采用量化离散余弦变换系数检测视频单帧连续多次复制粘贴篡改

目前大多数时域视频帧复制粘贴篡改检测算法都是针对至少20帧以上的视频子序列的复制粘贴篡改,而对单帧复制粘贴篡改无法判断。而根据人眼视觉感知的特性,修改视频内容需要至少15帧以上的帧操作,因此篡改帧想通过单帧复制粘贴篡改来达到想要的效果,必须进行连续多次粘贴操作。为了检测这种篡改方式,针对性地提出了一种基于量化离散余弦变换(DCT)系数的视频单帧连续多次复制-粘贴篡改检测算法。首先,将视频转换为图像,采用量化后的DCT系数作为视频帧图像特征向量,并通过计算巴氏(Bhattacharyya)系数来衡量两相邻帧帧间相似度;再设定阈值来判断两相邻帧帧间相似度是否有异常,最后根据出现相似度异常的帧是否连续,以及连续出现的帧数来判断视频是否经过篡改,并定位篡改位置。实验结果表明,所提算法对不同场景的视频都能检测,不仅检测速度快,而且不受再压缩因素影响,算法的正确率高、漏检率低。

Detection of continuously and repeated copy-move forgery to single frame in videos by quantized DCT coefficients

Most existing detection algorithms of video frame copy-move forgery in time domain were designed for the copy-move forgery of video sequence containing 20 frames at least, and are difficult to detect single frame forgery. While according to the characteristics of human visual perception, 15 frames at least were needed to modify the video meaning. So when goal in vision was made by the tampering, continuous operation and many times were needed. In order to detect the tampering, a detection algorithm based on quantized Discrete Cosine Transform (DCT) coefficients for continuous and repeated single frame copy-move forgery in videos was proposed. Firstly, the video was converted into images, and quantized DCT coefficients were taken as the feature vector of a frame image. Then, the similarity between frames was measured by calculating Bhattacharyya coefficient, and threshold was set to judge the abnormal similarity between two adjacent frames. Finally, whether the video was tampered and the tampered positions were determined by the continuity of frames with abnormal similarity and the number of continuous frames. The experimental results show that the proposed algorithm can detect the video with different scenarios, it possesses fast detection speed, and is not affected by further compression factors, but also is of high accuracy and low omission ratio.