Title :
Robust eyeball segmentation in noisy iris images using fourier spectral density
Author :
Puhan, N.B. ; Sudha, N. ; Jiang, Xudong
Author_Institution :
Nanyang Technol. Univ. Singapore, Singapore
Abstract :
In this paper, a new eyeball segmentation approach based on the Fourier spectral density is proposed for noisy iris images. The design of an accurate segmentation method for noisy iris images could make non-cooperative iris recognition possible. The proposed segmentation method aims to achieve high segmentation accuracy in defocused, reflection-contained and eyelid-occluded iris images. The proposed method could extract the eyeball region correctly in a significant number of noisy iris images from the UBIRIS database [16].
Keywords :
Fourier transforms; image recognition; image segmentation; eyelid-occluded iris images; fourier spectral density; noisy iris images; noncooperative iris recognition; robust eyeball segmentation; Acoustic reflection; Feature extraction; Image databases; Image edge detection; Image segmentation; Iris recognition; Optical reflection; Robustness; Waveguide discontinuities; Wavelet transforms; Fourier spectral density; iris recognition; segmentation; thresholding;
Conference_Titel :
Information, Communications & Signal Processing, 2007 6th International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-0982-2
Electronic_ISBN :
978-1-4244-0983-9
DOI :
10.1109/ICICS.2007.4449723