+
+This work considers digital images as covers and foundation is
+spatial least significant-bit (LSB) replacement.
+I 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.
+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
+and thus by steganalysis methods~\cite{DBLP:journals/tsp/DumitrescuWW03,DBLP:conf/mmsec/FridrichGD01,Dumitrescu:2005:LSB:1073170.1073176}
+
+This drawback is avoided in LSB matching (LSBM) where
+the $+1$ or $-1$ is randomly added to the cover pixel LSB value
+only if this one does not match the secret bit.
+Since probabilities of increasing or decreasing pixel value are the same, statistical approaches
+cannot be applied there to discover stego-images in LSBM.
+The most accurate detectors for this matching are universal steganalysers such as~\cite{LHS08,DBLP:conf/ih/2005,FK12}
+which classify images thanks to extracted features from neighboring elements of noise residual.
+
+LSB matching revisited (LSBMR)~\cite{Mielikainen06} have been recently introduced.
+This scheme deals with pairs of pixels instead of individual ones.
+It thus allows to decrease the number of modified bits per cover pixel
+for the same payload compared to LSB replacement and LSBM and
+and avoids the LSB replacement style asymmetry. Unfortunately,
+detectors referenced above are able to distinguish between
+stego content images and cover images.
+
+Instead of (efficiently) modifying LSBs, there is also a need to select pixels whose value
+modification minimizes a distortion function.
+This distortion may be computed thanks to feature vectors that are embedded for instance in steganalysers
+given above.
+Highly Undetectable steGO (HUGO) method~\cite{DBLP:conf/ih/PevnyFB10} is one of the most efficient instance of such a scheme.
+It takes into account SPAM features (whose size is larger than $10^7$) to avoid overfitting a particular
+steganalyser. Thus a distortion measure for each pixel is individually determined as the sum of differences between
+features of SPAM computed from the cover and from the stego images.
+Thanks to this feature set, HUGO allows to embed $7\times$ longer messages with the same level of
+indetectability than LSB matching.
+However, this improvement is time consuming, mainly due to the distortion function
+computation.
+
+There remains a large place between random selection of LSB and feature based modification of pixel values.
+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
+pixels. In other words, minor changes in regular area is 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 bee 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.
+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.
+However, it has been shown that the distinguish error with LSB embedding is fewer than the one with some binary embedding~\cite{DBLP:journals/tifs/FillerJF11}.
+We thus propose to take benefit of these optimized embedding, provided it is not too time consuming.
+Experiments have confirmed such a fact\JFC{Raphael....}.
+
+
+\JFC{Christophe : énoncer la problématique du besoin de crypto et de ``cryptographiquement sûr'', les algo déjà cassés....
+l'efficacité d'un encodage/décodage ...}
+To deal with security issues, message is encrypted
+
+In this paper, we thus propose to combine tried and tested techniques of signal theory (the adaptive edge detection), coding (the binary embedding), and cryptography
+(the encrypt the message) to compute an efficient steganography scheme that is amenable to be executed on small devices.
+
+The rest of the paper is organised as follows.
+Section~\ref{sec:ourapproach} presents the details of our steganographic scheme.
+Section~\ref{sec:experiments} shows experiments on image quality, steganalytic evaluation, complexity of our approach
+and compare them to state of the art steganographic schemes.
+Finally, concluding notes and future works are given in section~\ref{sec:concl}
+
+theory : ?
+
+
+
