-Edge Based Image Steganography schemes
-already studied~\cite{Luo:2010:EAI:1824719.1824720,DBLP:journals/eswa/ChenCL10,DBLP:conf/ih/PevnyFB10} differ
-how they select edge pixels, and
-how they modify these ones.
-
-First of all, let us discuss about compexity of edge detetction methods.
-Let then $M$ and $N$ be the dimension of the original image.
-According to~\cite{Hu:2007:HPE:1282866.1282944},
-even if the fuzzy logic based edge detection methods~\cite{Tyan1993}
-have promising results, its complexity is in $C_3 \times O(M \times N)$
-whereas the complexity on the Canny method~\cite{Canny:1986:CAE:11274.11275}
-is in $C_1 \times O(M \times N)$ where $C_1 < C_3$.
-\JFC{Verifier ceci...}
-In experiments detailled in this article, the canny method has been retained
-but the whole approach can be updated to consider
-the fuzzy logic edge detector.
+
+The edge based image steganography schemes
+already presented (\cite{Luo:2010:EAI:1824719.1824720,DBLP:journals/eswa/ChenCL10}) differ
+in how carefully they select edge pixels, and
+how they modify them.
+
+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 :-)}
+
+Many techniques have been proposed in the literature to detect
+edges in images.
+The most common ones are filter
+edge detection methods such as Sobel or Canny filters, low order methods such as
+first order and second order ones. 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.
+
+In order to be able to compute the same set of edge pixels, we suggest to consider all the bits of the image (cover or stego) without the LSB. With an 8 bits image, only the 7 first bits are considered. In our flowcharts, this is represented by LSB(7 bits Edge Detection).
+
+
+% First of all, let us discuss about compexity of edge detetction methods.
+% Let then $M$ and $N$ be the dimension of the original image.
+% According to~\cite{Hu:2007:HPE:1282866.1282944},
+% even if the fuzzy logic based edge detection methods~\cite{Tyan1993}
+% have promising results, its complexity is in $C_3 \times O(M \times N)$
+% whereas the complexity on the Canny method~\cite{Canny:1986:CAE:11274.11275}
+% is in $C_1 \times O(M \times N)$ where $C_1 < C_3$.
+% \JFC{Verifier ceci...}
+% In experiments detailled in this article, the Canny method has been retained
+% but the whole approach can be updated to consider
+% the fuzzy logic edge detector.
