Vessel Junction Detection From Retinal Images
نویسندگان
چکیده
This paper presents a perceptual organization based method for detecting Vessel Junctions (VJs) from retinal images. A retinal image is first segmented into edge traces which contain vessel boundaries. Each trace is divided into generic curve segments (GCSs) at curve partitioning points (CPPs). CPPs are the places on a trace from where the continuity of GCSs was broken according to perceptual organization criteria. The extracted CPPs and GCSs are the structure features of VJs. The detection algorithm uses CPPs as seeds for searching VJ patterns. VJs have two classes which include branching type and crossing type defined according to their structure features. Experiment results are provided.
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