Localizing the iris through memetic algorithms

1Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

Abstract

An iris recognition system requires efficient image processing techniques in order to duly represent and interpret the iris structural characteristics of an individual. The first processing stage should be the identification of the iris region in an eye image. This work introduces the application of evolutionary algorithms to localize the iris region in an eye image. A method based on memetic algorithms was proposed and used to find the circles that represent the external iris border and the pupil border. This method is applied after detecting the edges of the image through gradient algorithms. The efficiency of the memetic algorithm in solving the problem was compared to the application of the Wildes' method, which uses the Circular Hough Transform (CHT), a well-known algorithm employed to find circles in an edged image. To test the algorithms, images from the UBIRIS database (Proenca and Alexandre 2005) were used.

Cite

CITATION STYLE

APA

Carneiro, M. B. P., Veiga, A. C. P., De Castro, F. C., Flôres, E. L., & Carrijo, G. A. (2009). Localizing the iris through memetic algorithms. Applied Artificial Intelligence, 23(8), 738–757. https://doi.org/10.1080/08839510903208070

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free