OpenCV亚像素级的角点检测

目标

在本教程中我们将涉及以下内容:

• 使用OpenCV函数 cornerSubPix 寻找更精确的角点位置 (不是整数类型的位置，而是更精确的浮点类型位置).

理论

代码

这个教程的代码如下所示。源代码还可以从 这个链接下载得到

#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include <iostream>
#include <stdio.h>
#include <stdlib.h>

using namespace cv;
using namespace std;

/// Global variables
Mat src, src_gray;

int maxCorners = 10;
int maxTrackbar = 25;

RNG rng(12345);
char* source_window = "Image";

/// Function header
void goodFeaturesToTrack_Demo( int, void* );

/** @function main */
int main( int argc, char** argv )
{
  /// Load source image and convert it to gray
  src = imread( argv[1], 1 );
  cvtColor( src, src_gray, CV_BGR2GRAY );

  /// Create Window
  namedWindow( source_window, CV_WINDOW_AUTOSIZE );

  /// Create Trackbar to set the number of corners
  createTrackbar( "Max  corners:", source_window, &maxCorners, maxTrackbar, goodFeaturesToTrack_Demo);

  imshow( source_window, src );

  goodFeaturesToTrack_Demo( 0, 0 );

  waitKey(0);
  return(0);
}

/**
 * @function goodFeaturesToTrack_Demo.cpp
 * @brief Apply Shi-Tomasi corner detector
 */
void goodFeaturesToTrack_Demo( int, void* )
{
  if( maxCorners < 1 ) { maxCorners = 1; }

  /// Parameters for Shi-Tomasi algorithm
  vector<Point2f> corners;
  double qualityLevel = 0.01;
  double minDistance = 10;
  int blockSize = 3;
  bool useHarrisDetector = false;
  double k = 0.04;

  /// Copy the source image
  Mat copy;
  copy = src.clone();

  /// Apply corner detection
  goodFeaturesToTrack( src_gray,
                       corners,
                       maxCorners,
                       qualityLevel,
                       minDistance,
                       Mat(),
                       blockSize,
                       useHarrisDetector,
                       k );


  /// Draw corners detected
  cout<<"** Number of corners detected: "<<corners.size()<<endl;
  int r = 4;
  for( int i = 0; i < corners.size(); i++ )
     {