Iris Segmentation Based on Black Hole Algorithm for Biometric System
Tara Othman Qadir1, N.S.A.M Taujuddin2

1Tara Othman Qadir*, her postgraduate at this College of Science and was awarded M.SC. degree in Computer Science , University of Sulaimani City Sulaimani, Lecturer in Salahaddin University Erbil in Collge of Engineering department Software Engineering ,in city Erbil in Country.Iraq.
2N. S. A. M, Taujuddin, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, 86400 Parit Raja, Batu Pahat, Johor, Malaysia.

Manuscript received on December 02, 2020. | Revised Manuscript received on December 05, 2020. | Manuscript published on December 30, 2020. | PP: 281-287| Volume-10 Issue-2, December 2020. | Retrieval Number: 100.1/ijeat.B21111210220 | DOI: 10.35940/ijeat.B2111.1210220
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (

Abstract: Current iris recognition schemes such as Integro-Differential method, Hough Transform, Watershed Transform Circle Fitting, and Circular Hough Transformation (CHT) are used to find circular parameters between pupil and iris. Segmentation process of an eye image using the circular parameters toextracts the iris region still can be further improved. In this paper, we introduced an optimization method of circular parameters detection for iris segmentation based on Black Hole Algorithm (BHA). The proposed segmentation algorithm utilizes a computational model of the pixels’ value to detect the iris boundary. The BHA searches for center radius of both pupil and iris. The system tests the CASIA Iris Interval V3 database by on MATLAB. The segmented images show an accuracy of 98.3%. In short, the segmentation-based on BHA is efficient to identify the iris for any future access control applications. 
Keywords: Black Hole Algorithm, Biometric, Iris recognition, Image processing, Segmentation.
Scope of the Article: Image processing