Harris corner detector

Goal

In this tutorial you will learn:

• What features are and why they are important
• Use the function cornerHarris to detect corners using the Harris-Stephens method.

Theory

What is a feature?

• In computer vision, usually we need to find matching points between different frames of an environment. Why? If we know how two images relate to each other, we can use both images to extract information of them.
• When we say matching points we are referring, in a general sense, to characteristics in the scene that we can recognize easily. We call these characteristics features.
• So, what characteristics should a feature have?
  • It must be uniquely recognizable

Types of Image Features

To mention a few:

• Edges
• Corner (also known as interest points)
• Blobs (also known as regions of interest )

In this tutorial we will study the corner features, specifically.

Why is a corner so special?

Code

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

#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 thresh = 200;
int max_thresh = 255;

char* source_window = "Source image";
char* corners_window = "Corners detected";

/// Function header
void cornerHarris_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 a window and a trackbar
  namedWindow( source_window, CV_WINDOW_AUTOSIZE );
  createTrackbar( "Threshold: ", source_window, &thresh, max_thresh, cornerHarris_demo );
  imshow( source_window, src );

  cornerHarris_demo( 0, 0 );

  waitKey(0);
  return(0);
}

/** @function cornerHarris_demo */
void cornerHarris_demo( int, void* )
{

  Mat dst, dst_norm, dst_norm_scaled;
  dst = Mat::zeros( src.size(), CV_32FC1 );

  /// Detector parameters
  int blockSize = 2;
  int apertureSize = 3;
  double k = 0.04;

  /// Detecting corners
  cornerHarris( src_gray, dst, blockSize, apertureSize, k, BORDER_DEFAULT );

  /// Normalizing
  normalize( dst, dst_norm, 0, 255, NORM_MINMAX, CV_32FC1, Mat() );
  convertScaleAbs( dst_norm, dst_norm_scaled );

  /// Drawing a circle around corners
  for( int j = 0; j < dst_norm.rows ; j++ )
     { for( int i = 0; i < dst_norm.cols; i++ )
          {
            if( (int) dst_norm.at<float>(j,i) > thresh )
              {
               circle( dst_norm_scaled, Point( i, j ), 5,  Scalar(0), 2, 8, 0 );
              }
          }
     }
  /// Showing the result
  namedWindow( corners_window, CV_WINDOW_AUTOSIZE );
  imshow( corners_window, dst_norm_scaled );
}

Explanation

Result

The original image:

The detected corners are surrounded by a small black circle