Iris recognition and feature extraction in iris recognition System by employing 2D DCT

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract Biometric system is a reliable and highly accurate system for identification of individuals. Iris recognition system is a relatively new biometric system which produces better results in comparison with other biometric systems. The work presented in this paper involved an iris feature extraction and recognition based on 2D discrete cosine transform. A primary iris recognition system includes mainly four steps which includes image acquisition, image pre-process, feature extraction and matching. Iris localization has been done by circular Hough transform. After locating the iris, iris images are normalized by Daughman rubber-sheet model so as to transform the iris region into a fixed dimension. Feature encoding has been used to extract the most discriminating features of iris and is done by 2D DCT. The feature extraction capabilities of DCT has been tested on two publicly available CASIA V4 and IIITD database. Hamming distance is used for matching the iris templates. For verification, a variable threshold value has been applied to the distance metric and false acceptance rate and false rejection rate are recorded. An accuracy of 99.4% and 98.4% are recorded on CASIA V4 and IITD database respectively. The information and conclusion drawn in this paper will help others who are investigating the usefulness of iris recognition system for secure biometric identification.