Share Email Print

Journal of Electronic Imaging

Image textural features for steganalysis of spatial domain steganography
Author(s): Gang Xiong; Xijian Ping; Tao Zhang; Xiaodan Hou
Format Member Price Non-Member Price
PDF $20.00 $25.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

From the texture analysis of image content, we propose a steganalytic method to detect spatial domain steganography in grayscale images. First of all, based on the local linear vectors, which are selected carefully and sensitive to image texture, images are decomposed into several textural detail subbands by the local linear transform (LLT). Then the statistical distribution of the LLT coefficient is modeled by using the generalized Gaussian distribution. Finally, novel textural features of the LLT coefficient histogram and cooccurrence matrix are extracted for steganalyzers implemented by the support vector machine. Extensive experiments are performed on four diverse uncompressed image databases and seven typical spatial domain steganographic algorithms, such as the highly undetectable stego. The results reveal that the proposed scheme is universal for detecting spatial domain steganography. By comparison with other well-known feature sets, our presented feature set offers the best performance under most circumstances.

Paper Details

Date Published: 22 August 2012
PDF: 15 pages
J. Electron. Imag. 21(3) 033015 doi: 10.1117/1.JEI.21.3.033015
Published in: Journal of Electronic Imaging Volume 21, Issue 3
Show Author Affiliations
Gang Xiong, Zhengzhou Information Science and Technology Institute (China)
Xijian Ping, Zhengzhou Information Science and Technology Institute (China)
Tao Zhang, Zhengzhou Information Science and Technology Institute (China)
Xiaodan Hou, Zhengzhou Information Science and Technology Institute (China)

© SPIE. Terms of Use
Back to Top