Detection of Glaucoma in Retinal Fundus Images Using Fast Fuzzy C means clustering approach

Abstract

Glaucoma is one of the major causes of vision loss in today’s world. Glaucoma is the disease where fluid pressure in the eye increases; if it is not timely cured, the patient may lose their vision. Glaucoma can be detected by examining boundary of optics cup and optics disc acquired from retinal fundus images. The proposed method suggests automatic detection the boundary of optics cup and optics disc with processing of fundus images. This paper explores the new approach of fast fuzzy C-mean technique for segmenting the optic disc and optic cup in fundus images. Results evaluated by fast fuzzy C mean a technique is faster than fuzzy C-mean method. The proposed method reported results to 97.75% 92.50% and 95.00% when tested on DRIONS, DRIVE and STARE on publicly available databases of retinal fundus images.