My project is able to capture the bitmap of a target window and convert it into an IplImage
, and then display that image in a cvNamedWindow
, where further processing can take place.
For the sake of testing, I've loaded an image into MSPaint like so:
The user is then allowed to click and drag the mouse over any number of pixels within the image to create a vector<cv::Scalar_<BYTE>>
containing these RGB color values.
Then, with the help of ColorRGBToHLS()
, this array is then sorted from left to right by hue, like so:
// PixelColor is just a cv::Scalar_<BYTE>
bool comparePixelColors( PixelColor& pc1, PixelColor& pc2 ) {
WORD h1 = 0, h2 = 0;
WORD s1 = 0, s2 = 0;
WORD l1 = 0, l2 = 0;
ColorRGBToHLS(RGB(pc1.val[2], pc1.val[1], pc1.val[0]), &h1, &l1, &s1);
ColorRGBToHLS(RGB(pc2.val[2], pc2.val[1], pc2.val[0]), &h2, &l2, &s2);
return ( h1 < h2 );
}
//..(elsewhere in code)
std::sort(m_colorRange.begin(), m_colorRange.end(), comparePixelColors);
...and then shown in a new cvNamedWindow
, which looks something like:
Now, the idea here is to create a binary threshold image (or "mask") where this selected range of colors become white, and the rest of the source image becomes black... similar to the way the "Select By Color" tool operates in GIMP, or the "magic wand" tool works in Photoshop... except instead of limiting ourselves to a specific contoured selection, we are literally operating on the image as a whole.
I've read into cvInRangeS
, and it sounds like it's precisely what I need.
However, and for whatever reason, the thresholded image always ends up being totally black...
VOID ShowThreshedImage(const IplImage* src, const PixelColor& min, const PixelColor& max)
{
IplImage* imgHSV = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 3);
cvCvtColor(src, imgHSV, CV_RGB2HLS);
cvNamedWindow("T1");
cvShowImage("T1", imgHSV); // <-- Shows up like the image below
IplImage* imgThreshed = cvCreateImage(cvGetSize(src), IPL_DEPTH_8U, 1);
cvInRangeS(imgHSV, min, max, imgThreshed);
cvNamedWindow("T2");
cvShowImage("T2", imgThreshed); // <-- SHOWS UP PITCH BLACK!
}
This is what the "T1"
window ends up looking like (which I suppose is correct?):
Bearing in mind that because the color range vector is stored as RGB (and that OpenCV internally reverses this order into BGR), I have converted the min/max values into HLS before passing them into ShowThreshedImage()
like so:
CvScalar rgbPixelToHSV(const PixelColor& pixelColor)
{
WORD h = 0, s = 0, l = 0;
ColorRGBToHLS(RGB(pixelColor.val[2], pixelColor.val[1], pixelColor.val[0]), &h, &l, &s);
return PixelColor(h, s, l);
}
//...(elsewhere in code)
if(m_colorRange.size() > 0)
m_minHSV = rgbPixelToHSV(m_colorRange[0]);
if(m_colorRange.size() > 1)
m_maxHSV = rgbPixelToHSV(m_colorRange[m_colorRange.size() - 1]);
ShowThreshedImage(m_imgSrc, m_minHSV, m_maxHSV);
...But even without this conversion and simply passing RGB values instead, the result is still an entirely black image. I've even tried manually plugging in certain min/max values, and the best result I got was a few lit pixels (albeit, the incorrect ones).
What am I doing wrong here?
Is there something that I don't understand about the cvInRangeS
method?
Do I need to step through each and every single color in order to properly threshold the selected range out of the source image?
Are there any other ways of accomplishing this?
Thank you for your time.
I have discovered that cvInRangeS
expects all values for min
to be lower than that of max
. But when a range of colors are selected, there doesn't appear to be any guarantee that this will be the case, often resulting in a black thresholded image.
And swapping values to enforce this rule may result in unwanted colors within the new range (in some cases, this could include all colors instead of just the desired ones).
So I suppose the real question here would be:
"How do you segment an array of RGB colors, and use them to threshold an image?"
Your problem might be caused by the simple fact that OpenCV maintains a different range for values than for instanc MSpaint. For instance the HSV color space in paint is 360,100,100 while in OpenCV it is 180,255,255. Check your input values in openCV bu outputting the pixel value when clicking on a certain pixel. inRangeS should be the correct tool for the job. That said, in RGB it should work just as well because the range is the same as in paint.
cvSetMouseCallback("MyWindow", mouseEvent, (void*) &myImage);
void mouseEvent(int evt, int x, int y, int flags, void *param) {
if (evt == CV_EVENT_LBUTTONDOWN) {
printf("%d %d\n", x, y);
IplImage* imageSource = (IplImage*) param;
Mat image(imageSource);
cout << "Image cols " << image.cols << " rows " << image.rows << endl;
Mat imageHSV;
cvtColor(image, imageHSV, CV_BGR2HSV);
Vec3b p = imageHSV.at<Vec3b > (y, x);
char text[20];
sprintf(text, "H=%d, S=%d, V=%d", p[0], p[1], p[2]);
cout << text << endl;
}
}
When you have an idea about the HSV values by using this values, use these as lower and upper bounds for the in range method after converting the image to HSV by using cvtColor(image, imageHSV, CV_BGR2HSV)
. That should make you able to get the desired result.
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