CvMat CalculateBackProjection(CvMat _image, CvHistogram hist)
{
CvMat _backProject = new CvMat(_image.Rows, _image.Cols, MonoColorMatrix);
using (CvMat _imageHSV = ConvertToHSV(_image)) // Convert the image to HSV
using (CvMat imgH = new CvMat(_image.Rows, _image.Cols, MonoColorMatrix))
using (CvMat imgS = new CvMat(_image.Rows, _image.Cols, MonoColorMatrix))
using (CvMat imgV = new CvMat(_image.Rows, _image.Cols, MonoColorMatrix))
{
// Break image into H, S, V planes
// If the image were BGR, then it would split into B, G, R planes respectively
_imageHSV.CvtPixToPlane(imgH, imgS, imgV, null); // Cv.Split also does this
// Store HSV planes as an IplImage array to pass to openCV's hist function
// TODO: Why can't BackProjection accept CvMat?
IplImage[] hsvPlanes = { Cv.GetImage(imgH), Cv.GetImage(imgS),
Cv.GetImage(imgV) };
hist.CalcBackProject(hsvPlanes, _backProject);
}
return(_backProject);
}
// Takes an image and calculates its histogram for one channel.
// Color images have 3 channels (4 if you count alpha?)
// Webcam captures them in (R)ed, (G)reen, (B)lue.
// Convert to (H)ue, (S)aturation (V)alue to get better separation for thresholding
CvHistogram CalculateOneChannelHistogram(CvMat _image, int channelNum, float channelMax)
{
// 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).
// For HSV, Hue range is [0,179], Saturation range is [0,255] and Value range is [0,255]
if (channelNum > imColorChannels)
{
Debug.LogError("Desired channel number " + channelNum + " is out of range.");
}
float channelMin = 0;
float[] channelRanges = new float[2] {
channelMin, channelMax
};
float[][] ranges = { channelRanges };
// Note: You don't need to use all 3 channels for the histogram.
int channelBins = 32; // Number of bins in the Hue histogram (more bins = narrower bins)
// Number of bins per histogram channel
// If we use all 3 channels (H, S, V) then the histogram will have 3 dimensions.
int[] hist_size = new int[] { channelBins };
CvHistogram hist = new CvHistogram(hist_size, HistogramFormat.Array, ranges, true);
using (CvMat _imageHSV = ConvertToHSV(_image)) // Convert the image to HSV
// We could keep the image in B, G, R, A if we wanted to.
// Just split the channels into B, G, R planes
using (CvMat imgChannel = new CvMat(_imageHSV.Rows, _imageHSV.Cols, MonoColorMatrix))
{
// Break image into H, S, V planes
// If the image were BGR, then it would split into B, G, R planes respectively
switch (channelNum)
{
case 0:
_imageHSV.CvtPixToPlane(imgChannel, null, null, null); // Cv.Split also does this
break;
case 1:
_imageHSV.CvtPixToPlane(null, imgChannel, null, null); // Cv.Split also does this
break;
case 2:
_imageHSV.CvtPixToPlane(null, null, imgChannel, null); // Cv.Split also does this
break;
default:
Debug.LogError("Channel is out of range");
_imageHSV.CvtPixToPlane(imgChannel, null, null, null); // Cv.Split also does this
break;
}
hist.Calc(Cv.GetImage(imgChannel), false, null); // Call hist function (no accumulatation, no mask)
}
return(hist); // Return the histogram
}
// Takes an image and calculates its histogram in HSV color space
// Color images have 3 channels (4 if you count alpha?)
// Webcam captures them in (R)ed, (G)reen, (B)lue.
// Convert to (H)ue, (S)aturation (V)alue to get better separation for thresholding
CvHistogram CalculateHSVHistogram(CvMat _image)
{
// 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).
// For HSV, Hue range is [0,179], Saturation range is [0,255] and Value range is [0,255]
// hue varies from 0 to 179, see cvtColor
float hueMin = 0, hueMax = 179;
float[] hueRanges = new float[2] {
hueMin, hueMax
};
// saturation varies from 0 (black-gray-white) to
// 255 (pure spectrum color)
float satMin = 0, satMax = 255;
float[] saturationRanges = new float[2] {
satMin, satMax
};
float valMin = 0, valMax = 255;
float[] valueRanges = new float[2] {
valMin, valMax
};
float[][] ranges = { hueRanges, saturationRanges, valueRanges };
// Note: You don't need to use all 3 channels for the histogram.
int hueBins = 32; // Number of bins in the Hue histogram (more bins = narrower bins)
int satBins = 32; // Number of bins in the Saturation histogram (more bins = narrower bins)
int valueBins = 8; // Number of bins in the Value histogram (more bins = narrower bins)
float maxValue = 0, minValue = 0; // Minimum and maximum value of calculated histogram
// Number of bins per histogram channel
// If we use all 3 channels (H, S, V) then the histogram will have 3 dimensions.
int[] hist_size = new int[] { hueBins, satBins, valueBins };
CvHistogram hist = new CvHistogram(hist_size, HistogramFormat.Array, ranges, true);
using (CvMat _imageHSV = ConvertToHSV(_image)) // Convert the image to HSV
// We could keep the image in B, G, R, A if we wanted to.
// Just split the channels into B, G, R planes
using (CvMat imgH = new CvMat(_image.Rows, _image.Cols, MonoColorMatrix))
using (CvMat imgS = new CvMat(_image.Rows, _image.Cols, MonoColorMatrix))
using (CvMat imgV = new CvMat(_image.Rows, _image.Cols, MonoColorMatrix))
{
// Break image into H, S, V planes
// If the image were RGB, then it would split into R, G, B planes respectively
_imageHSV.CvtPixToPlane(imgH, imgS, imgV, null); // Cv.Split also does this
// Store HSV planes as an IplImage array to pass to openCV's hist function
IplImage[] hsvPlanes = { Cv.GetImage(imgH), Cv.GetImage(imgS), Cv.GetImage(imgV) };
hist.Calc(hsvPlanes, false, null); // Call hist function (no accumulatation, no mask)
// Do we need to normalize??
hist.GetMinMaxValue(out minValue, out maxValue);
// Scale the histogram to unity height
hist.Normalize(_imageHSV.Width * _imageHSV.Height * hist.Dim * hueMax / maxValue);
}
return(hist); // Return the histogram
}
