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.
Highlights
Exudates are a major cause of an increasing percentage of Diabetic Retinopathy (DR) in developing countries, especially in Thailand
To achieve the same goal, the application described in Goh et al (2001), an automated detection of the exudates in the digital retinal images using a Principle Component Analysis (PCA) method in RGB color component is adopted
In the coarse segmentation stage in RGB color space, the results reveal that there is some losing of exudates region and sometimes there are extra segmented regions
Summary
Exudates are a major cause of an increasing percentage of Diabetic Retinopathy (DR) in developing countries, especially in Thailand. A region growing method uses to detect the exudates (Sinthanayothin et al, 2002). To achieve the same goal, the application described in Goh et al (2001), an automated detection of the exudates in the digital retinal images using a Principle Component Analysis (PCA) method in RGB color component is adopted. This method works only for detection of exudates that can be approximated by the high resolution images it takes into consideration. This method works only for detection of exudates that can be approximated by the high resolution images it takes into consideration. Sopharak et al (2010) and Osareh et al
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