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 );
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]); }
}
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 );
imshow( "Good Matches", img_matches );
在FLANN特征匹配的基础上，还可以进一步利用Homography映射找出已知物体。具体来说就是利用findHomography函数利用匹配的关键点找出相应的变换，再利用perspectiveTransform函数映射点群。具体代码如下：
-
- std::vector<Point2f> obj;
- std::vector<Point2f> scene;
-
- for( int i = 0; i < good_matches.size(); i++ )
- {
-
- obj.push_back( keypoints_1[ good_matches[i].queryIdx ].pt );
- scene.push_back( keypoints_2[ good_matches[i].trainIdx ].pt );
- }
-
- Mat H = findHomography( obj, scene, CV_RANSAC );
