public double Apply(IntegralImage image, int x)
{
Func <double, double, double> comparer = SubtractLog;
switch (m_type)
{
case 0:
return(Filter0(image, x, m_y, m_width, m_height, comparer));
case 1:
return(Filter1(image, x, m_y, m_width, m_height, comparer));
case 2:
return(Filter2(image, x, m_y, m_width, m_height, comparer));
case 3:
return(Filter3(image, x, m_y, m_width, m_height, comparer));
case 4:
return(Filter4(image, x, m_y, m_width, m_height, comparer));
case 5:
return(Filter5(image, x, m_y, m_width, m_height, comparer));
}
return(0.0);
}
// oooooooooooooooo
// oooooooooooooooo
// oooooooooooooooo
// oooooooooooooooo
public static double Filter0(IntegralImage image, int x, int y, int w, int h, Func <double, double, double> cmp)
{
//Debug.Assert(x >= 0);
//Debug.Assert(y >= 0);
//Debug.Assert(w >= 1);
//Debug.Assert(h >= 1);
double a = image.Area(x, y, x + w - 1, y + h - 1);
double b = 0;
return(cmp(a, b));
}
public int CalculateSubfingerprint(IntegralImage image, int offset)
{
uint bits = 0;
for (int i = 0; i < m_num_classifiers; i++)
{
//for (int i = m_num_classifiers - 1; i >= 0; i--) {
// TODO: cast uint
bits = (bits << 2) | GrayCode[m_classifiers[i].Classify(image, offset)];
//bits = (bits << 2) | m_classifiers[i].Classify(image, offset);
}
return((int)bits);
}
// .......ooooooooo
// .......ooooooooo
// ooooooo.........
// ooooooo.........
public static double Filter3(IntegralImage image, int x, int y, int w, int h, Func <double, double, double> cmp)
{
//Debug.Assert(x >= 0);
//Debug.Assert(y >= 0);
//Debug.Assert(w >= 1);
//Debug.Assert(h >= 1);
int w_2 = w / 2;
int h_2 = h / 2;
double a = image.Area(x, y + h_2, x + w_2 - 1, y + h - 1) +
image.Area(x + w_2, y, x + w - 1, y + h_2 - 1);
double b = image.Area(x, y, x + w_2 - 1, y + h_2 - 1) +
image.Area(x + w_2, y + h_2, x + w - 1, y + h - 1);
return(cmp(a, b));
}
public int[] Calculate(Image image)
{
int length = image.Rows - m_max_filter_width + 1;
if (length <= 0)
{
//DEBUG() << "Chromaprint::FingerprintCalculator::Calculate() -- Not "
// << "enough data. Image has " << image.NumRows() << " rows, "
// << "needs at least " << m_max_filter_width << " rows.\n";
return(null);
}
IntegralImage integral_image = new IntegralImage(image);
var fingerprint = new int[length];
for (int i = 0; i < length; i++)
{
fingerprint[i] = CalculateSubfingerprint(integral_image, i);
}
return(fingerprint);
}
