Although current literature abounds in a variety of edge detection algorithms, they do not always lead to acceptable results in extracting various features in an image. In this paper, we address the problem of detecting blood vessels in retinal images. Blood vessels nsually have poor local contrast and the application of existing edge detection algorithms yield results which are not satisfactory. We introduce an operator for feature extraction based on the optical and spatial properties of objects to be recognized. The gray-level profile of the cross section of a blood vessel is approximated by a Gaussian shaped curve. The concept of matched filter detection of signals is used to detect piecewise linear segments of blood vessels in these images. We construct 12 different templates that are used to search for vessel segments along all possible directions. We discuss various issues related to the implementation of these matched filters. The results are compared to those obtained with other methods. The automatic detection of blood vessels in the retina could help physicians in diagnosing ocular diseases.
They have used the concept of matched filter for detection of signals to detect piecewise linear segments of blood vessels in retinal images and constructed 12 different templates to search for vessel segments along all possible directions REF .
Detection of blood vessels in retinal images using two-dimensional matched filters.
IEEE transactions on medical imaging
IEEE transactions on medical imaging
Mathematics Medicine