X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/canny.git/blobdiff_plain/274073a1e4ae1b4de1220e26626a582a08a890d6..53495cfa81215f89ff4e577247fda977b29ed265:/ourapproach.tex

diff --git a/ourapproach.tex b/ourapproach.tex
index f832695..0f2d7b5 100644
--- a/ourapproach.tex
+++ b/ourapproach.tex
@@ -1,5 +1,5 @@
 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.
+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}).
@@ -43,7 +43,7 @@ scheme.
 
 
 Edge Based Image Steganography schemes 
-already studied~\cite{Luo:2010:EAI:1824719.1824720,DBLP:journals/eswa/ChenCL10,DBLP:conf/ih/PevnyFB10} differ 
+already studied~\cite{Luo:2010:EAI:1824719.1824720,DBLP:journals/eswa/ChenCL10} differ 
 how they select edge pixels, and  
 how they modify these ones.
 
@@ -51,61 +51,62 @@ Image Quality: Edge Image Steganography
 \JFC{Raphael, les fuzzy edge detection sont souvent utilisÃ©s. 
   il faudrait comparer les approches en terme de nombre de bits retournÃ©s,
   en terme de complexitÃ©. } \cite{KF11}
-\RC{Ben, Ã  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 dÃ©tectable...  Finalement on devrait surement vendre notre truc en : on a choisi cet algo car il est performant en vitesse/qualitÃ©. Mais on peut aussi en utilisÃ© d'autres :-)}
+\RC{Ben, Ã  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 dÃ©tectable...  Finalement on devrait surement vendre notre truc en : on a choisi cet algo car il est performant en vitesse/qualitÃ©. Mais on peut aussi en utilisÃ© 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
+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
+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.
 
 
-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.   
+% 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.   
 
 Next, following~\cite{Luo:2010:EAI:1824719.1824720}, our scheme automatically
-modifies canny parameters to get a sufficiently large set of edge bits: this 
+modifies the Canny algorithm 
+parameters to get a sufficiently large set of edge bits: this 
 one is practically enlarged untill its size is at least twice as many larger 
 than the size of embedded message.
 
-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.   
-
-Next, following~\cite{Luo:2010:EAI:1824719.1824720}, our scheme automatically
-modifies canny parameters to get a sufficiently large set of edge bits: this 
-one is practically enlarged untill its size is at least twice as many larger 
-than the size of embedded message.
+% 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.   
+
+% Next, following~\cite{Luo:2010:EAI:1824719.1824720}, our scheme automatically
+% modifies Canny parameters to get a sufficiently large set of edge bits: this 
+% one is practically enlarged untill its size is at least twice as many larger 
+% than the size of embedded message.
 
 
 \subsubsection{Security Considerations}
