Reducing the False Rejection Rate of Iris Recognition Using Textural and Topological Features

This paper presents a novel iris recognition system using 1D log polar Gabor wavelet and Euler numbers. 1D log polar Gabor wavelet is used to extract the textural features, and Euler numbers are used to extract topological features of the iris. The proposed decision strategy uses these features to authenticate an individual's identity while maintaining a low false rejection rate. The algorithm was tested on CASIA iris image database and found to perform better than existing approaches with an overall accuracy of 99.93%. MONG the present biometric traits, iris is found to be the most reliable and accurate (1). The use of human iris as a biometric feature offers many advantages over other biometric features. Iris is the internal human body organ that is visible from outside, but well protected from external modifiers. It has epigenetic formation and it is formed from the individual DNA, but a large part of its final pattern is developed at random. Two eyes from the same individual, although are very similar, contain unique patterns. Similarly, identical twins would exhibit four different iris patterns. These characteristics make it attractive for use as a biometric feature to identify individuals. Pattern recognition and image processing algorithms can be used to extract the unique patterns of iris from an eye image and encode it into an iris template. This iris template contains mathematical representation of the unique information stored in the iris and allows comparisons to be made between templates. Since 1990s, many researchers have worked on this problem. Human iris recognition process is basically divided into four steps, • Localization: Inner and outer boundaries of the iris are extracted.