The scripts which have been used to try and figure out a license plate from some IR over-illuminated shots. Full blog post on https://corstianboerman.com.

LicenseComparison.cs

void Main()
{
	StreamReader csvreader = new StreamReader(@"C:\Documents\subset.csv");
	var font = new Font("kenteken", 300, FontStyle.Regular, GraphicsUnit.Pixel, 0x00);

	Dictionary<String, double[]> results = new Dictionary<String, double[]>();

	var reference = new Bitmap(@"C:\Documents\reference.bmp");
	var normalizedRef = Normalize(reference);

	var lines = csvreader.ReadToEnd().Split('\r', '\n').Where(q => !String.IsNullOrWhiteSpace(q));

	foreach (var line in lines)
	{
		var license = line.Split(',')[0];
		var image = DrawText(license, font, Color.Black, Color.FromArgb(209, 178, 36));
		results.Add(license, Normalize(ResizeImage(image, 13, 3)));
	}
	
	List<double[]> nextCluster = new List<double[]>(results.Select(q => q.Value));
	
	var resultingClusterSize = 5000;

	KMeans cluster = null;
	int labelToLookFor = 0;
	while (resultingClusterSize > 10)
	{
		var clusterData = nextCluster.ToArray();
		
		cluster = new KMeans(2)
		{
//			MaxIterations = resultingClusterSize
		};
		
		KMeansClusterCollection clusters = cluster.Learn(clusterData);
		int[] labels = clusters.Decide(clusterData);

		var d1 = Distance.SquareEuclidean(cluster.Centroids[0], normalizedRef);
		var d2 = Distance.SquareEuclidean(cluster.Centroids[1], normalizedRef);
		
		labelToLookFor = labels[d1 > d2 ? 0 : 1];

		nextCluster.Clear();

		for (var label = 0; label < labels.Length; label++)
		{
			if (labels[label] == labelToLookFor)
			{
				nextCluster.Add(clusterData[label]);
			}
		}

		resultingClusterSize = nextCluster.Count();
	}
	
	nextCluster.Dump();
	
	foreach (var c in nextCluster) {
		var dictItem = results.FirstOrDefault(q => q.Value == c);
		var distance = Distance.SquareEuclidean(dictItem.Value, cluster.Centroids[labelToLookFor]);
		var origin = Distance.SquareEuclidean(dictItem.Value, normalizedRef);

		$"lic: {dictItem.Key}, dstC: {distance}, dstN: {origin}".Dump();
		dictItem.Value.Dump();
	}
}

public double[] Normalize(Bitmap bmp)
{
	var array = new byte[bmp.Width * bmp.Height];

	for (var y = 0; y < bmp.Height; y++)
	{
		for (var x = 0; x < bmp.Width; x++)
		{
			array[(y * bmp.Width) + x] = bmp.GetPixel(x, y).B;
		}
	}

	var min = array.Min();
	var max = array.Max();
	
	double[] result = new double[array.Length];
	
	for (var i = 0; i < array.Length; i++)
	{
		result[i] = MinMax(array[i], max, min, 0x00, 0xFF);
	}

	return result;
}

public double MinMax(byte x, byte max, byte min, byte newMax, byte newMin)
{
	return ((x - min) * (newMax - newMin) / (max - min) + newMin);
}

public static byte[] ImageToByte(Image img)
{
	ImageConverter converter = new ImageConverter();
	return (byte[])converter.ConvertTo(img, typeof(byte[]));
}

private Image DrawText(String text, Font font, Color textColor, Color backColor)
{
	//first, create a dummy bitmap just to get a graphics object
	Image img = new Bitmap(1, 1);
	Graphics drawing = Graphics.FromImage(img);

	//measure the string to see how big the image needs to be
	SizeF textSize = drawing.MeasureString(text, font);

	//free up the dummy image and old graphics object
	img.Dispose();
	drawing.Dispose();

	//create a new image of the right size
	img = new Bitmap((int)textSize.Width, (int)textSize.Height);

	drawing = Graphics.FromImage(img);

	//paint the background
	drawing.Clear(backColor);

	//create a brush for the text
	Brush textBrush = new SolidBrush(textColor);

	drawing.DrawString(text, font, textBrush, 0, 0);

	drawing.Save();

	textBrush.Dispose();
	drawing.Dispose();

	return img;
}

/// <summary>
/// Resize the image to the specified width and height.
/// </summary>
/// <param name="image">The image to resize.</param>
/// <param name="width">The width to resize to.</param>
/// <param name="height">The height to resize to.</param>
/// <returns>The resized image.</returns>
public static Bitmap ResizeImage(Image image, int width, int height)
{
	var destRect = new Rectangle(0, 0, width, height);
	var destImage = new Bitmap(width, height);

	destImage.SetResolution(image.HorizontalResolution, image.VerticalResolution);

	using (var graphics = Graphics.FromImage(destImage))
	{
		graphics.CompositingMode = CompositingMode.SourceCopy;
		graphics.CompositingQuality = CompositingQuality.HighQuality;
		graphics.InterpolationMode = InterpolationMode.HighQualityBicubic;
		graphics.SmoothingMode = SmoothingMode.HighQuality;
		graphics.PixelOffsetMode = PixelOffsetMode.HighQuality;

		using (var wrapMode = new ImageAttributes())
		{
			wrapMode.SetWrapMode(WrapMode.TileFlipXY);
			graphics.DrawImage(image, destRect, 0, 0, image.Width, image.Height, GraphicsUnit.Pixel, wrapMode);
		}
	}

	return destImage;
}

LicenseFilter.cs

// First a script to filter the list containing all license plates

StreamReader csvreader = new StreamReader(@"C:\Downloads\Open_Data_RDW__Gekentekende_voertuigen.csv");
string inputLine = "";

List<string> results = new List<string>();

var lowerDate = DateTime.Parse("01-01-2010");
var upperDate = DateTime.Parse("01-01-2016");

csvreader.ReadLine();

while ((inputLine = csvreader.ReadLine()) != null)
{
	try
	{
		string[] row = inputLine.Split(new char[] { ',' });

		var license = row[0];
		var carType = row[1];

		if (carType != "Personenauto") continue;

		var brand = row[2];

		if (brand != "CITROEN") continue;

		var brandType = row[3];

		if (brandType != "C4") continue;

		var APK = DateTime.Parse(row[4]);
		if (APK < DateTime.UtcNow) continue;

		var doorCount = Int32.Parse(row[32]);
		if (doorCount != 4) continue;

		var firstDateAccepted = DateTime.Parse(row[20]);

		if (firstDateAccepted > lowerDate && firstDateAccepted < upperDate)
		{
			results.Add(inputLine);
		}
	} catch {
		
	}
}

results.Dump();