I have a problem went I use findHomography in first times it work. (stitching image1 and image2)
But when I warpPerspective third image with homography it show result in this picture.
My sorcecode
#include <iostream>
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv2/nonfree/features2d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
using namespace cv;
using namespace std;
void readme();
int main( int argc, char** argv )
{
if( argc != 5 ){ readme(); return -1; }
Mat image = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE);
Mat image1 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE);
Mat image2 = imread( argv[3], CV_LOAD_IMAGE_GRAYSCALE);
Mat featureImage = imread( argv[4], CV_LOAD_IMAGE_GRAYSCALE);
cv::Mat result;
// Construct the SURF feature detector object
cv::SurfFeatureDetector surf(2300); // threshold
// Construction of the SURF descriptor extractor
cv::SurfDescriptorExtractor surfDesc;
Mat right_Image;
Mat left_Image;
std::vector<cv::KeyPoint> right_keypoints, left_keypoints;
cv::Mat left_descriptors, right_descriptors;
FlannBasedMatcher matcher;
std::vector<DMatch> matches;
std::vector< DMatch > good_matches;
std::vector<Point2f> obj;
std::vector<Point2f> scene;
Mat H;
for(int i=0;i<2;i++){
if(i==0){
right_Image = image1;
left_Image = image;
}else if(i>=1){
right_Image = image2;
left_Image = result;
result.release();
}else{
exit(-1);
}
///////////////////////////////// image 0 ////////////////////////////////////
// Detect the SURF features
surf.detect(right_Image,right_keypoints);
std::cout << "right_keypoints : " << right_keypoints.size() << '\n';
surfDesc.compute(right_Image,right_keypoints,right_descriptors);
// Draw the keypoints with scale and orientation information
cv::drawKeypoints(right_Image, // original image
right_keypoints, // vector of keypoints
featureImage, // the resulting image
cv::Scalar(255,255,255), // color of the points
cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS); //flag
////////////////////////////// end image 0 //////////////////////////////////
///////////////////////////////// image 0 ////////////////////////////////////
// Detect the SURF features
surf.detect(left_Image,left_keypoints);
std::cout << "left_keypoints : " << left_keypoints.size() << '\n';
surfDesc.compute(left_Image,left_keypoints,left_descriptors);
// Draw the keypoints with scale and orientation information
cv::drawKeypoints(left_Image, // original image
left_keypoints, // vector of keypoints
featureImage, // the resulting image
cv::Scalar(255,255,255), // color of the points
cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS); //flag
////////////////////////////// end image 0 //////////////////////////////////
/////////////////////////// Match image & image1 ////////////////////////////
//-- Step 3: Matching descriptor vectors using FLANN matcher
matcher.match(right_descriptors, left_descriptors, matches);
std::cout << "matches : " << matches.size() << '\n';
double max_dist = 0; double min_dist = 100;
//-- Quick calculation of max and min distances between keypoints
for( int j = 0; j < right_descriptors.rows; j++ )
{
double dist = matches[j].distance;
if( dist < min_dist ) min_dist = dist;
if( dist > max_dist ) max_dist = dist;
}
printf("-- Max dist image & image1 : %f \n", max_dist );
printf("-- Min dist image & image1 : %f \n", min_dist );
//-- Draw only "good" matches (i.e. whose distance is less than 3*min_dist )
for(int j = 0; j < right_descriptors.rows; j++)
{
if(matches[j].distance <= 3*min_dist)
{
good_matches.push_back(matches[j]);
}
}
std::cout << "good_matches : " << good_matches.size() << '\n';
Mat img_matches;
drawMatches( right_Image, right_keypoints, left_Image, left_keypoints,
good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
//-- Localize the object
for( int j = 0; j < good_matches.size(); j++ )
{
//-- Get the keypoints from the good matches
obj.push_back( right_keypoints[ good_matches[j].queryIdx ].pt );
scene.push_back( left_keypoints[ good_matches[j].trainIdx ].pt );
}
H = findHomography( obj, scene, CV_RANSAC, 1. );
cout << "H = "<< endl << " " << H << endl << endl;
// Warp image 1 to image 2
cv::warpPerspective(right_Image, // input image
result, // output image
H, // homography
cv::Size(2*right_Image.cols, right_Image.rows));
if(i == 1){
imshow( "Good Matches & Object detection", result);
}
// Copy image 1 on the first half of full image
cv::Mat half(result,cv::Rect(0,0,left_Image.cols,left_Image.rows));
left_Image.copyTo(half); // copy image2 to image1 roi
//-- Show detected matches
matches.clear();
good_matches.clear();
obj.clear();
scene.clear();
}
waitKey(0);
return 0;
}
/**
* @function readme
*/
void readme()
{ std::cout << " Usage: ./BallMatch <input1> <input2> <output>" << std::endl; }
Thank!! and sorry about my bad language.
