现有的篡改检测方法中特征点提取不充分会导致篡改检测精度不高，特征点描述符识别率差，针对该问题提出一种基于颜色矩的区域划分和四元数Hu矩的彩色图像复制粘贴篡改检测算法。首先，使用自适应形态重建算法对图像进行超像素分割，通过密度聚类算法对图像自适应划分区域；其次，提出一种关键点提取方法得到均匀的SIFT特征点；然后，在一种新颖的彩色图像四元数表示方法中构建局部高斯金字塔提取Hu矩特征；最后，利用2NN进行特征匹配后，结合Delaunay三角形算法定位出复制粘贴篡改区域。在公共数据集上的实验结果表明，该算法可以更有效地定位篡改区域。
Aiming at the problem that the insufficient extraction of feature points in existing forgery detection methods leads to low accuracy of forgery detection and poor recognition rate of feature points descriptor, a color image copy-move forgery detection algorithm based on color moment region division and quaternion Hu moment is proposed. Firstly, an adaptive morphological reconstruction algorithm is adopted to perform superpixel segmentation on the image, and then a density clustering algorithm is used to adaptively divide the image into regions. Secondly, a key point extraction method is proposed to obtain uniform SIFT feature points, and then a local Gaussian pyramid is constructed in a novel color image quaternion representation method to extract the Hu moment features. Finally, after matching features using the 2NN, the paper proposes to locate the copy-move forgery region by the Delaunay triangle algorithm. Experimental results on public datasets show that this method can effectively locate the forgery region.


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