Representação e Classificação de Texturas da Íris Baseada na Transformada Ótima de Gabor

This paper proposes to investigate the application of the method developed by Manjunah and Ma [12], namely, the Optimal Gabor Wavelet Transform (OGWT), in the context of iris texture representation. The proposed method was tested in a widely known database of 1205 eye images [16]. In each one of these images, the iris region was segmented, and then represented in multiple scales using the OGWT; the íris texture patterns were represented by their statistics in the Wavelet domain, and compared using similarity metrics. The experimental results indicate that the proposed 1 Programa de Pós-Graduação em Engenharia Elétrica – PPGEE, Universidade Federal do Rio Grande do Sul – UFRGS, Av. Oswaldo Aranha, 103, Porto Alegre, RS, Brasil {fernanda.quartieri@ufrgs.br, schuck@ufrgs.br, jacobs@inf.ufrgs.br, letícia@eletro.ufrgs.br} Representação e Classificação de Texturas da Íris Baseada na Transformada Ótima de Gabor 106 RITA • Volume XV • Número 2 • 2008 method obtains a correct iris recognition rate of 94,68%, even considering out of focus images and iris occlusions; a correct iris recognition rate of 100% is obtained excluding problematic images. The proposed method is flexible, and allows to fine tune the iris recognition criterion according to the accuracy level required by the application.