X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/canny.git/blobdiff_plain/100ac9908382b8de480dae1fd68829f2a7778b5d..c1c8ac417383292fd1103aca552f689ff362426c:/ourapproach.tex

diff --git a/ourapproach.tex b/ourapproach.tex
index 4dce984..25defad 100644
--- a/ourapproach.tex
+++ b/ourapproach.tex
@@ -1,8 +1,8 @@
-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}).
+The flowcharts given in Fig.~\ref{fig:sch} summarize our steganography scheme denoted by
+STABYLO, which stands for STeganography with Canny, Bbs, binarY embedding at LOw cost.
+What follows successively details all the inner steps and flows inside 
+both the embedding stage (Fig.~\ref{fig:sch:emb}) 
+and the extraction one (Fig.~\ref{fig:sch:ext}).
 
 
 \begin{figure*}[t]
@@ -41,47 +41,112 @@ 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 
-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 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 :-)}
+
+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 that depend on the
+motivations behind that edges detection.   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 architectures like FPGAs, smartphones,  desktop machines, and
+GPUs. 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.   
 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.
-
+modifies the Canny algorithm 
+parameters to get a sufficiently large set of edge bits: this 
+one is practically enlarged until its size is at least twice as large 
+as the size of the 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}
 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) 
+that is based on the Blum Blum Shub~\cite{DBLP:conf/crypto/ShubBB82} pseudorandom 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, $x_{i+L-1}$,
+for any sequence of $L$ 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 
+Equivalent formulations of such a property can
+be found. They all lead to the fact that,
+even if the encrypted message is extracted, 
+it is impossible to retrieve the original one in 
 polynomial time.   
 
 
+%%RAPH: paragraphe en double :-)
+
+%% \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. 
+
 
 
 
@@ -93,7 +158,7 @@ polynomial time.
 \subsection{Data Extraction}
 Message extraction summarized in Fig.~\ref{fig:sch:ext} follows data embedding
 since there exists a reverse function for all its steps.
-First of all, the same edge detection is applied to get set,
+First of all, the same edge detection is applied (on the 7 first bits) to get set,
 which is  sufficiently large with respect to the message size given as a key.  
 Then the STC reverse algorithm is applied to retrieve the encrypted message.
 Finally, the Blum-Goldwasser decryption function is executed and the original
