An efficient randomized algorithm for detecting circles
Computer Vision and Image Understanding
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Summed-area tables for texture mapping
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Personal Identification Based on Iris Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
IEEE Transactions on Circuits and Systems for Video Technology
A new accurate technique for iris boundary detection
WSEAS Transactions on Computers
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With a growing emphasis on human identification, iris recognition has recently received increasing attention. In this paper, an efficient biometric scheme for iris recognition system with high performance is introduced. First, the irises are localized using an effective integral differential operator. Then the localized iris image is normalized to handle different size, variation in illumination and pupil dilation. Finally, we propose a novel and efficient approach to iris feature extraction using a set of filters, called difference-of-sum filters. These filters can take advantage of a pre-computed integral image, which makes the filtering process take constant computation time no matter how big the filters are. Experimental evaluation shows that the new method has higher recognition accuracy and is faster than previous methods. The false acceptance rate was reduced by 7% in comparison with the iris code method.