Segmentation of retinal blood vessels based on the second directional derivative and region growing

We present a method for the segmentation of blood vessels in retinal images based upon the second derivative of the intensity image which gives information about its topology and overcomes the problem of image intensity variations. The minimum eigenvalue and the magnitude of its gradient are used as features for a region growing procedure which is defined in two stages. For the first stage, growth is restricted to regions with low gradients, allowing vessels to grow where the values of the minimum eigenvalue lie within a wide interval and allowing rapid growth of background regions outside of the vessel boundaries. For the second stage, in which the borders between classes are defined, the algorithm grows vessel and background classes simultaneously without the gradient restriction.