From f96233fc65ad1523ba849069ed5b7daa8f5ef9b1 Mon Sep 17 00:00:00 2001
From: couchot <jf.couchot@gmail.com>
Date: Thu, 9 Jan 2014 21:25:15 +0100
Subject: [PATCH] style ante + complexite canny

---
 complexity.tex | 14 ++++++++------
 main.tex       | 14 +++++++-------
 2 files changed, 15 insertions(+), 13 deletions(-)

diff --git a/complexity.tex b/complexity.tex
index 6e108f8..4da4291 100644
--- a/complexity.tex
+++ b/complexity.tex
@@ -24,13 +24,15 @@ The overall complexity of the pixel selection is thus
 $O(n^2 +2.343^2 + 2\times 343^2 \times n^2 + 2.n^2 \ln(n))$, \textit{i.e}
 $O(2.n^2(343^2 + \ln(n)))$.
 
-Our edge selection is based on a Canny  Filter, 
-whose complexity is in $O(2n^2.\ln(n))$ thanks to the convolution step
-which can be implemented with FFT.
+Our edge selection is based on a Canny  Filter. When applied on a 
+$n \times n$ square image the Noise reduction steps is in $O(5^3 n^2)n$.
+Next, let $T$ be the size of the canny mask.
+Computing gradients is in $O(4Tn)$ since derivatives of each direction (vertical or horizontal) 
+are in $O(2Tn)$.
+Finally, thresholding with hysteresis is in $O(n^2)$.
+The overall complexity is thus in $O((5^3+4T+1)n^2)$.
 To summarize, for the embedding map construction, the complexity of Hugo is
-at least $343^2/\ln{n}$ times higher than 
-our scheme. For instance, for a squared image with 4M pixel per slide,
-this part of our algorithm is more than 14100 faster than Hugo.
+dramatically higher than our scheme.
 
 We are then left to express the complexity of the STC algorithm.
 According to~\cite{DBLP:journals/tifs/FillerJF11}, it  is 
diff --git a/main.tex b/main.tex
index e2b25ed..c4da7c3 100755
--- a/main.tex
+++ b/main.tex
@@ -1,4 +1,4 @@
-\documentclass{comjnl}
+\documentclass[twocolumn]{svjour3}          % twocolumn
 \usepackage{epsfig,psfrag}
 \usepackage{graphicx} 
 \usepackage{color}
@@ -38,20 +38,20 @@ Adaptive,  Bbs, and binarY embedding at LOw cost.}
 \author{Jean-Fran\c cois Couchot, Raphael Couturier, and  Christophe Guyeux\thanks{Authors in alphabetic order}}
 
 
-\affiliation{  FEMTO-ST Institute, UMR 6174 CNRS\\
+\institute{  FEMTO-ST Institute, UMR 6174 CNRS\\
   Computer Science Laboratory DISC,
   University of Franche-Comt\'{e},
   Besan\c con, France.}
 \email{\{jean-francois.couchot, raphael.couturier, christophe.guyeux\}@univ-fcomte.fr}
 
-\shortauthors{J.-F. Couchot, R. Couturier, and  C. Guyeux}
+
+\date{Received: date / Accepted: date}
+
 
 
 
 
 
-\received{...}
-\revised{...}
 
 
 
@@ -73,7 +73,7 @@ Adaptive,  Bbs, and binarY embedding at LOw cost.}
 
 
 
-
+\maketitle
 
 
 \begin{abstract}
@@ -92,7 +92,7 @@ coding theory, and cryptography are combined together, leading to
 a scheme that can reasonably face up-to-date steganalysers.
 \end{abstract}
 
-\maketitle
+
 
 
 
-- 
2.39.5