利用cnn -阿米巴进行二维静止图像分割

2003 IEEE International Workshop on Computer Architectures for Machine Perception Pub Date : 2003-05-12 DOI:10.1109/CAMP.2003.1598145

G. Iannizzotto, F. La Rosa, A. Rizzo, M. Xibilia

{"title":"利用cnn -阿米巴进行二维静止图像分割","authors":"G. Iannizzotto, F. La Rosa, A. Rizzo, M. Xibilia","doi":"10.1109/CAMP.2003.1598145","DOIUrl":null,"url":null,"abstract":"This paper introduces a still image segmentation technique based on an active contour obtained via single-layer CNNs. The contour initially laid on the frame of the image shrinks, deforms and multiplies until it matches the edges of each of the objects present in the scene. The shape of each object in the image is accurately extracted and nested objects, if any, are correctly detected. Experimental measures of the accuracy of the segmentation were carried out using the Hausdorff distance","PeriodicalId":443821,"journal":{"name":"2003 IEEE International Workshop on Computer Architectures for Machine Perception","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"2D still-image segmentation with CNN-Amoeba\",\"authors\":\"G. Iannizzotto, F. La Rosa, A. Rizzo, M. Xibilia\",\"doi\":\"10.1109/CAMP.2003.1598145\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a still image segmentation technique based on an active contour obtained via single-layer CNNs. The contour initially laid on the frame of the image shrinks, deforms and multiplies until it matches the edges of each of the objects present in the scene. The shape of each object in the image is accurately extracted and nested objects, if any, are correctly detected. Experimental measures of the accuracy of the segmentation were carried out using the Hausdorff distance\",\"PeriodicalId\":443821,\"journal\":{\"name\":\"2003 IEEE International Workshop on Computer Architectures for Machine Perception\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2003 IEEE International Workshop on Computer Architectures for Machine Perception\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAMP.2003.1598145\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2003 IEEE International Workshop on Computer Architectures for Machine Perception","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMP.2003.1598145","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 3

摘要

介绍了一种基于单层cnn获得的活动轮廓的静止图像分割技术。最初放置在图像框架上的轮廓会收缩、变形和倍增，直到它与场景中每个物体的边缘相匹配。准确提取图像中每个物体的形状，如果有嵌套物体，则正确检测嵌套物体。利用豪斯多夫距离对分割精度进行了实验测量

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

2D still-image segmentation with CNN-Amoeba

This paper introduces a still image segmentation technique based on an active contour obtained via single-layer CNNs. The contour initially laid on the frame of the image shrinks, deforms and multiplies until it matches the edges of each of the objects present in the scene. The shape of each object in the image is accurately extracted and nested objects, if any, are correctly detected. Experimental measures of the accuracy of the segmentation were carried out using the Hausdorff distance

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2003 IEEE International Workshop on Computer Architectures for Machine Perception

自引率

0.00%

发文量