From: couchot <couchot@couchot-Latitude-E6320.(none)>
Date: Fri, 21 Dec 2012 09:47:27 +0000 (+0100)
Subject: debut d'experiment
X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/canny.git/commitdiff_plain/4516d82b16c946a9e8a9cadd0011616e8a66cc31?hp=--cc

debut d'experiment
---

4516d82b16c946a9e8a9cadd0011616e8a66cc31
diff --git a/biblio.bib b/biblio.bib
index 8e5c9de..5680580 100644
--- a/biblio.bib
+++ b/biblio.bib
@@ -1,3 +1,30 @@
+@inproceedings{DBLP:conf/ih/PereiraVMMP01,
+  author    = {Shelby Pereira and
+               Sviatoslav Voloshynovskiy and
+               Maribel Madueno and
+               St{\'e}phane Marchand-Maillet and
+               Thierry Pun},
+  title     = {Second Generation Benchmarking and Application Oriented
+               Evaluation},
+  booktitle = {Information Hiding},
+  year      = {2001},
+  pages     = {340-353},
+  ee        = {http://dx.doi.org/10.1007/3-540-45496-9_25},
+  crossref  = {DBLP:conf/ih/2001},
+  bibsource = {DBLP, http://dblp.uni-trier.de}
+}
+@proceedings{DBLP:conf/ih/2001,
+  editor    = {Ira S. Moskowitz},
+  title     = {Information Hiding, 4th International Workshop, IHW 2001,
+               Pittsburgh, PA, USA, April 25-27, 2001, Proceedings},
+  booktitle = {Information Hiding},
+  publisher = {Springer},
+  series    = {Lecture Notes in Computer Science},
+  volume    = {2137},
+  year      = {2001},
+  isbn      = {3-540-42733-3},
+  bibsource = {DBLP, http://dblp.uni-trier.de}
+}
 @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},
diff --git a/experiments.tex b/experiments.tex
index a79b1d4..40cd93b 100644
--- a/experiments.tex
+++ b/experiments.tex
@@ -1,18 +1,39 @@
 
 \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 &      &      \\
+\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}
 
 
-biqi = 28.3
-psnr-hvs-m= 78,6
-psnr-hvs= 67.3
+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}
 
 
 \subsection{Steganalysis}
@@ -35,4 +56,22 @@ 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
+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}
+
+
 \JFC{Raphael, il faut donner des résultats ici}
\ No newline at end of file