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+\documentclass[a4paper]{article}
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+
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+\title{Teaching a computer to learn, find and read licence plates}
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+\date{November 17th, 2011}
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+
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+\begin{document}
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+\maketitle
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+
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+\section*{Project members}
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+Gijs van der Voort\\Richard Torenvliet\\Jayke Meijer\\Tadde\"us Kroes\\Fabi\'en Tesselaar
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+
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+\tableofcontents
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+\setcounter{secnumdepth}{1}
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+
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+\section{Introduction}
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+
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+Licence plates are used all over the world. The plates are, usually, attached to the front and rear
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+of a motorised vehicle and used for indentifying this vehicle. Every
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+country can have more or less its own version of a licence plate, but all these systems do not
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+differ greatly. We will be focusing on the dutch system for licence plates.
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+
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+\section{Problem Description}
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+
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+License plates are used for indentification and thus made to recognize from great
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+distances and still be seen in many weather conditions. Our learning set of photos contains
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+''' ik weet niet precies wat voor camera ''. The angle in which these pictures are taken or the angle
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+of the approaching vehicles are always different and some licence plates are a bit dirty,
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+but for a human they are still pretty easy to indentify. A computer or perhaps a small
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+chipset will need to be thourougly practiced. In short our program must be able to
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+do the following:
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+
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+\begin{itemize}
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+\item Find the location of the license plate.
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+\item Use transformations so it gets an upfront view.
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+\item Reduce noise where possible.
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+\item Get the locations of each letter and extracting it.
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+\item Apply a local binary pattern algorithm on each letter.
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+\item Matching the found patterns with found results and return the best match.
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+\end{itemize}
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+
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+\section{Solution}
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+
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+Now that we know the problem we can start with stating our solution. This will
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+come in a few steps aswell.
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+
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+\subsection{Localizing the plate}
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+
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+The photos are of very high contrast. Most of the time only the lights of a vehicle
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+are visible in addition to the license plate. We can first crop the image untill
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+it finds brighter pixel values in a row or column. Then we can apply ''?? weet niet hoor'' local histogram
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+matching to find out whether we have a light or license plate.
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+
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+\subsection{Transformations}
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+
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+Affine transformations will do the trick
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+
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+\subsection{Reducing noise}
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+
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+Weet niet precies hoe, maar van die kleine rondjes / vlekjes / stipjes moeten
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+we wel een beetje weghalen want die maken het wel een beetje lelijk
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+
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+\subsection{Extracting a letter}
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+
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+De karakteristiek bepalen van het dash/streepje (-) dan heb je in elk geval al
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+drie groepen met maar 1 of 2 letters (ws 2). Hier kun je volgens mij dan wel
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+makkelijk zoeken op een overgang van letter naar andere letter omdat er stuk
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+white-space tussenzit
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+
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+\subsection{Local binary patterns}
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+
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+Hier moet een vrij groot verhaal omdat dit ons belangrijkste algoritme moet zijn
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+
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++ not sure if it will work out :o
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+
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+\subsection{Matching the database}
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+
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+Als we al die histogrammen opslaan, hoe gaan we dat slim met elkaar vergelijken
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+(of naja sneller dan brute force)
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+
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+
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+\section{Conclusion}
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+
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+This will be fun.
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+
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+\end{document}
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Tessmore