The wide availability of easy-to-use image editors has made the authenticity of images questionable. Copy-move is one of the most applied forgery types. A new copy-move forgery detection and localization technique independent from the characteristics of the forged regions is proposed in this paper. SIFT keypoints are obtained from CLAHE applied sub-images extracted from the input image by using RGB and L*a*b* color-spaces. Keypoint matching is realized on the sub-images and duplicated regions are determined roughly to create roughly marked image R. RANSAC is also applied in this stage and generated homography matrix is used to construct transformed roughly marked image R^′. The method extracts DCT based features from R and R^′ to localize exact borders of the tampered regions on the roughly determined areas by using a dynamic threshold. The proposed method has a new suggestion to determine the threshold dynamically. Tamper localization procedure also utilizes from morphological operations (chosen depending on the characteristic of the image) and Connected Component Labeling to determine exact forge boundaries. Results indicate that the proposed method has a better performance compared with state-of-the-art copy-move forgery detection methods on the GRIP dataset. Scaling attack performance of the method is especially better than similar works as shown in the results.

易于使用的图像编辑器的广泛可用性使图像的真实性令人怀疑。复制移动是最常用的伪造类型之一。提出了一种独立于伪造区域特征的复制移动伪造检测与定位技术。通过使用RGB和L * a * b *颜色空间，从从输入图像中提取的CLAHE应用子图像中获取SIFT关键点。关键点匹配实现在子图像和确定重复区域大致以创建大致标记图像[R 。在该阶段还应用了RANSAC，并使用生成的单应性矩阵来构造变换后的大致标记图像R ^'。该方法从R和R中提取基于DCT的特征^'通过使用动态阈值来本地化的大致确定区域中的篡改区域的精确边界。该方法具有动态确定阈值的新建议。篡改定位过程还利用形态学操作（根据图像的特征选择）和连接组件标签来确定准确的伪造边界。结果表明，与GRIP数据集上最新的复制移动伪造检测方法相比，该方法具有更好的性能。结果表明，该方法的扩展攻击性能特别好于类似的工作。