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@@ -206,11 +206,38 @@ choices we made.
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In order to retrieve the license plate from the entire image, we need to
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perform a perspective transformation. However, to do this, we need to know the
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coordinates of the four corners of the licenseplate. For our dataset, this is
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-stored in XML files. So, the first step is to read these XML files.\\
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-\\
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-\paragraph*{XML reader}
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+stored in XML files. So, the first step is to read these XML files.
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+\paragraph*{XML reader}
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+The XML reader will return a 'license plate' object when given an XML file. The
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+licence plate holds a list of, up to six, NormalizedImage characters and from which country the
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+plate is from. The reader is currently assuming the XML file and image name are corresponding. Since this was the case
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+for the given dataset. This can easily be adjusted if required.
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+
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+To parse the XML file, the minidom module is used. So the XML file can be
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+treated as a tree, where one can search for certain nodes. In each XML
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+file it is possible that multiple versions exist, so the first thing the reader will do is
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+retrieve the current and most up-to-date version of the plate. The reader will only get results from this
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+version.
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+
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+Now we are only interested in the individual characters so we can skip the location
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+of the entire license plate. Each character has
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+a single character value, indicating what someone thought what the letter or digit was and four coordinates to create
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+a bounding box. To make things not to complicated a
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+Character class and Point class are used. They
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+act pretty much as associative lists, but it gives extra freedom on using the
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+data. If less then four points have been set the character will not be saved.
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+
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+When four points have been gathered the data from the actual image is being requested.
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+For each corner a small margin is added (around 3 pixels) so that no features will be lost and minimum
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+amounts of new features will be introduced by noise in the margin.
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+
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+In the next section you can read more about the perspective transformation that is being done. After the transformation the
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+character can be saved: Converted to grayscale, but nothing further. This was used
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+to create a learning set. If it doesn't need to be saved as an actual image it will be converted
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+to a NormalizedImage. When these actions have been completed for each character the license
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+plate is usable in the rest of the code.
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\paragraph*{Perspective transformation}
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Once we retrieved the cornerpoints of the license plate, we feed those to a
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Fabien