Fab*_*oni 2 opencv computer-vision surf feature-detection flann
我是OpenCV的新手.我正试图在iOS上的OpenCV中使用FLANN/SURF在图像之间绘制功能匹配.我正在关注这个例子:
这是我的代码,稍加一些修改(将示例中的代码包装在一个函数中,该函数返回一个UIImage作为结果并从bundle中读取起始图像):
UIImage* SURFRecognition::test()
{
UIImage *img1 = [UIImage imageNamed:@"wallet"];
UIImage *img2 = [UIImage imageNamed:@"wallet2"];
Mat img_1;
Mat img_2;
UIImageToMat(img1, img_1);
UIImageToMat(img2, img_2);
if( !img_1.data || !img_2.data )
{
std::cout<< " --(!) Error reading images " << std::endl;
}
//-- Step 1: Detect the keypoints using SURF Detector
int minHessian = 400;
SurfFeatureDetector detector( minHessian );
std::vector<KeyPoint> keypoints_1, keypoints_2;
detector.detect( img_1, keypoints_1 );
detector.detect( img_2, keypoints_2 );
//-- Step 2: Calculate descriptors (feature vectors)
SurfDescriptorExtractor extractor;
Mat descriptors_1, descriptors_2;
extractor.compute( img_1, keypoints_1, descriptors_1 );
extractor.compute( img_2, keypoints_2, descriptors_2 );
//-- Step 3: Matching descriptor vectors using FLANN matcher
FlannBasedMatcher matcher;
std::vector< DMatch > matches;
matcher.match( descriptors_1, descriptors_2, matches );
double max_dist = 0; double min_dist = 100;
//-- Quick calculation of max and min distances between keypoints
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 );
//-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist )
//-- PS.- radiusMatch can also be used here.
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]); }
}
//-- Draw only "good" matches
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 );
//-- Show detected matches
//imshow( "Good Matches", img_matches );
UIImage *imgTemp = MatToUIImage(img_matches);
for( int i = 0; i < good_matches.size(); i++ )
{
printf( "-- Good Match [%d] Keypoint 1: %d -- Keypoint 2: %d \n", i, good_matches[i].queryIdx, good_matches[i].trainIdx );
}
return imgTemp;
}
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结果我上面的函数是:

仅显示连接匹配的行,但不显示原始图像.如果我理解得很好,那么drawMatches函数会返回一个包含图像和相似特征之间连接的cv :: Mat.这是正确的还是我遗失了什么?有人能帮我吗?
我自己找到了解决方案.经过大量搜索后,似乎drawMatches需要img1和img2与1到3通道.我用alpha开了一个PNGa,所以这些是4通道图像.这是我的代码审查:
添加
UIImageToMat(img1, img_1);
UIImageToMat(img2, img_2);
cvtColor(img_1, img_1, CV_BGRA2BGR);
cvtColor(img_2, img_2, CV_BGRA2BGR);
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