detect all range colors on image

edit

Hi,

Do you need the actual pixel coordinates or just the number of pixels?

If the latter you would probably be better off using calcHist to generate a histogram of the hue value. See example here:

http://docs.opencv.org/2.4/doc/tutorials/imgproc/histograms/histogram_calculation/histogram_calculation.html

guy

I would use CV_BGR2HSV_FULL color conversion to get all colors within the range of 0..255 included . (For your info, the conversionCV_BGR2HSV returns Hue the range of 0..180 included)

// a sample image
cv::Mat src = (cv::Mat_<Vec3b>(3, 3) <<
    Vec3b(0, 0, 0), Vec3b(128, 128, 128), Vec3b(255, 255, 255),
    Vec3b(255, 0, 0),Vec3b(0, 255, 0), Vec3b(0, 0, 255), 
    Vec3b(255, 255, 0), Vec3b(255, 0, 255), Vec3b(0, 255, 255));
CV_Assert(src.type() == CV_8UC3);

cv::Mat hsvFull;
// this returns hue within the range 0..255
cv::cvtColor(src, hsvFull, CV_BGR2HSV_FULL);
vector<uchar> colorsCount(256,0);
Scalar pixel;
uchar color;
int maxColor=0, minColor=INT16_MAX;
// Scan image to count colors
// see http://docs.opencv.org/3.1.0/db/da5/tutorial_how_to_scan_images.html
// for alternative/efficient way to scan images
for (int r = 0; r < hsvFull.rows; r++)
{
    for (int c = 0; c < hsvFull.cols; c++)
    {
        pixel = hsvFull.at<Vec3b>(Point(c, r));
        color = pixel(0);
        colorsCount[color] +=1;
        if (color < minColor) minColor = color;
        if (color > maxColor) maxColor = color;
    }
}
int colorRange = maxColor - minColor;
int minCount, maxCount;
minCount = colorsCount[minColor];
maxCount = colorsCount[maxColor];

If you like you can apply a lookup table to reduce colors to %20

Mat lookUpTable(1, 256, CV_8U);
Mat hsvDiscrete;
uchar* p = lookUpTable.ptr();
for (int i = 0; i < 256; ++i)
    p[i] = i - i % 20;
LUT(hsvFull, lookUpTable, hsvDiscrete);
// get back an BGR image ready to show
Mat dst;
cvtColor(hsvDiscrete, dst, CV_HSV2BGR_FULL);
imshow("Src", src);
imshow("Discrete", dst);
waitKey(0);