Article,
Vessels Classification in Retinal Images by GraphBased Approach
International Journal on Recent and Innovation Trends in Computing and Communication, 3 (3): 1646--1648 (March 2015)
DOI: 10.17762/ijritcc2321-8169.1503163
Abstract
The classification of retinal vessels into artery/vein (A/V) is an important phase for automating the detection of vascular changes. This paper presents an automatic approach for A/V classification based on the analysis of a graph extracted from the retinal vasculature. Classifier classifies the entire vascular tree deciding on the type of each intersection point (graph nodes) and assigning one of two labels to each vessel segment (graph links). Final classification of a vessel segment as A/V is performed through the combination of the graph-based labeling results with a set of intensity features. Our method out performs recent approaches for A/V classification. Normal retinal images vessels are segmented using the morphological operations and then using graph trace algorithm for identification the center line of the vessels and trace the pixel values as a feature and use the KNN classifier to classify the feature and assign which is the artery and which is the vein in retinal image. From features we extract the thickness of the vessels to identify the disease details.
