Blood Vessels Extraction in Retinal Image Using New Generation Curvelet Transform and Adaptive Weighted Morphology Operators

According to many medical and biometric applications of retinal images، the automatic and accurate extraction of the retinal blood vessels is very important. In this paper، an effective method is introduced to extract the blood vessels from the background of colored images of retina. In this algorithm، by applying the equalizer function on the retinal images، the brightness of the images is considerably uniformed. Because of high ability of Curvelet transform in introducing image borders in various scale and directions، borders and، consequently the contrast of retinal images can be enhanced. Therefore، the enhanced retinal image can be prepared for the extraction of blood vessels by improving Curvelet coefficients of the retinal images، adaptively and locally. Since the blood vessels in retinal images are distributed in various directions، we use the adaptive weighted morphology operators to extract the blood vessels from retinal images. Morphology operators based on reconstruction are used to refine the appeared frills with the size of smaller than arterioles in images properly. Finally، by analyzing the connected component in the images and applying adaptive filter on the components locally، all residual frills are refined from the images. The proposed algorithm in this paper has been evaluated by the images in the DRIVE database. The results how that the blood vessels are extracted from background of the retinal images of DRIVE database with the high accuracy of 96. 15%، which in turn shows the high ability of the proposed algorithm in extracting the retinal blood vessels.