X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/canny.git/blobdiff_plain/fdf9d8855582d89072dcd1339af9f5b74a167ac6..274073a1e4ae1b4de1220e26626a582a08a890d6:/experiments.tex?ds=inline

diff --git a/experiments.tex b/experiments.tex
index a79b1d4..0011cd4 100644
--- a/experiments.tex
+++ b/experiments.tex
@@ -1,18 +1,43 @@
+\subsection{Adaptive Embedding Rate} 
+
+
 
 \subsection{Image Quality}
 The visual quality of the STABYLO scheme is evaluated in this section.
-Three metrics are computed in these experiments : 
+Four metrics are computed in these experiments : 
 the Peak Signal to Noise Ratio (PSNR), 
-the PSNR-HVS-M~\cite{PSECAL07,psnrhvsm11} and the BIQI~\cite{MB10,biqi11}.
+the PSNR-HVS-M familly~\cite{PSECAL07,psnrhvsm11} , 
+the BIQI~\cite{MB10,biqi11} and 
+the weigthed PSNR (wPSNR)~\cite{DBLP:conf/ih/PereiraVMMP01}.
 The first one is widely used but does not take into
 account Human Visual System (HVS).
-The two last ones have been designed to tackle this problem.
+The other last ones have been designed to tackle this problem.
+
+\begin{table}
+\begin{center}
+\begin{tabular}{|c|c|c|}
+\hline
+Embedding rate &  Adaptive 
+10 \% &  \\
+\hline
+PSNR &  66.55    & 61.86     \\
+\hline
+PSNR-HVS-M & 78.6  & 72.9 \\
+\hline
+BIQI & 28.3 & 28.4 \\
+\hline
+wPSNR & 86.43& 77.47 \\
+\hline
+\end{tabular}
+\end{center}
+\caption{Quality measeures 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}
 
-biqi = 28.3
-psnr-hvs-m= 78,6
-psnr-hvs= 67.3
 
 
 \subsection{Steganalysis}
@@ -35,4 +60,21 @@ can be a favourably executed thanks to an Ensemble Classiï¬ers.
 
 
 
-\JFC{Raphael, il faut donner des rÃ©sultats ici}
\ No newline at end of file
+\begin{table}
+\begin{center}
+\begin{tabular}{|c|c|c|c|}
+Shemes & \multicolumn{2}{|c|}{STABYLO} & HUGO\\
+\hline
+Embedding rate &  Adaptive & 10 \% &  10 \%\\
+\hline
+AUMP & 0.39  & 0.22     &  0.50     \\
+\hline
+Ensemble Classifier &   &      &      \\
+
+\hline
+\end{tabular}
+\end{center}
+\caption{Steganalysing STABYLO\label{table:steganalyse}} 
+\end{table}
+
+
