ajouts mineurs

diff --git a/intro.tex b/intro.tex
index 16e8c8b6d6dd236433c3d4e770f263f79587878f..745751fd2ce63effdb2e630fadc6be8887d84172 100644 (file)
--- a/intro.tex
+++ b/intro.tex
@@ -60,7 +60,7 @@ in cover image, edge pixels already break its continuity  and thus already conta
 pixels. In other words, minor changes in regular area are more dramatic than larger modifications in edge ones. 
 Our proposal is thus to embed message bits into edge shapes while preserving other smooth regions. 
 
 pixels. In other words, minor changes in regular area are more dramatic than larger modifications in edge ones. 
 Our proposal is thus to embed message bits into edge shapes while preserving other smooth regions. 
 

-Edge based steganographic schemes have bee already studied~\cite{Luo:2010:EAI:1824719.1824720,DBLP:journals/eswa/ChenCL10}.
+Edge based steganographic schemes have been already studied~\cite{Luo:2010:EAI:1824719.1824720,DBLP:journals/eswa/ChenCL10}.

 In the former, the authors show how to select sharper edge regions with respect 
 to embedding rate: the larger the number of bits to be embedded, the coarse the edge regions are.
 Then the data hiding algorithm is achieved by applying LSBMR on pixels of this region. 
 In the former, the authors show how to select sharper edge regions with respect 
 to embedding rate: the larger the number of bits to be embedded, the coarse the edge regions are.
 Then the data hiding algorithm is achieved by applying LSBMR on pixels of this region. 


@@ -81,7 +81,7 @@ schemes~\cite{Luo:2010:EAI:1824719.1824720,DBLP:journals/eswa/ChenCL10,DBLP:conf
 produce stego content 
 with only considering the payload, not the type of image signal: the higher the payload is, 
 the better the approach is said to be. 
 produce stego content 
 with only considering the payload, not the type of image signal: the higher the payload is, 
 the better the approach is said to be. 

-Contrarely, we argue that some images should'nt be taken as a cover because of the nature of their signal.
+Contrarely, we argue that some images should not be taken as a cover because of the nature of their signal.

 Consider for instance a uniformly black image: a very tiny modification of its pixels can be easily detectable.  
 The approach we propose is thus to provide a self adaptive algorithm with a high payload, which depends on the 
 cover signal.
 Consider for instance a uniformly black image: a very tiny modification of its pixels can be easily detectable.  
 The approach we propose is thus to provide a self adaptive algorithm with a high payload, which depends on the 
 cover signal.

diff --git a/main.tex b/main.tex
index 2a0860242a9c2ee9731649bc932be45994f66e6b..15b67a43d6d3358f4b6d316015490b1bebf1a6e9 100755 (executable)
--- a/main.tex
+++ b/main.tex
@@ -21,6 +21,7 @@ a lightweight stego-secure edge-base steganography approach}
 * Authors in alphabetic order.\\
 }
 \newcommand{\JFC}[1]{\begin{color}{green}\textit{#1}\end{color}}
 * Authors in alphabetic order.\\
 }
 \newcommand{\JFC}[1]{\begin{color}{green}\textit{#1}\end{color}}

+\newcommand{\RC}[1]{\begin{color}{red}\textit{#1}\end{color}}

 % make the title area
 \maketitle
 
 % make the title area
 \maketitle
 

diff --git a/ourapproach.tex b/ourapproach.tex
index 9626562e8cce5ff743db4e9ee4b374deb7988a65..ccd297b623739e90dec957e0757f307fd97587cc 100644 (file)
--- a/ourapproach.tex
+++ b/ourapproach.tex
@@ -43,7 +43,21 @@ 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}
 \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
 
 Presentation des algos de detection de contour
 Caractéristiques


@@ -68,4 +82,4 @@ BBS-based cryptographic version of the message
 \input{stc}
 
 
 \input{stc}
 
 

-\subsection{Data Extraction}
\ No newline at end of file
+\subsection{Data Extraction}