用MPEG-7(和类似MPEG-7)驱动的本地化描述符搜索图像:有效的基于内容的图像检索的简单答案

C. Iakovidou, N. Anagnostopoulos, Athanasios Ch. Kapoutsis, Y. Boutalis, S. Chatzichristofis
{"title":"用MPEG-7(和类似MPEG-7)驱动的本地化描述符搜索图像:有效的基于内容的图像检索的简单答案","authors":"C. Iakovidou, N. Anagnostopoulos, Athanasios Ch. Kapoutsis, Y. Boutalis, S. Chatzichristofis","doi":"10.1109/CBMI.2014.6849821","DOIUrl":null,"url":null,"abstract":"In this paper we propose and evaluate a new technique that localizes the description ability of the well established MPEG-7 and MPEG-7-like global descriptors. We employ the SURF detector to define salient image patches of blob-like textures and use the MPEG-7 Scalable Color (SC), Color Layout (CL) and Edge Histogram (EH) descriptors and the global MPEG-7-like Color and Edge Directivity Descriptor (CEDD), to produce the final local features' vectors. In order to test the new descriptors in the most straightforward fashion, we use the Bag-Of-Visual-Words framework for indexing and retrieval. The experimental results conducted on two different benchmark databases with varying codebook sizes, revealed an astonishing boost in the retrieval performance of the proposed descriptors compared both to their own performance (in their original form) and to other state-of-the-art methods of local and global descriptors. Open-source implementation of the proposed descriptors is available in c#, Java and MATLAB.","PeriodicalId":103056,"journal":{"name":"2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":"{\"title\":\"Searching images with MPEG-7 (& MPEG-7-like) Powered Localized dEscriptors: The SIMPLE answer to effective Content Based Image Retrieval\",\"authors\":\"C. Iakovidou, N. Anagnostopoulos, Athanasios Ch. Kapoutsis, Y. Boutalis, S. Chatzichristofis\",\"doi\":\"10.1109/CBMI.2014.6849821\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we propose and evaluate a new technique that localizes the description ability of the well established MPEG-7 and MPEG-7-like global descriptors. We employ the SURF detector to define salient image patches of blob-like textures and use the MPEG-7 Scalable Color (SC), Color Layout (CL) and Edge Histogram (EH) descriptors and the global MPEG-7-like Color and Edge Directivity Descriptor (CEDD), to produce the final local features' vectors. In order to test the new descriptors in the most straightforward fashion, we use the Bag-Of-Visual-Words framework for indexing and retrieval. The experimental results conducted on two different benchmark databases with varying codebook sizes, revealed an astonishing boost in the retrieval performance of the proposed descriptors compared both to their own performance (in their original form) and to other state-of-the-art methods of local and global descriptors. Open-source implementation of the proposed descriptors is available in c#, Java and MATLAB.\",\"PeriodicalId\":103056,\"journal\":{\"name\":\"2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI)\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"32\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMI.2014.6849821\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 12th International Workshop on Content-Based Multimedia Indexing (CBMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMI.2014.6849821","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 32

摘要

在本文中,我们提出并评估了一种新的技术,该技术可以定位已经建立的MPEG-7和MPEG-7类全局描述符的描述能力。我们使用SURF检测器来定义斑点状纹理的显著图像斑块,并使用MPEG-7可缩放颜色(SC),颜色布局(CL)和边缘直方图(EH)描述符以及全局MPEG-7类颜色和边缘方向性描述符(CEDD)来生成最终的局部特征向量。为了以最直接的方式测试新的描述符,我们使用Bag-Of-Visual-Words框架进行索引和检索。在具有不同码本大小的两个不同基准数据库上进行的实验结果显示,与它们自己的性能(原始形式)和其他最先进的局部和全局描述符方法相比,所建议的描述符的检索性能有了惊人的提高。所提出的描述符的开源实现可以在c#、Java和MATLAB中获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Searching images with MPEG-7 (& MPEG-7-like) Powered Localized dEscriptors: The SIMPLE answer to effective Content Based Image Retrieval
In this paper we propose and evaluate a new technique that localizes the description ability of the well established MPEG-7 and MPEG-7-like global descriptors. We employ the SURF detector to define salient image patches of blob-like textures and use the MPEG-7 Scalable Color (SC), Color Layout (CL) and Edge Histogram (EH) descriptors and the global MPEG-7-like Color and Edge Directivity Descriptor (CEDD), to produce the final local features' vectors. In order to test the new descriptors in the most straightforward fashion, we use the Bag-Of-Visual-Words framework for indexing and retrieval. The experimental results conducted on two different benchmark databases with varying codebook sizes, revealed an astonishing boost in the retrieval performance of the proposed descriptors compared both to their own performance (in their original form) and to other state-of-the-art methods of local and global descriptors. Open-source implementation of the proposed descriptors is available in c#, Java and MATLAB.
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:604180095
Book学术官方微信