opencv3/C++ FLANN特征匹配

使用函数detectAndCompute(）检测关键点并计算描述符
函数detectAndCompute(）参数说明：

void detectAndCompute(
InputArray image, //图像
InputArray mask, //掩模
CV_OUT std::vector<KeyPoint>& keypoints,//输出关键点的集合
OutputArray descriptors,//计算描述符（descriptors[i]是为keypoints[i]的计算描述符）
bool useProvidedKeypoints=false //使用提供的关键点
);


match(）从查询集中查找每个描述符的最佳匹配。
参数说明：

void match(
InputArray queryDescriptors, //查询描述符集
InputArray trainDescriptors, //训练描述符集合
CV_OUT std::vector<DMatch>& matches, //匹配
InputArray mask=noArray() //指定输入查询和描述符的列表矩阵之间的允许匹配的掩码
) const;



FLANN特征匹配示例：

#include<opencv2/opencv.hpp>
#include<opencv2/xfeatures2d.hpp>
using namespace cv;
using namespace cv::xfeatures2d;

//FLANN对高维数据较快
int main()
{
    Mat src1,src2;
    src1 = imread("E:/image/image/card2.jpg");
    src2 = imread("E:/image/image/cards.jpg");
    if (src1.empty() || src2.empty())
    {
        printf("can ont load images....\n");
        return -1;
    }
    imshow("image1", src1);
    imshow("image2", src2);

    int minHessian = 400;
    //选择SURF特征
    Ptr<SURF>detector = SURF::create(minHessian);
    std::vector<KeyPoint>keypoints1;
    std::vector<KeyPoint>keypoints2;
    Mat descriptor1, descriptor2;
    //检测关键点并计算描述符
    detector->detectAndCompute(src1, Mat(), keypoints1, descriptor1);
    detector->detectAndCompute(src2, Mat(), keypoints2, descriptor2);

    //基于Flann的描述符匹配器
    FlannBasedMatcher matcher;
    std::vector<DMatch>matches;
    //从查询集中查找每个描述符的最佳匹配
    matcher.match(descriptor1, descriptor2, matches);
    double minDist = 1000;
    double maxDist = 0;
    for (int i = 0; i < descriptor1.rows; i++)
    {
        double dist = matches[i].distance;
        printf("%f \n", dist);
        if (dist > maxDist)
        {
            maxDist = dist;
        }
        if (dist < minDist)
        {
            minDist = dist;
        }

    }
    //DMatch类用于匹配关键点描述符的
    std::vector<DMatch>goodMatches;
    for (int i = 0; i < descriptor1.rows; i++)
    {
        double dist = matches[i].distance;
        if (dist < max(2.5*minDist, 0.02))
        {
            goodMatches.push_back(matches[i]);
        }
    }
    Mat matchesImg;
    drawMatches(src1, keypoints1, src2, keypoints2, goodMatches, matchesImg, Scalar::all(-1), Scalar::all(-1), std::vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);
    imshow("output", matchesImg);

    waitKey();
    return 0;
}