opencv2基于SURF特征提取实现两张图像拼接融合

// Display the images显示图像cv::namedWindow("Image 1");cv::imshow("Image 1",image1);cv::namedWindow("Image 2");cv::imshow("Image 2",image2);

// Prepare the matcher准备匹配RobustMatcher rmatcher;rmatcher.setConfidenceLevel(0.98);rmatcher.setMinDistanceToEpipolar(1.0);rmatcher.setRatio(0.65f);cv::Ptr pfd= new cv::SurfFeatureDetector(10);rmatcher.setFeatureDetector(pfd);

// Match the two images std::vector matches;std::vector keypoints1, keypoints2;cv::Mat fundemental= rmatcher.match(image1,image2,matches, keypoints1, keypoints2);

// draw the matches画匹配结果cv::Mat imageMatches;cv::drawMatches(image1,keypoints1, // 1st image and its keypoints第一张图像及其关键点image2,keypoints2, // 2nd image and its keypoints第二张图像及其关键点matches, // the matches匹配结果imageMatches, // the image produced产生的图像cv::Scalar(255,255,255)); // color of the lines线的颜色cv::namedWindow("Matches");cv::imshow("Matches",imageMatches);

// Convert keypoints into Point2f将关键点转换为Point2f std::vector points1, points2;for (std::vector::const_iterator it= matches.begin();it!= matches.end(); ++it) {H

// Get the position of left keypoints得到左图关键点位置float x= keypoints1[it->queryIdx].pt.x;float y= keypoints1[it->queryIdx].pt.y;points1.push_back(cv::Point2f(x,y));// Get the position of right keypoints得到右图关键点位置x= keypoints2[it->trainIdx].pt.x;y= keypoints2[it->trainIdx].pt.y;points2.push_back(cv::Point2f(x,y));}

std::cout << points1.size() << " " << points2.size() << std::endl;

// Find the homography between image 1 and image 2找到图像1和图像2之间的单应性矩阵std::vector inliers(points1.size(),0);cv::Mat homography= cv::findHomography(cv::Mat(points1),cv::Mat(points2), // corresponding points对应点inliers, // outputed inliers matches 输出内点匹配CV_RANSAC, // RANSAC method RANSAC 方法1.); // max distance to reprojection point到对应点的最大距离

// Draw the inlier points画内点std::vector::const_iterator itPts= points1.begin();std::vector::const_iterator itIn= inliers.begin();while (itPts!=points1.end()) {

// draw a circle at each inlier location在每一个内点画一个圈if (*itIn) cv::circle(image1,*itPts,3,cv::Scalar(255,255,255),2);

++itPts;++itIn;}

itPts= points2.begin();itIn= inliers.begin();while (itPts!=points2.end()) {

// draw a circle at each inlier location在每一个内点画一个圈if (*itIn) cv::circle(image2,*itPts,3,cv::Scalar(255,255,255),2);

++itPts;++itIn;}

// Display the images with points显示画点的图像cv::namedWindow("Image 1 Homography Points");cv::imshow("Image 1 Homography Points",image1);cv::namedWindow("Image 2 Homography Points");cv::imshow("Image 2 Homography Points",image2);

// Warp image 1 to image 2变形图像1到图像2 cv::Mat result;cv::warpPerspective(image1, // input image输入的图像result, // output image输出的图像homography, // homography单应性矩阵cv::Size(2*image1.cols,image1.rows)); // size of output image输出图像的大小

// Copy image 1 on the first half of full image复制图像1的上一部分cv::Mat half(result,cv::Rect(0,0,image2.cols,image2.rows));image2.copyTo(half);

// Display the warp image显示变形后图像cv::namedWindow("After warping");cv::imshow("After warping",result);