The Analysis of Steganographic by Sub-Pixel Calibration
Qian Chen, Jing Xin Hong, Gang Ou, Chen Guang Xu, Ling Wang, Yi Xiong Zhang · Applied Mechanics and Materials · 2014
In order to achieve high accuracy, we present a new calibration technique aimed at blind steganalysis. The calibration can be considered as a preprocessing of stego image before extracting the features. The extracted features will be more effective for our classification [1] Moreover, the calibrated feature was used to train SVM (Support Vector Machine)[2], a nonlinear classifier, which is effective in class separation. For comparison, we conducted extensive experiments and drawn a conclusion that the steganalytic scheme based on our novel calibration can detect the stego information with high accuracy. Experimental results demonstrate that our proposed scheme outperforms the best effective JPEG steganalysis having been presented.