Abstract
In recent days, most of the diabetic patients are affected by vision problem due to Glaucoma. In many cases, an untreated glaucoma will lead to loss of sight. To avoid such complications and to identify the risk well in advance, a new image processing based approach is presented in this article. This method detects the existence of hard exudates and evaluate the brutality of the threat based on the extracted features. The proposed method involves three stages of process such as extraction of region of interest (ROI), feature selection and abnormality classification. Initially, a region of interest is calculated using segmentation and the foreground features are selected by estimating the presence of hard exudates from the centre of the optical disc. Finally, the severity of DR is identified with the help of extracted features based on the Bayes classifier. Experiment was carried in MATLAB environment and the performance was evaluated using the metrics such as accuracy, precision and false alarm.
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