#include "stdafx.h"
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv2/legacy/legacy.hpp"
#include "iostream"
#include "time.h"
using namespace cv;

int main( )
{
	long time = clock();
	Mat image1 = imread("F://army//person.jpg");
	Mat image2 = imread("F://army//person4.jpg");
	// 检测surf特征点
	vector<KeyPoint> keypoints1, keypoints2;
	SurfFeatureDetector detector(700);
	detector.detect(image1, keypoints1);
	detector.detect(image2, keypoints2);
	// 计算特征描述点
	SurfDescriptorExtractor surfDesc;
	Mat descriptros1, descriptros2;
	surfDesc.compute(image1, keypoints1, descriptros1);
	surfDesc.compute(image2, keypoints2, descriptros2);
	// 计算匹配点数
	BruteForceMatcher<L2<float>>matcher;
	vector<DMatch> matches;
	matcher.match(descriptros1, descriptros2, matches);//匹配特征向量
	// 对找到的匹配特征向量进行二分排序,将匹配度强的n个向量放到前面
	std::nth_element(matches.begin(), matches.begin() + 4, matches.end());
	matches.erase(matches.begin() + 5, matches.end());//擦除排序在阈值后面的所有匹配点
	// 画出匹配图
	Mat imageMatches;
	drawMatches(image1, keypoints1, image2, keypoints2, matches,imageMatches, Scalar(255, 0, 0));//进行绘制
	//获得并打印两张图匹配点的坐标
	vector<DMatch> ::iterator itor;//容器迭代器  
	printf("左边图像\n");
	itor = matches.begin();
	while (itor != matches.end())
	{
		printf("x:%.2f,y:%.2f\n", keypoints1[itor->queryIdx].pt.x, keypoints1[itor->queryIdx].pt.y);
		itor++;
	}
	printf("右边图像\n");
	itor = matches.begin();
	while (itor != matches.end())
	{
		printf("x:%.2f,y:%.2f\n", keypoints2[itor->trainIdx].pt.x, keypoints2[itor->trainIdx].pt.y);//注意这里用的是trainIdx，其保存着右边图像匹配点的序号，而上边的queryIdx保存着左边图像匹配点的序号
		itor++;
	}
	printf("匹配花费时间%dms", clock() - time);
	imshow("image2", imageMatches);
	//printf("\n%d",matches.end()-matches.begin());
	waitKey();
	return 0;
}

总结：可以自定义输出匹配坐标个数，可以用来直观的显示两张图片的相似之处，但输出比较单一，无法输出具体数值判断相似程度，适用于数量较少图片判断。