私はこのチュートリアルに基づいていくつかのiamgemathchingを行っています
http://docs.opencv.org/doc/tutorials/features2d/feature_homography/feature_homography.html
単独でもうまく機能しますが、関数に入れてメイン関数から呼び出すと、ヒープが破損します。プログラムは画像を表示し、スペースを押してプログラムを閉じると、画像が壊れます。
int main(int argc, char ** argv)
{
// Part 2 panorama
Mat im1=imread("panorama_image1.jpg", CV_LOAD_IMAGE_GRAYSCALE);
Mat im2=imread("panorama_image2.jpg", CV_LOAD_IMAGE_GRAYSCALE);
immosaic(im1,im2);
return 0;
}
そしてこれはチュートリアルからコピーされたモザイク関数です
void immosaic(Mat im_object, Mat im_scene)
{
//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 400;
SurfFeatureDetector detector( minHessian );
std::vector<KeyPoint> keypoints_object, keypoints_scene;
detector.detect( im_object, keypoints_object );
detector.detect( im_scene, keypoints_scene );
//-- Step 2: Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor;
Mat descriptors_object, descriptors_scene;
extractor.compute( im_object, keypoints_object, descriptors_object );
extractor.compute( im_scene, keypoints_scene, descriptors_scene );
//-- Step 3: Matching descriptor vectors using FLANN matcher
FlannBasedMatcher matcher;
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;
}
//-- 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 < 3*min_dist )
good_matches.push_back( matches[i]);
}
Mat img_matches;
drawMatches( im_object, keypoints_object, im_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( im_object.cols, 0 );
obj_corners[2] = cvPoint( im_object.cols, im_object.rows ); obj_corners[3] = cvPoint( 0, im_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( im_object.cols, 0), scene_corners[1] + Point2f( im_object.cols, 0), Scalar(0, 255, 0), 4 );
line( img_matches, scene_corners[1] + Point2f( im_object.cols, 0), scene_corners[2] + Point2f( im_object.cols, 0), Scalar( 0, 255, 0), 4 );
line( img_matches, scene_corners[2] + Point2f( im_object.cols, 0), scene_corners[3] + Point2f( im_object.cols, 0), Scalar( 0, 255, 0), 4 );
line( img_matches, scene_corners[3] + Point2f( im_object.cols, 0), scene_corners[0] + Point2f( im_object.cols, 0), Scalar( 0, 255, 0), 4 );
//-- Show detected matches
namedWindow("Matching");
imshow( "Matching", img_matches );
waitKey(0);
//return 0;
}