我正在尝试使用 ORB 进行检测和 FLANN 进行匹配,使用 OpenCV 提取和匹配特征,我得到了一个非常奇怪的结果。加载我的 2 张图像并将它们转换为灰度后,这是我的代码:
// Initiate ORB detector
Ptr<FeatureDetector> detector = ORB::create();
// find the keypoints and descriptors with ORB
detector->detect(gray_image1, keypoints_object);
detector->detect(gray_image2, keypoints_scene);
Ptr<DescriptorExtractor> extractor = ORB::create();
extractor->compute(gray_image1, keypoints_object, descriptors_object );
extractor->compute(gray_image2, keypoints_scene, descriptors_scene );
// Flann needs the descriptors to be of type CV_32F
descriptors_scene.convertTo(descriptors_scene, CV_32F);
descriptors_object.convertTo(descriptors_object, CV_32F);
FlannBasedMatcher matcher;
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;
}
//-- Use only "good" matches (i.e. whose distance is less than 3*min_dist )
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]);
}
}
vector< Point2f > obj;
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 );
}
// Find the Homography Matrix
Mat H = findHomography( obj, scene, CV_RANSAC );
// Use the Homography Matrix to warp the images
cv::Mat result;
warpPerspective(image1,result,H,Size(image1.cols+image2.cols,image1.rows));
cv::Mat half(result,cv::Rect(0,0,image2.cols,image2.rows));
image2.copyTo(half);
imshow( "Result", result );
这是我得到的奇怪结果的屏幕截图:屏幕截图
可能有什么问题?
谢谢!
您正在经历错误匹配的结果:拟合数据的单应性不"真实",因此扭曲了图像。
您可以调试与imshow( "Good Matches", img_matches );
的匹配,如示例中所示。
有多种方法可以改善匹配:
- 使用交叉检查选项
- 使用 SIFT 比率测试
- 使用 cv::findHompgraphy 中的 OutputArray
mask
来识别完全错误的单应性计算 - 。等等...
ORB 是不适用于 Flann 的二进制特征向量。请改用蛮力(BFMatcher)。