X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/canny.git/blobdiff_plain/b32ae50ac6a1fa30903bce7ee91e6e42c13ed3c6..80ed315cbcd8cb8806910d30bc116bfdb4f87fb8:/intro.tex?ds=sidebyside

diff --git a/intro.tex b/intro.tex
index cd2aeea..a13492f 100644
--- a/intro.tex
+++ b/intro.tex
@@ -16,7 +16,7 @@ steganalysis methods~\cite{DBLP:journals/tsp/DumitrescuWW03,DBLP:conf/mmsec/Frid
 
 Let us recall too that this drawback 
 can be fixed by considering the LSB matching (LSBM) subcategory, in which
-the $+1$ or $-1$ is randomly added to the cover pixel's LSB value 
+a $+1$ or $-1$ is randomly added to the cover pixel's LSB value 
 only if this one does not correspond to the secret bit.
 %TODO : modifier ceci
 By considering well-encrypted hidden messages, the probabilities of increasing or decreasing the value of pixels  are equal. Then usual statistical approaches 
@@ -60,15 +60,13 @@ The features embedded in WOW and UNIWARD are based on Wavelet-based
 directional filter. Thus, similarly, the distortion function is 
 the sum  of the differences between these wavelet coefficients  
 computed from the cover and from the stego images.
-
-
 Due to this distortion measures, HUGO, WOW and UNIWARD allow
 to embed messages that are $7$ times longer than the former
 ones with the same level of 
 indetectability as LSB matching. 
 However, this improvement has a larger computation cost, mainly due to
  the distortion function
-calculus. 
+computation.
 
 
 There remains a large place between random selection of LSB and feature based modification of pixel values.
@@ -98,7 +96,7 @@ the one with some binary embedding~\cite{DBLP:journals/tifs/FillerJF11}.
 We thus propose to take advantage of this optimized embedding, 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} 
+The Edge detection is computed by combining fuz\-zy logic~\cite{Tyan1993} 
 and Canny~\cite{Canny:1986:CAE:11274.11275} approaches. 
 The goal of this combination 
 is to enlarge the set of modified bits to increase the payload of the data hiding scheme. 
@@ -113,7 +111,7 @@ For instance, studied payloads range from 0.04 to 0.4 modified bits per pixel.
 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.
+pixels can be easily detected.
 Practically speaking, if Alice would send
 a hidden message to Bob, she would never consider
 such kind of image and a high embedding rate.   
@@ -126,7 +124,7 @@ The payload is further said to
 long message in the cover signal. 
 Practically speaking, our approach is efficient enough for
 payloads close to 0.06 bit per pixel which allows to embed 
-messages of length larger than 16000 bits in an 
+messages of length larger than 15,728 bits in an 
 image of size $512\times 512$ pixels. 
 
 % Message extraction is achieved by computing the same
@@ -143,12 +141,12 @@ 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.
 
-To sum up, in this research work, well-studied and experimented
+To sum up, well-studied and experimented
 techniques of signal processing (adaptive edges detection), 
 coding theory (syndrome-trellis codes), and cryptography 
-(Blum-Goldwasser encryption protocol) are combined 
-to compute an efficient steganographic
-scheme, whose principal characteristic is to take into 
+(Blum-Goldwas\-ser encryption protocol) are combined in this research work.
+The objective is to  compute an efficient steganographic
+sche\-me, whose principal characteristic is to take into 
 consideration the cover image and to be compatible with small computation resources.  
 
 The remainder of this document is organized as follows.