stitch two images in opencv C++ - c++

Question

I want to make a musaic image by stitching some images.
I am doing this by sift features.
when I stitch the following two images :
img1
img2
I achieve this result. as you can see the images are not aligned completely and there is a gap between them. Can you tell me what is the problem and how can I solve it?
Here is my function that I used for stitching :
Mat StitchVertical(Mat& imGrayImg1, Mat& imGrayImg2)
{
Mat GrayImg1(imGrayImg1, Rect(0, 0, imGrayImg1.cols, imGrayImg1.rows)); // init roi
Mat GrayImg2(imGrayImg2, Rect(0, 0, imGrayImg2.cols, imGrayImg2.rows));
cvtColor(GrayImg1, GrayImg1, COLOR_BGR2GRAY);
cvtColor(GrayImg2, GrayImg2, COLOR_BGR2GRAY);
vector<cv::KeyPoint> keypointsImg1, keypointsImg2;
Mat descriptorImg1, descriptorImg2;
BFMatcher matcher;
vector<cv::DMatch> matches, good_matches;
cv::Ptr<cv::SIFT> sift = cv::SIFT::create();
int i, dist = 80;
sift->detectAndCompute(GrayImg1, cv::Mat(), keypointsImg1, descriptorImg1); /* get keypoints of ROI image */
sift->detectAndCompute(GrayImg2, cv::Mat(), keypointsImg2, descriptorImg2); /* get keypoints of the image */
matcher.match(descriptorImg1, descriptorImg2, matches); // Matching between descriptors
double max_dist = 0; double min_dist = 5000;
for (int i = 0; i < descriptorImg1.rows; i++)
{
double dist = matches[i].distance;
if (dist < min_dist) min_dist = dist;
if (dist > max_dist) max_dist = dist;
}
for (i = 0; i < descriptorImg1.rows; i++)
{
if (matches[i].distance < 3 * min_dist)
{
good_matches.push_back(matches[i]);
}
}
Mat img_matches;
// Draw match
drawMatches(imGrayImg1, keypointsImg1, imGrayImg2, keypointsImg2,
good_matches, img_matches, Scalar::all(-1),
Scalar::all(-1), vector<char>(),
DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
//imshow("matches", img_matches);
vector<Point2f> keypoints1, keypoints2;
for (i = 0; i < good_matches.size(); i++)
{
keypoints1.push_back(keypointsImg2[good_matches[i].trainIdx].pt);
keypoints2.push_back(keypointsImg1[good_matches[i].queryIdx].pt);
}
Mat H, H2;
H = findHomography(keypoints1, keypoints2, RANSAC);
H2 = findHomography(keypoints2, keypoints1, RANSAC);
Mat stitchedImage;
int mRows = imGrayImg2.cols;
if (imGrayImg1.cols > imGrayImg2.cols)
{
mRows = imGrayImg1.cols;
}
int count = 0;
for (int i = 0; i < keypoints2.size(); i++)
{
if (keypoints2[i].y >= imGrayImg2.rows / 3) { count++; }
}
int minx,miny;
if (count / float(keypoints2.size()) >= 0.5) // To be spliced imGrayImg2 The image is on the right
{
cout << "imGrayImg1 should left" << endl;
vector<Point2f>corners(4);
vector<Point2f>corners2(4);
corners[0] = Point(0, 0);
corners[1] = Point(0, imGrayImg2.rows);
corners[2] = Point(imGrayImg2.cols, imGrayImg2.rows);
corners[3] = Point(imGrayImg2.cols, 0);
stitchedImage = Mat::zeros( mRows, imGrayImg2.rows + imGrayImg1.rows, CV_8UC3);
warpPerspective(imGrayImg2, stitchedImage, H, Size(mRows, imGrayImg1.cols + imGrayImg2.cols));
perspectiveTransform(corners, corners2, H);
Mat half(stitchedImage, Rect(0, 0, imGrayImg1.cols, imGrayImg1.rows));
imGrayImg1.copyTo(half);
minx = stitchedImage.size().width;
miny = stitchedImage.size().height;
if ((int(corners2[2].x) - 10) < stitchedImage.size().width) {
minx = (int(corners2[2].x) - 10);
}
if ((int(corners2[2].y) - 10) < stitchedImage.size().height) {
miny = (int(corners2[2].y) - 10);
}
Rect crop_region(0, 0, minx, miny);
Mat cropped_image = stitchedImage(crop_region);
return cropped_image;
}
else
{
cout << "imGrayImg2 should be up" << endl;
stitchedImage = Mat::zeros(mRows, imGrayImg2.rows + imGrayImg1.rows, CV_8UC3);
warpPerspective(imGrayImg1, stitchedImage, H2, Size(mRows, imGrayImg1.cols + imGrayImg2.cols));
//imshow("temp", stitchedImage);
vector<Point2f>corners(4);
vector<Point2f>corners2(4);
corners[0] = Point(0, 0);
corners[1] = Point(0, imGrayImg1.rows);
corners[2] = Point(imGrayImg1.cols, imGrayImg1.rows);
corners[3] = Point(imGrayImg1.cols, 0);
cout << "second if in up and down" << endl;
perspectiveTransform(corners, corners2, H2); // Affine transformations correspond to endpoints
Mat half(stitchedImage, Rect(0, 0, imGrayImg2.cols, imGrayImg2.rows));
imGrayImg2.copyTo(half);
minx = stitchedImage.size().width;
miny = stitchedImage.size().height;
if ((int(corners2[2].x) - 10) < stitchedImage.size().width) {
minx = (int(corners2[2].x) - 10);
}
if ((int(corners2[2].y) - 10) < stitchedImage.size().height) {
miny = (int(corners2[2].y) - 10);
}
Rect crop_region(0, 0, minx, miny);
Mat cropped_image = stitchedImage(crop_region); return cropped_image;
}
imwrite("result.bmp", stitchedImage);
return stitchedImage;
}