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dc.contributor.authorXie, Jiezhenzh_CN
dc.contributor.authorYu, Xiaoxingzh_CN
dc.contributor.authorZheng, Xulingzh_CN
dc.contributor.author郑旭玲zh_CN
dc.date.accessioned2015-07-22T02:39:50Z
dc.date.available2015-07-22T02:39:50Z
dc.date.issued2012zh_CN
dc.identifier.citationProceedings - 2012 5th International Symposium on Computational Intelligence and Design, ISCID 2012, 2012,2:202-205zh_CN
dc.identifier.other20130716008328zh_CN
dc.identifier.urihttps://dspace.xmu.edu.cn/handle/2288/86804
dc.descriptionConference Name:2012 5th International Symposium on Computational Intelligence and Design, ISCID 2012. Conference Address: Hangzhou, China. Time:October 28, 2012 - October 29, 2012.zh_CN
dc.description.abstractIn this paper, we propose a novel hybrid method for the segmentation and automatic counting of biological cell image. The method is based on techniques of morphology, thresholding and watershed. It performs well in low contrast image where gradient-based method may fail. Experimental results on practical cell images are shown in the paper with the emphasis on the comparisons between the novel hybrid method and the gradient-based methods: Sobel [1], Canny [2] and GAC [3] of level-set. 漏 2012 IEEE.zh_CN
dc.language.isoen_USzh_CN
dc.publisherIEEEzh_CN
dc.source.urihttp://dx.doi.org/10.1109/ISCID.2012.202zh_CN
dc.subjectArtificial intelligencezh_CN
dc.subjectCellszh_CN
dc.subjectMorphologyzh_CN
dc.subjectWatershedszh_CN
dc.titleBiological cell image segmentation using novel hybrid morphology-based methodzh_CN
dc.typeConferencezh_CN


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