static void Main(string[] args)
{
string[] pathes = Directory.GetFiles("C:\\Users\\Tanya\\Documents\\tests_data\\db");
StreamWriter writer = new StreamWriter("C:\\Users\\Tanya\\Documents\\Results\\AlgorithmVSCOMEResult.txt", true);
for (int i = 0; i < 3 /*pathes.GetLength(0)*/; i++)
{
Tuple <int, int> redPoint = ImageHelper.FindColorPoint(pathes[i]);
double[,] imgBytes = ImageEnhancementHelper.EnhanceImage(ImageHelper.LoadImage(pathes[i]));
double[,] orientationField = OrientationFieldGenerator.GenerateOrientationField(imgBytes.Select2D(x => (int)x));
Complex[,] complexOrientationField = orientationField.Select2D(x => (new Complex(Math.Cos(2 * x), Math.Sin(2 * x))));
Complex[,] filter = Filter.GetFilter(orientationField);
Complex[,] complexFilteredField = ConvolutionHelper.ComplexConvolve(complexOrientationField, filter);
double[,] filteredField = complexFilteredField.Select2D(x => x.Magnitude);
VSCOME vscome = new VSCOME(orientationField, filteredField);
double[,] vscomeValue = vscome.CalculateVscomeValue();
Tuple <int, int> corePoint = KernelHelper.Max2dPosition(vscomeValue);
writer.WriteLine(GetDistance(redPoint, corePoint));
// ImageHelper.SaveArray(orientationField, "C:\\Users\\Tanya\\Documents\\Results\\orientationField.jpg");
// ImageHelper.SaveArray(filteredField, "C:\\Users\\Tanya\\Documents\\Results\\filteredField.jpg");
//ImageHelper.SaveArray(vscomeValue, "C:\\Users\\Tanya\\Documents\\Results\\vscomeValue_1.jpg");
}
writer.Close();
}
static void Main(string[] args)
{
string[] pathes = Directory.GetFiles("C:\\Users\\Tanya\\Documents\\tests_data\\db");
StreamWriter writer = new StreamWriter("C:\\Users\\Tanya\\Documents\\Results\\ModelBasedAlgorithmResult.txt", true);
StreamWriter writerResult = new StreamWriter("C:\\Users\\Tanya\\Documents\\Results\\ModelBasedAlgorithmSummaryResult.txt", true);
List <double> distances = new List <double>();
double sum15 = 0;
double sum30 = 0;
double sumOther = 0;
double distance = 0;
for (int i = 0; i < pathes.GetLength(0); i++)
{
break;
Tuple <int, int> redPoint = ImageHelper.FindColorPoint(pathes[i]);
double[,] imgBytes = ImageEnhancementHelper.EnhanceImage(ImageHelper.LoadImage(pathes[i]));
double[,] orientationField = PixelwiseOrientationFieldGenerator.GenerateOrientationField(imgBytes);
List <Tuple <int, int> > singularPoints = PoincareIndexMethod.FindSingularPoins(orientationField);
ModelBasedAlgorithmCUDAFingerprinting.ReferencePoint.HoughPoincare.ModelBasedAlgorithm modelBasedAlgorithm = new ModelBasedAlgorithmCUDAFingerprinting.ReferencePoint.HoughPoincare.ModelBasedAlgorithm(orientationField);
List <Tuple <int, int> > corePoints = modelBasedAlgorithm.FindSingularPoints(singularPoints);
writer.WriteLine("---Fingerprint---");
foreach (Tuple <int, int> corePoint in corePoints)
{
distance = GetDistance(redPoint, corePoint);
distances.Add(distance);
writer.WriteLine(distance);
}
//ImageHelper.SaveArray(orientationField, "C:\\Users\\Tanya\\Documents\\Results\\china\\orientationField.jpg");
}
foreach (double d in distances)
{
if (d <= 15)
{
sum15 += d;
}
else if (d <= 30)
{
sum30 += d;
}
else
{
sumOther += d;
}
}
writerResult.WriteLine("0..15 => {0}", sum15);
writerResult.WriteLine("15..30 => {0}", sum30);
writerResult.WriteLine(">30 => {0}", sumOther);
writer.Close();
}
public float[] BinarizeImage(float[] image, int rows, int columns, bool useCuda = false)
{
if (useCuda)
{
var result = new float[rows * columns];
CudaGlobalBinarization((float)Constants.BinarizationThreshold, result, image, columns, rows);
return(result);
}
var newImage = ImageEnhancementHelper.EnhanceImage(image.Make2D(rows, columns).Select2D(x => (double)x));
return
(GlobalBinarization.Binarization(newImage, Constants.BinarizationThreshold)
.Make1D()
.Select(x => (float)x)
.ToArray());
}
public static double[,] BinarizeImage(double[,] image, int rows, int columns)
{
var newImage = ImageEnhancementHelper.EnhanceImage(image);
return(GlobalBinarization.Binarization(newImage, Constants.BinarizationThreshold));
}
