\u5728FLANN\u7279\u5fb5\u4e0a\uff0c\u9084\u53ef\u4ee5\u9032\u4e00\u6b65\u5229\u7528Homography\u6620\u5c04\u627e\u51fa\u5df2\u77e5\u7269\u9ad4\u3002
\n\u5c31\u662f\u5229\u7528findHomography\u51fd\u6578\uff0c\u5229\u7528\u5339\u914d\u7684\u95dc\u9375\u9ede\u627e\u51fa\u76f8\u61c9\u7684\u8b8a\u63db\uff0c\u518d\u5229\u7528perspectiveTransform\u51fd\u6578\u6620\u5c04\u9ede\u7fa4\u3002<\/p>\n
\r\n#include <stdio.h>\r\n#include <iostream>\r\n#include <opencv2\/core\/core.hpp>\r\n#include <opencv2\/features2d\/features2d.hpp>\r\n#include <opencv2\/nonfree\/features2d.hpp>\r\n#include <opencv2\/highgui\/highgui.hpp>\r\n#include <opencv2\/calib3d\/calib3d.hpp>\r\n#include <opencv2\/nonfree\/nonfree.hpp>\r\n\r\n\r\nusing namespace cv;\r\n\r\nvoid readme();\r\n\r\n\/** @function main *\/\r\nint main( int argc, char** argv )\r\n{\r\n \r\n \r\n Mat img_1 = imread( "\/Users\/powenko\/Desktop\/doughnut.png", CV_LOAD_IMAGE_GRAYSCALE );\r\n Mat img_2 = imread( "\/Users\/powenko\/Desktop\/doughnuts.png", CV_LOAD_IMAGE_GRAYSCALE );\r\n \r\n \r\n Mat img_object =img_1; \/\/ imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );\r\n Mat img_scene = img_2; \/\/imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );\r\n \r\n if( !img_object.data || !img_scene.data )\r\n { std::cout<< " --(!) Error reading images " << std::endl; return -1; }\r\n \r\n \/\/-- Step 1: Detect the keypoints using SURF Detector\r\n int minHessian = 400;\r\n \r\n SurfFeatureDetector detector( minHessian );\r\n \r\n std::vector<KeyPoint> keypoints_object, keypoints_scene;\r\n \r\n detector.detect( img_object, keypoints_object );\r\n detector.detect( img_scene, keypoints_scene );\r\n \r\n \/\/-- Step 2: Calculate descriptors (feature vectors)\r\n SurfDescriptorExtractor extractor;\r\n \r\n Mat descriptors_object, descriptors_scene;\r\n \r\n extractor.compute( img_object, keypoints_object, descriptors_object );\r\n extractor.compute( img_scene, keypoints_scene, descriptors_scene );\r\n \r\n \/\/-- Step 3: Matching descriptor vectors using FLANN matcher\r\n FlannBasedMatcher matcher;\r\n std::vector< DMatch > matches;\r\n matcher.match( descriptors_object, descriptors_scene, matches );\r\n \r\n double max_dist = 0; double min_dist = 100;\r\n \r\n \/\/-- Quick calculation of max and min distances between keypoints\r\n for( int i = 0; i < descriptors_object.rows; i++ )\r\n { double dist = matches[i].distance;\r\n if( dist < min_dist ) min_dist = dist;\r\n if( dist > max_dist ) max_dist = dist;\r\n }\r\n \r\n printf("-- Max dist : %f \\n", max_dist );\r\n printf("-- Min dist : %f \\n", min_dist );\r\n \r\n \/\/-- Draw only "good" matches (i.e. whose distance is less than 3*min_dist )\r\n std::vector< DMatch > good_matches;\r\n \r\n for( int i = 0; i < descriptors_object.rows; i++ )\r\n { if( matches[i].distance < 3*min_dist )\r\n { good_matches.push_back( matches[i]); }\r\n }\r\n \r\n Mat img_matches;\r\n drawMatches( img_object, keypoints_object, img_scene, keypoints_scene,\r\n good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),\r\n vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );\r\n \r\n \/\/-- Localize the object\r\n std::vector<Point2f> obj;\r\n std::vector<Point2f> scene;\r\n \r\n for( int i = 0; i < good_matches.size(); i++ )\r\n {\r\n \/\/-- Get the keypoints from the good matches\r\n obj.push_back( keypoints_object[ good_matches[i].queryIdx ].pt );\r\n scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );\r\n }\r\n \r\n Mat H = findHomography( obj, scene, CV_RANSAC );\r\n \r\n \/\/-- Get the corners from the image_1 ( the object to be "detected" )\r\n std::vector<Point2f> obj_corners(4);\r\n obj_corners[0] = cvPoint(0,0); obj_corners[1] = cvPoint( img_object.cols, 0 );\r\n obj_corners[2] = cvPoint( img_object.cols, img_object.rows ); obj_corners[3] = cvPoint( 0, img_object.rows );\r\n std::vector<Point2f> scene_corners(4);\r\n \r\n perspectiveTransform( obj_corners, scene_corners, H);\r\n \r\n \/\/-- Draw lines between the corners (the mapped object in the scene - image_2 )\r\n line( img_matches, scene_corners[0] + Point2f( img_object.cols, 0), scene_corners[1] + Point2f( img_object.cols, 0), Scalar(0, 255, 0), 4 );\r\n line( img_matches, scene_corners[1] + Point2f( img_object.cols, 0), scene_corners[2] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );\r\n line( img_matches, scene_corners[2] + Point2f( img_object.cols, 0), scene_corners[3] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );\r\n line( img_matches, scene_corners[3] + Point2f( img_object.cols, 0), scene_corners[0] + Point2f( img_object.cols, 0), Scalar( 0, 255, 0), 4 );\r\n \r\n \/\/-- Show detected matches\r\n imshow( "Good Matches & Object detection", img_matches );\r\n \r\n waitKey(0);\r\n return 0;\r\n}\r\n\r\n\/** @function readme *\/\r\nvoid readme()\r\n{ std::cout << " Usage: .\/SURF_descriptor <img1> <img2>" << std::endl; }\r\n<\/pre>\n![\"screen-shot-2016-12-02-at-8-45-54-pm\"](\"httpss:\/\/www.powenko.com\/wordpress\/wp-content\/uploads\/2016\/12\/Screen-Shot-2016-12-02-at-8.45.54-PM.png\")
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