Proposal of a Content Based retinal Image Retrieval system using Kirsch template based edge detection

In this work, a Content Based Image Retrieval (CBIR) frame work is developed based on edge detection method for diagnosis of diabetic retinopathy. Normal and abnormal retinal fundus images are subjected to preprocessing methods to enhance the edge information. Two different methods namely Kirsch template and Canny edge based detection techniques are considered for segmentation of blood vessels. The structure and texture based features obtained from segmented images are analyzed. Best features for retinal image retrieval are selected from the quantitative analysis of features. Similarity matching is carried out using Euclidean distance method and the retrieved images are ranked. Retrieval efficiency is calculated in terms of precision and recall. The results show that the Kirsch template based edge detection method identifies most of the blood vessels compared to the other method. High degree of precision and recall are observed using the Kirsch template based CBIR system. It appears that the Kirsch edge based detection could be useful in CBIR system for diagnosis of retinal abnormalities.