Creating yor own corner detector

Goal

In this tutorial you will learn how to:

• Use the OpenCV function cv::cornerEigenValsAndVecs to find the eigenvalues and eigenvectors to determine if a pixel is a corner.
• Use the OpenCV function cv::cornerMinEigenVal to find the minimum eigenvalues for corner detection.
• To implement our own version of the Harris detector as well as the Shi-Tomasi detector, by using the two functions above.

Theory

Code

This tutorial code's is shown lines below. You can also download it from here

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

using namespace cv;
using namespace std;

Mat src, src_gray;
Mat myHarris_dst; Mat myHarris_copy; Mat Mc;
Mat myShiTomasi_dst; Mat myShiTomasi_copy;

int myShiTomasi_qualityLevel = 50;
int myHarris_qualityLevel = 50;
int max_qualityLevel = 100;

double myHarris_minVal; double myHarris_maxVal;
double myShiTomasi_minVal; double myShiTomasi_maxVal;

RNG rng(12345);

const char* myHarris_window = "My Harris corner detector";
const char* myShiTomasi_window = "My Shi Tomasi corner detector";

void myShiTomasi_function( int, void* );
void myHarris_function( int, void* );

int main( int, char** argv )
{
  src = imread( argv[1], 1 );
  cvtColor( src, src_gray, COLOR_BGR2GRAY );

  int blockSize = 3; int apertureSize = 3;

  myHarris_dst = Mat::zeros( src_gray.size(), CV_32FC(6) );
  Mc = Mat::zeros( src_gray.size(), CV_32FC1 );

  cornerEigenValsAndVecs( src_gray, myHarris_dst, blockSize, apertureSize, BORDER_DEFAULT );

  /* calculate Mc */
  for( int j = 0; j < src_gray.rows; j++ )
     { for( int i = 0; i < src_gray.cols; i++ )
          {
            float lambda_1 = myHarris_dst.at<Vec6f>(j, i)[0];
            float lambda_2 = myHarris_dst.at<Vec6f>(j, i)[1];
            Mc.at<float>(j,i) = lambda_1*lambda_2 - 0.04f*pow( ( lambda_1 + lambda_2 ), 2 );
          }
     }

  minMaxLoc( Mc, &myHarris_minVal, &myHarris_maxVal, 0, 0, Mat() );

  /* Create Window and Trackbar */
  namedWindow( myHarris_window, WINDOW_AUTOSIZE );
  createTrackbar( " Quality Level:", myHarris_window, &myHarris_qualityLevel, max_qualityLevel, myHarris_function );
  myHarris_function( 0, 0 );

  myShiTomasi_dst = Mat::zeros( src_gray.size(), CV_32FC1 );
  cornerMinEigenVal( src_gray, myShiTomasi_dst, blockSize, apertureSize, BORDER_DEFAULT );

  minMaxLoc( myShiTomasi_dst, &myShiTomasi_minVal, &myShiTomasi_maxVal, 0, 0, Mat() );

  /* Create Window and Trackbar */
  namedWindow( myShiTomasi_window, WINDOW_AUTOSIZE );
  createTrackbar( " Quality Level:", myShiTomasi_window, &myShiTomasi_qualityLevel, max_qualityLevel, myShiTomasi_function );
  myShiTomasi_function( 0, 0 );

  waitKey(0);
  return(0);
}

void myShiTomasi_function( int, void* )
{
  myShiTomasi_copy = src.clone();

  if( myShiTomasi_qualityLevel < 1 ) { myShiTomasi_qualityLevel = 1; }

  for( int j = 0; j < src_gray.rows; j++ )
     { for( int i = 0; i < src_gray.cols; i++ )
          {
            if( myShiTomasi_dst.at<float>(j,i) > myShiTomasi_minVal + ( myShiTomasi_maxVal - myShiTomasi_minVal )*myShiTomasi_qualityLevel/max_qualityLevel )
              { circle( myShiTomasi_copy, Point(i,j), 4, Scalar( rng.uniform(0,255), rng.uniform(0,255), rng.uniform(0,255) ), -1, 8, 0 ); }
          }
     }
  imshow( myShiTomasi_window, myShiTomasi_copy );
}

void myHarris_function( int, void* )
{
  myHarris_copy = src.clone();

  if( myHarris_qualityLevel < 1 ) { myHarris_qualityLevel = 1; }

  for( int j = 0; j < src_gray.rows; j++ )
     { for( int i = 0; i < src_gray.cols; i++ )
          {
            if( Mc.at<float>(j,i) > myHarris_minVal + ( myHarris_maxVal - myHarris_minVal )*myHarris_qualityLevel/max_qualityLevel )
              { circle( myHarris_copy, Point(i,j), 4, Scalar( rng.uniform(0,255), rng.uniform(0,255), rng.uniform(0,255) ), -1, 8, 0 ); }
          }
     }
  imshow( myHarris_window, myHarris_copy );
}

Explanation

Result