int method = 0;
std::vector<cv::KeyPoint> keypoints_object, keypoints_scene;
cv::Mat descriptors_object, descriptors_scene;
cv::ORB orb;
int minHessian = 500;
cv::OrbFeatureDetector detector(25, 1.0f, 2, 10, 0, 2, 0, 10);
cv::OrbDescriptorExtractor extractor;
if( method == 0 ) {
orb.detect(img_object, keypoints_object);
orb.compute(img_object, keypoints_object, descriptors_object);
} else {
detector.detect(img_object, keypoints_object);
extractor.compute(img_object, keypoints_object, descriptors_object);
}
cv::Mat frame = cv::imread("E:\\Projects\\Images\\2-134-2.bmp", 1);
cv::Mat img_scene = cv::Mat(frame.size(), CV_8UC1);
cv::cvtColor(frame, img_scene, cv::COLOR_RGB2GRAY);
if( method == 0 ) {
orb.detect(img_scene, keypoints_scene);
orb.compute(img_scene, keypoints_scene, descriptors_scene);
} else {
detector.detect(img_scene, keypoints_scene);
extractor.compute(img_scene, keypoints_scene, descriptors_scene);
}
cv::BFMatcher matcher;
std::vector<cv::DMatch> matches;
cv::Mat img_matches;
if(!descriptors_object.empty() && !descriptors_scene.empty()) {
matcher.match (descriptors_object, descriptors_scene, matches);
double max_dist = 0; double min_dist = 100;
for( int i = 0; i < descriptors_object.rows; i++)
{ double dist = matches[i].distance;
if( dist < min_dist ) min_dist = dist;
if( dist > max_dist ) max_dist = dist;
}
std::vector< cv::DMatch >good_matches;
for( int i = 0; i < descriptors_object.rows; i++ )
{ if( matches[i].distance < (max_dist/1.6) )
{ good_matches.push_back( matches[i]); }
}
cv::drawMatches(img_object, keypoints_object, img_scene, keypoints_scene, \
good_matches, img_matches, cv::Scalar::all(-1), cv::Scalar::all(-1),
std::vector<char>(), cv::DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
std::vector<cv::Point2f> obj;
std::vector<cv::Point2f> scene;
for( size_t i = 0; i < good_matches.size(); i++) {
obj.push_back( keypoints_object[ good_matches[i].queryIdx ].pt );
scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );
}
if( !obj.empty() && !scene.empty() && good_matches.size() >= 4) {
cv::Mat H = cv::findHomography( obj, scene, cv::RANSAC );
std::vector<cv::Point2f> obj_corners(4);
obj_corners[0] = cv::Point(0,0);
obj_corners[1] = cv::Point(img_object.cols,0);
obj_corners[2] = cv::Point(img_object.cols,img_object.rows);
obj_corners[3] = cv::Point(0,img_object.rows);
std::vector<cv::Point2f> scene_corners(4);
cv::perspectiveTransform( obj_corners, scene_corners, H);
cv::line( img_matches, \
scene_corners[0] + cv::Point2f(img_object.cols, 0), \
scene_corners[1] + cv::Point2f(img_object.cols, 0), \
cv::Scalar(0,255,0), 4 );
cv::line( img_matches, \
scene_corners[1] + cv::Point2f(img_object.cols, 0), \
scene_corners[2] + cv::Point2f(img_object.cols, 0), \
cv::Scalar(0,255,0), 4 );
cv::line( img_matches, \
scene_corners[2] + cv::Point2f(img_object.cols, 0), \
scene_corners[3] + cv::Point2f(img_object.cols, 0), \
cv::Scalar(0,255,0), 4 );
cv::line( img_matches, \
scene_corners[3] + cv::Point2f(img_object.cols, 0), \
scene_corners[0] + cv::Point2f(img_object.cols, 0), \
cv::Scalar(0,255,0), 4 );
}
}
Here I am performing template matching between two Images. where I extract key points using ORB algorithm and matching that with BF Matcher but I am not getting good result. Here I am adding Image to understand problem Finding Object Image from frame Image. Here as you can see Dark Blue line on teddy which is actually a rectangle which would be drawn around object from frame Image when object will be recognized by matching key points. Here I am using Opencv 2.4.9, what changes should I make to get good result?