OpenCV教程(48) 特征值匹配

OpenCV中通过下面的代码，可以匹配两幅的图像的特征值。

// Read input images
cv::Mat image1= cv::imread("../church01.jpg",0);
cv::Mat image2= cv::imread("../church02.jpg",0);
if (!image1.data || !image2.data)
return 0;

// Display the images
cv::namedWindow("Right Image");
cv::imshow("Right Image",image1);
cv::namedWindow("Left Image");
cv::imshow("Left Image",image2);

// vector of keypoints
std::vector<cv::KeyPoint> keypoints1;
std::vector<cv::KeyPoint> keypoints2;

// Construction of the SURF feature detector
cv::SurfFeatureDetector surf(3000);

// Detection of the SURF features
surf.detect(image1,keypoints1);
surf.detect(image2,keypoints2);

std::cout << "Number of SURF points (1): " << keypoints1.size() << std::endl;
std::cout << "Number of SURF points (2): " << keypoints2.size() << std::endl;

// Draw the kepoints
cv::Mat imageKP;
cv::drawKeypoints(image1,keypoints1,imageKP,cv::Scalar(255,255,255),cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
cv::namedWindow("Right SURF Features");
cv::imshow("Right SURF Features",imageKP);
cv::drawKeypoints(image2,keypoints2,imageKP,cv::Scalar(255,255,255),cv::DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
cv::namedWindow("Left SURF Features");
cv::imshow("Left SURF Features",imageKP);

// Construction of the SURF descriptor extractor
cv::SurfDescriptorExtractor surfDesc;

// Extraction of the SURF descriptors
cv::Mat descriptors1, descriptors2;
surfDesc.compute(image1,keypoints1,descriptors1);
surfDesc.compute(image2,keypoints2,descriptors2);

std::cout << "descriptor matrix size: " << descriptors1.rows << " by " << descriptors1.cols << std::endl;

// Construction of the matcher
cv::BruteForceMatcher<cv::L2<float>> matcher;

// Match the two image descriptors
std::vector<cv::DMatch> matches;
matcher.match(descriptors1,descriptors2, matches);

std::cout << "Number of matched points: " << matches.size() << std::endl;

std::nth_element(matches.begin(),    // initial position
    matches.begin()+24, // position of the sorted element
    matches.end());     // end position
// remove all elements after the 25th
matches.erase(matches.begin()+25, matches.end());

cv::Mat imageMatches;
cv::drawMatches(image1,keypoints1, // 1st image and its keypoints
    image2,keypoints2, // 2nd image and its keypoints
    matches,            // the matches
    imageMatches,        // the image produced
    cv::Scalar(255,255,255)); // color of the lines
cv::namedWindow("Matches");
cv::imshow("Matches",imageMatches);

程序执行后匹配图如下：