关键词: 数字图像盲取证, 图像拼接检测, 图像质量评价量, 矩特征量, 支持向量机

Abstract: Image splicing is a technique commonly used in image tampering. To implement image splicing blind detection，a new splicing detection scheme was proposed. Image splicing detection could be regarded as a two-class pattern recognition problem and the model was established based on moment features and some Image Quality Metrics (IQMs) extracted from the given test image. This model could measure statistical differences between original image and spliced image. Kernel-based Support Vector Machine (SVM) was chosen as a classifier to train and test the given images. Experimental results demonstrate that this new splicing detection scheme has some advantages of high-accuracy and wide-application.

Key words: blind image forensics, image splicing detection, image quality metrics (IQMs), moment features, Support Vector Machine (SVM)