Abstract: This Diabetic retinopathy contributes to serious health problem in many parts of the world. With the motivation of the needs of the medical community system for early screening of diabetics and other diseases, a computer aided diagnosis system is proposed. This work is aimed to develop an automated system to analyze the retinal images for important features of diabetic retinopathy using image processing techniques and an image classifier based on artificial neural network which classify the images according to the disease conditions. Retinal haemorrhage is a disorder of the eye in which bleeding occurs into the retina. A retinal hemorrhage can be caused by hypertension, retinal vein occlusion (a blockage of a retinal vein), or diabetes mellitus (which causes small fragile blood vessels to form, which are easily damaged). Exudates is a fluid with a high content of protein and cellular debris which has escaped from blood vessels and has been deposited in tissues or on tissue surfaces, usually as a result of inflammation. Different findings such as exudates and hemorrhage in the retina over time can be used for the early detection of diabetic retinopathy. For the detection the scope of digital image processing and artificial neural networking is utilized and the working environment used in our project is matlab.
Keywords: Artificial Neural Network Algorithm, Diabetic Retinopathy, Image Processing.