|
|
|
/**
|
|
|
|
* @file SURF_FlannMatcher
|
|
|
|
* @brief SURF detector + descriptor + FLANN Matcher
|
|
|
|
* @author A. Huaman
|
|
|
|
*/
|
|
|
|
|
|
|
|
#include <stdio.h>
|
|
|
|
#include <iostream>
|
|
|
|
#include "opencv2/core/core.hpp"
|
|
|
|
#include "opencv2/features2d/features2d.hpp"
|
|
|
|
#include "opencv2/highgui/highgui.hpp"
|
|
|
|
#include "opencv2/nonfree/features2d.hpp"
|
|
|
|
|
|
|
|
using namespace cv;
|
|
|
|
|
|
|
|
void readme();
|
|
|
|
|
|
|
|
/**
|
|
|
|
* @function main
|
|
|
|
* @brief Main function
|
|
|
|
*/
|
|
|
|
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 \n", max_dist );
|
|
|
|
printf("-- Min dist : %f \n", 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 \n", 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; }
|