Digital Image Processing and Recognition in Industrial and Public Environments

R. Vasil, F. Frigura-Iliasa, Mirela Iorga, H. Filipescu, M. Rogobete, M. Nen
{"title":"Digital Image Processing and Recognition in Industrial and Public Environments","authors":"R. Vasil, F. Frigura-Iliasa, Mirela Iorga, H. Filipescu, M. Rogobete, M. Nen","doi":"10.1109/IRCE.2019.00015","DOIUrl":null,"url":null,"abstract":"Because the internet broadcasting, most photos or video streams need copyright protection or forgery detection. Nowadays, the metadata tries to embed and preserve copyright data and general information. The ownership metadata should never be removed, for an efficient protection, but practically it could be relatively easy extracted. This research proposes, based on a comparison between metadata and watermarking methods, a watermarking framework that inserts visual and hide information into digital images, instead of metadata protection. The visible watermark inserted into the host image could be removable or not, based on the objective or non-bijective embedding watermark function. A removable watermark allows the far end receiver to eliminate the visible watermark, whether it uses a framework that uses the invers embedding function. In this way, only the controlled receivers could profit by the clean photos/video stream. More of this, the hidden watermark could embed typical information that identify the owner.","PeriodicalId":298781,"journal":{"name":"2019 2nd International Conference of Intelligent Robotic and Control Engineering (IRCE)","volume":"137 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 2nd International Conference of Intelligent Robotic and Control Engineering (IRCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRCE.2019.00015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Because the internet broadcasting, most photos or video streams need copyright protection or forgery detection. Nowadays, the metadata tries to embed and preserve copyright data and general information. The ownership metadata should never be removed, for an efficient protection, but practically it could be relatively easy extracted. This research proposes, based on a comparison between metadata and watermarking methods, a watermarking framework that inserts visual and hide information into digital images, instead of metadata protection. The visible watermark inserted into the host image could be removable or not, based on the objective or non-bijective embedding watermark function. A removable watermark allows the far end receiver to eliminate the visible watermark, whether it uses a framework that uses the invers embedding function. In this way, only the controlled receivers could profit by the clean photos/video stream. More of this, the hidden watermark could embed typical information that identify the owner.
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
工业和公共环境中的数字图像处理和识别
由于互联网传播,大多数照片或视频流需要版权保护或伪造检测。如今,元数据试图嵌入和保存版权数据和一般信息。为了有效的保护,不应该删除所有权元数据,但实际上它可以相对容易地提取。本研究在比较元数据和水印方法的基础上,提出了一种将可视和隐藏信息插入数字图像的水印框架,而不是元数据保护。基于客观或非双客观嵌入水印功能,嵌入到宿主图像中的可见水印可以被去除或不可去除。可移动水印允许远端接收端消除可见水印,无论它是否使用使用反相嵌入功能的框架。这样,只有被控制的接收器才能从干净的照片/视频流中获利。更重要的是,隐藏的水印可以嵌入识别所有者的典型信息。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
IRCE 2019 Committees Digital Image Processing and Recognition in Industrial and Public Environments Object Detection with Task Description Only A Scan Matching Method For Quadruped Robots In Outdoor Environment Intergrated Production System using ERP and MES
×
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