Keypoint detectors and texture analysis based comprehensive comparison in different color spaces for automatic detection of the optic disc in retinal fundus images

3Citations
Citations of this article
10Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Detection of the optic disc which has similar brightness with the hard and soft exudate lesions seen in the early stage of diabetic retinopathy is very difficult due to different light conditions and contrast values. Automatic detection of these lesions by expert systems in the medical field is very important. In this context, we propose a new approach based on the analysis of color spaces, keypoint detectors, and texture for retinal fundus images. If the keypoint information is contained within the actual optic disc region, this is an important consideration for the automated detection of the optic disc. This study can be divided into five sections, respectively, image preprocessing, image processing, keypoint detection, texture analysis, and performance evaluation. The analyses of patch images compatible with the keypoints obtained from the Red–Green–Blue (RGB) image and its color channels were carried out. The performance of the study was validated on the Digital Retinal Images for Vessel Extraction public dataset. According to the results, Local Binary Pattern texture analysis performed in region of interest around keypoints detected by different keypoint detectors presented good performance in RGB and green channel images.

Cite

CITATION STYLE

APA

Akyol, K., & Şen, B. (2021). Keypoint detectors and texture analysis based comprehensive comparison in different color spaces for automatic detection of the optic disc in retinal fundus images. SN Applied Sciences, 3(9). https://doi.org/10.1007/s42452-021-04754-7

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free