Black hole algorithm along edge detector and circular hough transform based iris projection with biometric identification systems

Tara Othman Qadir, Tara Othman Qadir and N.S.A.M Taujuddin, N.S.A.M Taujuddin (2024) Black hole algorithm along edge detector and circular hough transform based iris projection with biometric identification systems. International Journal of Electrical and Computer Engineering Systems, 15 (1). pp. 59-68.

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Abstract

The circular parameters between the pupil and the iris are found using current iris identification techniques but the accuracy creates an issue for the detection process during image processing. The procedure of extracting the iris region from an eye image using circular parameters can be improved via approximately too many approaches in literature but remain some portions under slightly unconstrained circumstances. In this study, we presented a Black Hole Algorithm (BHA) along the Canny edge detector and circular Hough transform-based optimization technique for circular parameter identification of iris segmentation. The iris boundary is discovered using the suggested segmentation approach and a computational model of the pixel value. The BHA looks for the central radius of the iris and pupil. The system uses MATLAB to test the CASIA-V3 database. The segmented images exhibit 98.71% accuracy. For all future access control applications, the segmentation-based BHA is effective at identifying the iris. The integration of the BHA with the Hough transforms and Canny edge detector is the main method by which the iris segmentation is accomplished. This novel technique improves the accuracy and effectiveness of iris segmentation, with potential uses in image analysis and biometric identification.

Item Type:	Article
Uncontrolled Keywords:	identification, segmentation, biometric, image-processing, iris detection, accuracy, edge detector, circular hough transformation
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA168 Systems engineering
Divisions:	Faculty of Computer Science and Information Technology > FSKTM
Depositing User:	Mr. Mohamad Zulkhibri Rahmad
Date Deposited:	20 May 2024 01:30
Last Modified:	20 May 2024 01:30
URI:	http://eprints.uthm.edu.my/id/eprint/10984

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