Retinal vessel segmentation based on adaptive difference of Gauss filter

Based on the difference of Gauss (DoG) filter, a new retinal vessel segmentation method is proposed in this paper. Firstly, contrast limited adaptive histogram equalization (CLAHE) is used to improve the contrast of the image and then anisotropic diffusion equation is applied to smooth the image for the central reflex of the vessel. Secondly, adaptive DoG (ADoG) with different scale factor σ is used to give the initial vessel segmentation result. Then, the refined vessel enhancement result is computed by the superposition of ADoG in twelve directions. At last, the non-vessel is removed based on the bimodality of histogram of the image after enhancement and smoothing. We evaluate experimental results on the public DRIVE and STARE datasets qualitatively and quantitatively, and demonstrate the performance of the proposed method.