OpenCV get coordinates of red-only rectangle area - c++

Question

I have the following output from red-only filtration done by the following algorithm:
cv::Mat findColor(const cv::Mat & inputBGRimage, int rng=20)
{
// Make sure that your input image uses the channel order B, G, R (check not implemented).
cv::Mat mt1, mt2;
cv::Mat input = inputBGRimage.clone();
cv::Mat imageHSV; //(input.rows, input.cols, CV_8UC3);
cv::Mat imgThreshold, imgThreshold0, imgThreshold1; //(input.rows, input.cols, CV_8UC1);
assert( ! input.empty() );
// blur image
cv::blur( input, input, Size(11, 11) );
// convert input-image to HSV-image
cv::cvtColor( input, imageHSV, cv::COLOR_BGR2HSV );
// In the HSV-color space the color 'red' is located around the H-value 0 and also around the
// H-value 180. That is why you need to threshold your image twice and the combine the results.
cv::inRange( imageHSV, cv::Scalar( H_MIN, S_MIN, V_MIN ), cv::Scalar( H_MAX, S_MAX, V_MAX ), imgThreshold0 );
if ( rng > 0 )
{
// cv::inRange(imageHSV, cv::Scalar(180-rng, 53, 185, 0), cv::Scalar(180, 255, 255, 0), imgThreshold1);
// cv::bitwise_or( imgThreshold0, imgThreshold1, imgThreshold );
}
else
{
imgThreshold = imgThreshold0;
}
// cv::dilate( imgThreshold0, mt1, Mat() );
// cv::erode( mt1, mt2, Mat() );
return imgThreshold0;
}
And here is the output:
And I want to detect the four coordinates of the rectangle. As you can see, the output is not perfect, I used cv::findContours in conjunction with cv::approxPolyDP before, but it's not working good anymore.
Is there any filter that I can apply for input image (except blur, dilate, erode) to make image better for processing?
Any suggestions?
Updated:
When I am using findContours like this:
findContours( src, contours, hierarchy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE );
double largest_area = 0;
for( int i = 0; i < contours.size(); i++) { // get the largest contour
area = fabs( contourArea( contours[i] ) );
if( area >= largest_area ) {
largest_area = area;
largestContours.clear();
largestContours.push_back( contours[i] );
}
}
if( largest_area > 5000 ) {
cv::approxPolyDP( cv::Mat(largestContours[0]), approx, 100, true );
cout << approx.size() << endl; /* ALWAYS RETURN 2 ?!? */
}
The approxPolyDP is not working as expected.

Answer 1

I think your result is quite good, maybe if you select the contour with greatest area using Image Moments and then finding the minimal rotated rectangle of the bigger contour.
vector<cv::RotatedRect> cv::minRect( contours.size() );
for( size_t = 0; i < contours.size(); i++ )
{
minRect[i] = minAreaRect( cv::Mat(contours[i]) );
}
Rotated Rect class already has a vector of Point2f to store the points.
RotatedRect rRect = RotatedRect(Point2f(100,100), Size2f(100,50), 30);
Point2f vertices[4];
rRect.points(vertices);
for(int i = 0; i < 4; i++){
std::cout << vertices[i] << " ";
}