Iris recognition using circular symmetric filters

Abstract

Proposes a method for personal identification based on iris recognition. The method consists of three major components: image preprocessing, feature extraction and classifier design. A bank of circular symmetric filters is used to capture local iris characteristics to form a fixed length feature vector. In iris matching, an efficient approach called nearest feature line (NFL) is used. Constraints are imposed on the original NFL method to improve performance. Experimental results show that the proposed method has an encouraging performance.