sift匹配描述子距离判断选择更好的匹配点

    opencv中自带的sift函数，就不过多解释了。

    网上太多的大咖，已经都快写烂了，各种函数调用很简单的啦。下面我说一种关于，描述子匹配时，距离判断从而选择更加优良的点！

#include<opencv2/opencv.hpp>
#include<opencv2/features2d/features2d.hpp>
#include<opencv2/nonfree/nonfree.hpp>
#include<opencv2/legacy/legacy.hpp>
#include<vector>
using namespace std;
using namespace cv;

int main(void)
{
Mat img = imread("C:\\Users\\Lvmeng\\Desktop\\photo-sample\\map1.png");
Mat img2 = imread("C:\\Users\\Lvmeng\\Desktop\\photo-sample\\map2.png");

//显示图像
imshow("image before", img);
imshow("image2 before", img2);

//sift特征检测
SiftFeatureDetector  siftdtc;
vector<KeyPoint>kp1, kp2;
siftdtc.detect(img, kp1);
Mat outimg1;
drawKeypoints(img, kp1, outimg1);
imshow("image1 keypoints", outimg1);

siftdtc.detect(img2, kp2);
Mat outimg2;
drawKeypoints(img2, kp2, outimg2);
imshow("image2 keypoints", outimg2);

SiftDescriptorExtractor extractor;
Mat descriptor1, descriptor2;
BruteForceMatcher<L2<float>> matcher;
vector<DMatch> matches;
Mat img_matches;
extractor.compute(img, kp1, descriptor1);
extractor.compute(img2, kp2, descriptor2);

// imshow("desc", descriptor1);
// imshow("desc2", descriptor2);
//cout << endl << descriptor1 << endl;
matcher.match(descriptor1, descriptor2, matches);

double max_dist = 0; double min_dist = 100;

//-- Quick calculation of max and min distances between keypoints
for (int i = 0; i < descriptor1.rows; i++)
{
double dist = matches[i].distance;
if (dist < min_dist) min_dist = dist;
if (dist > max_dist) max_dist = dist;
}

std::vector< DMatch > good_matches;

for (int i = 0; i <descriptor1.rows; i++)    //判断距离从而选择更加优良的点进行匹配
{
if (matches[i].distance < 1.3 * min_dist)   //1.3进行修改可以对描述子匹配进行优化！！
{
good_matches.push_back(matches[i]);
}
}

drawMatches(img, kp1, img2, kp2,
good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);

imshow("Result", img_matches);

//此函数等待按键，按键盘任意键就返回
waitKey();
return 0;
}

实验环境：opencv2.43+VS2013。好像是的，不对你再试试呗！

当值设为3的时候，各种的描述子匹配，一头雾水。有不有想撞豆腐的冲动？

设置之后！很清晰嘛！看着自己都觉得爽歪歪了！！

切记，值不能设太小呦，要是做匹配1.5刚刚好！！