High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Classifying Facial Attributes Using a 2-D Gabor Wavelet and Discriminant Analysis
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
Comparison of texture features based on Gabor filters
IEEE Transactions on Image Processing
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The interface of computer technologies and biology is having a huge impact on society. Human recognition technology research projects promises new life to many security consulting firms and personal identification system manufacturers. Iris recognition is considered to be the most reliable biometric authentication system. Very few iris recognition algorithms were commercialised. The method proposed in this paper differed from the existing work in the iris segmentation and feature extraction phase. Digitised greyscale images of Chinese Academy of Sciences - Institute of Automation (CASIA) database were used for determining the performance of the proposed system. The circular iris and pupil of the eye image were segmented using Morphological operators and Hough transform. The localised iris region was then normalised in to a rectangular block to account for imaging inconsistencies. Finally, the iris code was generated using 2D Gabor Wavelets. A bank of Gabor filters has been used to capture both local and global iris characteristics to generate 2400 bits of iris code. Measuring the Hamming distance did the matching of the iris code. The two iris codes were found to match if the hamming distance is below 0.20. The experimental results show that the proposed method is effective and encouraging.