X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/canny.git/blobdiff_plain/16874923aed7a3bc8380a6041e5c6b3d82f5683c..c6d3dd0e0b8e5c982b6a8d28649ab4079666815d:/ourapproach.tex?ds=inline diff --git a/ourapproach.tex b/ourapproach.tex index fc22e8f..4099700 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] @@ -42,10 +42,10 @@ scheme. \subsubsection{Edge Based Image Steganography} -Edge Based Image Steganography schemes -already studied~\cite{Luo:2010:EAI:1824719.1824720,DBLP:journals/eswa/ChenCL10} differ -how they select edge pixels, and -how they modify these ones. +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. @@ -53,9 +53,11 @@ Image Quality: Edge Image Steganography 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 +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.