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[canny.git] / intro.tex

diff --git a/intro.tex b/intro.tex
index deecdb76e25e766a4216967ba442cf57c92f0f81..ccdad7553ea62011f2c5604748df74a925531391 100644 (file)
--- a/intro.tex
+++ b/intro.tex
@@ -5,21 +5,21 @@ It belongs to the well-known large category
 of spatial least significant bits (LSBs) replacement schemes.
 Let us recall that, in this LSBR category, a subset of all the LSBs of the cover image is modified 
 with a secret bit stream depending on: a secret key, the cover, and the message to embed.
 of spatial least significant bits (LSBs) replacement schemes.
 Let us recall that, in this LSBR category, a subset of all the LSBs of the cover image is modified 
 with a secret bit stream depending on: a secret key, the cover, and the message to embed.

-In this well studied steganographic approach,
+In this well-studied steganographic approach,

 if we consider that a LSB is the last bit of each pixel value,  
 pixels with an even value (resp. an odd value) 
 are never decreased (resp. increased), 
 thus such schemes may break the 
 structural symmetry of the host images.
 And these structural alterations can be detected by 
 if we consider that a LSB is the last bit of each pixel value,  
 pixels with an even value (resp. an odd value) 
 are never decreased (resp. increased), 
 thus such schemes may break the 
 structural symmetry of the host images.
 And these structural alterations can be detected by 

-well designed statistical investigations, leading to known steganalysis methods~\cite{DBLP:journals/tsp/DumitrescuWW03,DBLP:conf/mmsec/FridrichGD01,Dumitrescu:2005:LSB:1073170.1073176}.
+well-designed statistical investigations, leading to known steganalysis methods~\cite{DBLP:journals/tsp/DumitrescuWW03,DBLP:conf/mmsec/FridrichGD01,Dumitrescu:2005:LSB:1073170.1073176}.

 
 Let us recall too that this drawback 
 can be corrected considering the LSB matching (LSBM) subcategory, in which
 the $+1$ or $-1$ is randomly added to the cover pixel LSB value 
 only if this one does not correspond to the secret bit.
 %TODO : modifier ceci
 
 Let us recall too that this drawback 
 can be corrected considering the LSB matching (LSBM) subcategory, in which
 the $+1$ or $-1$ is randomly added to the cover pixel LSB value 
 only if this one does not correspond to the secret bit.
 %TODO : modifier ceci

-Since it is possible to make that probabilities of increasing or decreasing the pixel value, for instance by considering well encrypted hidden messages, usual statistical approaches 
+Since it is possible to make that probabilities of increasing or decreasing the pixel value, for instance by considering well-encrypted hidden messages, usual statistical approaches 

 cannot be applied here to discover stego-contents in LSBM.
 The most accurate detectors for this matching are universal steganalysers such as~\cite{LHS08,DBLP:conf/ih/Ker05,FK12},
 which classify images according to extracted features from neighboring elements of residual noise.  
 cannot be applied here to discover stego-contents in LSBM.
 The most accurate detectors for this matching are universal steganalysers such as~\cite{LHS08,DBLP:conf/ih/Ker05,FK12},
 which classify images according to extracted features from neighboring elements of residual noise.  


@@ -72,7 +72,7 @@ Edge based steganographic schemes have already been  studied,
 the most interesting 
 approaches being detailed in~\cite{Luo:2010:EAI:1824719.1824720} and 
 in~\cite{DBLP:journals/eswa/ChenCL10}.
 the most interesting 
 approaches being detailed in~\cite{Luo:2010:EAI:1824719.1824720} and 
 in~\cite{DBLP:journals/eswa/ChenCL10}.

-In the former, the authors presents the Edge Adaptive
+In the former, the authors present the Edge Adaptive

 Image Steganography based on LSB matching revisited further denoted as to 
 EAISLSBMR. This approach selects sharper edge
  regions with respect 
 Image Steganography based on LSB matching revisited further denoted as to 
 EAISLSBMR. This approach selects sharper edge
  regions with respect 


@@ -83,7 +83,7 @@ The authors show that their proposed method is more efficient than all the LSB,
 thanks to extensive experiments.
 However, it has been shown that the distinguishing error with LSB embedding is lower than 
 the one with some binary embedding~\cite{DBLP:journals/tifs/FillerJF11}.
 thanks to extensive experiments.
 However, it has been shown that the distinguishing error with LSB embedding is lower than 
 the one with some binary embedding~\cite{DBLP:journals/tifs/FillerJF11}.

-We thus propose to take benefit of these optimized embedding, provided they are not too time consuming.
+We thus propose to take benefit of these optimized embeddings, provided they are not too time consuming.

 In the latter, an hybrid edge detector is presented followed by an ad hoc
 embedding. 
 The Edge detection is computed by combining fuzzy logic~\cite{Tyan1993} 
 In the latter, an hybrid edge detector is presented followed by an ad hoc
 embedding. 
 The Edge detection is computed by combining fuzzy logic~\cite{Tyan1993} 


@@ -96,7 +96,7 @@ schemes~\cite{Luo:2010:EAI:1824719.1824720,DBLP:journals/eswa/ChenCL10,DBLP:conf
 produce stego contents 
 by 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 contents 
 by only considering the payload, not the type of image signal: the higher the payload is, 
 the better the approach is said to be. 

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

 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. 
 % Message extraction is achieved by computing the same
 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. 
 % Message extraction is achieved by computing the same


@@ -113,7 +113,7 @@ even in the worst case scenario, the attacker
 will not be able to obtain the original message content.
 Doing so makes our steganographic protocol, to a certain extend, an asymmetric one.
 
 will not be able to obtain the original message content.
 Doing so makes our steganographic protocol, to a certain extend, an asymmetric one.
 

-To sum up, in this research work, well studied and experimented
+To sum up, in this research work, well-studied and experimented

 techniques of signal processing (adaptive edges detection), 
 coding theory (syndrome-trellis codes), and cryptography 
 (Blum-Goldwasser encryption protocol) are combined 
 techniques of signal processing (adaptive edges detection), 
 coding theory (syndrome-trellis codes), and cryptography 
 (Blum-Goldwasser encryption protocol) are combined 


@@ -124,7 +124,7 @@ consideration the cover image and to be compatible with small computation resour
 The remainder of this document is organized as follows. 
 Section~\ref{sec:ourapproach} presents the details of the proposed steganographic scheme and applies it on a running example.
 Section~\ref{sec:experiments} shows experiments on image quality, steganalytic evaluation, complexity of our approach,
 The remainder of this document is organized as follows. 
 Section~\ref{sec:ourapproach} presents the details of the proposed steganographic scheme and applies it on a running example.
 Section~\ref{sec:experiments} shows experiments on image quality, steganalytic evaluation, complexity of our approach,

-and compares it to the state of the art steganographic schemes.
+and compare them to the state of the art steganographic schemes.

 Finally, concluding notes and future work are given in Section~\ref{sec:concl}.
 
 
 Finally, concluding notes and future work are given in Section~\ref{sec:concl}.