Hadoop 平台下基于 BoVW 模型的船舶图像检索研究

R. Hu, J. Yang, Bangpei Zhu, Zhiqiang Guo
{"title":"Hadoop 平台下基于 BoVW 模型的船舶图像检索研究","authors":"R. Hu, J. Yang, Bangpei Zhu, Zhiqiang Guo","doi":"10.1145/3209914.3209948","DOIUrl":null,"url":null,"abstract":"Image data is one of the key data in the ship's navigation record. Ship scene reappearance depends on its efficient retrieval. Recently, the exponential growth of the number of images makes the traditional single-machine image retrieval method gradually show the problem of inefficiency. In this paper, the image retrieval method based on the Bag of Visual Words (BoVW) model under the Hadoop platform is proposed and the distributed image retrieval is realized. Firstly, this paper takes BoVW model as the research object. Based on the Hadoop platform, the construction method of traditional visual dictionary is improved and the word frequency vectors are weighted by Term Frequency-Inverse Document Frequency (TF-IDF). Then the inverted index is generated in parallel for image retrieval. Experimental results show this method doubled the efficiency of visual dictionary construction while maintaining the original retrieval results and effectively improved the efficiency of image retrieval.","PeriodicalId":174382,"journal":{"name":"Proceedings of the 1st International Conference on Information Science and Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Research on Ship Image Retrieval Based on BoVW Model under Hadoop Platform\",\"authors\":\"R. Hu, J. Yang, Bangpei Zhu, Zhiqiang Guo\",\"doi\":\"10.1145/3209914.3209948\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image data is one of the key data in the ship's navigation record. Ship scene reappearance depends on its efficient retrieval. Recently, the exponential growth of the number of images makes the traditional single-machine image retrieval method gradually show the problem of inefficiency. In this paper, the image retrieval method based on the Bag of Visual Words (BoVW) model under the Hadoop platform is proposed and the distributed image retrieval is realized. Firstly, this paper takes BoVW model as the research object. Based on the Hadoop platform, the construction method of traditional visual dictionary is improved and the word frequency vectors are weighted by Term Frequency-Inverse Document Frequency (TF-IDF). Then the inverted index is generated in parallel for image retrieval. Experimental results show this method doubled the efficiency of visual dictionary construction while maintaining the original retrieval results and effectively improved the efficiency of image retrieval.\",\"PeriodicalId\":174382,\"journal\":{\"name\":\"Proceedings of the 1st International Conference on Information Science and Systems\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1st International Conference on Information Science and Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3209914.3209948\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st International Conference on Information Science and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3209914.3209948","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

图像数据是船舶航行记录中的关键数据之一。船舶场景再现依赖于船舶场景的高效检索。近年来,图像数量的指数增长使得传统的单机图像检索方法逐渐显示出效率低下的问题。本文提出了在Hadoop平台下基于BoVW (Bag of Visual Words)模型的图像检索方法,实现了分布式图像检索。首先,本文以BoVW模型为研究对象。基于Hadoop平台,改进了传统视觉词典的构建方法,采用术语频率-逆文档频率(TF-IDF)对词频向量进行加权。然后并行生成倒排索引用于图像检索。实验结果表明,该方法在保持原始检索结果的同时,将视觉词典构建效率提高了一倍,有效地提高了图像检索的效率。
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
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Research on Ship Image Retrieval Based on BoVW Model under Hadoop Platform
Image data is one of the key data in the ship's navigation record. Ship scene reappearance depends on its efficient retrieval. Recently, the exponential growth of the number of images makes the traditional single-machine image retrieval method gradually show the problem of inefficiency. In this paper, the image retrieval method based on the Bag of Visual Words (BoVW) model under the Hadoop platform is proposed and the distributed image retrieval is realized. Firstly, this paper takes BoVW model as the research object. Based on the Hadoop platform, the construction method of traditional visual dictionary is improved and the word frequency vectors are weighted by Term Frequency-Inverse Document Frequency (TF-IDF). Then the inverted index is generated in parallel for image retrieval. Experimental results show this method doubled the efficiency of visual dictionary construction while maintaining the original retrieval results and effectively improved the efficiency of image retrieval.
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
期刊最新文献
Design and Implementation of Student Information Management System Based On Java Improving RealSense by Fusing Color Stereo Vision and Infrared Stereo Vision for the Visually Impaired Expert Recommendation Based on Collaborative Filtering in Subject Research An Approach for Information Discovery Using Ontology In Semantic Web Content Detecting Phone Theft Using Machine Learning
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1