// => hue and normalize, if null, may be created and assigned
// <= ROI
private CvMat detectROI(CvMat input, ref CvMat hue, ref CvMat normalize)
{
// TODO : Like I said above, if I get the minimum/maximum values, I have an accurate lowerBound/upperBound pair to work with!!!
CvMat roi;
CvScalar lowerBound;
CvScalar upperBound;
// IDEA 3:
// Determine if I should check for "features" in the "thresholded" image, or in a cropped grayscale version of the original one!!
// For now, lets search the thresholded one...
if (boxEstimationType == BoxEstimationType.HUE)
{
roi = MatOps.CopySize(input, MatrixType.U8C1);
lowerBound = boxEstimatedValue - floodHueTolerance / 1; // TODO : this should be +-(MAX VALUE)
upperBound = boxEstimatedValue + floodHueTolerance / 1;
if (hue == null)
{
hue = MatOps.BGRtoHue(input);
}
hue.InRangeS(lowerBound, upperBound, roi);
}
else if (boxEstimationType == BoxEstimationType.NORMALIZE)
{
// TODO : must investigate, range doesn't return anything
roi = MatOps.CopySize(input, MatrixType.U8C1);
lowerBound = boxEstimatedValue - floodNormTolerance;
upperBound = boxEstimatedValue + floodNormTolerance;
if (normalize == null)
{
normalize = MatOps.MyNormalize(input);
}
normalize.InRangeS(lowerBound, upperBound, roi);
}
else
{
// Couldn't estimate either way? We are off to a bad start, but lets try to see if features can be extracted anyway.
roi = MatOps.ConvertChannels(input); // we are already losing valuable info here!!
}
return(roi);
}
// Threshold the image based on the HSV value
// From and To are CvScalars of 3 values {Hue, Saturation, and (Brightness) Value)
CvMat GetThresholdedImage(CvMat img, CvScalar from, CvScalar to)
{
// Hue, Saturation, Value or HSV is a color model that describes colors (hue or tint)
// in terms of their shade (saturation or amount of gray)
// and their brightness (value or luminance).
// Hue is expressed as a number from 0 to 360 degrees representing hues of red (starts at 0),
// yellow (starts at 60), green (starts at 120), cyan (starts at 180),
// blue (starts at 240), and magenta (starts at 300).
// Saturation is the amount of gray (0% to 100%) in the color.
// Value (or Brightness) works in conjunction with saturation and
// describes the brightness or intensity of the color from 0% to 100%.
CvMat imgHsv = ConvertToHSV(img);
CvMat imgThreshed = new CvMat(img.Rows, img.Cols, MonoColorMatrix);
imgHsv.InRangeS(from, to, imgThreshed);
return(imgThreshed);
}
