Reputation: 71
I have two vector of contours OUTERCONT and INNERCONT defined in openCV as vector(vector(Points)). I want to check if one contour exists inside another.I would also like to know, how many contours exist inside each OUTERCONT. I am currently drawing a minEnclosingRect around each contour and checking the following:
for (int i = 0; i < outerrect.size(); i++)
{
count = 0;
for (int j = 0; j < innerrect.size(); j++)
{
bool is_inside = ((innerrect[j] & outerrect[i]) == innerrect[j]);
if (is_inside == 1)
count++;
}
if (count > 0)
{
//DO SOMETHING
}
cout << count << endl;
This does not seem to be working, it always returns the count as some number around 120, which is not right. Could you suggest any change to make this work correctly?
NOTE: I cannot use hierarchy because these are two separate set of contours returned from 2 different functions.
I know PointPloygon test is an option, but could you suggest any more methods of doing this?
Upvotes: 2
Views: 1921
Reputation: 20130
Here's my idea from the comments:
// stacked contours
int main(int argc, char* argv[])
{
cv::Mat input = cv::imread("C:/StackOverflow/Input/Contours_in_Contours.png");
cv::Mat input_red = cv::imread("C:/StackOverflow/Input/Contours_in_Contours_RED.png");
cv::Mat reds;
cv::inRange(input_red, cv::Scalar(0, 0, 200), cv::Scalar(50, 50, 255), reds);
std::vector<std::vector<cv::Point> > contours1;
cv::findContours(reds, contours1, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
cv::Mat input_yellow = cv::imread("C:/StackOverflow/Input/Contours_in_Contours_YELLOW.png");
cv::Mat yellows;
cv::inRange(input, cv::Scalar(0, 200, 200), cv::Scalar(0, 255, 255), yellows);
std::vector<std::vector<cv::Point> > contours2;
cv::findContours(yellows, contours2, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
// now we have 2 sets of contours and want to find out whether contours of set2 are completely within a contour of contours1 without hierarchy information.
std::vector<cv::Mat> masks1;
std::vector<int> nMaskPixels1;
// for each contour in contours1: create a contour mask:
for (int i = 0; i < contours1.size(); ++i)
{
cv::Mat mask1 = cv::Mat::zeros(input.size(), CV_8UC1);
cv::drawContours(mask1, contours1, i, cv::Scalar::all(255), -1); // draw filled
int nPixel1 = cv::countNonZero(mask1);
masks1.push_back(mask1);
nMaskPixels1.push_back(nPixel1);
}
std::vector<cv::Mat> masks2;
std::vector<int> nMaskPixels2;
// for each contour in contours2: test whether it is completely within the reference contour:
for (int j = 0; j < contours2.size(); ++j)
{
cv::Mat mask2 = cv::Mat::zeros(input.size(), CV_8UC1);
cv::drawContours(mask2, contours2, j, cv::Scalar::all(255), -1); // draw filled
int nPixel2 = cv::countNonZero(mask2);
masks2.push_back(mask2);
nMaskPixels2.push_back(nPixel2);
}
for (int i = 0; i < masks1.size(); ++i)
{
cv::Mat mask1 = masks1[i];
// draw mask again for visualization:
cv::Mat outIm = input.clone();
cv::drawContours(outIm, contours1, i, cv::Scalar(0, 0, 0), 3);
for (int j = 0; j < masks2.size(); ++j)
{
cv::Mat mask2 = masks2[j];
cv::Mat overlap = mask1 & mask2;
int nOverlapPixels = cv::countNonZero(overlap);
if (nOverlapPixels == 0) continue; // no overlap at all. Test next contour.
if (nOverlapPixels == nMaskPixels2[j] && nOverlapPixels < nMaskPixels1[i])
{
// second contour is completely within first contour
cv::drawContours(outIm, contours2, j, cv::Scalar(0, 255, 0), 3);
}
else if (nOverlapPixels == nMaskPixels2[j] && nOverlapPixels == nMaskPixels1[i])
{
// both contours are identical
std::cout << "WARNING: " << "contours " << i << " and " << j << " are identical" << std::endl;
}
else if (nOverlapPixels < nMaskPixels2[j] && nOverlapPixels == nMaskPixels1[i])
{
// first contour is completely within second contour
std::cout << "WARNING: " << "contour " << i << " of the first set is inside of " << j << std::endl;
}
else if (nOverlapPixels < nMaskPixels2[j] && nOverlapPixels < nMaskPixels1[i])
{
// both contours intersect
cv::drawContours(outIm, contours2, j, cv::Scalar(255, 0, 255), 3);
}
}
cv::imshow("contours", outIm);
cv::imwrite("C:/StackOverflow/Output/contours.png", outIm);
cv::waitKey(0);
}
cv::imshow("input", input);
cv::waitKey(0);
return 0;
}
This code will create two sets of contours from these 2 images:
compute contour masks and compare them.
results will be displayed per contour. black contour is the reference, green are the ones that are completely within the reference, purple are intersecting contours.
I'm using this image to draw the results on:
getting these results:
contour1:
contour2:
As you can see, the lonely yellow contour isn't detected to intersect or be contained in any of those red contours.
Upvotes: 2