Automated Retinal Vessel Segmentation Using Entropic Thresholding Based Spatial Correlation Histogram of Gray Level Images
Belhadi Soumia and Benblidia Nadjia
Faculty of science, Saad Dahlab University, Algeria
Abstract: After highlighting vessel like structure by an appropriate filter in matched filter technique, thresholding strategy is needed for the automated detection of blood vessels in retinal images. For the purpose, we propose to use a new technique of entropic thresholding based on Gray Level Spatial Correlation (GLSC) histogram which takes into account the image local property. Results obtained show robustness and high accuracy detection of retinal vessel tree. An appropriate technique of thresholding allows significant improvement of the retinal vessel detection method.
Keywords: Automated screening, retinal vessel segmentation, matched filtering, thresholding.
Received July 20, 2012; accepted January 29, 2013
