OpenCV  3.1.0-dev
Open Source Computer Vision
Harris corner detector

Goal

In this tutorial you will learn:

Theory

What is a feature?

Types of Image Features

To mention a few:

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

Why is a corner so special?

How does it work?

Code

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

#include <iostream>
using namespace cv;
using namespace std;
Mat src, src_gray;
int thresh = 200;
int max_thresh = 255;
const char* source_window = "Source image";
const char* corners_window = "Corners detected";
void cornerHarris_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( "Threshold: ", source_window, &thresh, max_thresh, cornerHarris_demo );
imshow( source_window, src );
cornerHarris_demo( 0, 0 );
waitKey(0);
return(0);
}
void cornerHarris_demo( int, void* )
{
Mat dst, dst_norm, dst_norm_scaled;
dst = Mat::zeros( src.size(), CV_32FC1 );
int blockSize = 2;
int apertureSize = 3;
double k = 0.04;
cornerHarris( src_gray, dst, blockSize, apertureSize, k, BORDER_DEFAULT );
normalize( dst, dst_norm, 0, 255, NORM_MINMAX, CV_32FC1, Mat() );
convertScaleAbs( dst_norm, dst_norm_scaled );
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 );
}
}
}
namedWindow( corners_window, WINDOW_AUTOSIZE );
imshow( corners_window, dst_norm_scaled );
}

Explanation

Result

The original image:

Harris_Detector_Original_Image.jpg

The detected corners are surrounded by a small black circle

Harris_Detector_Result.jpg