Seyyed Mohammad Sadegh Moosavi

  abstract

  A biometric system provides automatic recognition of an individual based on some sort of unique feature or characteristic possessed by the individual. Biometric systems have been developed based on fingerprints, facial features, voice, hand geometry, handwriting, the retina, and the one presented in this thesis, the iris. Biometrics based on iris has been widely used in recent years because of the useful features of iris.

  The iris recognition system is to be composed of a number of sub-systems, which correspond to each stage of iris recognition. These stages are segmentation – locating the iris region in an eye image, normalisation – creating a dimensionally consistent representation of the iris region, and feature encoding – creating a template containing only the most discriminating features of the iris. The input to the system will be an eye image, and the output will be an iris template, which will provide a mathematical representation of the iris region.

    The segmentation stage is critical to the success of an iris recognition system, since data that is falsely represented as iris pattern data will corrupt the biometric templates generated, resulting in poor recognition rates. The unacceptable performance of traditional segmentation methods like Hough Transform in boundary detection leaded to developing Active Contours. Hence, current research is directed toward resolving the drawbacks of some active contours such as Balloon and Greedy in order to segment iris images. In fact, three different Iris Recognition systems have been developed based on the mentioned active contours as well as Hough transform. The simulation results show that the proposed active contours yield better results than Hough transform from both view points of Accuracy and time. Besides, the employed data-base is CASIA Iris Database.

  Defense Date: Saturday, March, 5, 2011  11 AM

  Location: Class No. 303, Department of Electrical Engineering