Popular medical arena, Diabetic Retinopathy stands an oddity that arises into eyes which is gradually expanded and its diagnosis at a primary phase is very critical for retaining vision of several patients. A computerized mass screening of diabetic retinopathy in retinal pictures can assist in diminishing the probability of widespread blindness because of DR together with dropping the work-pressure on ophthalmologists. An automatic identification systems are also accessible which lead to explore numerous eye wounds like micro-aneurysms, haemorrhages , hard exudates and cotton wool exudates by means of colour fundus images. The existence of micro-aneurysms in the retinal images is the most indicative signal of diabetic retinopathy. Stable identification and classification of numerous lesions handle as an important criteria towards automatic grading and severity of the disease. Now we review the diverse previous studies which help in spontaneous diagnose the eye diseases with the intent of affording decision approval in extension to lessening the load of an ophthalmologist.

Retinal coloured fundus images, Diabetic Retinopathy, optic disk, Red and bright lesions, image processing techniques, classification

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[16] Yanhui Guo, Umit Budak, Lucas J.Vespa, Eiham Khorasani, Abdulkadir Sengur, “ A retinal vessel detection approach using convolution neural network with reinforcement sample learning strategy”, Measurement , Elsevier 125 (2018),pp:586–591,Doi: 10.1016/j.measurement.2018.05.003
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