使用sift特征点进行knn最近邻匹配

 1 #include 
 2 #include 
 3 #include 
 4 #include 
 5 #include 
 6 
 7 
 8 using namespace cv;
 9 using namespace std;
10 
11 int main(int argc, char** argv)
12 {
13     Mat img1 = imread(argv[1]);
14     Mat img2 = imread(argv[2]);
15     vector keypoints_1, keypoints_2;
16     Mat descriptor_1, descriptor_2;
17     Ptr sift = xfeatures2d::SIFT::create(0, 3, 0.04, 10);
18 
19     sift->detectAndCompute(img1, noArray(), keypoints_1, descriptor_1);
20     sift->detectAndCompute(img2, noArray(), keypoints_2, descriptor_2);
21     cout<< keypoints_1.size()<<" "<endl;
22     Mat outimg1;
23     drawKeypoints(img1, keypoints_1, outimg1, Scalar::all(-1), DrawMatchesFlags::DEFAULT);
24     imshow("KeyPoint", outimg1);
25 
26     vector matches;
27     vector> knn_matches;
28 
29     BFMatcher matcher(NORM_L2);
30     matcher.knnMatch(descriptor_1, descriptor_2, knn_matches, 2);
31 
32     for (size_t r = 0; r < knn_matches.size(); ++r)
33     {
34         if (knn_matches[r][0].distance > 0.8*knn_matches[r][1].distance ) continue;
35         matches.push_back(knn_matches[r][0]);
36     }
37 
38     Mat img_match;
39     Mat img_goodmatch;
40     drawMatches (img1, keypoints_1, img2, keypoints_2, matches, img_goodmatch);
41     imshow("good match", img_goodmatch);
42     waitKey(0);
43     
44     return 0;
45 
46 }

输入两张图像

提取sift特征点

 

使用knnmatch进行最近邻匹配

 

转载于:https://www.cnblogs.com/feifanrensheng/p/9390697.html