Robust iris segmentation on uncalibrated noisy images using mathematical morphology

被引:37
作者
Luengo-Oroz, Miguel A. [1 ,4 ]
Faure, Emmanuel [2 ,4 ]
Angulo, Jesus [3 ]
机构
[1] Univ Politecn Madrid, Biomed Image Technol Lab, ETSI Telecomunicac, E-28040 Madrid, Spain
[2] Ecole Polytech, CNRS, Ctr Rech Epistemol Appl, F-75005 Paris, France
[3] MINES Paristech, Ctr Morphol Math Math & Syst, F-77300 Fontainebleau, France
[4] ISC PIF, Complex Syst Inst Paris, F-75005 Paris, France
关键词
Iris segmentation; Non-cooperative iris biometry; Spatially variant mathematical morphology; Grey-level generalized distance;
D O I
10.1016/j.imavis.2009.04.018
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper proposes a new approach for fast iris segmentation that relies on the closed nested structures of iris anatomy (the sclera is brighter than the iris, and the iris is brighter than the pupil) and on its polar symmetry. The described method applies mathematical morphology for polar/radial-invariant image filtering and for circular segmentation using shortest paths from generalized grey-level distances. The proposed algorithm obtained good results on the NICE-I contest and showed a very robust behavior, especially when dealing with half-closed eyes, different skin colours/illumination or subjects wearing glasses. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码:278 / 284
页数:7
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