A Novel 5x5 Edge Detection Operator for Blood Vessel Images
Toufic El-Arwadi
Department of Mathematics and Computer Science, Faculty of Science, Beirut Arab University, Lebanon.
Ali El-Zaart *
Department of Mathematics and Computer Science, Faculty of Science, Beirut Arab University, Lebanon.
*Author to whom correspondence should be addressed.
Abstract
Background: Blood vessel appearance is an important indicator for many diagnoses, including diabetes, hypertension, and arteriosclerosis.
Aims: Blood Vessel edge detection in retinal images is very important in medical image processing. A lot of algorithms have been suggested for extracting medical image edges.
Methodology: In this paper a new 5x5 edge detection masks are proposed based on the finite difference method.
Results: The proposed method is applied on a set of blood vessel images and we obtained good results in comparison with 5x5 Sobel mask.
Keywords: Blood vessel detection, edge detection, 5xr5 mask operator, Taylor’s expansion