使用sift特征点进行knn最近邻匹配

 #include <opencv2/xfeatures2d/nonfree.hpp>

 #include <opencv2/features2d/features2d.hpp>

 #include <opencv2/highgui/highgui.hpp>

 #include <opencv2/calib3d/calib3d.hpp>

 #include <iostream>

 using namespace cv;

 using namespace std;

 int main(int argc, char** argv)

 {

     Mat img1 = imread(argv[]);

     Mat img2 = imread(argv[]);

     vector<KeyPoint> keypoints_1, keypoints_2;

     Mat descriptor_1, descriptor_2;

     Ptr<Feature2D> sift = xfeatures2d::SIFT::create(, , 0.04, );

     sift->detectAndCompute(img1, noArray(), keypoints_1, descriptor_1);

     sift->detectAndCompute(img2, noArray(), keypoints_2, descriptor_2);

     cout<< keypoints_1.size()<<" "<<keypoints_2.size()<<endl;

     Mat outimg1;

     drawKeypoints(img1, keypoints_1, outimg1, Scalar::all(-), DrawMatchesFlags::DEFAULT);

     imshow("KeyPoint", outimg1);

     vector<DMatch> matches;

     vector<vector<DMatch>> knn_matches;

     BFMatcher matcher(NORM_L2);

     matcher.knnMatch(descriptor_1, descriptor_2, knn_matches, );

     for (size_t r = ; r < knn_matches.size(); ++r)

     {

         if (knn_matches[r][].distance > 0.8*knn_matches[r][].distance ) continue;

         matches.push_back(knn_matches[r][]);

     }

     Mat img_match;

     Mat img_goodmatch;

     drawMatches (img1, keypoints_1, img2, keypoints_2, matches, img_goodmatch);

     imshow("good match", img_goodmatch);

     waitKey();

     return ;

 }

输入两张图像

提取sift特征点

使用knnmatch进行最近邻匹配