Blind Image Steganalysis Based on Statistical Analysis of Empirical Matrix

Authors:
Xiaochuan Chen;Yunhong Wang;Tieniu Tan;Lei Guo
Affiliations:
Chinese Academy of Sciences, P.O.Box 2728, Beijing;Beihang University, China;Chinese Academy of Sciences, P.O.Box 2728, Beijing;Chinese Academy of Sciences, P.O.Box 2728, Beijing
Venue:
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Year:
2006

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Abstract

In this paper, a novel steganalysis method based on statistical analysis of empirical matrix (EM) is proposed to detect the presence of hidden message in an image. The projection histogram ..PH.. of EM is used to extract features composed of two parts: the moments of PH and the moments of the characteristic function of PH. Also, features extracted from prediction-error image [7] are included to enhance performance. SVM is utilized as classifier. A test database is constructed, based on which a detailed test for different categories of features and a comparison with methods in prior arts are conducted. Experiments show that the features we proposed are more effective than prior arts and our steganalysis method could blindly detect the presence of data hiding for various embedding schemes with high performance.