Detection of planar objectsΒΆ

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.

1. Create a new console project. Read two input images.

```Mat img1 = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE);
```
2. Detect keypoints in both images.

```// detecting keypoints
FastFeatureDetector detector(15);
vector<KeyPoint> keypoints1;
detector.detect(img1, keypoints1);

... // do the same for the second image
```
3. Compute descriptors for each of the keypoints.

```// computing descriptors
SurfDescriptorExtractor extractor;
Mat descriptors1;
extractor.compute(img1, keypoints1, descriptors1);

... // process keypoints from the second image as well
```
4. 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);
```
5. 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);
```
6. 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), CV_RANSAC, ransacReprojThreshold);
```
7. Create a set of inlier matches and draw them. Use perspectiveTransform function to map points with homography:

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

8. Use drawMatches for drawing inliers.

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