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。

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.