Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34707
Title: Detecting eyelash and reflection for accurate iris segmentation
Authors: Kong, WK
Zhang, D 
Keywords: Segmentation
Eyelash
Reflection
Iris recognition
Biometric
Issue Date: 2003
Publisher: World Scientific Publishing
Source: International journal of pattern recognition and artificial intelligence, 2003, v. 17, no. 6, p. 1025-1034 How to cite?
Journal: International journal of pattern recognition and artificial intelligence
Abstract: Accurate iris segmentation is presented in this paper, which is composed of two parts, reflection detection and eyelash detection. Eyelashes are classified into two categories, separable and multiple. An edge detector is applied to detect separable eyelashes, and intensity variances are used to recognize multiple eyelashes. Reflection is also divided into two types, strong and weak. A threshold and statistical model is proposed to recognize the strong and weak reflection, respectively. We have developed an iris recognition approach for testing the effectiveness of the proposed segmentation method. The results show that the proposed method can reduce recognition error for the iris recognition approach.
URI: http://hdl.handle.net/10397/34707
ISSN: 0218-0014
DOI: 10.1142/S0218001403002733
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