文章基本信息

标题：PERFORMANCE AND RELIABILITY FOR IRIS RECOGNITION BASED ON CORRECT SEGMENTATION
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作者：KHIDER NASSIF JASSIM ; ASAMA KUDER NSEAF
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2016
卷号：93
期号：2
出版社：Journal of Theoretical and Applied
摘要：The recognition of Iris is regarded as the most dependable and accurate system of biometric identification so far. This system captures an individual's eye image in which the iris in the image is used for further normalization as well as segmentation to extract its feature. The iris recognition systems performance relies heavily on the segmentation process. In fact, segmentation process is employed for localizing the accurate iris region in a certain portion of an eye and this must be correctly and accurately carried out to take out the eyelashes, reflection, eyelids and pupil noises found in the region of iris. In this study, Enhance Hough Transform (EHT) approach in the segmentation process will be used. The enhancement locates the pupil region of eye image by using threshold and Circle Hough Transform (CHT). Hence, the pupil parameter will capture the region of iris from the image of eye and then apply Hough Transform for locating outer boundary in less space search. This approach is found more effective in emphasizing the accuracy of iris segmentation. The segmented iris region is normalized so as to reduce the dimensional inconsistencies among the regions of iris through adopting the Model of Daugmans Rubber Sheet. The iris features were, then, encoded through convolving the normalized region of the iris with 1D Log-Gabor filters and phase quantizing the output so as to create a bit-wise biometric template. The distance of Hamming was selected as corresponding metric which provided the measure of a number of bits which did not match up among the iris templates. This proposed method is tested with the eye images obtained from MMU V1 iris database. The performance of such a proposed method showed that the accuracy of the iris recognition increased.
关键词：Iris Biometrics; Iris Recognition; Enhance Iris Segmentation; Hough Transform; Geodesic Active Contour; MMU Iris Database