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Advisor(s)
Abstract(s)
Iris recognition is a well-known biometric technique. John Daugman has proposed a method for iris recogni tion, which is divided into four steps: segmentation, normalization, feature extraction and matching. In this
paper, we evaluate, modify and extend John Daugman’s method. We study the images of CASIA and UBIRIS
databases to establish some modifications and extensions on Daugman’s algorithm. The major modification is
on the computationally demanding segmentation stage, for which we propose a template matching approach.
The extensions on the algorithm address the important issue of pre-processing, that depends on the image
database, being especially important when we have a non infra-red red camera (e.g. a WebCam). For this
typical scenario, we propose several methods for reflexion removal and pupil enhancement and isolation. The
tests, carried out by our C# application on grayscale CASIA and UBIRIS images, show that our template
matching based segmentation method is accurate and faster than the one proposed by Daugman. Our fast
pre-processing algorithms efficiently remove reflections on images taken by non infra-red cameras.
Description
Keywords
iris recognition biometrics image processing image segmentation
Citation
Ferreira A., Lourenço A., Pinto B. and Tendeiro J. (2009). Modifications and Improvements on Iris Recognition. In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing, pages 72-79 DOI: 10.5220/0001536100720079