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Steganalysis Using Joint Moment of Wavelet Subbands  

Park, Tae-Hee (Dept. Mechatronics Eng., TongMyong University)
Hyun, Seung-Hwa (School of Electrical Eng., Pusan National University)
Kim, Jae-Ho (School of Electrical Eng., Pusan National University)
Eom, Il-Kyu (School of Electrical Eng., Pusan National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.48, no.3, 2011 , pp. 71-78 More about this Journal
Abstract
This paper propose image steganalysis scheme based on independence between parent and child subband on the multi-layer wavelet domain. The proposed method decompose cover and stego images into 12 subbands by applying 3-level Haar UWT(Undecimated Wavelet Transform), analyze statistical independency between parent and child subband. Because this independency is appeared more difference in stego image than in cover image, we can use it as feature to differenciate between cover and stego image. Therefore we extract 72D features by calculation first 3 order statistical moments from joint characteristic function between parent and child subband. Multi-layer perceptron(MLP) is applied as classifier to discriminate between cover and stego image. We test the performance of proposed scheme over various embedding rates by the LSB, SS, BSS embedding method. The proposed scheme outperforms the previous schemes in detection rate to existence of hidden message as well as exactness of discrimination.
Keywords
steganalysis; undecimated wavelet transform; statistical moment; characteristic function; MLP;
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