An Automated System for Detecting Anatomical Structures and Exudates in Retinal Fundus Images

This paper proposes an automated system for the detection of important anatomical structures such as the Blood Vessels, Optic Disc (OD), Macula and also Exudates in digital fundus retinal images. Blood vessel Detection (BVD) was done using canny edge detection. Optic disc localization was done using pyramidal decomposition and Hausdorff-based template matching. Macula was located using pyramidal decomposition. Exudates are found using machine learning algorithm which uses k-nearest neighbor classifier and a linear discriminant classifier. The procedure has been tested on a database of about 100 color fundus images acquired from a digital non-mydriatic fundus camera and the experimental results show the accuracy of the system.