Finding contours in your image

Goal

In this tutorial you will learn how to:

Theory

Code

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

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

using namespace cv;
using namespace std;

Mat src; Mat src_gray;
int thresh = 100;
int max_thresh = 255;
RNG rng(12345);

void thresh_callback(int, void* );

int main( int, char** argv )
{
  src = imread(argv[1], IMREAD_COLOR);
  if (src.empty())
  {
    cerr << "No image supplied ..." << endl;
    return -1;
  }

  cvtColor( src, src_gray, COLOR_BGR2GRAY );
  blur( src_gray, src_gray, Size(3,3) );

  const char* source_window = "Source";
  namedWindow( source_window, WINDOW_AUTOSIZE );
  imshow( source_window, src );

  createTrackbar( " Canny thresh:", "Source", &thresh, max_thresh, thresh_callback );
  thresh_callback( 0, 0 );

  waitKey(0);
  return(0);
}

void thresh_callback(int, void* )
{
  Mat canny_output;
  vector<vector<Point> > contours;
  vector<Vec4i> hierarchy;

  Canny( src_gray, canny_output, thresh, thresh*2, 3 );
  findContours( canny_output, contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0) );

  Mat drawing = Mat::zeros( canny_output.size(), CV_8UC3 );
  for( size_t i = 0; i< contours.size(); i++ )
     {
       Scalar color = Scalar( rng.uniform(0, 255), rng.uniform(0,255), rng.uniform(0,255) );
       drawContours( drawing, contours, (int)i, color, 2, 8, hierarchy, 0, Point() );
     }

  namedWindow( "Contours", WINDOW_AUTOSIZE );
  imshow( "Contours", drawing );
}

Explanation

Result

Here it is:

_images/Find_Contours_Original_Image.jpg _images/Find_Contours_Result.jpg