Seam-Carving forgery detection based on expanded Markov features - Guo-rui SHENG; Tie-gang GAO; Li FAN; Lin GAO; Fu-sheng YANG; Shun ZHANG (Tongxin xuebao)
To deal with the digital image forgery using Seam-Carving, a detection algorithm based on expanded Markov features was proposed. The algorithm takes full acount of the image frequency domain change caused by Seam-Carving operation, merges the features based on traditional and expands Markov transfer-probability matrix. Trained by SVM, the merged Markov feature can identify the Seam-Carving forgery more effectively. The experiment result shows that the performance of the proposed method is better than that of the method based on traditional Markov features and other existing methods.