The flowcharts given in Fig.~\ref{fig:sch} summarize our steganography scheme denoted as to
STABYLO for STeganography with cAnny, Bbs, binarY embedding at LOw cost.
What follows successively details all the inner steps and flow inside 
the embedding stage (Fig.\ref{fig:sch:emb}) 
and inside the extraction one(Fig.~\ref{fig:sch:ext}).


\begin{figure*}[t]
  \begin{center}
    \subfloat[Data Embedding.]{
      \begin{minipage}{0.49\textwidth}
        \begin{center}
%          \includegraphics[width=5cm]{emb.pdf}
          \includegraphics[width=5cm]{emb.ps}
        \end{center}
      \end{minipage}
      \label{fig:sch:emb}
    }%\hfill
    \subfloat[Data Extraction.]{
      \begin{minipage}{0.49\textwidth}
        \begin{center}
%          \includegraphics[width=5cm]{rec.pdf}
          \includegraphics[width=5cm]{rec.ps}
        \end{center}
      \end{minipage}
      \label{fig:sch:ext}
    }%\hfill
  \end{center}
  \caption{The STABYLO Scheme.}
  \label{fig:sch}
\end{figure*}




\subsection{Data Embedding} 




\subsubsection{Edge Based Image Steganography}
Image Quality: Edge Image Steganography
\JFC{Raphael, les fuzzy edge detection sont souvent utilisés. 
  il faudrait comparer les approches en terme de nombre de bits retournés,
  en terme de complexité. } \cite{KF11}
\RC{Ben, à voir car on peut choisir le nombre de pixel avec canny. Supposons que les fuzzy edge soient retourne un peu plus de points, on sera probablement plus détectable...  Finalement on devrait surement vendre notre truc en : on a choisi cet algo car il est performant en vitesse/qualité. Mais on peut aussi en utilisé d'autres :-)}

There are  many techniques to  detect edges in  images. Main methods  are filter
edge detection methods such as Sobel  or Canny filter, low order methods such as
first order  and second order  methods, these methods  are based on  gradient or
Laplace  operators and  fuzzy edge  methods which  are based  on fuzzy  logic to
highlight edges.

Of course, all the algorithms have  advantages and drawbacks which depend on the
motivation  to  highlight  edges.   Unfortunately  unless testing  most  of  the
algorithms, which  would require many  times, it is  quite difficult to  have an
accurate idea on what would produce  such algorithm compared to another. That is
why we have  chosen canny algorithm which is well  known, fast and implementable
on many  kinds of architecture, such  as FPGA, smartphone,  desktop machines and
GPU. And of course, we do not pretend that this is the best solution.

Presentation des algos de detection de contour
Caractéristiques

Comparaison théoriques, références

Algo de stegano basé juste sur cela : (pas de bbs, pas de stc, même message).

Quels paramètres sont optimaux ? Combinaison ? 





\subsubsection{Security Considerations}

Security aspect:
BBS-based cryptographic version of the message 

\subsubsection{Minimizing Distortion with Syndrome-Treillis Codes} 

\input{stc}


\subsection{Data Extraction}
