From 36f33066d192d54e79b234d89f223b3f4016ff12 Mon Sep 17 00:00:00 2001 From: =?utf8?q?Jean-Fran=C3=A7ois=20Couchot?= Date: Fri, 21 Dec 2012 17:08:57 +0100 Subject: [PATCH] modifs avant vacances --- biblio.bib | 24 +++++++++++++++++++++- experiments.tex | 54 +++++++++++++++++++++++++++++++++++++++---------- 2 files changed, 66 insertions(+), 12 deletions(-) diff --git a/biblio.bib b/biblio.bib index 22bcda2..3c06dc7 100644 --- a/biblio.bib +++ b/biblio.bib @@ -25,6 +25,28 @@ isbn = {3-540-42733-3}, bibsource = {DBLP, http://dblp.uni-trier.de} } + +@article{Chang20101286, +title = "Hybrid wet paper coding mechanism for steganography employing n-indicator and fuzzy edge detector", +journal = "Digital Signal Processing", +volume = "20", +number = "4", +pages = "1286 - 1307", +year = "2010", +note = "", +issn = "1051-2004", +doi = "10.1016/j.dsp.2009.11.005", +url = "http://www.sciencedirect.com/science/article/pii/S1051200409002413", +author = "Chin-Chen Chang and Jung-San Lee and T. Hoang Ngan Le", +keywords = "Security", +keywords = "Wet paper coding", +keywords = "Steganography", +keywords = "Indicator", +keywords = "Fuzzy edge detector" +} + + + @article{Hu:2007:HPE:1282866.1282944, author = {Hu, Liming and Cheng, H. D. and Zhang, Ming}, title = {A high performance edge detector based on fuzzy inference rules}, @@ -203,7 +225,7 @@ author = {Jessica J. Fridrich and interhash = {bc34a5f04661fee24ee62c39e76361be}, intrahash = {28889a4ab329da28559f0910469f054b}, journal = {Expert Syst. Appl.}, - keywords = {dblp}, + keywords = {dblp}, number = 4, pages = {3292-3301}, timestamp = {2010-07-21T15:44:10.000+0200}, diff --git a/experiments.tex b/experiments.tex index 0011cd4..45f0b87 100644 --- a/experiments.tex +++ b/experiments.tex @@ -1,14 +1,37 @@ \subsection{Adaptive Embedding Rate} - +Two strategies have been developed in our scheme with respect to the rate of +embedding which is either \emph{ adaptive} or \emph{fixed}. + +In the former the embedding rate depends on the number of edge pixels. +The higher it is, the larger is the message length that can be considered. +Practically, a set of edge pixels is computed according to the +Canny algorithm with high threshold. +The message length is thus defined to be the half of this set cardinality. +The rate between available bits and bit message length is then more than two.This constraint is indeed induced by the fact that the efficiency +of the stc algorithm is unsatisfactory under that threshold. + + +In the latter, the embedding rate is defined as a percentage between the +number of the modified pixels and the length of the bit message. +This is the classical approach adopted in steganography. +Practically, the Canny algorithm generates a +a set of edge pixels with threshold that is decreasing until its cardinality +is sufficient. If the set cardinality is more than twice larger than the +bit message length an stc is again applied. +Otherwise, pixels are randomly chosen from the set of pixels to build the +subset with a given size. The BBS PRNG is again applied there. + + + \subsection{Image Quality} The visual quality of the STABYLO scheme is evaluated in this section. Four metrics are computed in these experiments : the Peak Signal to Noise Ratio (PSNR), -the PSNR-HVS-M familly~\cite{PSECAL07,psnrhvsm11} , +the PSNR-HVS-M family~\cite{PSECAL07,psnrhvsm11} , the BIQI~\cite{MB10,biqi11} and -the weigthed PSNR (wPSNR)~\cite{DBLP:conf/ih/PereiraVMMP01}. +the weighted PSNR (wPSNR)~\cite{DBLP:conf/ih/PereiraVMMP01}. The first one is widely used but does not take into account Human Visual System (HVS). The other last ones have been designed to tackle this problem. @@ -17,8 +40,7 @@ The other last ones have been designed to tackle this problem. \begin{center} \begin{tabular}{|c|c|c|} \hline -Embedding rate & Adaptive -10 \% & \\ +Embedding rate & Adaptive & 10 \% \\ \hline PSNR & 66.55 & 61.86 \\ \hline @@ -30,14 +52,19 @@ wPSNR & 86.43& 77.47 \\ \hline \end{tabular} \end{center} -\caption{Quality measeures of our steganography approach\label{table:quality}} +\caption{Quality measures of our steganography approach\label{table:quality}} \end{table} -Compare to the Edge Adpative scheme detailed in~\cite{Luo:2010:EAI:1824719.1824720}, our both wPSNR and PSNR values are always higher than their ones. - -\JFC{comparer aux autres approaches} - +Let us compare the STABYLO approach with other edge based steganography +schemes with respect to the image quality. +Fist off all, wPSNR and PSNR of the Edge Adaptive +scheme detailed in~\cite{Luo:2010:EAI:1824719.1824720} are lower than ours. +Next both the approaches~\cite{DBLP:journals/eswa/ChenCL10,Chang20101286} +focus on increasing the payload while the PSNR is acceptable, bu do not +give quality metrics for fixed embedding rate from a large base of images. +Our approach outperforms the former thanks to the introduction of the stc +algorithm. \subsection{Steganalysis} @@ -63,7 +90,8 @@ can be a favourably executed thanks to an Ensemble Classifiers. \begin{table} \begin{center} \begin{tabular}{|c|c|c|c|} -Shemes & \multicolumn{2}{|c|}{STABYLO} & HUGO\\ +\hline +Schemes & \multicolumn{2}{|c|}{STABYLO} & HUGO\\ \hline Embedding rate & Adaptive & 10 \% & 10 \%\\ \hline @@ -78,3 +106,7 @@ Ensemble Classifier & & & \\ \end{table} +Results show that our approach is more easily detectable than HUGO which is +is the more secure steganography tool, as far we know. However due to its +huge number of features integration, it is not lightweight. + -- 2.39.5