Authors: B. Vinoth Kumar; Siwen Zhang; Tao Wu; J. Prakash; Liang Zhou; Kexin Li
Addresses: Department of Information Technology, PSG College of Technology, Coimbatore, Tamil Nadu, India ' School of Economics and Management, Tongji University, Shanghai, China ' Shanghai University of Medicine and Health Sciences, Shanghai, China ' Department of Computer Science and Engineering, PSG College of Technology, Coimbatore, Tamil Nadu, India ' Jiading District Central Hospital, Shanghai, China; Affiliated to: Shanghai University of Medicine and Health Sciences, Shanghai, China ' Shanghai University of Medicine and Health Sciences, Shanghai, China
Abstract: Retinal images are extensively used for the disclosure of retinal vascular disorders like diabetic retinopathy, glaucoma, age-related macular degeneration and optic neuritis. The analysis of a diagnostic retinal image using a computer is necessary to ease the optometrist for automating the load screening mechanism to identify these disorders. The primary step in technology aided diagnoses is optic disc segmentation and it is considered as an interesting search problem. The proposed methodology involves pre-processing of fundus images and optic disc localisation using Jaya algorithm. A new fitness function is proposed in order to improve the accuracy of the optic disc localisation. The efficiency of the proposed methodology is examined on different datasets such as DIARETDB1, DIARETDB0, CHASEDB1, DRIONS and DRIVE. The results infer that the proposed methodology has achieved a 99% of location accuracy and shows its superiority in localising the optic disc by comparing it with existing literature.
Keywords: fundus image; Jaya algorithm; optic disc localisation; fitness function; diabetic retinopathy; glaucoma.
International Journal of Computational Vision and Robotics, 2022 Vol.12 No.3, pp.324 - 342
Received: 19 Nov 2020
Accepted: 09 Nov 2021
Published online: 04 Apr 2022 *