X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/canny.git/blobdiff_plain/9c37522d37b3caa216649cc98987e4c89b42091f..5178f772a789c49b261c48acc466a982d413a9a9:/experiments.tex

diff --git a/experiments.tex b/experiments.tex
index 61d2971..9590b1c 100644
--- a/experiments.tex
+++ b/experiments.tex
@@ -153,7 +153,7 @@ considered as state of the art steganalysers.
 \JFC{Features that are embedded into this steganalysis process 
 are CCPEV and SPAM features as described 
 in~\cite{DBLP:dblp_conf/mediaforensics/KodovskyPF10}.
-These one are extracted from the 
+These latter are extracted from the 
 set of cover images and the set of training images.}
 Next a small 
 set of weak classifiers is randomly built,
@@ -216,3 +216,13 @@ 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.
+
+\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}
+}
