########## Features2D ########## .. highlight:: cpp Detection of planar objects =========================== 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], CV_LOAD_IMAGE_GRAYSCALE); Mat img2 = imread(argv[2], CV_LOAD_IMAGE_GRAYSCALE); #. Detect keypoints in both images. :: // detecting keypoints FastFeatureDetector detector(15); vector keypoints1; detector.detect(img1, keypoints1); ... // do the same for the second image #. 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 #. Now, find the closest matches between descriptors from the first image to the second: :: // matching descriptors BruteForceMatcher > matcher; vector 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 points1, points2; // fill the arrays with the points .... Mat H = findHomography(Mat(points1), Mat(points2), CV_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.