Textures and Intensity Histogram Based Retinal Image Classification System Using Hybrid Colour Structure Descriptor

Medical image classiûcation system is widely used by the radiologists to segment the medical images into meaningful regions. Diabetic retinopathy is an ocular manifestation of diabetes, and diabetics are at a risk of loss of eyesight due to diabetic retinopathy. Diabetes being a bloodrelated phenomenon, causes vascular changes, which can often be detected visually by examining the retina, since the retina is well-irrigated by blood vessels. Worldwide, DR is a leading cause of blindness among working populations. DR is also the most frequent micro-vascular complication of diabetes. The eye is one of the first places where micro-vascular damage becomes apparent. Though diabetes is still incurable, treatments exist for DR, using laser surgery and glucose control routines. In this article, computer assisted, multi class lesion classification system using hybrid color image structure descriptor and pair of RBF kernel based SVM in retinal images is developed. It classifies the lesions in to Normal and abnormal classes.The overall classification accuracy of HCSID with HKSVM is 94%, HCSID with SVM is 90 % HCSID with RBF is 84% and HCSID with FFNN is 84%..

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