融合彩色信息与SIFT特征的帧内复制粘贴篡改检测

近年来在同源复制粘贴篡改检测中，SIFT特征得到了广泛的应用.但由于该特征在提取过程中摒弃了颜色信息，会造成一部分特征点的误匹配和漏匹配.为此，提出一种基于彩色信息与SIFT融合的CSIFT特征的检测方法，在提取特征点时加入颜色不变量信息，提高了匹配的准确性和效率.算法首先利用结构相似度将视频帧序列分段，提取每段序列的关键帧；然后提取关键帧的CSIFT特征；最终定位复制粘贴区域，并利用目标跟踪算法计算篡改区域在后续帧上的位置.通过实验验证了算法的鲁棒性，与基于SIFT等特征的算法相比，时间效率和准确性更高.

Forgery Detection of Copy-Paste Video Based on Fusion of Color Information and SIFT Feature

SIFT feature has been widely used in the homologous copy-paste forgery detection. Due to the rejection of color information, it results in some mismatching of key points, so we propose another method based on Colored Scale Invariant Feature Transform (CSIFT), a feature combining variable color information with Scale Invariant Feature Transform (SIFT) when extracting feature points decreasing the possibility of false matching and greatly reducing the time of feature point extraction and matching. In this study, we firstly segment video by Structural Similarity Index Measurement (SSIM) and extract the first frame of every part as the key frame. Then, we extract CSIFT feature points of the key frame and match feature points. After that, we locate copy-paste areas. The final step is a target tracking algorithm used to calculate the copy-paste areas in the following frame sequence. The robustness and efficiency of the algorithm is verified by experiments. Compared with algorithms based on SIFT, the proposed method has higher time efficiency and accuracy.