Detection of seam carving in JPEG images

Wen-Lung Chang, T. Shih, Hui-Huang Hsu
{"title":"Detection of seam carving in JPEG images","authors":"Wen-Lung Chang, T. Shih, Hui-Huang Hsu","doi":"10.1109/ICAWST.2013.6765516","DOIUrl":null,"url":null,"abstract":"The content-aware image retargeting algorithm is used for modifying the image size into the suitable size in different device. \"Seam carving\" is a kind of content aware image retargeting algorithm. In this paper, based on the blocking artifact characteristics matrix (BACM), we propose a method to detect seam carving in natural images without knowledge of the original image. In detail, for the original JPEG images, the BACM exhibits regular symmetrical shapes; for the images that are damaged, the regular symmetrical property of the BACM is destroyed. After found BACM from images, we define 18 features to detect the damage from BACM to train a support vector machine (SVM) classifier for recognizing whether an image is an original or it has been modified by seam-carving. We show that BACM is useful for detect the damage by seam-carving in JPEG format images.","PeriodicalId":68697,"journal":{"name":"炎黄地理","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"19","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"炎黄地理","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.1109/ICAWST.2013.6765516","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 19

Abstract

The content-aware image retargeting algorithm is used for modifying the image size into the suitable size in different device. "Seam carving" is a kind of content aware image retargeting algorithm. In this paper, based on the blocking artifact characteristics matrix (BACM), we propose a method to detect seam carving in natural images without knowledge of the original image. In detail, for the original JPEG images, the BACM exhibits regular symmetrical shapes; for the images that are damaged, the regular symmetrical property of the BACM is destroyed. After found BACM from images, we define 18 features to detect the damage from BACM to train a support vector machine (SVM) classifier for recognizing whether an image is an original or it has been modified by seam-carving. We show that BACM is useful for detect the damage by seam-carving in JPEG format images.
JPEG图像中接缝雕刻的检测
内容感知图像重定位算法用于将图像大小修改为不同设备中的合适大小。“接缝雕刻”是一种内容感知的图像重定向算法。本文基于块伪影特征矩阵(BACM),提出了一种无需了解原始图像即可检测自然图像中接缝雕刻的方法。对于原始JPEG图像,BACM呈现规则的对称形状;对于被破坏的图像,破坏了BACM的规则对称特性。在从图像中发现BACM后,定义18个特征来检测BACM的损伤,训练支持向量机(SVM)分类器来识别图像是原始图像还是被缝切修改过。结果表明,BACM算法可用于检测JPEG格式图像的缝切损伤。
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 求助全文
来源期刊
自引率
0.00%
发文量
784
×
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