DocumentCode :
3445043
Title :
Iris image segmentation based on K-means cluster
Author :
Jin, Liu ; Xiao, Fu ; Haopeng, Wang
Author_Institution :
Dept. of Fundamental Courses, Air Force Aviation Univ., Changchun, China
Volume :
3
fYear :
2010
fDate :
29-31 Oct. 2010
Firstpage :
194
Lastpage :
198
Abstract :
Iris segmentation is an important step for automatic iris recognition. This paper presents a new iris segmentation method based on K-means clustering. we propose a limbic boundary localization algorithm based on K-Means clustering for pupil detection. We locates the centers of the pupil and the iris in the input image. Then two image strips containing the iris boundaries are extracted. The outer boundary of iris is localized based on shrunk image using Hough transform. The proposed method was evaluated in the UBIRIS.v2 testing database by the NICE.I organizing committee and results are well.
Keywords :
Hough transforms; image segmentation; iris recognition; pattern clustering; Hough transform; Iris image segmentation; K-means clustering; UBIRIS v2 testing database; limbic boundary localization algorithm; pupil detection; Image segmentation; Boundayr detection; Iris segmentation; K-Means clustering;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on
Conference_Location :
Xiamen
Print_ISBN :
978-1-4244-6582-8
Type :
conf
DOI :
10.1109/ICICISYS.2010.5658566
Filename :
5658566
Link To Document :
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