X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/canny.git/blobdiff_plain/100ac9908382b8de480dae1fd68829f2a7778b5d..53495cfa81215f89ff4e577247fda977b29ed265:/ourapproach.tex

diff --git a/ourapproach.tex b/ourapproach.tex
index 4dce984..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}).
@@ -41,28 +41,72 @@ scheme.
 
 \subsubsection{Edge Based Image Steganography}
 
+
 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.
 
-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.   
+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 :-)}
+
+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.
+
+
+% 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.
 
 
 \subsubsection{Security Considerations}
@@ -82,6 +126,21 @@ it would thus be not possible to retrieve the original one in a
 polynomial time.   
 
 
+\subsubsection{Security Considerations}
+Among methods of message encryption/decryption 
+(see~\cite{DBLP:journals/ejisec/FontaineG07} for a survey)
+we implement the Blum-Goldwasser cryptosystem~\cite{Blum:1985:EPP:19478.19501}
+which is based on the Blum Blum Shub~\cite{DBLP:conf/crypto/ShubBB82} Pseudo Random Number Generator (PRNG) 
+for security reasons.
+It has been indeed proven~\cite{DBLP:conf/crypto/ShubBB82} that this PRNG 
+has the cryptographically security property, \textit{i.e.}, 
+for any sequence $L$ of output bits $x_i$, $x_{i+1}$, \ldots, $x_{i+L-1}$,
+there is no algorithm, whose time complexity is polynomial  in $L$, and 
+which allows to find $x_{i-1}$ and $x_{i+L}$ with a probability greater
+than $1/2$.
+Thus, even if the encrypted message would be extracted, 
+it would thus be not possible to retrieve the original one in a 
+polynomial time.   
 
 
 
