Added description on fautly classifications.

docs/report.tex

@@ -204,7 +204,8 @@ In our case the support vector machine uses a radial gauss kernel function. The
 \section{Implementation}
 
 In this section we will describe our implementation in more detail, explaining
-the choices we made in the process.
+the choices we made in the process. We spent a lot of attention on structuring
+the code in such a fashion that it can easily be extended.
 
 \subsection{Character retrieval}
 
@@ -528,6 +529,27 @@ grid-searches, finding more exact values for $c$ and $\gamma$, more tests
 for finding $\sigma$ and more experiments on the size and shape of the
 neighbourhoods.
 
+\subsubsection*{Faulty classified characters}
+
+As we do not have a $100\%$ score, it is interesting to see what characters are
+classified wrong. These characters are shown in appendix \ref{faucla}. Most of
+these errors are easily explained. For example, some 0's are classified as
+'D', some 1's are classified as 'T' and some 'F's are classified as 'E'.
+
+Of course, these are not as interesting as some of the weird matches. For
+example, a 'P' is classified as 7. However, if we look more closely, the 'P' is
+standing diagonal, possibly because the datapoints where not very exact in the
+XML file. This creates a large diagonal line in the image, which explains why
+this can be classified as a 7. The same has happened with a 'T', which is also
+marked as 7.
+
+Other strange matches include a 'Z' as a 9, but
+this character has a lot of noise surrounding it, which makes classification
+harder, and a 3 that is classified as 9, where the exact opposite is the case.
+This plate has no noise, due to which the background is a large area of equal
+color. This might cause the classification to focus more on this than on the
+actual character.
+
 \subsection{Speed}
 
 Recognizing license plates is something that has to be done fast, since there
@@ -689,12 +711,13 @@ were instantaneous! A crew to remember.
 
 \appendix
 
-\section{Faulty Classifications}
+\section{Faulty classified characters}
+\label{faucla}
 
 \begin{figure}[H]
     \hspace{-2cm}
     \includegraphics[scale=0.5]{faulty.png}
-    \caption{Faulty classifications of characters}
+    \caption{Faulty classificatied characters}
 \end{figure}
 
 \begin{thebibliography}{9}