#include "opencv2/opencv.hpp"

#include <opencv2/nonfree/nonfree.hpp>//SIFT

#include <opencv2/legacy/legacy.hpp>//BFMatch暴力匹配

#include <vector>

#include<iostream>

using namespace std;

using namespace cv;

void main()

{

    Mat srcImg1 = imread("E://11.jpg");

    Mat srcImg2 = imread("E://22.jpg");

    //定义SIFT特征检测类对象

    SiftFeatureDetector siftDetector;

    //定义KeyPoint变量

    vector<KeyPoint>keyPoints1;

    vector<KeyPoint>keyPoints2;

    //特征点检测

    siftDetector.detect(srcImg1, keyPoints1);

    siftDetector.detect(srcImg2, keyPoints2);

    //绘制特征点(关键点)

    Mat feature_pic1, feature_pic2;

    drawKeypoints(srcImg1, keyPoints1, feature_pic1, Scalar::all(-));

    drawKeypoints(srcImg2, keyPoints2, feature_pic2, Scalar::all(-));

    //显示原图

    //imshow("src1", srcImg1);

    //imshow("src2", srcImg2);

    //显示结果

    imshow("feature1", feature_pic1);

    imshow("feature2", feature_pic2);

    //计算特征点描述符 / 特征向量提取

    SiftDescriptorExtractor descriptor;

    Mat description1;

    descriptor.compute(srcImg1, keyPoints1, description1);

    Mat description2;

    descriptor.compute(srcImg2, keyPoints2, description2);

    cout<<description1.cols<<endl;

    cout<<description1.rows<<endl;

    //进行BFMatch暴力匹配

    BruteForceMatcher<L2<float>>matcher;    //实例化暴力匹配器

    vector<DMatch>matches;   //定义匹配结果变量

    matcher.match(description1, description2, matches);  //实现描述符之间的匹配

    //匹配结果筛选

    nth_element(matches.begin(), matches.begin()+, matches.end());   //提取出前30个最佳匹配结果

    matches.erase(matches.begin()+, matches.end());    //剔除掉其余的匹配结果

    Mat result;

    drawMatches(srcImg1, keyPoints1, srcImg2, keyPoints2, matches, result,  Scalar(, , ), Scalar::all(-));//匹配特征点绿色，单一特征点颜色随机

    imshow("Match_Result", result);

    waitKey();

}

前面代码相同

    //进行BFMatch暴力匹配

    BruteForceMatcher<L2<float>>matcher;    //实例化暴力匹配器

    vector<DMatch>matches;   //定义匹配结果变量

    matcher.match(description1, description2, matches);  //实现描述符之间的匹配

    //计算向量距离的最大值与最小值：距离越小越匹配

    double max_dist=matches[].distance,min_dist=matches[].distance;

    for(int i=; i<description1.rows; i++)

    {

        if(matches.at(i).distance > max_dist)

            max_dist = matches[i].distance;

        if(matches.at(i).distance < min_dist)

            min_dist = matches[i].distance;

    }

    cout<<"min_distance="<<min_dist<<endl;

    cout<<"max_distance="<<max_dist<<endl;

    //匹配结果删选

    vector<DMatch>good_matches;

    for(int i=; i<matches.size(); i++)

    {

        if(matches[i].distance < *min_dist)

            good_matches.push_back(matches[i]);

    }

    Mat result;

    drawMatches(srcImg1, keyPoints1, srcImg2, keyPoints2, good_matches, result,  Scalar(, , ), Scalar::all(-));//匹配特征点绿色，单一特征点颜色随机

    imshow("Match_Result", result);