A COMPARISON OF MULTIPLE WAVELET ALGORITHMS FOR IRIS RECOGNITION

Personal identification has become the need of modern day life. The identification must be fast, automatic and foolproof. Biometrics has emerged as a strong alternative to identify a person compared to the traditional ways. Also biometric identification can be made fast, automatic and is already foolproof. Among other biometrics, Iris recognition has emerged as a strong way of identifying any person. Iris recognition is one of the newer biometric technologies used for personal identification. It is one of the most reliable and widely used biometric techniques available. In general, a typical iris recognition method includes capturing iris images, testing iris liveness, image segmentation, and image recognition using traditional and statistical methods. Each method has its own strengths and limitations. In this paper, we compare the performance of various wavelets for Iris recognition like complex wavelet transform, Gabor wavelet, and discrete wavelet transform.