opencv 特徵點匹配 ORB、SURF、SIFT 以及 RANSAC 過濾的範例代碼

void sift1(string name1, string name2){
    Mat img_1 = imread(name1, CV_LOAD_IMAGE_GRAYSCALE);
    Mat img_2 = imread(name2, CV_LOAD_IMAGE_GRAYSCALE);
    Mat img_matches;
    Mat img_test;

    if(!img_1.data || !img_2.data){
        cout << "opencv error" << endl;
        return;
    }

    // cv::Ptr<Feature2D> f2d = xfeatures2d::SIFT::create();
    // cv::Ptr<Feature2D> f2d = xfeatures2d::SURF::create();
    cv::Ptr<Feature2D> f2d = ORB::create();

    //-- Step 1: Detect the keypoints:
    std::vector<KeyPoint> keypoints_1, keypoints_2;
    f2d->detect(img_1, keypoints_1);
    f2d->detect(img_2, keypoints_2);

    img_test = img_1;
    drawKeypoints(img_1, keypoints_1, img_test, Scalar::all(-1));
    imshow("Keypoints", img_test);

    //-- Step 2: Calculate descriptors (feature vectors)    
    Mat descriptors_1, descriptors_2;
    f2d->compute(img_1, keypoints_1, descriptors_1);
    f2d->compute(img_2, keypoints_2, descriptors_2);

    //-- Step 3: Matching descriptor vectors using BFMatcher :
    BFMatcher matcher;
    std::vector< DMatch > matches;
    matcher.match(descriptors_1, descriptors_2, matches);
    drawMatches(img_1, keypoints_1, img_2, keypoints_2,
        matches, img_matches, Scalar::all(-1), Scalar::all(-1),
    std::vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
    imshow("Matches", img_matches);

    //-- Quick calculation of max and min distances between keypoints
    double max_dist = 0; double min_dist = 100;
    for(int i = 0; i < descriptors_1.rows; i++){
        double dist = matches[i].distance;
        if(dist < min_dist) min_dist = dist;
        if(dist > max_dist) max_dist = dist;
    }
    printf("-- Max dist : %f \n", max_dist);
    printf("-- Min dist : %f \n", min_dist);
    //-- Draw only "good" matches (i.e. whose distance is less than 3*min_dist )
    std::vector< DMatch > good_matches;
    for(int i = 0; i < descriptors_1.rows; i++){
        if(matches[i].distance < 3 * min_dist)
            good_matches.push_back(matches[i]);
    }
    drawMatches(img_1, keypoints_1, img_2, keypoints_2,
        good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
        std::vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
    imshow("Good Matches", img_matches);

    vector<DMatch>& Input_matches = matches; // good_matches, matches
    // get feat point
    vector<Point2f> featPoint1;
    vector<Point2f> featPoint2;
    for(size_t i = 0; i < Input_matches.size(); i++){
        //-- Get the keypoints from the good matches
        featPoint1.push_back(keypoints_1[Input_matches[i].queryIdx].pt);
        featPoint2.push_back(keypoints_2[Input_matches[i].trainIdx].pt);
    }
    // get Homography and RANSAC mask
    vector<char> RANSAC_mask;
    Mat Hog = findHomography(featPoint1, featPoint2, RANSAC, 3, RANSAC_mask, 2000, 0.995);
    drawMatches(img_1, keypoints_1, img_2, keypoints_2,
        Input_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
        RANSAC_mask, DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
    imshow("RANSAC Matches", img_matches);

    waitKey(0);
}

​