DocumentCode :
2759033
Title :
Iris Localization Scheme Based on Morphology and Gaussian Filtering
Author :
Gui, Feng ; Qiwei, Lin
Author_Institution :
Dept. of Electron. & Commun., HuaQiao Univ., Quanzhou
fYear :
2007
fDate :
16-18 Dec. 2007
Firstpage :
798
Lastpage :
803
Abstract :
One of the basic techniques in iris recognition system is iris localization. To find a fast, effective and exact iris localization algorithm is the key step of iris recognition. After analyzing the principle, strong points and short points of some common used iris localization methods, a morphological theory based iris localization algorithm was proposed in this paper. Based on the concept of all the object can be regarded as the subset in Euclidean space, and this subset can totally reflect the shape, volume, texture and grey value of the object, so we can apply the morphology operation to identify the feature in different eye area. The proposed iris localization algorithm is as follow: iris image preprocessing at first, where we apply a suitable Gauss filter to lessen the influence of noise. Then apply the morphology operation to extract the inner and outer iris edge, determine the iris area. The proposed algorithm was tested using CASIA iris database(V1.0). And the experimental result shown the method was superior in processing speed under the same localization precision.
Keywords :
Gaussian processes; edge detection; feature extraction; filtering theory; image recognition; mathematical morphology; visual databases; CASIA iris database; Gaussian filtering; iris edge extraction; iris image preprocessing; iris localization scheme; iris recognition; morphological theory; Algorithm design and analysis; Filtering; Filters; Gaussian noise; Image databases; Iris recognition; Morphology; Noise shaping; Shape; Testing; iris recognition; localization; morphology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal-Image Technologies and Internet-Based System, 2007. SITIS '07. Third International IEEE Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3122-9
Type :
conf
DOI :
10.1109/SITIS.2007.39
Filename :
4618855
Link To Document :
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