Video-based noncooperative iris image segmentation.
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.
Du
Yingzi
Y
Biometrics and Pattern Recognition Laboratory, Department of Electrical and Computer Engineering, Purdue School of Engineering and Technology, Indiana University–Purdue University Indianapolis, Indianapolis, IN 46202, USA. yidu@iupui.edu
Arslanturk
Emrah
E
Zhou
Zhi
Z
Belcher
Craig
C
D000465:Algorithms; D056667:Biometric Identification; D016208:Databases, Factual; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D007498:Iris / Q000033:anatomy & histology*; D016018:Least-Squares Analysis; D025341:Principal Component Analysis; D011680:Pupil; D014741:Video Recording / Q000379:methods*