Jamaludin, Shahrizan and Mohamad Ayob, Ahmad Faisal and Mohd Norzeli, Syamimi and Mohamed, Saiful Bahri (2022) Adaptive Initial Contour and Partly-Normalization Algorithm for Iris Segmentation of Blurry Iris Images. Journal of Information and Communication Technology, 21 (03). pp. 411-435. ISSN 2180-3862

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Abstract

Iris segmentation is a process to isolate the accurate iris region from the eye image for iris recognition. Iris segmentation on non-ideal and noisy iris images is accurate with active contour. Nevertheless, it is currently unclear on how active contour responds to blurry iris images or motion blur, which presents a significant obstacle in iris segmentation. Investigation on blurry iris images, especially on the initial contour position, is rarely published and must be clarified. Moreover, evolution or convergence speed remains a significant challenge for active contour as it segments the precise iris boundary. Therefore, this study carried out experiments to achieve an efficient iris segmentation algorithm in terms of accuracy and fast execution, according to the aforementioned concerns. In addition, initial contour was explored to clarify its position. In order to accomplish these goals, the Wiener filter and morphological closing were used for preprocessing and reflection removal. Next, the adaptive initial contour (AIC), δ, and stopping function were integrated to create the adaptive Chan-Vese active contour (ACVAC) algorithm. Finally, the partly -normalization method for normalization and feature extraction was designed by selecting the most prominent iris features. The findings revealed that the algorithm outperformed the other active contour-based approaches in computational time and segmentation accuracy. It proved that in blurry iris images, the accurate initial contour position could be established. This algorithm is significant to solve inaccurate segmentation on blurry iris images.

Item Type:	Article
Uncontrolled Keywords:	Iris segmentation, adaptive initial contour, adaptive ChanVese active contour, partly-normalization, segmentation accuracy
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	College of Arts and Sciences
Depositing User:	Mrs Nurin Jazlina Hamid
Date Deposited:	27 Jul 2022 01:52
Last Modified:	08 Feb 2023 01:21
URI:	https://repo.uum.edu.my/id/eprint/28744

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