ajout d'experiments

diff --git a/biblio.bib b/biblio.bib
index 2ddab01ce654eb78e41cc63d0db3f55e281694f5..ba246075d9a4f97c4aa3117728bb9f9fbbcfb2e8 100644 (file)
--- a/biblio.bib
+++ b/biblio.bib
@@ -474,4 +474,106 @@ author    = {Jessica J. Fridrich and
  acmid = {2333587},
  publisher = {IEEE Press},
  address = {Piscataway, NJ, USA},
  acmid = {2333587},
  publisher = {IEEE Press},
  address = {Piscataway, NJ, USA},

-} 
\ No newline at end of file
+} 
+
+
+@inproceedings{Tyan1993,
+    abstract = {{Novel algorithms for image enhancement, filtering and edge detection using the fuzzy logic approach are proposed. An enhancement technique based on various combinations of fuzzy logic linguistic statements in the form of if-then rules modifies the image contrast and provides a linguistic approach to image enhancement. A fuzzy filtering technique based on the tuning of fuzzy membership functions in the frequency domain results in improved restoration of an image which is degraded by additive random noise. An improved performance compared with traditional mask convolution filtering is also evident from the SNR improvement of 4.03 dB. The fuzzy edge detection algorithm provides a variety of edge information. The fuzzy edge detection algorithm is compared with some existing edge detection algorithms to show its novelty}},
+    address = {{San Francisco, CA, USA}},
+    author = {Tyan, C. Y. and Wang, P. P.},
+    booktitle = {{Proceedings of the Second IEEE International Conference on Fuzzy Systems}},
+    citeulike-article-id = {7936501},
+    keywords = {additive, and, approach, computational, detection, domain, edge, enhancement, filtering, frequency, functions, fuzzy, if-then, image, linguistic, linguistics, logic, membership, noise, prediction, processing, random, restoration, rules, set, statements, theory},
+    pages = {600--605},
+    posted-at = {2010-10-01 17:27:48},
+    priority = {0},
+    title = {{Image processing-enhancement, filtering and edge detection using the fuzzy logic approach}},
+    volume = {1},
+    year = {1993}
+}
+
+
+@article{Canny:1986:CAE:11274.11275,
+ author = {Canny, J},
+ title = {A Computational Approach to Edge Detection},
+ journal = {IEEE Trans. Pattern Anal. Mach. Intell.},
+ issue_date = {June 1986},
+ volume = {8},
+ number = {6},
+ month = jun,
+ year = {1986},
+ issn = {0162-8828},
+ pages = {679--698},
+ numpages = {20},
+ url = {http://dx.doi.org/10.1109/TPAMI.1986.4767851},
+ doi = {10.1109/TPAMI.1986.4767851},
+ acmid = {11275},
+ publisher = {IEEE Computer Society},
+ address = {Washington, DC, USA},
+ keywords = {Edge detection, feature extraction, image processing, machine vision, multiscale image analysis},
+} 
+
+
+@inproceedings{DBLP:conf/ih/FridrichKHG11a,
+  author    = {Jessica J. Fridrich and
+               Jan Kodovsk{\'y} and
+               Vojtech Holub and
+               Miroslav Goljan},
+  title     = {Steganalysis of Content-Adaptive Steganography in Spatial
+               Domain},
+  booktitle = {Information Hiding},
+  year      = {2011},
+  pages     = {102-117},
+  ee        = {http://dx.doi.org/10.1007/978-3-642-24178-9_8},
+  crossref  = {DBLP:conf/ih/2011},
+  bibsource = {DBLP, http://dblp.uni-trier.de}
+}
+@proceedings{DBLP:conf/ih/2011,
+  editor    = {Tom{\'a}s Filler and
+               Tom{\'a}s Pevn{\'y} and
+               Scott Craver and
+               Andrew D. Ker},
+  title     = {Information Hiding - 13th International Conference, IH 2011,
+               Prague, Czech Republic, May 18-20, 2011, Revised Selected
+               Papers},
+  booktitle = {Information Hiding},
+  publisher = {Springer},
+  series    = {Lecture Notes in Computer Science},
+  volume    = {6958},
+  year      = {2011},
+  isbn      = {978-3-642-24177-2},
+  ee        = {http://dx.doi.org/10.1007/978-3-642-24178-9},
+  bibsource = {DBLP, http://dblp.uni-trier.de}
+}
+
+@inproceedings{DBLP:conf/iwdw/Fridrich11,
+  author    = {Jessica J. Fridrich},
+  title     = {Modern Trends in Steganography and Steganalysis},
+  booktitle = {IWDW},
+  year      = {2011},
+  pages     = {1},
+  ee        = {http://dx.doi.org/10.1007/978-3-642-32205-1_1},
+  crossref  = {DBLP:conf/iwdw/2011},
+  bibsource = {DBLP, http://dblp.uni-trier.de}
+}
+@proceedings{DBLP:conf/iwdw/2011,
+  editor    = {Yun-Qing Shi and
+               Hyoung-Joong Kim and
+               Fernando P{\'e}rez-Gonz{\'a}lez},
+  title     = {Digital Forensics and Watermarking - 10th International
+               Workshop, IWDW 2011, Atlantic City, NJ, USA, October 23-26,
+               2011, Revised Selected Papers},
+  booktitle = {IWDW},
+  publisher = {Springer},
+  series    = {Lecture Notes in Computer Science},
+  volume    = {7128},
+  year      = {2012},
+  isbn      = {978-3-642-32204-4},
+  ee        = {http://dx.doi.org/10.1007/978-3-642-32205-1},
+  bibsource = {DBLP, http://dblp.uni-trier.de}
+}
+
+
+
+
+

diff --git a/experiments.tex b/experiments.tex
index 60b0f2f45b628e206ca7836a337d6a529428cb45..cf8dfa6119530cb9ba1f6c718f7de663d6ef395d 100644 (file)
--- a/experiments.tex
+++ b/experiments.tex
@@ -1,6 +1,17 @@
 \subsection{Steganalysis}
 
 
 \subsection{Steganalysis}
 
 

-Détailler \cite{Fillatre:2012:ASL:2333143.2333587}

 
 

-Vainqueur du BOSS challenge~\cite{DBLP:journals/tifs/KodovskyFH12}
+The quality of our approach has been evaluated through the two 
+AUMP~\cite{Fillatre:2012:ASL:2333143.2333587}
+and Ensemble Classifier~\cite{DBLP:journals/tifs/KodovskyFH12} based steganalysers.
+Both aims at detecting hidden bits in grayscale natural images and are 
+considered as the state of the art of steganalysers in spatial domain~\cite{FK12}.
+The former approach is based on a simplified parametric model of natural images.
+Parameters are firstly estimated and a adaptive Asymptotically Uniformly Most Powerful
+(AUMP) test is designed (theoretically and practically) to check whether
+a natural image has stego content or not.  
+In the latter, the authors show that the 
+machine learning step, (which is often
+implemented as support vector machine)
+can be a favourably executed thanks to an Ensemble Classifiers.

diff --git a/intro.tex b/intro.tex
index 54b59e22a035981495cfd38843b811de061865b6..16e8c8b6d6dd236433c3d4e770f263f79587878f 100644 (file)
--- a/intro.tex
+++ b/intro.tex
@@ -49,7 +49,8 @@ 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
 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.
+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. 
 
 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. 


@@ -65,17 +66,37 @@ to embedding rate: the larger the number of bits to be embedded, the coarse the
 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.
 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}.
+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.
 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....}. 
+In the latter, an hybrid edge detector is presented followed by an ad'hoc
+embedding approach. 
+The Edge detection is computed by combining fuzzy 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. 
+
+
+But, one can notice that all the previous referenced 
+schemes~\cite{Luo:2010:EAI:1824719.1824720,DBLP:journals/eswa/ChenCL10,DBLP:conf/ih/PevnyFB10}
+produce stego content 
+with only considering the payload, not the type of image signal: the higher the payload is, 
+the better the approach is said to be. 
+Contrarely, we argue that some images should'nt be taken as a cover because of the nature of their signal.
+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.
+

  
 
 \JFC{Christophe : énoncer la problématique du besoin de crypto et de ``cryptographiquement sûr'',  les algo déjà cassés....
 l'efficacité d'un encodage/décodage ...} 
  
 
 \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 
+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.  
+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, which takes into consideration the cover image 
+an which 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.
 
 The rest of the paper is organised as follows. 
 Section~\ref{sec:ourapproach} presents the details of our steganographic scheme.

diff --git a/stc.tex b/stc.tex
index e8c695cf1a3963369fa61f56df0c1abe0b4d369f..7ce100b8be84e7d3623b727a49ae7755b84b6e4f 100644 (file)
--- a/stc.tex
+++ b/stc.tex
@@ -77,6 +77,6 @@ Next, the  process of finding $y$ consists of a forward and a backward part:
 \item Backward determinization of $y$ which minimizes $D$ starting with 
 the complete path with minimal weight
 \end{enumerate} 
 \item Backward determinization of $y$ which minimizes $D$ starting with 
 the complete path with minimal weight
 \end{enumerate} 

-Let us now give some details about these two parts.
+