public static byte[] getDifferenceOfGaussins(byte[] imageBytes, int k = 7)
{
double[] image = setGrayScale(doubleArray(imageBytes));
/*double[,] gaussKer = new double[,] { { 1 / 16.0, 1 / 8.0, 1 / 16.0 },
* { 1 / 8.0, 1 / 4.0, 1 / 8.0 },
* { 1 / 16.0, 1 / 8.0, 1 / 16.0 }};*/
double[,] gaussKer = Kernels.getGaussian(0.7);
double[][] smoothedImages = new double[Height][];
smoothedImages[0] = image.Clone() as double[];
for (int i = 1; i < Height; i++)
{
smoothedImages[i] = applyMatrix(smoothedImages[i - 1], gaussKer);
}
double[][] lapassedImages = new double[Height - 1][];
for (int i = 0; i < Height - 1; i++)
{
lapassedImages[i] = substractArrays(smoothedImages[i + 1], smoothedImages[i]);
}
return(byteArray(Array.ConvertAll(lapassedImages[k], x => x / 2 + 120)));
}
public static List <double[]> getBlobCoordsUsingLaplacianKernel(byte[] imageBytes)
{
List <double[]> BLOBS = new List <double[]>();
double[] image = setGrayScale(doubleArray(imageBytes));
double[][] lapassedImages = new double[Height - 1][];
lapassedImages[0] = applyMatrix(image, Kernels.getLaplacian(0.7));
for (int i = 1; i < Height - 1; i++)
{
lapassedImages[i] = applyMatrix(image, Kernels.getLaplacian(1.4 * (i + 1)));
}
/*double[][] gaussedImages = new double[Height][];
* gaussedImages[0] = applyMatrix(image, Kernels.getGaussian(0.7));
*
* for (int i = 1; i < Height; i++) {
* gaussedImages[i] = applyMatrix(gaussedImages[0], Kernels.getGaussian(1.4 * (i)));
* }
*
* for (int i = 0; i < Height - 1; i++) {
* lapassedImages[i] = substractArrays(gaussedImages[i + 1] , gaussedImages[i]);
* }*/
List <double[]> OUTPUTBLOBS = new List <double[]>();
for (int w = 10; w < W - 10; w++)
{
for (int h = 10; h < H - 10; h++)
{
for (int t = 1; t < Height - 2; t++)
{
bool isLocalMinma = true;
bool isLocalMaxima = true;
double current = lapassedImages[t][h * W + w];
double currentMinBound = current > 0 ? current * 1.01 : current * 0.99;
double currentMaxBound = current > 0 ? current * 0.99 : current * 1.01;
for (int dw = -1; dw <= 1; dw++)
{
for (int dh = -1; dh <= 1; dh++)
{
for (int dt = -1; dt <= 1; dt++)
{
if ((dt != 0 || dh != 0 || dw != 0))
{
if ((lapassedImages[t + dt][(h + dh) * W + (w + dw)]) <= current)
{
isLocalMinma = false;
}
if ((lapassedImages[t + dt][(h + dh) * W + (w + dw)]) >= current)
{
isLocalMaxima = false;
}
}
}
}
}
if (isLocalMaxima || isLocalMinma)
{
bool hasLocalMinimaOnScale = false;
bool hasLocalMaximaOnScale = false;
int pix = h * W + w;
for (int T = 1; T < Height - 2; T++)
{
if (lapassedImages[T][pix] > lapassedImages[T + 1][pix] && lapassedImages[T][pix] > lapassedImages[T - 1][pix])
{
hasLocalMaximaOnScale = true;
}
if (lapassedImages[T][pix] < lapassedImages[T + 1][pix] && lapassedImages[T][pix] < lapassedImages[T - 1][pix])
{
hasLocalMinimaOnScale = true;
}
}
if (hasLocalMaximaOnScale ^ hasLocalMinimaOnScale)
{
OUTPUTBLOBS.Add(new double[4] {
w / (W + 0.0), h / (H + 0.0), 2 * (t + 1) / (W + 0.0), Math.Abs(current)
});
}
}
}
}
}
OUTPUTBLOBS = OUTPUTBLOBS.Where(blob => {
double x = blob[0];
return(true);
}).ToList();
return(OUTPUTBLOBS);
}
