Accurately identifying the location of hard exudate in retinal fundus helps to reduce the risk of blindness caused by diabetic retinopathy. An approach based on IHBMO-RF was proposed for hard exudate detection. The preprocessing procedure contains brightness correction, nonlinear wavelet denoising and high-hat filter enhancement. We used 2D Gaussian matched filter to locate the center of the optic disc and eliminate it. Secondly, the morphological methods were applied to obtain exudate candidate areas. Finally, the candidate regions were classified by using the IHBMO-RF algorithm to extract the final and accurate hard exudate. This method was tested in the published DiaretDB1 fundus image database and the accuracy of extraction of hard exudate was 96.8%. The experiment shows that based on the IHBMO-RF algorithm can accurately identify the position of hard exudate in fundus images and has good robust performance.
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