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
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;
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
DOI :
10.1109/WCSP.2012.6542908