Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
Improving Features Subset Selection Using Genetic Algorithms for Iris Recognition
ANNPR '08 Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition
A New Method for Iris Recognition Systems Based on Fast Pupil Localization
ICCSA '08 Proceeding sof the international conference on Computational Science and Its Applications, Part I
An efficient approach to iris detection for iris biometric processing
International Journal of Computer Applications in Technology
Using empirical mode decomposition for iris recognition
Computer Standards & Interfaces
A novel approach for iris recognition using local edge patterns
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Accurate iris boundary detection in iris-based biometric authentication process
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Recognizing human iris by modified empirical mode decomposition
PSIVT'07 Proceedings of the 2nd Pacific Rim conference on Advances in image and video technology
Fast and accurate personal identification based on iris biometric
International Journal of Biometrics
Iris recognition using genetic algorithms and asymmetrical SVMs
Machine Graphics & Vision International Journal
Engineering Applications of Artificial Intelligence
Localized iris image quality using 2-d wavelets
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
A reliable iris recognition algorithm based on reverse biorthogonal wavelet transform
Pattern Recognition Letters
Iris recognition based on zigzag collarette region and asymmetrical support vector machines
ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Iris recognition based on bidimensional empirical mode decomposition and fractal dimension
Information Sciences: an International Journal
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There has been a rapid increase in the need of accurate and reliable personal identification infrastructure in recent years, and biometrics has become an important technology for security. The iris recognition system consists of four-process: image acquisition, preprocessing, feature extraction and identification or verification. In this paper, we propose the methods for localizing the iris area between the inner boundary and the collarette boundary, to remove unnecessary areas and to increase the recognition rate. For finding the collarette boundary, histogram equalization and a high pass filter, after using an one-dimensional DFT, are applied to the image. The collarette boundary is found using an statistical information from the image which removes low-frequencies, and, finally, the iris is localized between the inner boundary and the collarette boundary. The iris is localized by two kinds of methods, and the recognition rate were compared. The recognition rate was evaluated by using DWT and SVM. These show that the iris localization by the proposed methods contains more information than the previous methods and improves the recognition rate.