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Abstract. Diabetic Retinopathy is considered as a root cause of vision loss for diabetic patients. For Diabetic patients, regular check-up and screening is required. At times lesions are not visible through fundus image, Dr. Recommends angiography. However Angiography is not advisable in certain conditions like if patient is of very old age, if patient is a pregnant woman, if patient is a child, if patient has some critical disease or if patient has undergone some major surgery. In this paper we propose a system Automated Diabetic Retinopathy Detection System (ADRDS) through which fundus image will be processed in such a way that it will have the similar quality to that of angiogram where lesions are clearly visible. It will also identify the Optic Disk (OD) and extract blood vessels because pattern of these blood vessels near optic disc region plays an important role in diagnosis for eye disease. We have passed 100 images in the system collected from Dr. Manoj Saswade and Dr. Neha Deshpande and got true positive rate of 100%, false positive rate of 3%, and accuracy score is 0.9902.

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Glaucoma is an eye disease. In glaucoma retinal nerve fiber layers are damaged and if it is not treated earlier then it can cause permanent vision loss. This paper represents algorithm for detection of glaucoma using retinal nerve fiber layers. For this work we have used 2D median filter and HAAR wavelet transform methods. For this work we have also used Drishti-GS dataset which contains101 glaucomatous images and HRF (High Resolution Fundus image) database. We have extracted the retinal nerve fiber layer Arteries. Then we have calculated its area and diameter. On the normal database we got the 100% result. We got 71.28% accuracy on glaucomatous images and when we have combined the normal and glaucomatous images then we got the 62.06% accuracy.

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