Progression Detection of Glaucoma Using K-means and GLCM Algorithm

Abstract

Diabetes mellitus (DM) is one of the main medical issues far and wide causing national financial weight and low personal satisfaction. People with diabetes have an extended possibility of glaucoma. The hurt brought about by glaucoma is irreversible. This can occur if abnormal vein growth, which can occur because of diabetic retinopathy, is the significant consequence of diabetic illness is diabetic retinopathy (DR), it will hinder the characteristic misuse of the eye which impacts the retina of diabetic individuals, and the basic period of diabetic retinopathy can prompt changeless vision misfortune. The early discovery and observation of diabetic retinopathy are critical to forestall it or for compelling treatment, yet the issue related to early identification of diabetic retinopathy (DR) is minor changes on retinal fundus picture, and it incorporates hemorrhages, exudates, red sore, cotton fleece spots, drusen, and so forth. The early location or screening of changes on the retinal picture is exceptionally testing and tedious for ophthalmologists, as the size and shading changes are at first coordinated with neighborhood veins I retinal picture. So the glaucoma is one of the most unsafe visual maladies, keeps on influencing and weight a huge area of our populace. Accordingly, it is basic to distinguish glaucoma at the beginning. The proposed frameworks have focused on the parameter cup to plate proportion (CDR) for identification of glaucoma that might be the best methodology for building proficient, vigorous, and precise computerized framework for glaucoma diagnosis, and this strategy advocates the utilization of half and half methodology of manual element making with profound learning. It holds the guarantee of improving the precision of glaucoma conclusion through the robotized systems.