基于光源颜色和噪声的图像拼接篡改检测方法

数字图像拼接篡改是一种常见的图像伪造手段。在图像取证中，检测拼接伪造仍然是一项艰巨的任务。现有的拼接伪造检测方法多根据一种图像特性的不一致检测并定位篡改区域，而实际拼接篡改伪造往往会造成多种图像特性的改变。针对现有单一特征提取不能充分反映拼接图像特性导致检测精确率低的问题，提出一种通过提取光源颜色和噪声的混合特征来定位并显示拼接区域的高效图像拼接检测方法。实验结果表明，混合特征提取方法较单一特征提取方法能取得更高的检测精确率。

An image splicing detection method based on illuminant color and noise

Image splicing is a common image content tampering operation. It is still a difficult task to detect splicing areas in image forensics. Most of the existing splicing detection methods detect tampered areas based on the inconsistency of an image characteristic, while the actual splicing forgery often causes the change of a variety of image characteristics. Aiming at the problem that the single feature extraction can not fully reflect the image characteristics to lead to the low detection accuracy, this paper proposes a new method for detecting the image splicing efficiently by extracting the mixed features of the illuminant color and noise in the local regions. The experimental results show that the mixed feature extraction method can achieve higher accuracy than single feature extraction method.