关键词: 数字图像防伪鉴定, 拼接检测, 信息熵, 马尔可夫特征, 分块离散余弦变换, 支持向量机

Abstract: With the popularity of graphic editing software, tampering a digital image becomes more and more easier, so it is urgent to solve digital image forensics problem. Aiming at the problem, this paper proposes an image splicing detection method based on image information entropy feature and multi-step Markov feature. Image splicing detection can be treated as a two-class pattern recognition problem. This method consists of entropy feature extracted from the original image, three-level Haar Discrete Wavelet Transform(DWT) and multiple-size block Discrete Cosine Transform(DCT), and multi-step Markov feature transition probability matrix is extracted from block DCT. The statistical characteristics consist of information entropy and multi-step Markov feature. Support Vector Machine(SVM) is used to judge the image category and get judgment result. Experimental results show that the proposed method applied to the Columbia image dataset possesses promising capability in splicing detection, and it can achieve a detection accuracy of 89.91%.

Key words: digital image anti-counterfeiting identification, splicing detection, information entropy, Markov feature, block Discrete Cosine Transform(DCT), Support Vector Machine(SVM)