Automatic detection of the macula in retinal fundus images using multilevel thresholding

Jiri Minar, Kamil Riha, Ales Krupka, Hejung Tong


The paper proposes a novel method for detection of macula in medical image of human eye – retinal fundus images, that can be used in ophthalmology for detecting various eye’s diseases as glaucoma, diabetic retinopathy or macula oedema. The method utilizes an approach of multilevel thresholding ofred channel of fundus retinal image. Subsequently, thethresholded layers are preprocessed by application of median blur filter. And algorithm for ellipse detection from OpenCVlibrary is used on all thresholding level. Then proposed technique analyzes detection and evaluates position of macula in fundus image. The precision of the method is evaluated on dataset from public fundus image library DRIVE. The results were 100% for image with visible macula.

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