automated detection of optic disk in retinal fundus images using intuitionistic fuzzy histon segmentation the human eye is one of the most sophisticated organs with perfectly interrelated retina pupil iris cornea lens and optic nerve automatic retinal image analysis is emerging as an important screening tool for early detection of eye diseases uncontrolled diabetic retinopathy dr and glaucoma may lead to blindness the identification of retinal anatomical regions is a prerequisite for the computeraided diagnosis of several retinal diseases the manual examination of optic disk od is a standard procedure used for detecting different stages of dr and glaucoma in this article a novel automated reliable and efficient od localization and segmentation method using digital fundus images is proposed generalpurpose edge detection algorithms often fail to segment the od due to fuzzy boundaries inconsistent image contrast or missing edge features this article proposes a novel and probably the first method using the attanassov intuitionistic fuzzy histon aifshbased segmentation to detect od in retinal fundus images od pixel intensity and columnwise neighborhood operation are employed to locate and isolate the od the method has been evaluated on 100 images comprising 30 normal 39 glaucomatous and 31 dr images our proposed method has yielded precision of 093 recall of 091 fscore of 092 and mean segmentation accuracy of 934 we have also compared the performance of our proposed method with the otsu and gradient vector flow gvf snake methods overall our result shows the superiority of proposed fuzzy segmentation technique over other two segmentation methods