Automatic Detection of Optic Disc for Diabetic Retinopathy
Priyanka Konatham1, Mounika Venigalla2, Lakshmi Pooja Amaraneni3, K. Suvarna Vani4
1Priyanka Konatham*, CSE, VR Siddhartha Engineering College, Vijayawada, India.
2Mounika Venigalla, CSE, VR Siddhartha Engineering College, Vijayawada, India.
3Lakshmi Pooja Amaraneni, CSE, VR Siddhartha Engineering College, Vijayawada, India.
4Dr. K. Suvarna Vani, Professor, VR Siddhartha Engineering College, Vijayawada, India.
Manuscript received on April 20, 2020. | Revised Manuscript received on April 30, 2020. | Manuscript published on May 10, 2020. | PP: 1013-1015 | Volume-9 Issue-7, May 2020. | Retrieval Number: F4390049620/2020©BEIESP | DOI: 10.35940/ijitee.F4390.059720
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Diabetic Retinopathy affects the retina of the eye and eventually it may lead to total visual impairment. Total blindness can be avoided by detecting Diabetic Retinopathy at an early stage. Various manual tests are used by the doctors to detect the presence of disease, but they are tedious and expensive. Some of the features of Diabetic Retinopathy are exudates, haemorrhages and micro aneurysms. Detection and removal of optic disc plays a vital role in extraction of these features. This paper focuses on detection of optic disc using various image processing techniques, algorithms such as Canny edge, Circular Hough (CHT). Retinal images from IDRiD, Diaret_db0, Diaret_db1, Chasedb and Messidor datasets were used.
Keywords: Canny edge, Circular Hough (CHT), Diabetic Retinopathy, Image processing, Optic disc.
Scope of the Article: Image Processing and Pattern Recognition