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Proceedings Paper

Multi-class Markov models for JPEG steganalysis
Author(s): Hao Zhang; Xijian Ping
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Paper Abstract

Partially ordered Markov models based features were proposed in very recent years, which were shown to be quite effective in JPEG steganalysis. This paper presents an improvement of the original models. The proposed models here have two new characters. First, they are established on absolute values of coefficients instead of the values themselves. Second, the Markov models for coefficients were classified by comparing JPEG modes, not by directions. Besides, we recommended using Cartesian calibration technique to enhance the corresponding steganalytic features. Experimental results show that our proposed features outperform the original features, as well as some joint density features, in detecting several common steganographic algorithms.

Paper Details

Date Published: 19 July 2013
PDF: 5 pages
Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 887847 (19 July 2013); doi: 10.1117/12.2031619
Show Author Affiliations
Hao Zhang, Zhengzhou Information Science and Technology Institute (China)
Xijian Ping, Zhengzhou Information Science and Technology Institute (China)


Published in SPIE Proceedings Vol. 8878:
Fifth International Conference on Digital Image Processing (ICDIP 2013)
Yulin Wang; Xie Yi, Editor(s)

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