technique paired with the SVM classifier exhibited promising outcomes. With an accuracy of 91.4% and a precision of 94.7%, Gabor features showcased their capability to enhance iris recognition accuracy.