| public GetSum ( int x, int y, int width, int height ) : long | ||
| x | int | The horizontal position of the rectangle |
| y | int | The vertical position of the rectangle |
| width | int | The rectangle's width |
| height | int | The rectangle's height |
| return | long | |
/// <summary>
/// Gets the sum of the areas of the rectangular features in an integral image.
/// </summary>
///
public double GetSum(IntegralImage2 image, int x, int y)
{
double sum = 0.0;
if (!Tilted)
{
// Compute the sum for a standard feature
foreach (HaarRectangle rect in Rectangles)
{
sum += image.GetSum(x + rect.ScaledX, y + rect.ScaledY,
rect.ScaledWidth, rect.ScaledHeight) * rect.ScaledWeight;
}
}
else
{
// Compute the sum for a rotated feature
foreach (HaarRectangle rect in Rectangles)
{
sum += image.GetSumT(x + rect.ScaledX, y + rect.ScaledY,
rect.ScaledWidth, rect.ScaledHeight) * rect.ScaledWeight;
}
}
return sum;
}
/// <summary>
/// Detects the presence of an object in a given window.
/// </summary>
///
public bool Compute(IntegralImage2 image, Rectangle rectangle)
{
int x = rectangle.X;
int y = rectangle.Y;
int w = rectangle.Width;
int h = rectangle.Height;
double mean = image.GetSum(x, y, w, h) * invArea;
double var = image.GetSum2(x, y, w, h) * invArea - (mean * mean);
double sdev = (var >= 0) ? Math.Sqrt(var) : 1;
// For each classification stage in the cascade
foreach (HaarCascadeStage stage in cascade.Stages)
{
// Check if the stage has rejected the image
if (stage.Classify(image, x, y, sdev) == false)
{
return false; // The image has been rejected.
}
}
// If the object has gone all stages and has not
// been rejected, the object has been detected.
return true; // The image has been detected.
}
