Contrast Normalization Filtering Modules for Segmentations of Retinal Blood Vessels from Color Retinal Fundus Images
DOI:
https://doi.org/10.30537/sjet.v5i1.1025Keywords:
Diabetic retinopathy: retinal image: optic disc: morphological tactics:Principle component analysis: double thersholdAbstract
Vision loss is one of the main complications of eye disease, especially diabetic retinopathy (DR), because DR is a silent disease affecting the retina of the eye and resulting in loss of vision. Manual observation of eye disease takes time and delays effective treatment, so computerized methods are used to diagnose eye disease by extracting their features such as blood vessels, optic disc, and other abnormalities. Many computerized methods are proposed but it is still lacking to obtain small vessels. To overcome this problem, we have proposed methods based on image processing techniques for detection of retinal vessels. The proposed method is based on the elimination of uneven illumination using morphological tactics and principal component analysis. These initial steps are known as the preprocessing module, and our post-processing module contains the vessel coherence and the double threshold binarization method to obtain an image of the segmented vessels. Our proposed method obtained comparable results (average results (sensitivity: 0.78, specificity: 0.95 and precision: 0.951)) compared to the existing methods on the DRIVE and STARE databases.
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