Abstract—The authentication of people using iris-based recognition is a widely developing technology. Personal identification system consists of localization of the iris region, extracting iris features, generation of data set of iris images and then iris pattern recognition. This paper presents an iris detection and recognition method, which adopts the wavelet transform to extract iris texture features and an artificial neural network as classifier. The classification is done using Multi Layer Perceptron with sigmoid transfer function. The classification accuracy obtained is 92.14% and MSE is 0.0052. The corresponding FRR and FAR is 0% and 7.8% respectively.
Index Terms—Artificial neural network, iris segmentation, pupil detection, wavelet transform.
F. A. S .R. Ganorkar is Professor in E&TC with Sinhgad Technical Education Society’s Sinhgad College of Engineering, Pune-411041, Maharashtra, India. E-mail: firstname.lastname@example.org
F. B. J. A. Deshpande is Lecturer in E&TC with Sinhgad Technical Education Society’s Sou. Venutai Chavan Polytechnic, Pune-411041, Maharashtra, India. E-mail: email@example.com
Cite: S. R. Ganorkar and J. A. Deshpande, "Person Identification Using Iris Recognition," International Journal of Engineering and Technology vol. 3, no. 1, pp. 40-43, 2011.