COMPARATIVE STUDY OF DIABETIC RETINOPATHY USING K-NN AND BAYESIAN CLASSIFIER

Authors

  • S.P.ARADE Department of Electronics and Telecommunication, Shivaji University/Bharati Vidyapeeth’s College of Engineering, Kolhapur, India
  • J.K. PATIL Department of Electronics and Telecommunication, Shivaji University/Bharati Vidyapeeth’s College of Engineering, Kolhapur, India

Keywords:

Digital retinal images, Healthy retina

Abstract

Diabetic retinopathy is damage to the retina,specifically blood vessels in the retina, caused by diabetes. Itnormally starts without any noticeable change in vision. For diagnosis of diabetic retinopathy, ophthalmologists use the retinal image of a patient which is known as fundus image. The blood vessels can be captured directlyfrom retina.This paper presents an automated image processing system which detects the gradationof diabetic retinopathy. Segmentation of blood vessels is performed by using kirsch method. Gray level features of segmented vessels are extracted using moment invariants. The severity of diabetic retinopathy is detected using feed forward neural network along with K-NN and Bayesian classifier.

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Published

2021-03-27

Issue

Vol. 4 No. 5 (2017): IJIERT

Section

Articles

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How to Cite

S.P.ARADE, & J.K. PATIL. (2021). COMPARATIVE STUDY OF DIABETIC RETINOPATHY USING K-NN AND BAYESIAN CLASSIFIER. International Journal of Innovations in Engineering Research and Technology, 4(5), 1-7. https://repo.ijiert.org/index.php/ijiert/article/view/1384