Title: Diagnosis of diseases from retinal images using support vector machine

Authors: C. Malathy; Sneha Das

Addresses: CSE Department, SRM Institute of Science and Technology Kattankulathur, India ' CSE Department, SRM Institute of Science and Technology Kattankulathur, India

Abstract: The retina is a thin membrane present at the back of our eye which allows us to see the world around us. Identifying retinal diseases at an early stage is very important, as it may lead to loss of vision. The problem arises in the recognition procedure of some patients. The focus was made to automatically diagnose the retinal diseases from the retinal images using machine learning technique. The images were taken from the DRIVE database and also from retina_gallery.com website. Input images were pre-processed and the region of interest (ROI) was taken. Then by local binary pattern (LBP) the features of the images were extracted, image segmentation was done on the images and finally support vector machine (SVM) was applied to diagnose the diseases. The accuracy with SVM was found to be more compared to other algorithms of machine learning.

Keywords: local binary pattern; LBP; support vector machine; SVM.

DOI: 10.1504/IJHTM.2021.119161

International Journal of Healthcare Technology and Management, 2021 Vol.18 No.3/4, pp.275 - 292

Received: 28 May 2018
Accepted: 07 Dec 2018
Published online: 26 Nov 2021 *

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