vioft2nntf2t|tblJournal|Abstract_paper|0xf4ffa3a925000000c874030001000800 Eye is a vital organ of vision of the human body. Eyes are used almost in every activity whether in reading, affect developmental learning, working and in other untold ways. But, the eye diseases like Cataracts, Macular degeneration, Retinopathy, Glaucoma etc. gradually influence on the eye and leads to blindness. For the early detection of symptoms of eye diseases the ophthalmologist uses the manual observation method. But, that is time consuming and error prone. In this paper, to save the time and reduce the probability of the error, eye disease prediction approach for Glaucoma is developed. For this eye disease prediction approach firstly, the continuous and non-continuous Blood Vessels are segmented using the Coye Filter Approach. Secondly, the bright region of the Optic Disc is segmented using the MRF and Compensation Factor Method. Finally, the channels intensities of the bright region of Optic Disc is compared with the range of channels intensity of the set of bright region of the healthy Retinal images for prediction of the Glaucoma affection. The range for each channel consist of the intensity value starts from minimum to maximum intensities from the set of healthy Retinal images. For this, the Retinal Fundus image is captured by digital Fundus camera with the field of view between 35o to 50o. The Coye Filter Approach, MRF and Compensation Factor Method is applied for the Diaretdb1 and DRIVE which successfully segment the Blood Vessels as well as Optic Disc and also the eye disease prediction approach is applied for the 10 Glaucoma images which correctly predict for the Glaucoma affection.
Rahul Jadhav, Manish Narnaware
Walchand College of Engineering, India
Retinal Fundus Image, Glaucoma, Optic Disc, Blood Vessels, Retinopathy
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| Published By :
ICTACT
Published In :
ICTACT Journal on Image and Video Processing
( Volume: 8 , Issue: 3 , Pages: 1696-1707 )
Date of Publication :
Februray 2018
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