\HeaderA{segment}{Segmentation and edge detection}{segment}
\aliasA{edge}{segment}{edge}
\aliasA{edge,Image-method}{segment}{edge,Image.Rdash.method}
\aliasA{segment,Image-method}{segment}{segment,Image.Rdash.method}
\keyword{manip}{segment}
\begin{Description}\relax
Fucntions to segment images and detect edges.
\end{Description}
\begin{Usage}
\begin{verbatim}
  ## S4 method for signature 'Image':
  edge(x, r=0, ...)
  ## S4 method for signature 'Image':
  segment(x, cl=10, s=1.5, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{x}] An object of \code{\LinkA{Image}{Image.Rdash.class}}. 
\item[\code{r}] The radius of the pixel neighbourhood to take into account. 
The 0 value enables automatic radius selection. 
\item[\code{cl}] Minimum cluster size in pixels . 
\item[\code{s}] The smoothing threshold. 
\item[\code{...}] Reserved. 
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
\code{edge} returns an image of edges between different colours in the 
original image. Most effective on binary images.

\code{segment} segment an image by analyzing the histograms of the color 
components and identifying units that are homogeneous with the fuzzy 
C-means technique (source and implementation \code{ImageMagick}). The
smoothing threshold eliminates noise in the second derivative of the 
histogram. As the value is increased, you can expect a smoother second
derivative.
\end{Details}
\begin{Value}
A transformed image in an object of \code{\LinkA{Image}{Image.Rdash.class}}.
\end{Value}
\begin{Author}\relax
Oleg Sklyar, \email{osklyar@ebi.ac.uk}, 2005-2006
\end{Author}
\begin{References}\relax
\emph{ImageMagick}: \url{http://www.imagemagick.org}.
\end{References}
\begin{SeeAlso}\relax
\code{
  \LinkA{Image}{Image.Rdash.class}
}
\end{SeeAlso}

