An Efficient Iris Recognition System Using Contourlet Transform and Neural Networks

摘要

Iris recognition is the most accurate and reliable biometric identification system used for security purposesThe iris recognition system consists of image acquisition, localization, normalization enhancement, feature extraction and classification. Segmentation is used for the localization of the correct iris region in an eye and it should be done to remove the reflection, eyelids, eyelashes, and pupil noises present in iris region. The proposed method uses Hough Transform segmentation method, then the iris and pupil boundary are detected from rest of the eye image in order to extract the noises. The segmented iris region is normalized to minimize the dimensional inconsistencies between the iris regions by using Daugman’s Rubber Sheet Model. The features of the normalized iris are extracted by contour let transform. LDA, SOM technique was chosen to classify the image. Iris Recognition is more efficient than using username and password technique and prevents the malicious action by the intruders. The above recognition experiment can be simulated using MATLAB.