CODEWITHSUNDEEP
c++opencvorb
Anirudh
Anirudh

Reputation: 558

How to stitch two images after calculating their homography

I am trying to stitch two overlapping images in opencv c++. I used ORB for feature matching and I calculated Homography between two images. Now using this Homography matrix I would like to go further to add two Images. But I don't know how to go further. Can any one please tell me the next steps. Code I had written till now is:

detector->detect(img1, kp1,descriptors_img1);
detector->detect(img2, kp2,descriptors_img2);


Ptr<DescriptorExtractor> extractor = ORB::create();
extractor->compute(img1, kp1, descriptors_img1 );
extractor->compute(img2, kp2, descriptors_img2 );

if ( descriptors_img1.empty() )
    cvError(0,"MatchFinder","1st descriptor empty",__FILE__,__LINE__);
if ( descriptors_img2.empty() )
    cvError(0,"MatchFinder","2nd descriptor empty",__FILE__,__LINE__);
descriptors_img1.convertTo(descriptors_img1, CV_32F);
descriptors_img2.convertTo(descriptors_img2, CV_32F);
FlannBasedMatcher matcher;
std::vector<DMatch> matches;
matcher.match(descriptors_img1,descriptors_img2,matches);
double max_dist = 0; double min_dist = 100;

//-- Quick calculation of max and min distances between keypoints
for( int i = 0; i < descriptors_img1.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_img1.rows; i++ )
{
    if( matches[i].distance < 3*min_dist )
    {
        good_matches.push_back( matches[i]);
    }
}
Mat img_matches;
drawMatches(img1,kp1,img2,kp2,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( kp1[ good_matches[i].queryIdx ].pt );
    scene.push_back( kp2[ good_matches[i].trainIdx ].pt );
}

Mat H = findHomography( obj, scene, CV_RANSAC );

Upvotes: 2

Views: 1939

Answers (1)

Lakshya Kejriwal
Lakshya Kejriwal

Reputation: 1388

After calculating the homography matrix, you just need to warp the images and blend them together. This can be done with the warpPerspective function as follows. 

cv::Mat result;

warpPerspective( img1, result, H, cv::Size( img1.cols+img2.cols, img1.rows) );
cv::Mat half(result, cv::Rect(0, 0, img2.cols, img2.rows) );
img2.copyTo(half);

The result is your final stitched image. Hope this solves your problem.

Upvotes: 1

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