-Next, our approach is more easily detectable than HUGO, which
-is the most secure steganographic tool, as far as we know.
-However by combining \emph{adaptive} and \emph{STC} strategies
-our approach obtains similar results to HUGO ones.
-
-%%%%et pour b= 6 ?
-
-
-Compared to EAILSBMR, we obtain better results when the strategy is
-\emph{adaptive}.
-However due to its
-huge number of integration features, it is not lightweight, which justifies
-in the authors' opinion the consideration of the proposed method.
+Next, our approach is more easily detectable than HUGO,
+WOW and UNIWARD which are the most secure steganographic tool,
+as far as we know.
+However by combining Adaptive and STC strategies
+our approach obtains similar results than the ones of these schemes.
+
+Compared to EAILSBMR, we obtain similar
+results when the strategy is
+Adaptive.
+However due to its huge number of integration features, it is not lightweight.
+
+All these numerical experiments confirm
+the objective presented in the motivations:
+providing an efficient steganography approach in a lightweight manner
+for small payload.
+
+In Figure~\ref{fig:error},
+Ensemble Classifier has been used with all the previous
+steganographic schemes with 4 different payloads.
+It can be observed that face to high values of payload,
+STABYLO is definitely not secure enough.
+However thanks to an efficient very low-complexity (Fig.\ref{fig:compared}),
+we argue that the user should embed tiny messages in many images
+than a larger message in only one image.
+\begin{figure}
+\begin{center}
+\includegraphics[scale=0.5]{error}
+\end{center}
+\caption{Testing errors obtained by Ensemble classifier with
+WOW/UNIWARD, HUGO, and STABYLO w.r.t. payload.}
+\label{fig:error}
+\end{figure}
