Image Steganalysis System optimization Based on Boundary Samples

Image Steganalysis System optimization Based on Boundary Samples

In the image steganalysis,the training samples often determine the performance of the model when the features and classification are in the same condition.However the existing research on steganalysis lacks the in-depth study of the classifier＇s training method which may deeply influence the detecti...

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Veröffentlicht in:哈尔滨工业大学学报（英文版） 2014-12, Vol.21 (6), p.57-62
1. Verfasser: Li-Na Wang Min-Jie Wang Ting-Ting Zhu Qing Dou
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description In the image steganalysis,the training samples often determine the performance of the model when the features and classification are in the same condition.However the existing research on steganalysis lacks the in-depth study of the classifier＇s training method which may deeply influence the detection performance.This paper provides an optimization of universal steganalysis based on the boundary samples classification concerning about image steganalysis.This paper proposes a strategy of selecting boundary samples in steganalysis and divides the training samples into good samples,poor samples and boundary samples three categories and then chose the optimal threshold to get boundary samples through experiments.The experimental results show the effectiveness of boundary sample,which dramatically improve detection capability especially for the low embedding rate Stego-image.
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title Image Steganalysis System optimization Based on Boundary Samples
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