Overview

Original Research

AUTOMATIC GLAUCOMA SEGMENTATION ON HYBRID METHOD USING CSO AND HMM

K.GAYATHRI 1, and Dr. R. SHOBARANI 2.

Vol 17, No 08 ( 2022 )   |  DOI: 10.5281/zenodo.7014877   |   Author Affiliation: Research Scholar, Department of Computer Science, Dr. M.G.R Educational & Research Institute, Maduravoyal 1; Professor, Department of Computer Science and Engineering, Dr. M.G.R Educational & Research Institute, Maduravoyal, Chennai 2.   |   Licensing: CC 4.0   |   Pg no: 1458-1473   |   To cite: K.GAYATHRI, and Dr. R. SHOBARANI. (2022). AUTOMATIC GLAUCOMA SEGMENTATION ON HYBRID METHOD USING CSO AND HMM. 17(08), 1458–1473. https://doi.org/10.5281/zenodo.7014877   |   Published on: 20-08-2022

Abstract

The most challenging part of processing and analysing medical images is detecting glaucoma. A neuropsychiatric condition called glaucoma is characterized by dynamic neurodegeneration of the optic nerve, which impairs vision. Glaucoma is an eye condition that, if not identified and treated right away, can cause blindness. It might lead to irreversible vision loss. In this paper, we proposed a novel method for glaucoma detection by retinal disc segmentation. In our method we used a novel method for image segmentation with hybrid method combining HMM (Hidden Morkov Model) and CSO (Cuckoo Search Optimization) .Our proposed method using shows better performance on segmentation results. So our proposed method shows better result than existing works.

Keywords

Glaucoma Detection, HMM, CSO