Diabetes mellitus is a major disease spread all across the globe. Long-time diabetes mellitus causes the complication in the retina called Diabetic Retinopathy (DR), which results in visual loss and sometimes blindness. In this paper, we discuss a simple and effective algorithm for segmentation of the optic disk (OD) and bright lesions such as hard exudates from color retinal images. Color fundus images are enhanced using brightness transform function. Morphological operator along with the Circular Hough Transform (CHT) is used for optic disk segmentation. Further, local mean and entropy based region growing technique is applied in order to classify exudatenon-exudate pixels in retinal images. The performance of the proposed algorithm has been tested on publicly available standard Messidor database images with varied disease levels and nonuniform illumination. Experimentation yields 94% success rate for localization of the optic disk, 99% accuracy of classification of exudate -non-exudate pixels and subject level accuracy is found to be 93% and 67% in identifying the abnormal (with exudates) and normal (without exudates) images respectively.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.