DocumentCode :
1585495
Title :
Image Steganalysis Based on Statistical Moments of Wavelet Subband Histograms in Different Frequencies and Support Vector Machine
Author :
Mehrabi, Mohammad Ali ; Faez, Karim ; Bayesteh, Ali Reza
Author_Institution :
Amirkabir Univ. of Technol., Tehran
Volume :
1
fYear :
2007
Firstpage :
587
Lastpage :
590
Abstract :
This paper proposed a new image steganalysis scheme based on statistical moments of histogram of multi-level wavelet subbands in frequency domain. Different frequencies of histogram have different sensitivity to various data embedding. Then we decompose the test image using three-level Haar discrete wavelet transform (DWT) into 13 subbands (here the image itself is considered as the LLO subband). The DFT of each subband, is calculated. It is divided into low and high frequency bands. The first three statistical moments of each band are selected to form a 78-dimensional feature vector for Steganalysis. Support vector machines (SVM) classifier is then used to discriminate between stego- images and innocent images. Experimental results show that the proposed algorithm outperforms previously existing techniques.
Keywords :
Haar transforms; data encapsulation; image coding; statistical analysis; support vector machines; wavelet transforms; frequency domain analysis; image steganalysis; statistical moments; support vector machine classifier; three-level Haar discrete wavelet transform; wavelet subband histograms; Art; Discrete wavelet transforms; Frequency conversion; Frequency domain analysis; Histograms; Steganography; Support vector machine classification; Support vector machines; Testing; Wavelet domain;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
Type :
conf
DOI :
10.1109/ICNC.2007.432
Filename :
4344258
Link To Document :
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