This paper presents an efficient model for automatic detection and extraction of blood vessels in ocular fundus images. The model is formed using a combination of the concept of ribbon snakes and twin snakes. On each edge, the twin concept is introduced by using two snakes, one inside and one outside the boundary. The ribbon concept integrates the pair of twins on the two vessel edges into a single ribbon. The twins maintain the consistency of the vessel width, particularly on very blurred, thin and noisy vessels. The model exhibits excellent performance in extracting the boundaries of vessels, with improved robustness compared to alternative models in the presence of occlusion, poor contrast or noise. Results are presented which demonstrate the performance of the discussed edge extraction method, and show a significant improvement compared to classical snake formulations
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