Survey of Classification Approaches for Glaucoma Diagnosis from Retinal Images

The eye is a vital and complex organ of vision that helps us in interaction with the outside world. It helps us to visualize the outside world by detecting light and converting it into impulses for sending them to the brain via the optic nerve. As it is sensitive in nature, so it is easily vulnerable to many diseases. Glaucoma is one of the second largest eye disease resulting in irreversible blindness, due to the damage of optic nerve. Ophthalmologists use retinal fundus images for assessment of this disease by manually outlining the optic cup and optic disc for analysis of the abnormality. The aim of this paper is to analyze different approaches used so far for classification of retinal images as abnormal or normal using feature extraction and classification.