Method for Image Splicing Detection Based on Statistical Features and Markov Feature
基于统计特征和马尔可夫特征的图像拼接盲检测

The authenticity detection of digital images is of great significance in judicial identification. Image splicing is used very often as a falsification method and it will certainly decrease the correlation between image pixels which can be reflected by some statistical features. Combined with Markov features, a new approach which uses moment and phase congruency to extract features was proposed and SVM classifier was used to judge the category an image belongs to.The experimental results show that the proposed method can achieve a detection accuracy of 91. 75%.