{"title":"基于混合形态学的生物细胞图像分割方法","authors":"Jiezhen Xie, Xiaoqing Yu, Xuling Zheng","doi":"10.1109/ISCID.2012.202","DOIUrl":null,"url":null,"abstract":"In 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.","PeriodicalId":246432,"journal":{"name":"2012 Fifth International Symposium on Computational Intelligence and Design","volume":"8 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Biological Cell Image Segmentation Using Novel Hybrid Morphology-Based Method\",\"authors\":\"Jiezhen Xie, Xiaoqing Yu, Xuling Zheng\",\"doi\":\"10.1109/ISCID.2012.202\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In 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.\",\"PeriodicalId\":246432,\"journal\":{\"name\":\"2012 Fifth International Symposium on Computational Intelligence and Design\",\"volume\":\"8 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fifth International Symposium on Computational Intelligence and Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISCID.2012.202\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fifth International Symposium on Computational Intelligence and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISCID.2012.202","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Biological Cell Image Segmentation Using Novel Hybrid Morphology-Based Method
In 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.