基于HMMD色彩空间色度特征的图像检索

L. Pavithra, T. Sharmila
{"title":"基于HMMD色彩空间色度特征的图像检索","authors":"L. Pavithra, T. Sharmila","doi":"10.1109/ICCCSP.2017.7944073","DOIUrl":null,"url":null,"abstract":"This paper proposes a new chrominance feature extraction method in HMMD color space. Image dependent multi-level thresholding is performed in the HMMD color space to obtain the 64-IeveI quantized images. The occurrence count of each color pixel represents the color information of those quantized images. This technique is tested over Wang's database of 10 different category images. The distance measure of this feature between the query and database image are calculated. Then, the proposed method performance is evaluated using average precision and recall. Moreover, the proposed method is a benchmark against the state-of-the-art color feature extraction methods and gives approximately 6.3% to 18.05% and 7.54% to 14.52 % high precision and recall than the conventional techniques.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Image retrieval based on chrominance feature of the HMMD color space\",\"authors\":\"L. Pavithra, T. Sharmila\",\"doi\":\"10.1109/ICCCSP.2017.7944073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a new chrominance feature extraction method in HMMD color space. Image dependent multi-level thresholding is performed in the HMMD color space to obtain the 64-IeveI quantized images. The occurrence count of each color pixel represents the color information of those quantized images. This technique is tested over Wang's database of 10 different category images. The distance measure of this feature between the query and database image are calculated. Then, the proposed method performance is evaluated using average precision and recall. Moreover, the proposed method is a benchmark against the state-of-the-art color feature extraction methods and gives approximately 6.3% to 18.05% and 7.54% to 14.52 % high precision and recall than the conventional techniques.\",\"PeriodicalId\":269595,\"journal\":{\"name\":\"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCSP.2017.7944073\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCSP.2017.7944073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

提出了一种在HMMD色彩空间中提取色彩特征的新方法。在HMMD色彩空间中进行图像依赖的多级阈值分割,得到64级量化图像。每个颜色像素的出现次数代表这些量化图像的颜色信息。这项技术在Wang的10个不同类别图像的数据库上进行了测试。计算该特征在查询和数据库图像之间的距离度量。然后,用平均查准率和查全率对该方法的性能进行了评价。此外,该方法是最先进的颜色特征提取方法的基准,与传统技术相比,其精度和召回率分别为6.3% ~ 18.05%和7.54% ~ 14.52%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image retrieval based on chrominance feature of the HMMD color space
This paper proposes a new chrominance feature extraction method in HMMD color space. Image dependent multi-level thresholding is performed in the HMMD color space to obtain the 64-IeveI quantized images. The occurrence count of each color pixel represents the color information of those quantized images. This technique is tested over Wang's database of 10 different category images. The distance measure of this feature between the query and database image are calculated. Then, the proposed method performance is evaluated using average precision and recall. Moreover, the proposed method is a benchmark against the state-of-the-art color feature extraction methods and gives approximately 6.3% to 18.05% and 7.54% to 14.52 % high precision and recall than the conventional techniques.
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