Kamal Vahdati Bana, Amin Rezaeian Delui, Amir Azizi



In this paper we propose a new feature extraction method for iris recognition based on contourlet transform. Contourlet transform captures the intrinsic geometrical structures of iris image. It decomposes the iris image into a set of directional sub-bands with texture details captured in different orientations at various scales so for reducing the feature vector dimensions we use the method for extract only significant bit and information from normalized iris images. In this method we ignore fragile bits. At last, the feature vector is created by using Co-occurrence matrix properties. For analyzing the desired performance of our proposed method, we use the CASIA dataset, which is comprised of 108 classes with 7 images in each class and each class represented a person. And finally we use SVM and KNN classifier for approximating the amount of people identification in our proposed system. Experimental results show that the proposed increase the classification accuracy and also the iris feature vector length is much smaller versus the other methods.


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Paper Citation

in Harvard Style

Vahdati Bana K., Rezaeian Delui A. and Azizi A. (2009). A NOVEL TECHNIQUE FOR IRIS RECOGNITION SYSTEM . In Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009) ISBN 978-989-674-014-6, pages 530-533. DOI: 10.5220/0002282805300533

in Bibtex Style

author={Kamal Vahdati Bana and Amin Rezaeian Delui and Amir Azizi},
booktitle={Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009)},

in EndNote Style

JO - Proceedings of the International Joint Conference on Computational Intelligence - Volume 1: ICNC, (IJCCI 2009)
SN - 978-989-674-014-6
AU - Vahdati Bana K.
AU - Rezaeian Delui A.
AU - Azizi A.
PY - 2009
SP - 530
EP - 533
DO - 10.5220/0002282805300533