OpenCV Tutorials —— Detection of planar objects

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这篇教程其实是上一篇的总结 ，利用 features2d 和 calib3d 模块来发掘场景中的物体 ~~

1. 1, 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);

2. 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. 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. 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. 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. 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. 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. 8,Use drawMatches for drawing inliers.

OpenCV Tutorials —— Detection of planar objects

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原文地址：http://www.cnblogs.com/sprint1989/p/4125583.html