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
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;
Conference_Titel :
Multimedia Computing and Systems (ICMCS), 2012 International Conference on
Conference_Location :
Tangier
Print_ISBN :
978-1-4673-1518-0
DOI :
10.1109/ICMCS.2012.6320292