DocumentCode
2445007
Title
Improved and robust eyelash and eyelid location method
Author
Ting Wang ; Min Han ; Honglin Wan
Author_Institution
Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan, China
fYear
2012
fDate
25-27 Oct. 2012
Firstpage
1
Lastpage
4
Abstract
Iris recognition has been very popular among researchers as an important personal identification technology due to its unique, stable and noninvasive properties. However, because of iris occlusion such as eyelid and eyelashes, high accuracy of iris recognition system is challenged. In this paper, we firstly improve our previous work on eyelashes localization algorithm based on Expectation Maximization (EM) and Gaussian Mixture Model (GMM). Then, we propose a novel and robust approach to search the eyelid via hybrid edge detection and Hough transform, which reduces the noise fitting points and selects the eyelid fitting area automatically. Experimental results reveal our proposal can detect eyelid and eyelashes accurately and effectively.
Keywords
Gaussian processes; Hough transforms; edge detection; expectation-maximisation algorithm; filtering theory; hidden feature removal; image segmentation; iris recognition; nonlinear filters; Gaussian mixture model; Hough transform; expectation maximization; eyelid fitting area selection; hybrid edge detection; iris occlusion; iris recognition; noise fitting point redeuction; nonideal iris segmentation; order statistic filter; personal identification technology; robust eyelash location method; robust eyelid location method; EM; Eyelash detection; GMM; eyelid localization; order statistic filter;
fLanguage
English
Publisher
ieee
Conference_Titel
Wireless Communications & Signal Processing (WCSP), 2012 International Conference on
Conference_Location
Huangshan
Print_ISBN
978-1-4673-5830-9
Electronic_ISBN
978-1-4673-5829-3
Type
conf
DOI
10.1109/WCSP.2012.6542908
Filename
6542908
Link To Document