Date of Graduation


Document Type


Degree Type



Statler College of Engineering and Mineral Resources


Lane Department of Computer Science and Electrical Engineering

Committee Chair

Xin Li.


The human iris has been demonstrated to be a very accurate, non-invasive and easy-to-use biometric for personal identification. Most of the current state-of-the-art iris recognition systems require the iris acquisition to be ideal. A lot of constraints are hence put on the user and the acquisition process.;Our aim in this research is to relax these conditions and to develop a pre-processing algorithm, which can be used in conjunction with any matching algorithm to handle the so-called non-ideal iris images. In this thesis we present a few robust techniques to process the non-ideal iris images so as to give a segmented iris image to the matching algorithm. The motivation behind this work is to reduce the false reject rates of the current recognition systems and to reduce the intra-class variability. A new technique for estimating and compensating the angle in non-frontal iris images is presented. We have also developed a novel segmentation algorithm, which uses an ellipse-fitting approach for localizing the pupil. A fast and simple limbus boundary segmentation algorithm is also presented.