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Detection and Classification of Microaneurysms for Diabetic Retinopathy 1

Detection of Microaneurysm at an early stage is the first step in preventing Diabetic Retinopathy. Diabetic Retinopathy is caused by the complications of diabetes which can eventually lead to blindness. This paper proposes Support Vector Machine classifier to impove the detection of the microaneurysm in digital fundus images so that the detections are not faulty. Support Vector Machines are supervised learning models with associated algorithms that analyse data and recognise patterns used for classification and regression analysis.The proposed algorithm classifies the images using Support Vector Machine Classifier. Pre-processing methods are used to enhance the image. The candidates are then extracted from the pre-processed image using the methods described. These extracted candidates is the problem domain for the Support Vector Machine classifier. The Support Vector Machine classifier classifies the images to correctly determine the findings of candidate extraction to be microaneursym or not. The simulations of the algorithms are done and the