Title :
Video-Based Noncooperative Iris Image Segmentation
Author :
Du, Yingzi ; Arslanturk, Emrah ; Zhou, Zhi ; Belcher, Craig
Author_Institution :
Dept. of Electr. & Comput. Eng., Indiana Univ., Indianapolis, IN, USA
Abstract :
In this paper, we propose a video-based noncooperative iris image segmentation scheme that incorporates a quality filter to quickly eliminate images without an eye, employs a coarse-to-fine segmentation scheme to improve the overall efficiency, uses a direct least squares fitting of ellipses method to model the deformed pupil and limbic boundaries, and develops a window gradient-based method to remove noise in the iris region. A remote iris acquisition system is set up to collect noncooperative iris video images. An objective method is used to quantitatively evaluate the accuracy of the segmentation results. The experimental results demonstrate the effectiveness of this method. The proposed method would make noncooperative iris recognition or iris surveillance possible.
Keywords :
gradient methods; image denoising; image segmentation; interference suppression; iris recognition; least squares approximations; video signal processing; ellipses method; image segmentation; iris recognition; least squares fitting; noise removal; noncooperative iris video images; window gradient based method; Active contours; Biometrics; Deformable models; Filters; Image segmentation; Iris recognition; Laboratories; Least squares methods; Pattern recognition; Surveillance; Direct least squares fitting of ellipses; iris recognition; noncooperative iris image segmentation; video-based iris image segmentation; Algorithms; Biometric Identification; Databases, Factual; Humans; Image Processing, Computer-Assisted; Iris; Least-Squares Analysis; Principal Component Analysis; Pupil; Video Recording;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMCB.2010.2045371