Open AccessIris Segmentation
Author(s) -
Anis Farihan Mat Raffei,
Rohayanti Hassan,
Shahreen Kasim,
Hishamudin Asmuni,
Abdul-Rahim Ahmad,
Rahmat Hidayat,
Ansari Saleh Ahmar
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i2.5.13956
Subject(s) - artificial intelligence , computer vision , iris (biosensor) , segmentation , computer science , hough transform , iris recognition , noise (video) , image segmentation , image (mathematics) , pattern recognition (psychology) , biometrics
The quality of eye image data become degraded particularly when the image is taken in the non-cooperative acquisition environment such as under visible wavelength illumination. Consequently, this environmental condition may lead to noisy eye images, incorrect localization of limbic and pupillary boundaries and eventually degrade the performance of iris recognition system. Hence, this study has compared several segmentation methods to address the abovementioned issues. The results show that Circular Hough transform method is the best segmentation method with the best overall accuracy, error rate and decidability index that more tolerant to ‘noise’ such as reflection.