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  • OpenCV使用FLANN进行特征点匹配

    使用FLANN进行特征点匹配

    目标

    在本教程中我们将涉及以下内容:

    • 使用 FlannBasedMatcher 接口以及函数 FLANN 实现快速高效匹配( 快速最近邻逼近搜索函数库(Fast Approximate Nearest Neighbor Search Library) )

    理论

    代码

    这个教程的源代码如下所示。你还可以从 以下链接下载得到源代码

    #include <stdio.h>
    #include <iostream>
    #include "opencv2/core/core.hpp"
    #include "opencv2/features2d/features2d.hpp"
    #include "opencv2/highgui/highgui.hpp"
    
    using namespace cv;
    
    void readme();
    
    /** @function main */
    int main( int argc, char** argv )
    {
      if( argc != 3 )
      { readme(); return -1; }
    
      Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
      Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );
    
      if( !img_1.data || !img_2.data )
      { std::cout<< " --(!) Error reading images " << std::endl; return -1; }
    
      //-- Step 1: Detect the keypoints using SURF Detector
      int minHessian = 400;
    
      SurfFeatureDetector detector( minHessian );
    
      std::vector<KeyPoint> keypoints_1, keypoints_2;
    
      detector.detect( img_1, keypoints_1 );
      detector.detect( img_2, keypoints_2 );
    
      //-- Step 2: Calculate descriptors (feature vectors)
      SurfDescriptorExtractor extractor;
    
      Mat descriptors_1, descriptors_2;
    
      extractor.compute( img_1, keypoints_1, descriptors_1 );
      extractor.compute( img_2, keypoints_2, descriptors_2 );
    
      //-- Step 3: Matching descriptor vectors using FLANN matcher
      FlannBasedMatcher matcher;
      std::vector< DMatch > matches;
      matcher.match( descriptors_1, descriptors_2, matches );
    
      double max_dist = 0; double min_dist = 100;
    
      //-- Quick calculation of max and min distances between keypoints
      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 
    ", max_dist );
      printf("-- Min dist : %f 
    ", min_dist );
    
      //-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist )
      //-- PS.- radiusMatch can also be used here.
      std::vector< DMatch > good_matches;
    
      for( int i = 0; i < descriptors_1.rows; i++ )
      { if( matches[i].distance < 2*min_dist )
        { good_matches.push_back( matches[i]); }
      }
    
      //-- Draw only "good" matches
      Mat img_matches;
      drawMatches( img_1, keypoints_1, img_2, keypoints_2,
                   good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
                   vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
    
      //-- Show detected matches
      imshow( "Good Matches", img_matches );
    
      for( int i = 0; i < good_matches.size(); i++ )
      { printf( "-- Good Match [%d] Keypoint 1: %d  -- Keypoint 2: %d  
    ", i, good_matches[i].queryIdx, good_matches[i].trainIdx ); }
    
      waitKey(0);
    
      return 0;
     }
    
     /** @function readme */
     void readme()
     { std::cout << " Usage: ./SURF_FlannMatcher <img1> <img2>" << std::endl; }
    

    解释

    结果

    1. 这里是第一张图特征点检测结果:

      ../../../../_images/Featur_FlannMatcher_Result.jpg
    2. 此外我们通过控制台输出FLANN匹配关键点结果:

      ../../../../_images/Feature_FlannMatcher_Keypoints_Result.jpg

    翻译者

    Shuai Zheng, <kylezheng04@gmail.com>, http://www.cbsr.ia.ac.cn/users/szheng/

    from: http://www.opencv.org.cn/opencvdoc/2.3.2/html/doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.html#feature-flann-matcher

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  • 原文地址:https://www.cnblogs.com/GarfieldEr007/p/5292276.html
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