{"title":"Color image segmentation","authors":"Yining Deng, B. S. Manjunath, H. Shin","doi":"10.1109/CVPR.1999.784719","DOIUrl":null,"url":null,"abstract":"In this work, a new approach to fully automatic color image segmentation, called JSEG, is presented. First, colors in the image are quantized to several representing classes that can be used to differentiate regions in the image. Then, image pixel colors are replaced by their corresponding color class labels, thus forming a class-map of the image. A criterion for \"good\" segmentation using this class-map is proposed. Applying the criterion to local windows in the class-map results in the \"J-image\", in which high and low values correspond to possible region boundaries and region centers, respectively. A region growing method is then used to segment the image based on the multi-scale J-images. Experiments show that JSEG provides good segmentation results on a variety of images.","PeriodicalId":20644,"journal":{"name":"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1999-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"687","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CVPR.1999.784719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 687

Abstract

In this work, a new approach to fully automatic color image segmentation, called JSEG, is presented. First, colors in the image are quantized to several representing classes that can be used to differentiate regions in the image. Then, image pixel colors are replaced by their corresponding color class labels, thus forming a class-map of the image. A criterion for "good" segmentation using this class-map is proposed. Applying the criterion to local windows in the class-map results in the "J-image", in which high and low values correspond to possible region boundaries and region centers, respectively. A region growing method is then used to segment the image based on the multi-scale J-images. Experiments show that JSEG provides good segmentation results on a variety of images.
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彩色图像分割
在这项工作中,提出了一种新的全自动彩色图像分割方法——JSEG。首先,图像中的颜色被量化为几个代表类,可以用来区分图像中的区域。然后,将图像像素颜色替换为其对应的颜色类标签,从而形成图像的类映射。提出了使用类映射进行“良好”分割的标准。将该准则应用于类图的局部窗口得到“J-image”,其中高值和低值分别对应可能的区域边界和区域中心。然后在多尺度j图像的基础上,采用区域增长方法对图像进行分割。实验表明,JSEG在多种图像上都有很好的分割效果。
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