Beginnetje van plan van aanpak

plan.tex

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