Blood vessels segmentation in retina via wavelet transforms using steerable filters

This paper presents an efficient method for automatic segmentation of blood vessels in retinal images. A set of directional basis filters based on dyadic wavelet transform is designed to enhance blood vessels. It attempts to utilize the linear combination of the wavelet transforms to fix on the blood vessels directional information in retinal images. The directional maps are processed by thresholding scheme in order to segment blood vessels from the background. The proposed thresholding approach evaluates 2-D entropies based on the gray level-gradient co-occurrence matrix. The 2-D thresholding vector that maximizes the edge class entropies is selected. The thresholding method utilizes the gray level and gradient information in the enhanced image. The new method promises the simpleness and flexibility in many image enhancement and segmentation applications.