基于SIFT和GMM的复制移动伪造检测

N. Yadav, Rupal A. Kapdi
{"title":"基于SIFT和GMM的复制移动伪造检测","authors":"N. Yadav, Rupal A. Kapdi","doi":"10.1109/NUICONE.2015.7449647","DOIUrl":null,"url":null,"abstract":"Modifying or enhancing an image is ubiquitous but, when enhancement tends to change the interpretation of the image they are termed as an attempt of forgery on digital images. Copy move forgery (CMF) is a simple technique and has a number of well built tools in a number of image enhancement software. CMF detection techniques often tend to establish similarity between copied and pasted region on the same image as both are from same original image. Keypoint and block based techniques are used to determine the CMF. SIFT keypoints are combined with different techniques to accurately localize forgery. High dimensionality of feature vector acts as a bottle neck in SIFT based analysis. We propose a method to detect CMF using SIFT descriptors which are clustered using GMM and segment the obtained suspect region speeding up the analysis.","PeriodicalId":131332,"journal":{"name":"2015 5th Nirma University International Conference on Engineering (NUiCONE)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Copy move forgery detection using SIFT and GMM\",\"authors\":\"N. Yadav, Rupal A. Kapdi\",\"doi\":\"10.1109/NUICONE.2015.7449647\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Modifying or enhancing an image is ubiquitous but, when enhancement tends to change the interpretation of the image they are termed as an attempt of forgery on digital images. Copy move forgery (CMF) is a simple technique and has a number of well built tools in a number of image enhancement software. CMF detection techniques often tend to establish similarity between copied and pasted region on the same image as both are from same original image. Keypoint and block based techniques are used to determine the CMF. SIFT keypoints are combined with different techniques to accurately localize forgery. High dimensionality of feature vector acts as a bottle neck in SIFT based analysis. We propose a method to detect CMF using SIFT descriptors which are clustered using GMM and segment the obtained suspect region speeding up the analysis.\",\"PeriodicalId\":131332,\"journal\":{\"name\":\"2015 5th Nirma University International Conference on Engineering (NUiCONE)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 5th Nirma University International Conference on Engineering (NUiCONE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NUICONE.2015.7449647\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 5th Nirma University International Conference on Engineering (NUiCONE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NUICONE.2015.7449647","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

修改或增强图像是无处不在的,但是,当增强倾向于改变图像的解释时,它们被称为数字图像伪造的企图。复制移动伪造(CMF)是一种简单的技术,在许多图像增强软件中有许多良好构建的工具。CMF检测技术往往倾向于在同一图像上建立复制和粘贴区域之间的相似性,因为两者都来自同一原始图像。关键点和基于块的技术被用来确定CMF。SIFT关键点与不同的技术相结合,可以准确地定位伪造。特征向量的高维是基于SIFT分析的瓶颈。我们提出了一种利用SIFT描述子检测CMF的方法,这些描述子使用GMM聚类,并对得到的可疑区域进行分割,从而加快分析速度。
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
Copy move forgery detection using SIFT and GMM
Modifying or enhancing an image is ubiquitous but, when enhancement tends to change the interpretation of the image they are termed as an attempt of forgery on digital images. Copy move forgery (CMF) is a simple technique and has a number of well built tools in a number of image enhancement software. CMF detection techniques often tend to establish similarity between copied and pasted region on the same image as both are from same original image. Keypoint and block based techniques are used to determine the CMF. SIFT keypoints are combined with different techniques to accurately localize forgery. High dimensionality of feature vector acts as a bottle neck in SIFT based analysis. We propose a method to detect CMF using SIFT descriptors which are clustered using GMM and segment the obtained suspect region speeding up the analysis.
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
Brain computer interface: A review A comparative study of various community detection algorithms in the mobile social network TCP with sender assisted delayed acknowledgement — A novel ACK thinning scheme Data streams and privacy: Two emerging issues in data classification ANFIS as a controller for fractional order system
×
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