PERFORMANCE EVALUATION OF TWO HIGH PROFILE SEGMENTATION ALGORITHMS IN IRIS RECOGNITION SYSTEM

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dc.contributor.authorADEPOJU, SUNDAY FEMI
dc.date.accessioned2017-02-20T12:03:20Z
dc.date.available2017-02-20T12:03:20Z
dc.date.issued2014-11
dc.descriptionA THESIS SUBMITTED TO THE POSTGRADUATE SCHOOL, AHMADU BELLO UNIVERSITY, ZARIA IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE AWARD OF M.SC. DEGREE IN COMPUTER SCIENCE DEPARTMENT OF MATHEMATICS, FACULTY OF SCIENCE, AHMADU BELLO UNIVERSITY, ZARIAen_US
dc.description.abstractIris is an effective biometric application of an individual for security-related applications. However, the iris segmentation process is challenging due to the presence of eye lashes that occlude the iris. Iris segmentation is an important phase in the whole iris recognition system, for it determines the accuracy of matching. To find a fast, effective and exact iris segmentation algorithm is the key step of iris recognition. This thesis compares the two high profile segmentation algorithms of Daugman (integro-differential) and Wildes (circular hough). Simulating the two algorithms with MATLAB 2012 and image datasets from Chinese Academy of Science Institute of Automation (CASIA) version 4, the evaluation of the algorithms was carried out using the performance metric False Acceptance Rate (FAR), False Rejection Rate (FRR) and Recognition Accuracy. The analysis of the result, indicated that the Circular Hough is more accurate than intego-differential as it shows higher recognition accuracy and lower error rateen_US
dc.identifier.urihttps://kubanni.abu.edu.ng/handle/123456789/8738
dc.language.isoenen_US
dc.subjectPERFORMANCE EVALUATION,en_US
dc.subjectHIGH PROFILE,en_US
dc.subjectSEGMENTATION ALGORITHMS,en_US
dc.subjectIRIS RECOGNITION SYSTEM,en_US
dc.titlePERFORMANCE EVALUATION OF TWO HIGH PROFILE SEGMENTATION ALGORITHMS IN IRIS RECOGNITION SYSTEMen_US
dc.typeThesisen_US
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