CoMo: A Compact Composite Moment-Based Descriptor for Image Retrieval

S. A. Vassou, N. Anagnostopoulos, A. Amanatiadis, Klitos Christodoulou, S. Chatzichristofis
{"title":"CoMo: A Compact Composite Moment-Based Descriptor for Image Retrieval","authors":"S. A. Vassou, N. Anagnostopoulos, A. Amanatiadis, Klitos Christodoulou, S. Chatzichristofis","doi":"10.1145/3095713.3095744","DOIUrl":null,"url":null,"abstract":"Low level features play a vital role in image retrieval. Image moments can effectively represent global information of image content while being invariant under translation, rotation, and scaling. This paper briefly presents a moment based composite and compact low-level descriptor for image retrieval. In order to test the proposed feature, the authors employ the Bag-of-Visual-Words representation to perform experiments on two well-known benchmarking image databases. The robust and highly competitive retrieval performances, reported in all tested diverse collections, verify the promising potential that the proposed descriptor introduces.","PeriodicalId":310224,"journal":{"name":"Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing","volume":"166 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 15th International Workshop on Content-Based Multimedia Indexing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3095713.3095744","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 15

Abstract

Low level features play a vital role in image retrieval. Image moments can effectively represent global information of image content while being invariant under translation, rotation, and scaling. This paper briefly presents a moment based composite and compact low-level descriptor for image retrieval. In order to test the proposed feature, the authors employ the Bag-of-Visual-Words representation to perform experiments on two well-known benchmarking image databases. The robust and highly competitive retrieval performances, reported in all tested diverse collections, verify the promising potential that the proposed descriptor introduces.
CoMo:一种用于图像检索的紧凑复合矩描述符
低层次特征在图像检索中起着至关重要的作用。图像矩可以有效地表示图像内容的全局信息,并且在平移、旋转和缩放下保持不变。本文简要地提出了一种基于矩量的复合压缩低级描述符。为了测试所提出的特征,作者采用视觉词袋表示在两个知名的基准图像数据库上进行实验。在所有测试的不同集合中报告的鲁棒性和高度竞争性检索性能,验证了所提出的描述符引入的有希望的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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