A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Iris Recognition Using Wavelet Features
Journal of VLSI Signal Processing Systems
A New Iris Segmentation Method for Recognition
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Iris recognition for partially occluded images: methodology and sensitivity analysis
EURASIP Journal on Applied Signal Processing
UBIRIS: a noisy iris image database
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
Efficient iris recognition by characterizing key local variations
IEEE Transactions on Image Processing
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An iris recognition system requires efficient image processing techniques in order to duly represent and interpret the iris structural characteristics of an individual. The first processing stage should be the identification of the iris region in an eye image. This work introduces the application of evolutionary algorithms to localize the iris region in an eye image. A method based on memetic algorithms was proposed and used to find the circles that represent the external iris border and the pupil border in an edge map. The efficiency of the memetic algorithm in solving the problem was compared to the application of the Wildes' method, which uses the Circular Hough Transform, a well known algorithm employed to find circles in an edged image. To test the algorithms, images from a public database were used. The results show that the proposed application has an encouraging performance.