Vessel detection is a fundamental step in retinal analysis which helps to extract further information such as characterization of changes in blood vessels width and tortuosity. In this paper, we present an automatic algorithm based on edge detection and fuzzy inference. In the proposed method, the direction of linear structures are determined with Radon transform, then Sobel operator is used for extracting edges along with the predetermined direction. The combination of gradient information of vessel edges with fuzzy theory and genetic algorithm help us in the vessel validation process. Ultimately, the vessel is reconstructed via the extracted edges and morphological algorithms. Experimental results on 40 images of DRIVE database show that the proposed algorithm despite its simplicity has a high performance in comparison with other edge detector algorithms which are found to be sensitive to noise.

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