X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/canny.git/blobdiff_plain/fdf9d8855582d89072dcd1339af9f5b74a167ac6..f919ede766f1129e330f7d12d04ed3e8ca8111b0:/intro.tex?ds=inline

diff --git a/intro.tex b/intro.tex
index 745751f..18ea7ab 100644
--- a/intro.tex
+++ b/intro.tex
@@ -1,8 +1,8 @@
 
-This work considers digital images as covers and foundation is
+This work considers digital images as covers and it is based on
 spatial least significant-bit (LSB) replacement.
 In this data hiding scheme a subset of all the LSB of the cover image is modified 
-with a secret bit stream depending on to a key, the cover, and the message to embed.
+with a secret bit stream depending on a key, the cover, and the message to embed.
 This well studied steganographic approach  never decreases (resp. increases)
 pixel with even value (resp. odd value) and may break structural symmetry.
 These structural modification can be detected  by statistical approaches 
@@ -56,13 +56,14 @@ There remains a large place between random selection of LSB and feature based mo
 We argue that modifying edge pixels is an acceptable compromise. 
 Edges form the outline of an object: they are the boundary between overlapping objects or between an object
 and the background. A small modification of pixel value in the stego image should not be harmful to the image quality:
-in cover image, edge pixels already break its continuity  and thus already contains large variation with neighbouring 
+in cover image, edge pixels already break its continuity  and thus already contain large variation with neighbouring 
 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 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.