Dual iris matching for biometric identification

In this paper, a dual iris-based biometric identification system that increases the accuracy and the performance of a typical human iris recognition system is proposed. This system detects, isolates, and extracts the iris region from the eye images and maps the circular regions into rectangular polar coordinates according to the preset radial and angular resolutions. The phase responses, obtained from convolving the polar images with 1D log Gabor filter, are quantized to generate the binary iris templates which are compared using the hamming distance. Unlike the conventional method which examines a single eye, the proposed method takes images from both eyes simultaneously. Using it on CASIA Iris database V3, false positive rate and false negative rate were found to be 0 and 9.96 %, respectively, while the overall accuracy was 99.92 %.