Automatic segmentation of blood vessels in retinal image based on fuzzy K-median clustering

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dc.contributor.authorSupot, Sookpotharom
dc.contributor.authorThanapong, Chaichana
dc.contributor.authorChuchart, Pintavirooj
dc.contributor.authorManas, Sangworasil
dc.date.accessioned2026-08-06T09:56:08Z
dc.date.available2026-08-06T09:56:08Z
dc.date.issued2007-12-01
dc.description.abstractThis paper presents an efficient method for automatic segmentation of blood vessels in retinal images. Specifically, we also delineate vascular intersections/crossovers. The proposed algorithm is composed of three steps: matched filter, fuzzy k-median (FKMED), and length filter. The segmentation results are compared with clinically generated vessel segmentation and are evaluated in terms of sensitivity and specificity. The results are encouraging and will be used for further application such as personal identification. © 2007 IEEE.
dc.identifier.citationIEEE Icit 2007 2007 IEEE International Conference on Integration Technology, 584-588, 2007
dc.identifier.doi10.1109/ICITECHNOLOGY.2007.4290384
dc.identifier.other2-s2.0-46449110650
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/1875
dc.sourceIEEE Icit 2007 2007 IEEE International Conference on Integration Technology
dc.subjectBlood vessel
dc.subjectFuzzy c-mean
dc.subjectFuzzy k-median
dc.subjectMatched filter
dc.subjectRetinal image
dc.titleAutomatic segmentation of blood vessels in retinal image based on fuzzy K-median clustering
dc.typeConference Paper

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