An Efficient Method to Detect Diabetic Retinopathy Using Gaussian-Bilateral and Haar Filters with Threshold Based Image Segmentation

A digital imaging technique is utilized in almost all the fields. Based on image processing concept image particle shape can be analyzed in detail. Nowadays, in eye clinics, imaging of the eye fundus with modern technology is in high demand because of its worth and expected lifetime. Eye fundus imaging is considered a noninvasive and painless route to screen and monitor the micro vascular distinction of diabetes and diabetic retinopathy. In general, Optic Disc (OD) signifies the creation of the optic nerve. It is the point where the axons of retinal ganglion cells gain nearer. The Optic Disc is an access point of major blood vessels which provides the retina. In this study a method is introduced to automatically detect the position of the OD in digital retinal fundus images. The OD detection algorithm is based on the identical expected directional pattern of the retinal blood vessels. In this study two types of filters are proposed, one is Gaussian based bilateral filter, to reduce/eliminate the noise of the fundus images and another is a Haar filter to detect the diabetic retinopathy in the fundus images. The most excellent method to segment the images is thresholding based connected component pixels. The results have been taken from many diabetic retinopathy images. In this study for implementation efficient image filtering was used and named as OpenCV 2.4.9.0 and cvblobslib to accomplish successful result. In future development, the fovea detection will be applied.