A new dynamic thresholding based technique for detection of hard exudates in digital retinal fundus image

Diabetic retinopathy is one of the major causes of blindness among diabetes mellitus patients. In case of diabetic retinopathy blood vessels of retina gets ruptured and lipoprotein substances gets leaked out of the damaged blood vessels and are deposited in the intra retinal space. The part of optic nerve beneath these substances are barred from being excited by light rays and failed to produce any nerve impulse to brain and leads to partial loss of vision. These lipoprotein substances are yellowish in color and are termed as exudates. Exudates are the primary as well as most important sign of the presence of diabetic retinopathy. If the disease is not detected in early stages then it may lead to complete loss of vision to the diabetes patients. But detection of exudates is extremely difficult to detect by visual inspection due to small inner diameter of retina. Sometimes inadequate illumination makes the problem worse. An efficient image analysis program can detect the presence effectively. In this paper we have proposed one such method is proposed. The proposed method uses various image processing techniques, such as median filtering, image thresholding etc. with a goal to detect hard exudates. The proposed method exhibits a sensitivity of 97.25% and specificity of 96.85%.