Hey there,
I found the example for feature detection and homography here:
So I copied the code and tried it with my own pictures. But it don't want to work. So I get suitable features in my object image, but in the scene image there are quite to less features for the matching I guess...
int main(int argc, char** argv)
{
Mat img_object = imread("/data/Images/HappyLittleFish_teil.png", CV_LOAD_IMAGE_GRAYSCALE);
Mat img_scene = imread("/data/Images/HappyLittleFish.png", CV_LOAD_IMAGE_GRAYSCALE);
if (!img_object.data || !img_scene.data)
{
std::cout << " --(!) Error reading images " << std::endl; return -1;
}
//-- Step 1: Detect the keypoints using SURF Detector
Ptr<FeatureDetector> detector = FeatureDetector::create("ORB");
std::vector<KeyPoint> keypoints_object, keypoints_scene;
detector->detect(img_object, keypoints_object);
detector->detect(img_scene, keypoints_scene);
//-- Step 2: Calculate descriptors (feature vectors)
Ptr<DescriptorExtractor> extractor = DescriptorExtractor::create("ORB");
Mat descriptors_object, descriptors_scene;
extractor->compute(img_object, keypoints_object, descriptors_object);
extractor->compute(img_scene, keypoints_scene, descriptors_scene);
//-- Step 3: Matching descriptor vectors
Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create("BruteForce-Hamming");
std::vector< DMatch > matches;
matcher->match(descriptors_object, descriptors_scene, matches);
double max_dist = 0; double min_dist = 100;
//-- Quick calculation of max and min distances between keypoints
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;
}
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 3*min_dist )
std::vector< DMatch > good_matches;
for (int i = 0; i < descriptors_object.rows; i++)
{
if (matches[i].distance < 8 * min_dist)
{
good_matches.push_back(matches[i]);
}
}
Mat img_matches;
drawMatches(img_object, keypoints_object, img_scene, keypoints_scene,
good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
//-- Localize the object
std::vector<Point2f> obj;
std::vector<Point2f> scene;
for (int i = 0; i < good_matches.size(); i++)
{
//-- Get the keypoints from the good matches
obj.push_back(keypoints_object[good_matches[i].queryIdx].pt);
scene.push_back(keypoints_scene[good_matches[i].trainIdx].pt);
}
Mat H = findHomography(obj, scene, CV_RANSAC);
//-- Get the corners from the image_1 ( the object to be "detected" )
std::vector<Point2f> obj_corners(4);
obj_corners[0] = cvPoint(0, 0);
obj_corners[1] = cvPoint(img_object.cols, 0);
obj_corners[2] = cvPoint(img_object.cols, img_object.rows);
obj_corners[3] = cvPoint(0, img_object.rows);
std::vector<Point2f> scene_corners(4);
perspectiveTransform(obj_corners, scene_corners, H);
//-- Draw lines between the corners (the mapped object in the scene - image_2 )
line(img_matches, scene_corners[0] + Point2f(img_object.cols, 0), scene_corners[1] + Point2f(img_object.cols, 0), Scalar(0, 255, 0), 4);
line(img_matches, scene_corners[1] + Point2f(img_object.cols, 0), scene_corners[2] + Point2f(img_object.cols, 0), Scalar(0, 255, 0), 4);
line(img_matches, scene_corners[2] + Point2f(img_object.cols, 0), scene_corners[3] + Point2f(img_object.cols, 0), Scalar(0, 255, 0), 4);
line(img_matches, scene_corners[3] + Point2f(img_object.cols, 0), scene_corners[0] + Point2f(img_object.cols, 0), Scalar(0, 255, 0), 4);
//-- Show detected matches
namedWindow( "img", WINDOW_NORMAL );
imshow("img", img_matches);
waitKey(0);
return 0;
}
My scene image is HappyLittleFish.png
The object image is just a part from the scene image like the fin of the fish.
So does anyone knows were the problem is??
