Iris segmentation using Hough Transform method and Fuzzy C-Means method


Complementary and Alternative Medicine (CAM) therapy is quite popular for chronic diseases such as diabetes, arthritis, and others. CAM has become very popular in the last period. One area of CAM is iridology, which is an alternative diagnosis that links iris patterns, color, tissue weakness, damage and other characteristics, which can obtain evidence about the patient’s systemic health. In identification based on the eye image, it requires an iris separation process. This separation process in image processing is done by segmentation. So that segmentation plays an important role in the identification of diseases based on images. In this research segmentation is done by combining the Hough Transform method and the clustering-based segmentation method, the Fuzzy C-Means method. The segmentation is done on the iris object which is sourced from UBIRIS V2 database. System evaluation is done by measuring accuracy, sensitivity, specificity and execution time. Test results on the tested iris image indicate the proposed method is able to segment the iris image properly.

R K Hapsari1,2, M I Utoyo3, R Rulaningtyas4 and H Suprajitno3

Published 1 March 2020 Published under licence by IOP Publishing Ltd
Journal of Physics: Conference Series, Volume 1477, Computer and Mathematics