an alternative approach based on minAreaRect of contours and distance between minAreaRect points. by this way it is possible to filter contours by their angles as seen on sample result image.
you can change width & height ratio and angel by changing following lines
if(dist0 > dist1 *4) // dist0 and dist1 means width and height you can change as you wish
.
.
if( fabs(angle) > 35 & fabs(angle) < 150 ) // you can change angle criteria
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
using namespace cv;
using namespace std;
//! Compute the distance between two points
/*! Compute the Euclidean distance between two points
*
* @param a Point a
* @param b Point b
*/
static double distanceBtwPoints(const cv::Point2f &a, const cv::Point2f &b)
{
double xDiff = a.x - b.x;
double yDiff = a.y - b.y;
return std::sqrt((xDiff * xDiff) + (yDiff * yDiff));
}
int main( int argc, char** argv )
{
Mat src,gray;
src = imread(argv[1]);
if(src.empty())
return -1;
cvtColor( src, gray, COLOR_BGR2GRAY );
gray = gray < 200;
vector<vector<Point> > contours;
findContours(gray.clone(), contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE);
RotatedRect _minAreaRect;
for (size_t i = 0; i < contours.size(); ++i)
{
_minAreaRect = minAreaRect( Mat(contours[i]) );
Point2f pts[4];
_minAreaRect.points(pts);
double dist0 = distanceBtwPoints(pts[0], pts[1]);
double dist1 = distanceBtwPoints(pts[1], pts[2]);
double angle = 0;
if(dist0 > dist1 *4)
angle =atan2(pts[0].y - pts[1].y,pts[0].x - pts[1].x) * 180.0 / CV_PI;
if(dist1 > dist0 *4)
angle =atan2(pts[1].y - pts[2].y,pts[1].x - pts[2].x) * 180.0 / CV_PI;
if( fabs(angle) > 35 & fabs(angle) < 150 )
for( int j = 0; j < 4; j++ )
line(src, pts[j], pts[(j+1)%4], Scalar(0, 0, 255), 1, LINE_AA);
}
imshow("result", src);
waitKey(0);
return 0;
}
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