图像原始签名

J. Kinser
{"title":"图像原始签名","authors":"J. Kinser","doi":"10.1109/AIPR.2004.28","DOIUrl":null,"url":null,"abstract":"Image signatures are generated from the comparison of segments contained within an image to a database of segments collected over a large variety of images. It is impossible to retain all of the segments from all of the images so the segments are clustered becomes an image primitive as each cluster contains a unique set of similar segments. The size of the image signature is NK where N is the number of segments and K is the number of clusters. These numbers are significantly smaller than the dimensions of the image and so a signature is a condensed representation of the contents of the image.","PeriodicalId":120814,"journal":{"name":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Image primitive signatures\",\"authors\":\"J. Kinser\",\"doi\":\"10.1109/AIPR.2004.28\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image signatures are generated from the comparison of segments contained within an image to a database of segments collected over a large variety of images. It is impossible to retain all of the segments from all of the images so the segments are clustered becomes an image primitive as each cluster contains a unique set of similar segments. The size of the image signature is NK where N is the number of segments and K is the number of clusters. These numbers are significantly smaller than the dimensions of the image and so a signature is a condensed representation of the contents of the image.\",\"PeriodicalId\":120814,\"journal\":{\"name\":\"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AIPR.2004.28\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"33rd Applied Imagery Pattern Recognition Workshop (AIPR'04)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2004.28","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

图像签名是通过将图像中包含的片段与从大量图像上收集的片段数据库进行比较而生成的。从所有图像中保留所有的片段是不可能的,所以这些片段被聚类成为一个图像原语,因为每个聚类包含一组唯一的相似片段。图像签名的大小为NK,其中N为段数,K为簇数。这些数字明显小于图像的尺寸,因此签名是图像内容的浓缩表示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image primitive signatures
Image signatures are generated from the comparison of segments contained within an image to a database of segments collected over a large variety of images. It is impossible to retain all of the segments from all of the images so the segments are clustered becomes an image primitive as each cluster contains a unique set of similar segments. The size of the image signature is NK where N is the number of segments and K is the number of clusters. These numbers are significantly smaller than the dimensions of the image and so a signature is a condensed representation of the contents of the image.
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
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信