Journal of Computer Science

Automatic Detection of Exudates in Retinal Images using Region-Based, Neighborhood and Block Operation

Kittipol Wisaeng and Worawat Sa-Ngiamvibool

DOI : 10.3844/jcssp.2018.438.452

Journal of Computer Science

Volume 14, Issue 4

Pages 438-452

Abstract

Exudates detection is one of the research areas attracting great attention of physicians and scientists. A region-based, neighborhood, block operation and optimal global thresholding are proposed as new methods to exudates detection. The exudates are coarse and fine segmentation following preprocessing steps, i.e., color mapping, image contrast enhancement, fuzzy filtering and optic disc localization. To classify the retinal images into non-exudates and exudates, a set of features such as texture, color, size and the edge is extracted. The exudates procedure succeeded in an overall generalization accuracy of 98.62% with 98.18% sensitivity and 98.32% specificity in local databases. Moreover, the results are presented to show the advantage of the proposed method in a public database with an accuracy of 92.14.

Copyright

© 2018 Kittipol Wisaeng and Worawat Sa-Ngiamvibool. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.