DocumentCode
3543374
Title
Novel Iris Segmentation Method
Author
Guesmi, H. ; Trichili, Hanene ; Alimi, Adel M. ; Solaiman, Basel
Author_Institution
REGIM: Res. Group on Intell. Machines, Nat. Eng. Sch. of Sfax, Sfax, Tunisia
fYear
2012
fDate
10-12 May 2012
Firstpage
260
Lastpage
265
Abstract
Iris recognition is a proven, accurate means to identify people. Iris is a part of an eye image. To be possible the uses of this modality, it´s indispensable to be detected and segmented. In this paper, we present our both methods: eye image preprocessing by method of Bias-Corrected Fuzzy C-Mean (BCFCM) and iris segmentation based on the active contours “Snake”. The performance of iris recognition system highly depends on segmentation step. For instance, even an effective feature extraction method would not be able to obtain useful information from an iris image that is not segmented properly. This paper presents a straightforward method for segmenting the iris patterns. To prove the performance of our iris method segmentation, we have integrated it in an iris verification system. Experiments are performed using iris images obtained from CASIA V.1 database.
Keywords
feature extraction; fuzzy set theory; image segmentation; iris recognition; CASIA V.1 database; active contours; bias-corrected fuzzy c-mean; effective feature extraction method; eye image preprocessing by method; iris patterns; iris recognition; iris verification system; novel iris segmentation method; snake; straightforward method; Eyelids; Image segmentation; Iris recognition; Reliability; BCFCM; Snake; iris recognition; iris segmentation;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia Computing and Systems (ICMCS), 2012 International Conference on
Conference_Location
Tangier
Print_ISBN
978-1-4673-1518-0
Type
conf
DOI
10.1109/ICMCS.2012.6320292
Filename
6320292
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