From: couchot Date: Tue, 8 Jan 2013 09:08:29 +0000 (+0100) Subject: tarata X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/canny.git/commitdiff_plain/e1408e22528148d27bf1cc1edc56764345c64cba tarata --- diff --git a/experiments.tex b/experiments.tex index 45f0b87..cd2ed1a 100644 --- a/experiments.tex +++ b/experiments.tex @@ -9,7 +9,7 @@ Practically, a set of edge pixels is computed according to the Canny algorithm with high threshold. The message length is thus defined to be the half of this set cardinality. The rate between available bits and bit message length is then more than two.This constraint is indeed induced by the fact that the efficiency -of the stc algorithm is unsatisfactory under that threshold. +of the STC algorithm is unsatisfactory under that threshold. In the latter, the embedding rate is defined as a percentage between the @@ -18,7 +18,7 @@ This is the classical approach adopted in steganography. Practically, the Canny algorithm generates a a set of edge pixels with threshold that is decreasing until its cardinality is sufficient. If the set cardinality is more than twice larger than the -bit message length an stc is again applied. +bit message length an STC step is again applied. Otherwise, pixels are randomly chosen from the set of pixels to build the subset with a given size. The BBS PRNG is again applied there. @@ -27,7 +27,7 @@ subset with a given size. The BBS PRNG is again applied there. \subsection{Image Quality} The visual quality of the STABYLO scheme is evaluated in this section. -Four metrics are computed in these experiments : +Four metrics are computed in these experiments: the Peak Signal to Noise Ratio (PSNR), the PSNR-HVS-M family~\cite{PSECAL07,psnrhvsm11} , the BIQI~\cite{MB10,biqi11} and @@ -61,9 +61,9 @@ schemes with respect to the image quality. Fist off all, wPSNR and PSNR of the Edge Adaptive scheme detailed in~\cite{Luo:2010:EAI:1824719.1824720} are lower than ours. Next both the approaches~\cite{DBLP:journals/eswa/ChenCL10,Chang20101286} -focus on increasing the payload while the PSNR is acceptable, bu do not +focus on increasing the payload while the PSNR is acceptable, but do not give quality metrics for fixed embedding rate from a large base of images. -Our approach outperforms the former thanks to the introduction of the stc +Our approach outperforms the former thanks to the introduction of the STC algorithm. @@ -97,7 +97,7 @@ Embedding rate & Adaptive & 10 \% & 10 \%\\ \hline AUMP & 0.39 & 0.22 & 0.50 \\ \hline -Ensemble Classifier & & & \\ +Ensemble Classifier & 0.47 & 0.35 & 0.48 \\ \hline \end{tabular} diff --git a/intro.tex b/intro.tex index 745751f..f69d926 100644 --- a/intro.tex +++ b/intro.tex @@ -62,7 +62,8 @@ Our proposal is thus to embed message bits into edge shapes while preserving oth 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. +to embedding rate: the larger the number of bits to be embedded, the coarser +the edge regions are. Then the data hiding algorithm is achieved by applying LSBMR on pixels of this region. The authors show that this method is more efficient than all the LSB, LSBM, LSBMR approaches thanks to extensive experiments. 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 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 :-)} +\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 +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}