| 同源视频Copy-Move篡改检测及恢复 |
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| 引用本文： | 陈智文,黄添强,吴铁浩,袁秀娟,苏伟峰.同源视频Copy-Move篡改检测及恢复[J].计算机系统应用,2013,22(9):102-110. |
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| 作者姓名： | 陈智文 黄添强 吴铁浩 袁秀娟 苏伟峰 |
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| 作者单位： | 福建师范大学 数学与计算机科学学院, 福州 350007;福建师范大学 数学与计算机科学学院, 福州 350007;福建师范大学 网络安全与密码技术福建省高校重点实验室, 福州 350007;福建师范大学 数学与计算机科学学院, 福州 350007;福建师范大学 数学与计算机科学学院, 福州 350007;北京师范大学-香港浸会大学联合国际学院 理工科技学部, 珠海 519085 |
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| 基金项目： | 国家自然科学基金(61070062);福建省高校产学合作科技重大项目(2012H6006);福建省高校服务海西建设重点项目(2008HX200941-4-5);
福建省高等学校新世纪优秀人才支持计划(JAI1038) |
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| 摘 要： | 针对同源视频序列的copy-move篡改方式, 提出一种通过度量图像内容间的相关性, 来实现对视频序列的copy-move篡改检测并恢复的方法. 首先将视频帧内容转化为一系列连续的图像帧, 对图像分块, 提取每帧图像的8个特征矢量, 再利用欧氏距离计算帧间相关性, 并通过添加偏差矩阵构造动态偏差阈值, 检测出copy-move篡改序列且精确至帧, 从而实现对视频序列的篡改检测与恢复. 实验表明, 该算法对同源视频序列的copy-move篡改检测及恢复能够取得理想的效果.
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| 关 键 词： | 视频篡改 序列copy-move 偏差矩阵 视频恢复 |
| 收稿时间： | 2013/1/28 0:00:00 |
| 修稿时间： | 2013/2/28 0:00:00 |
Detection and Recovery for Copy-Move Forgery in Homologous Video |
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| CHEN Zhi-Wen,HUANG Tian-Qiang,WU Tie-Hao,YUAN Xiu-Juan and SU Wei-Feng.Detection and Recovery for Copy-Move Forgery in Homologous Video[J].Computer Systems& Applications,2013,22(9):102-110. |
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| Authors: | CHEN Zhi-Wen HUANG Tian-Qiang WU Tie-Hao YUAN Xiu-Juan and SU Wei-Feng |
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| Affiliation: | School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, China;School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, China;Key Laboratory of Network Security and Cryptography, Fujian Normal University, Fuzhou 350007, China;School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, China;School of Mathematics and Computer Science, Fujian Normal University, Fuzhou 350007, China;Department of Computer Science and Technology, BUN-HKBU United International College, Zhuhai 519085, China |
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| Abstract: | With regard to the copy-move forgery of video frame sequence, this paper proposes a algorithm for video detection and recovery base on the correlation of the contents between frames. Firstly, the video frames are translated into a series of consecutive image frames, and by blocking the frame to extract eight dimensional feature vectors. With Euclidean distance computed the correlation between frames, a deviation matrix is import in the algorithm to reduce the false alarm rate. A threshold value is used to localize the modifications to a frame level and recover the original video. Experimental results show that this method can effectively detect the copy-move forgery of video frame sequence and video restoration. |
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| Keywords: | video tampering frame sequential copy-move deviation-matrix video restoration |
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