Image Forgery Detection Based on Motion Blur Estimated Using Convolutional Neural Network | |
Song CH(宋纯贺)3,4; Zeng P(曾鹏)3,4![]() ![]() | |
刊名 | IEEE SENSORS JOURNAL
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2019 | |
卷号 | 19期号:23页码:11601-11611 |
关键词 | Digital forensics image tamper detection motion blur deep learning |
ISSN号 | 1530-437X |
产权排序 | 1 |
英文摘要 | Currently images are key evidences in many judicial or other identification occasions, and image forgery detection has become a research hotspot. This paper proposes a novel motion blur based image forgery detection method, which includes three steps. First, a convolutional neural network (CNN)-based motion blur kernel reliability estimation method is proposed, which is used to determine whether an image patch should be involved in the image forgery detection process. Second, a shared motion blur kernels-based image tamper detection method is proposed to detect whether a group of motion blur kernels are projected from the same 3D camera trajectory effectively. Third, a consistency propagation method is proposed to localize tampered regions efficiently. Experiments on synthetic images and natural images show the availability of the proposed method. |
语种 | 英语 |
WOS记录号 | WOS:000503385100070 |
资助机构 | National Key R&D Program of China under Grant 2017YFA0700300 ; State Grid Corporation Science and Technology Project under Contract SG2NK00DWJS1800123 |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/26039] ![]() |
专题 | 沈阳自动化研究所_工业控制网络与系统研究室 |
通讯作者 | Zeng P(曾鹏) |
作者单位 | 1.State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China 2.Liaoning Electric Power Research Institute, State Grid Liaoning Electric Power Co., Ltd., Shenyang 110006, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China 4.Key Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China |
推荐引用方式 GB/T 7714 | Song CH,Zeng P,Wang ZF,et al. Image Forgery Detection Based on Motion Blur Estimated Using Convolutional Neural Network[J]. IEEE SENSORS JOURNAL,2019,19(23):11601-11611. |
APA | Song CH,Zeng P,Wang ZF,Li, Tong,Qiao, Lin,&Shen, Li.(2019).Image Forgery Detection Based on Motion Blur Estimated Using Convolutional Neural Network.IEEE SENSORS JOURNAL,19(23),11601-11611. |
MLA | Song CH,et al."Image Forgery Detection Based on Motion Blur Estimated Using Convolutional Neural Network".IEEE SENSORS JOURNAL 19.23(2019):11601-11611. |
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