基于自适应提点鲁棒定位的图像复制粘贴篡改检测

复制-粘贴篡改检测(Copy-Move Forgery Detection, CMFD)是数字图像篡改的一种常见方式, 近年来已成为多媒体取证领域一个重要的研究方向. 本文提出一种鲁棒的复制-粘贴篡改检测算法, 基于构造波动函数自适应获取阈值的方法均匀提取图像特征点, 可在篡改区域小或平滑的情况下进行鲁棒检测. 引入DBQ-LSH匹配算法进行特征匹配, 降低了时间复杂度. 提出基于不变矩LBP图像的定位方法, 在图像受到噪声攻击和JPEG压缩攻击下能精准定位篡改位置. 实验结果表明, 该算法具有优良的检测正确率(图像级)和检测精度 (像素级).

Copy-Move Forgery Detection Based on Adaptive Keypoints Extraction and Robust Localization

Copy move forgery is a common way of digital image tampering, which has become an important research direction in the field of multimedia forensics in recent years. We propose a robust copy-move forgery detection algorithm. We construct wave function to extract keypoint evenly in the image, which can extract enough keypoint even in small or smooth areas. We introduce DBQ-LSH for feature matching, which greatly reduces time consumption. We propose a novel approach which use invariant moment LBP image to locate forged areas, even if the image is seriously attacked, the algorithm detection accuracy is still excellent. A large number of experimental results verify the reliability of proposed algorithm, in terms of validity and accuracy.