Texture-Based Image Steganography Using Adaptive Pixel Pair Matching
Received date: 2016-08-04
Revised date: 2016-08-18
Online published: 2016-09-30
Compared with flat regions, texture-rich regions in an image are more randomlike, and therefore are more secure for hidden messages. Based on the adaptive pixel pair matching (APPM) scheme, we propose an improved steganographic algorithm that embeds secret data preferentially in texture regions. A criterion for image texture assessment is defined. According to the length of secret data, We use the the criterion to adaptively select appropriate regions for embedding. A pixel value adjustment strategy based on optimizing a minimum distortion function through local search is proposed to deal with possible abnormal situations in embedding. Experimental results show that the proposed algorithm outperforms the original APPM in terms of embedding efficiency and Kullback-Leibler divergence. It is also more robust against several representative steganalytic attacks than a number of least significant bits (LSB) algorithms and APPM.
LIU Shuo-wei, HU Yong-jian, LIU Bei-bei, HUA Xiao-qian . Texture-Based Image Steganography Using Adaptive Pixel Pair Matching[J]. Journal of Applied Sciences, 2016 , 34(5) : 515 -526 . DOI: 10.3969/j.issn.0255-8297.2016.05.004
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