Projection based algorithm for detecting exudates in color fundus images

The detection and analysis of spot lesions associated with the retinal diseases, such as exudates, microaneurysms, and hemorrhages, play an important role in the screening of retinal diseases. This paper presents an algorithm for segmentation of automated exudates from color fundus images. The proposed algorithm comprises two major stages, namely, pre-processing and segmentation. A novel pre-processing method is employed for background removal through contrast enhancement and noise removal. In the second stage, the pre-processed image is sliced horizontally and vertically into a number of slices and then the corresponding projection values are obtained in order to select an appropriate threshold value for each of the image slices. Finally, optic disc is removed to facilitate the correct identification of exudates and to decrease the false positive cases. DIARETDB1 database is used to measure the accuracy of the proposed method. Based on the experiments which are conducted on pixel basis, it is found that the proposed algorithm achieves better results compared to known algorithms. With the proposed algorithm, average values of 71.2%, 72.77%, 99.98%, 97.72%, 99.74%, and 83.28% are obtained in terms of overlap, sensitivity, specificity, PPV, accuracy, and kappa coefficient respectively.