private static void startImageProcessing(Bitmap A, Bitmap B, string outputfolder)
{
ImageProcessor imageProcessor = new ImageProcessor();
Exporter exporter = new Exporter();
RegistrationProcessor registrationProcessor = new RegistrationProcessor();
//Create binary image of A with otsu threshold and save
Bitmap image1bin = imageProcessor.createBinaryOtsu(A);
image1bin.Save(outputfolder + "\\Abin.png", ImageFormat.Png);
//Create binary image of B with otsu threshold and save
Bitmap image2bin = imageProcessor.createBinaryOtsu(B);
image2bin.Save(outputfolder + "\\Bbin.png", ImageFormat.Png);
//Find contour of A - Only longest!
List<Contour<Point>> contours_image1 = imageProcessor.findContoursWithOpenCV(image1bin);
exporter.exportToCSV(contours_image1, outputfolder, "contourA.csv");
Bitmap contour_image1 = exporter.exportToImage(contours_image1, outputfolder, "contourA.png", A.Height, A.Width);
//Find contour of B - Only longest!
List<Contour<Point>> contours_image2 = imageProcessor.findContoursWithOpenCV(image2bin);
exporter.exportToCSV(contours_image2, outputfolder, "contourB.csv");
Bitmap contour_image2 = exporter.exportToImage(contours_image2, outputfolder, "contourB.png", B.Height, B.Width);
//Calculate transformation with help of the two contours
try
{
Transformation t1 = registrationProcessor.calculateTransformation(contours_image1, contours_image2);
//Start registration of contours
Bitmap registrated_Contours = registrationProcessor.registrationContour(t1, contour_image1, contour_image2);
registrated_Contours.Save(outputfolder + "\\contoursR.png", ImageFormat.Png);
//Start registration of orginial images
Bitmap registrated_originals = registrationProcessor.registrationBitmap(t1, A, B);
registrated_originals.Save(outputfolder + "\\registration.png", ImageFormat.Png);
}
catch (Exception e)
{
Console.WriteLine(e.ToString());
}
}
public Transformation calculateTransformation(List<Contour<Point>> contours_image1, List<Contour<Point>> contours_image2)
{
List<Feature> image1_features = new List<Feature>();
List<Feature> image2_features = new List<Feature>();
//Get the points of the FIRST (=0) contour
Point[] points1 = contours_image1[0].ToArray();
//Calculate the angle at every pixel for picture 1
for (int i = 0; i < points1.Length; i++)
{
AngleCalculator angleCalculator = new AngleCalculator();
double angle = angleCalculator.calculateAngle (points1, i);
Feature f = new Feature();
f.point = points1[i];
f.angle_at_pixel = angle;
image1_features.Add(f);
}
//Get the points of the FIRST (=0) contour
Point[] points2 = contours_image2[0].ToArray();
//Calculate the angle at every pixel for picture 2
for (int i = 0; i < points2.Length; i++)
{
AngleCalculator angleCalculator = new AngleCalculator();
double angle = angleCalculator.calculateAngle(points2, i);
Feature f = new Feature();
f.point = points2[i];
f.angle_at_pixel = angle;
image2_features.Add(f);
}
GraphAnalyzer graphanalyzer = new GraphAnalyzer();
//Normalize the shorter contour to longer one
List<Feature> image1_features_normalized;
List<Feature> image2_features_normalized;
if (image1_features.Count < image2_features.Count)
{
image1_features_normalized = graphanalyzer.normalize(image2_features, image1_features);
image2_features_normalized = image2_features;
}
else
{
image2_features_normalized = graphanalyzer.normalize(image1_features, image2_features);
image1_features_normalized = image1_features;
}
//Moves the contour(graph) of image1 to best matching
image1_features_normalized = graphanalyzer.matchGraphs(image1_features_normalized, image2_features_normalized);
//Get the best Features by using extrema [0] image1 --> [1] image2, ....
List<Feature> bestFeatures = graphanalyzer.findBestFeaturesWithExtrema(image1_features_normalized, image2_features_normalized);
bestFeatureStorage1.Add(bestFeatures[0]);
bestFeatureStorage1.Add(bestFeatures[2]);
bestFeatureStorage2.Add(bestFeatures[1]);
bestFeatureStorage2.Add(bestFeatures[3]);
//Calculating the transformation for the best features
Transformation transformation = calculateTransformationValues(bestFeatures);
//Exporting the graph
Exporter exporter = new Exporter();
exporter.exportFeatures(image1_features_normalized, image2_features_normalized);
return transformation;
}