\JFC{Raphael, les fuzzy edge detection sont souvent utilisés.
il faudrait comparer les approches en terme de nombre de bits retournés,
en terme de complexité. } \cite{KF11}
-
+\RC{Ben, à voir car on peut choisir le nombre de pixel avec canny. Supposons que les fuzzy edge soient retourne un peu plus de points, on sera probablement plus détectable... Finalement on devrait surement vendre notre truc en : on a choisi cet algo car il est performant en vitesse/qualité. Mais on peut aussi en utilisé d'autres :-)}
+
+There are many techniques to detect edges in images. Main methods are filter
+edge detection methods such as Sobel or Canny filter, low order methods such as
+first order and second order methods, these methods are based on gradient or
+Laplace operators and fuzzy edge methods which are based on fuzzy logic to
+highlight edges.
+
+Of course, all the algorithms have advantages and drawbacks which depend on the
+motivation to highlight edges. Unfortunately unless testing most of the
+algorithms, which would require many times, it is quite difficult to have an
+accurate idea on what would produce such algorithm compared to another. That is
+why we have chosen canny algorithm which is well known, fast and implementable
+on many kinds of architecture, such as FPGA, smartphone, desktop machines and
+GPU. And of course, we do not pretend that this is the best solution.
Presentation des algos de detection de contour
Caractéristiques
\input{stc}
-\subsection{Data Extraction}
\ No newline at end of file
+\subsection{Data Extraction}
