Open AccessDetection of Glaucoma in Retinal Fundus Images using Fast Fuzzy C Mean Clustering
Author(s) -
Law Kumar Singh,
Pooja Pooja,
Hitendra Garg
Publication year - 2020
Publication title -
international journal of fuzzy systems and advanced applications
Language(s) - English
Resource type - Journals
ISSN - 2313-0512
DOI - 10.46300/91017.2020.7.4
Subject(s) - glaucoma , fundus (uterus) , optic disc , optic cup (embryology) , artificial intelligence , computer vision , computer science , ophthalmology , fuzzy logic , optometry , medicine , biochemistry , gene , eye development , phenotype , chemistry
Glaucoma is one of the major causes of vision loss in today’s world. Glaucoma is a disease in the eye 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 fundus images. The proposed method suggest automatic detect the boundary of optics cup and optics disc with processing of fundus images. This paper explores the new approach 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 91.91%, 90.49% and 90.17% when tested on DRIONS, DRIVE and STARE on publicly available databases of fundus images.