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{\scriptsize \bf 06/06}
\vspace{4ex}

\centerline{\Huge\bf Results}
\vspace{1cm}

\Large
\begin{itemize}

\item Object separation
\begin{itemize}
 \item Sobel edge detector is used; insensitive of noises
 \item colour depth is decreased for thinning 
 \item filling the objects is not implemented because the results are not 
      recognizable even for a human
 \item object separation outputs starting point, width and height of the objects
\end{itemize}
\vspace{0.5cm}

\item Feature space transformation
\begin{itemize}
 \item idea of tomograph applied to pictures
 \item first 16 even frequences are probably enough for signal characterization
 \item transforming feature space to activation: exponential scale factor (base 2)
\end{itemize}
\vspace{0.5cm}

\item Hopfield network
\begin{itemize}
 \item data size grows very fast ($16\times16$ neurons $\rightarrow$ 32670 Connections!)
 \item probably very many learning cycles to reach a stable state
 \item much experimentation necessary
\end{itemize}
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\end{itemize}
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