目标

在本教程中，您将学习如何：

• 使用OpenCV函数cv :: cornerSubPix查找更准确的corners位置（比整数像素更准确）。

Code

本教程代码如下所示。您也可以从这里下载

#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>
using namespace cv;
using namespace std;
Mat src, src_gray;
int maxCorners = 10;
int maxTrackbar = 25;
RNG rng(12345);
const char* source_window = "Image";
void goodFeaturesToTrack_Demo( int, void* );
int main( int, char** argv )
{
  src = imread( argv[1], IMREAD_COLOR );
  cvtColor( src, src_gray, COLOR_BGR2GRAY );
  namedWindow( source_window, WINDOW_AUTOSIZE );
  createTrackbar( "Max  corners:", source_window, &maxCorners, maxTrackbar, goodFeaturesToTrack_Demo );
  imshow( source_window, src );
  goodFeaturesToTrack_Demo( 0, 0 );
  waitKey(0);
  return(0);
}
void goodFeaturesToTrack_Demo( int, void* )
{
  if( maxCorners < 1 ) { maxCorners = 1; }
  vector<Point2f> corners;
  double qualityLevel = 0.01;
  double minDistance = 10;
  int blockSize = 3, gradiantSize = 3;
  bool useHarrisDetector = false;
  double k = 0.04;
  Mat copy;
  copy = src.clone();
  goodFeaturesToTrack( src_gray,
               corners,
               maxCorners,
               qualityLevel,
               minDistance,
               Mat(),
               blockSize,
               gradiantSize,
               useHarrisDetector,
               k );
  cout<<"** Number of corners detected: "<<corners.size()<<endl;
  int r = 4;
  for( size_t i = 0; i < corners.size(); i++ )
     { circle( copy, corners[i], r, Scalar(rng.uniform(0,255), rng.uniform(0,255), rng.uniform(0,255)), -1, 8, 0 ); }
  namedWindow( source_window, WINDOW_AUTOSIZE );
  imshow( source_window, copy );
  Size winSize = Size( 5, 5 );
  Size zeroZone = Size( -1, -1 );
  TermCriteria criteria = TermCriteria( TermCriteria::EPS + TermCriteria::COUNT, 40, 0.001 );
  cornerSubPix( src_gray, corners, winSize, zeroZone, criteria );
  for( size_t i = 0; i < corners.size(); i++ )
     { cout<<" -- Refined Corner ["<<i<<"]  ("<<corners[i].x<<","<<corners[i].y<<")"<<endl; }

结果

这是结果：