simplAR 2: 99 Lines of Code for Augmented Reality with OpenCV using Chessboard

This is a simple program that implements Augmented Reality in OpenCV. This is a follow-up for the previous post that was implemented in the old 1.0 API.

Files:
Download from DsynFLO box folder -  https://app.box.com/s/nh82nmjt2w3fxj85g399

Usage:

cmake .
make
./app

Overlay Image:
Photo by Bharath P.  Zero License.

Pattern:

Source:

//______________________________________________________________________________________
// Program : SimplAR 2 - OpenCV Simple Augmented Reality Program with Chessboard
// Author  : Bharath Prabhuswamy
//______________________________________________________________________________________

#include <iostream>
#include <opencv2/opencv.hpp>

using namespace std;
using namespace cv;

#define CHESSBOARD_WIDTH 6
#define CHESSBOARD_HEIGHT 5
//The pattern actually has 6 x 5 squares, but has 5 x 4 = 20 'ENCLOSED' corners

int main ( int argc, char **argv )
{

 Mat img;
 Mat display = imread("shingani.jpg");
 VideoCapture capture(0);

 Size board_size(CHESSBOARD_WIDTH-1, CHESSBOARD_HEIGHT-1);
    
 vector<Point2f> corners;

 if(display.empty())
 {
  cerr << "ERR: Unable to find overlay image.\n" << endl;
  return -1;
 }
 
 if ( !capture.isOpened() )
 {
  cerr << "ERR: Unable to capture frames from device 0" << endl;
  return -1;
 }
    
    int key = 0;
 
 while(key!='q')
 {
  // Query for a frame from Capture device
  capture >> img;

  Mat cpy_img(img.rows, img.cols, img.type());
  Mat neg_img(img.rows, img.cols, img.type());
  Mat gray;
  Mat blank(display.rows, display.cols, display.type());

        cvtColor(img, gray, CV_BGR2GRAY);
        
  bool flag = findChessboardCorners(img, board_size, corners);

  if(flag == 1)
  {            
   // This function identifies the chessboard pattern from the gray image, saves the valid group of corners
   cornerSubPix(gray, corners, Size(11,11), Size(-1,-1), TermCriteria(CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 30, 0.1));
    
   vector<Point2f> src;   // Source Points basically the 4 end co-ordinates of the overlay image
   vector<Point2f> dst;   // Destination Points to transform overlay image 
   
   src.push_back(Point2f(0,0));
   src.push_back(Point2f(display.cols,0));
   src.push_back(Point2f(display.cols, display.rows));
   src.push_back(Point2f(0, display.rows));
 
   dst.push_back(corners[0]);
   dst.push_back(corners[CHESSBOARD_WIDTH-2]);
   dst.push_back(corners[(CHESSBOARD_WIDTH-1)*(CHESSBOARD_HEIGHT-1)-1]);
   dst.push_back(corners[(CHESSBOARD_WIDTH-1)*(CHESSBOARD_HEIGHT-2)]);
 
   // Compute the transformation matrix, 
   // i.e., transformation required to overlay the display image from 'src' points to 'dst' points on the image
   Mat warp_matrix = getPerspectiveTransform(src, dst);

   blank = Scalar(0);
   neg_img = Scalar(0);        // Image is white when pixel values are zero
   cpy_img = Scalar(0);        // Image is white when pixel values are zero

   bitwise_not(blank,blank);

   // Note the jugglery to augment due to OpenCV's limitation passing two images of DIFFERENT sizes while using "cvWarpPerspective"

   warpPerspective(display, neg_img, warp_matrix, Size(neg_img.cols, neg_img.rows)); // Transform overlay Image to the position - [ITEM1]
   warpPerspective(blank, cpy_img, warp_matrix, Size(cpy_img.cols, neg_img.rows));  // Transform a blank overlay image to position 
   bitwise_not(cpy_img, cpy_img);       // Invert the copy paper image from white to black
   bitwise_and(cpy_img, img, cpy_img);      // Create a "hole" in the Image to create a "clipping" mask - [ITEM2]      
   bitwise_or(cpy_img, neg_img, img);      // Finally merge both items [ITEM1 & ITEM2]
 
  }

  imshow("Camera", img);
  key = cvWaitKey(1); 
 }
    
 destroyAllWindows();
 return 0;
}