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# Detecting corners location in subpixeles

## Goal

In this tutorial you will learn how to:

- Use the OpenCV function cornerSubPix to find more exact corner positions (more exact than integer pixels).

## Theory

## Code

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

    #include "opencv2/highgui.hpp"
    #include "opencv2/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, COLOR_BGR2GRAY );

      /// Create Window
      namedWindow( source_window, 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++ )
         { circle( copy, corners[i], r, Scalar(rng.uniform(0,255), rng.uniform(0,255),
                                                     rng.uniform(0,255)), -1, 8, 0 ); }

      /// Show what you got
      namedWindow( source_window, WINDOW_AUTOSIZE );
      imshow( source_window, copy );

      /// Set the neeed parameters to find the refined corners
      Size winSize = Size( 5, 5 );
      Size zeroZone = Size( -1, -1 );
      TermCriteria criteria = TermCriteria( TermCriteria::EPS + TermCriteria::MAX_ITER, 40, 0.001 );

      /// Calculate the refined corner locations
      cornerSubPix( src_gray, corners, winSize, zeroZone, criteria );

      /// Write them down
      for( int i = 0; i < corners.size(); i++ )
         { cout<<" -- Refined Corner ["<<i<<"]  ("<<corners[i].x<<","<<corners[i].y<<")"<<endl; }
    }

## Explanation

## Result

Here is the result:

## Help and Feedback

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### Navigation

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- next |
- previous |
- OpenCV 3.0.0-dev documentation »
- OpenCV Tutorials »
- feature2d module. 2D Features framework »