基于HSV和CLAHE的复制粘贴篡改检测算法

Copy-Move Forgery Detection Algorithm Based on HSV and CLAHE

针对现有的局部特征提取算法,如尺度不变特征变换、加速稳健特征等对面积较小的篡改区域和平滑区域无法准确提取特征点进行复制粘贴篡改检测的问题,提出了一种基于色调、饱和度、明度(HSV)颜色空间和限制对比度自适应直方图均衡化(CLAHE)的2阶段篡改检测方法.第1阶段,将待检测图像从红、绿、蓝颜色空间转换到(HSV)颜色空间进行加速稳健特征提取;第2阶段,针对平滑区域的篡改,通过CLAHE算法对图像进行特征增强之后,再采用加速稳健特征进行特征提取;然后利用广义2近邻算法进行特征匹配,并利用随机抽样一致性算法剔除错误的匹配点;最后通过形态学操作实现篡改区域的标示定位.实验结果表明,该算法能抵抗小面积区域和具有非显著视觉特征的平滑区域复制粘贴篡改,并对旋转、缩放等后处理攻击具有一定的鲁棒性.

The existing local feature point-based methods such as scale-invariant feature transform（ SIFT） and speeded up robust features（ SURF） cannot be accurately extracted as feature points especially in terms of forgeries involving small areas and smooth regions. A two-stage forgery detection method which is based on the hue,saturation and value（ HSV） color space and contrast limited adaptive histogram equalization（ CLAHE） was proposed. In the first stage,the tested image is converted from red,green and blue（ RGB） color space to HSV and then SURF features were extracted in this space. In the second stage,in order to resist tampering in smooth regions,CLAHE algorithm was used as a preprocessing stage to the SURF algorithm. After feature extraction,generalized 2 nearest neighbor（ g2NN） matching skills were used in the matching step. At last,the random sample consensus（ RANSAC） was used to remove the false matches. The location of the tampered area is achieved by morphological operations.Experiments show that the proposed algorithm not only can resist copy-move forgeries in small areas and flat regions with non-significant visual features but also robust to post-processing operations such as rota-tion,scaling and so on.