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Taddeüs Kroes
licenseplates
Commits
16018f03
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16018f03
authored
13 years ago
by
Richard Torenvliet
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16018f03
...
@@ -480,9 +480,7 @@ classification and the accuracy. In this section we will show our findings.
...
@@ -480,9 +480,7 @@ classification and the accuracy. In this section we will show our findings.
Of course, it is vital that the recognition of a license plate is correct,
Of course, it is vital that the recognition of a license plate is correct,
almost correct is not good enough here. Therefore, we have to get the highest
almost correct is not good enough here. Therefore, we have to get the highest
accuracy score we possibly can.
\\
accuracy score we possibly can.
\\
\\
According to Wikipedia
\\
According to Wikipedia
\cite
{
wikiplate
}
\footnote
{
\url
{
http://en.wikipedia.org/wiki/Automatic
_
number
_
plate
_
recognition
}}
,
commercial license plate recognition software score about
$
90
\%
$
to
$
94
\%
$
,
commercial license plate recognition software score about
$
90
\%
$
to
$
94
\%
$
,
under optimal conditions and with modern equipment.
\\
under optimal conditions and with modern equipment.
\\
\\
\\
...
@@ -601,6 +599,33 @@ to help out. Further communication usually went through e-mails and replies
...
@@ -601,6 +599,33 @@ to help out. Further communication usually went through e-mails and replies
were instantaneous! A crew to remember.
were instantaneous! A crew to remember.
\section
{
Discussion
}
\section
{
Discussion
}
We had some good results but of course there are more things to explore.
For instance we did a research on three different patterns. There are more patterns
to try. For instane we only tried (8,3)-, (8,5)- and (12,5). The interesting to
do is to test which pattern gives the best result. This is also done by grid-
searching, changing the size of circle and the amount of neighbours.
One important feature of our framework is that the LBP class can be changed by
an other technique. This may be a different algorithm than LBP. Also the classifier
can be changed in an other classifier. By applying these kind of changes we can
find the best way to recognize licence plates.
We don't do assumption when a letter is recognized. For instance dutch licence plates
exist of three blocks, two digits or two characters. Or for the new licence plates
there are three blocks, two digits followed by three characters, followed by one or
two digits. The assumption we can do is when there is have a case when one digit
is moste likely to follow by a second digit and not a character. Maybe these assumption
can help in future research to achieve a higher accuracy rate.
\appendix
\section
{
Faulty Classifications
}
\begin{figure}
[H]
\center
\includegraphics
[scale=0.5]
{
faulty.png
}
\caption
{
Faulty classifications of characters
}
\end{figure}
\end{document}
\begin{thebibliography}
{
9
}
\begin{thebibliography}
{
9
}
...
@@ -617,12 +642,3 @@ were instantaneous! A crew to remember.
...
@@ -617,12 +642,3 @@ were instantaneous! A crew to remember.
Retrieved from http://en.wikipedia.org/wiki/Automatic
\_
number
\_
plate
\_
recognition
Retrieved from http://en.wikipedia.org/wiki/Automatic
\_
number
\_
plate
\_
recognition
\end{thebibliography}
\end{thebibliography}
\appendix
\section
{
Faulty Classifications
}
\begin{figure}
[H]
\center
\includegraphics
[scale=0.5]
{
faulty.png
}
\caption
{
Faulty classifications of characters
}
\end{figure}
\end{document}
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