Support Vector Machine Based Method for Automatic Detection of Diabetic Eye Disease using Thermal Images

Mrinmayee Wankhade , Abhishek Yadav , Sonam Manwatkar , Supriya Sarak

— Diabetic eye disease, Infrared Thermography, GLCM, Support Vector Machine

Diabetic eye disease is one of the major problems worldwide. Early detection of eye diseases increases the survival rate by successful treatment. The proposed methodology is to explore machine learning technique to detect diabetic diseased using thermography images of an eye and to introduce the effect of thermal variation of abnormality in the eye structure as a diagnosis imaging modality which are useful for ophthalmologists to do the clinical diagnosis. Thermal images are pre-processed, and then Gray Level Cooccurrence Matrix (GLCM) based texture features from gray images, statistical features from RGB and HSI images are extracted and classified using classifier with various combination of features. To detect diabetic diseased eye, here Support Vector Machine classifier is used for classification and their performance are compared. A 5-fold cross validation scheme is used to enhance the generalization capability of the proposed method. Experimental results obtained for various feature combinations gives maximum accuracy of 86. 22%, sensitivity of 94. 07% and specificity of 79. 17% using SVM classifier with five-fold validation.

Published Paper   E-Certificate

"Support Vector Machine Based Method for Automatic Detection of Diabetic Eye Disease using Thermal Images", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.5, Issue 1, page no.15 - 24, January-2020, Available :https://ijsdr.org/papers/IJSDR2001003.pdf

Volume 5 Issue 1, January-2020

Pages : 15 - 24

Paper Reg. ID: IJSDR_191176

Published Paper Id: IJSDR2001003

Downloads: 000347253

Research Area: Engineering

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2001003

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2001003

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition