基于视频感知哈希的视频篡改检测与多粒度定位

朱映映; 文振焜; 杜以华; 邓良太

doi:10.11834/jig.20130806

图像分析和识别 | 浏览量 : 0 下载量: 290 CSCD: 0

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基于视频感知哈希的视频篡改检测与多粒度定位
Video forgery detection and multi-granularity location based on video perceptual hashing
2013年18卷第8期页码：924-932
纸质出版：2013
DOI： 10.11834/jig.20130806
稿件说明：

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朱映映, 文振焜, 杜以华, 邓良太. 基于视频感知哈希的视频篡改检测与多粒度定位[J]. 中国图象图形学报, 2013,18(8):924-932. DOI： 10.11834/jig.20130806.

Zhu Yingying, Wen Zhenkun, Du Yihua, Deng Liangtai. Video forgery detection and multi-granularity location based on video perceptual hashing[J]. Journal of Image and Graphics, 2013, 18(8): 924-932. DOI： 10.11834/jig.20130806.

摘要

为了对被篡改过的视频进行准确快速的篡改检测与定位

引入人类视觉可计算模型

提出一种多层次、多粒度的视频篡改快速检测与定位算法。采用随机分块采样技术

提取视频结构感知特征及视频图像时域感知特征

利用哈希理论的单向摘要特性量化感知特征

获取视频摘要哈希。通过应用相似度矩阵进行多粒度、多层次篡改部位检测与定位。实验结果表明

相似度拟合图能够体现视频篡改攻击强度和攻击部位

算法表现出更好的篡改检测准确率与定位精确度。

Abstract

To fast and accurately detect videos that were tampered

the human visual model is introduced to our algorithm. A multi-level and multi-granularity algorithm to detect and locate video tampering is presented in this paper. The random block sampling technology is used

and video structure perceptual features and time-domain perceptual features of video images are extracted. Then

the unidirectional abstract of the hash theory is used to quantify perceptual features

and the video abstract hash value is obtained. The similarity matrix is applied to give a multi-level and multi-granularity detection and location for tampered data. Experimental results show that similarity fitting diagram can reflect the attack power and the attack site of video tampering. The proposed algorithm shows better precision and positioning accuracy.

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融合HVS计算模型的视频感知哈希算法研究