A simple single seeded region growing algorithm for color image segmentation using adaptive thresholding

dc.contributor.authorVerma, O.P.
dc.contributor.authorHanmandlu, M.
dc.contributor.authorSusan, S.
dc.contributor.authorKulkarni, M.
dc.contributor.authorJain, P.K.
dc.date.accessioned2020-03-30T09:58:32Z
dc.date.available2020-03-30T09:58:32Z
dc.date.issued2011
dc.description.abstractIn this paper, we present a region growing technique for color image segmentation. Conventional image segmentation techniques using region growing requires initial seeds selection, which increases computational cost & execution time. To overcome this problem, a single seeded region growing technique for image segmentation is proposed, which starts from the center pixel of the image as the initial seed. It grows region according to the grow formula and selects the next seed from connected pixel of the region. We use intensity based similarity index for the grow formula and Otsu's Adaptive thresholding is used to calculate the stopping criteria for the grow formula. We apply the proposed method to the Berkley segmentation database images and discuss results based on Liu's F-factor that shows efficient segmentation. � 2011 IEEE.en_US
dc.identifier.citationProceedings - 2011 International Conference on Communication Systems and Network Technologies, CSNT 2011, 2011, Vol., , pp.500-503en_US
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/7130
dc.titleA simple single seeded region growing algorithm for color image segmentation using adaptive thresholdingen_US
dc.typeBook chapteren_US

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