--- /dev/null
+# Analysis description
+set encoding iso_8859_1
+set terminal x11
+set size 1,0.5
+set term postscript enhanced portrait "Helvetica" 12
+set ylabel "Average testing error"
+set xlabel "Payload"
+set key on inside bottom left
+plot 'error.txt' using 1:2 t "STABYLO" with linespoints lt 1 lw 2 ps 0 pt 5,\
+ 'error.txt' using 1:3 t "HUGO" with linespoints lt 1 lw 2 ps 1 pt 2,\
+ 'error.txt' using 1:4 t "EAISLSBMR" with linespoints lt 3 lw 2 ps 0 pt 1,\
+ 'error.txt' using 1:5 t "WOW" with linespoints lt 1 lw 2 ps 1 pt 1,\
+ 'error.txt' using 1:6 t "UNIWARD" with linespoints lt 5 lw 2 ps 0 pt 1
+
+
+
--- /dev/null
+# stabylo hugo adapt edge wow uniward
+0.0635 0.47 0.4920 0.47 0.4911 0.49
+0.1213 0.42 0.482 0.435 0.482 0.47
+0.2924 0.24 0.4345 0.30 0.4333 0.39
All these numerical experiments confirm
the objective presented in the motivations:
providing an efficient steganography approach in a lightweight manner.
+
+\RC{In Figure~\ref{fig:error}, Ensemble Classifier has been used with all the previsou steganalizers with 3 different payloads. It can be observed that with important payload, STABYLO is not efficient, but as mentionned its complexity is far more simple compared to other tools.\\
+\begin{figure}
+\begin{center}
+\includegraphics[scale=0.5]{error}
+\end{center}
+\caption{Error obtained by Ensemble classifier with WOW/UNIWARD, HUGO, and STABYLO and different paylaods.}
+\label{fig:error}
+\end{figure}
+}
\newcommand{\JFC}[1]{\begin{color}{green}\textit{#1}\end{color}}
-\newcommand{\RC}[1]{\begin{color}{red}\textit{}\end{color}}
-\newcommand{\CG}[1]{\begin{color}{blue}\textit{}\end{color}}
+\newcommand{\RC}[1]{\begin{color}{red}\textit{#1}\end{color}}
+\newcommand{\CG}[1]{\begin{color}{blue}\textit{#1}\end{color}}
% make the title area