Detection of planar objects

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Original author	Victor Eruhimov
Compatibility	OpenCV >= 3.0

The goal of this tutorial is to learn how to use features2d and calib3d modules for detecting known planar objects in scenes.

Test data: use images in your data folder, for instance, box.png and box_in_scene.png.

• Create a new console project. Read two input images. :

  Mat img1 = imread(argv[1], IMREAD_GRAYSCALE);
  Mat img2 = imread(argv[2], IMREAD_GRAYSCALE);
  

• Detect keypoints in both images and compute descriptors for each of the keypoints. :

  // detecting keypoints
  Ptr<Feature2D> surf = SURF::create();
  vector<KeyPoint> keypoints1;
  Mat descriptors1;
  surf->detectAndCompute(img1, Mat(), keypoints1, descriptors1);
  
  ... // do the same for the second image
  

• Now, find the closest matches between descriptors from the first image to the second: :

  // matching descriptors
  BruteForceMatcher<L2<float> > matcher;
  vector<DMatch> matches;
  matcher.match(descriptors1, descriptors2, matches);
  

• Visualize the results: :

  // drawing the results
  namedWindow("matches", 1);
  Mat img_matches;
  drawMatches(img1, keypoints1, img2, keypoints2, matches, img_matches);
  imshow("matches", img_matches);
  waitKey(0);
  

• Find the homography transformation between two sets of points: :

  vector<Point2f> points1, points2;
  // fill the arrays with the points
  ....
  Mat H = findHomography(Mat(points1), Mat(points2), RANSAC, ransacReprojThreshold);
  

• Create a set of inlier matches and draw them. Use perspectiveTransform function to map points with homography:

  Mat points1Projected; perspectiveTransform(Mat(points1), points1Projected, H);

• Use drawMatches for drawing inliers.