模糊图像有助于找到代码中的交叉点
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
using namespace cv;
int main( int argc, char** argv )
{
Mat src = imread( argv[1] );
Mat gray, blurred;
cvtColor( src, gray, COLOR_BGR2GRAY );
threshold( gray, gray, 127, 255, THRESH_BINARY );
GaussianBlur( gray, blurred, Size(), 9 );
threshold( blurred, blurred, 200, 255, THRESH_BINARY_INV );
gray.setTo( 255, blurred );
imshow("result",gray);
waitKey();
return 0;
}
结果图片:
第二步
简单来说,借用generalContours_demo2.cpp的代码
#include "opencv2/imgproc.hpp"
#include "opencv2/highgui.hpp"
using namespace cv;
using namespace std;
int main( int argc, char** argv )
{
Mat src = imread( argv[1] );
Mat gray, blurred;
cvtColor( src, gray, COLOR_BGR2GRAY );
threshold( gray, gray, 127, 255, THRESH_BINARY );
GaussianBlur( gray, blurred, Size(), 5 );
threshold( blurred, blurred, 180, 255, THRESH_BINARY_INV );
gray.setTo( 255, blurred );
imshow("result of step 1",gray);
vector<vector<Point> > contours;
/// Find contours
findContours( gray.clone(), contours, RETR_TREE, CHAIN_APPROX_SIMPLE );
/// Find the rotated rectangles and ellipses for each contour
vector<RotatedRect> minRect( contours.size() );
vector<RotatedRect> minEllipse( contours.size() );
for( size_t i = 0; i < contours.size(); i++ )
{
minRect[i] = minAreaRect( Mat(contours[i]) );
if( contours[i].size() > 5 )
{
minEllipse[i] = fitEllipse( Mat(contours[i]) );
}
}
/// Draw contours + rotated rects + ellipses
for( size_t i = 0; i< contours.size(); i++ )
{
Mat drawing = src.clone();
// contour
//drawContours( drawing, contours, (int)i, color, 1, 8, vector<Vec4i>(), 0, Point() );
// ellipse
ellipse( drawing, minEllipse[i], Scalar( 0, 0, 255 ), 2 );
// rotated rectangle
Point2f rect_points[4];
minRect[i].points( rect_points );
for( int j = 0; j < 4; j++ )
line( drawing, rect_points[j], rect_points[(j+1)%4], Scalar( 0, 255, 0 ), 2 );
/// Show in a window
imshow( "results of step 2", drawing );
waitKey();
}
return 0;
}
您可以获得以下结果图像。我希望你能解决最后一步。