Dynamic thresholding technique for detection of hemorrhages in retinal images

Abstract

The paper proposes a dynamic thresholding based image processing technique for the detection of hemorrhages in retinal images. The algorithm uses the information about color and size of hemorrhages as a tool for classifying hemorrhages from other dark lesions present in the retinal images. The algorithm uses the concepts of contrast enhancement, background estimation and intensity variation at edges that is gradient magnitude information supported by some morphological operations. The algorithm follows a simple approach of step by step removal of unwanted features from targeted images using concepts of thresholding and morphology without compromising with accuracy and time of execution. The experimental results indicate that hemorrhages are detected with good accuracy in the retinal images.