surf特征检测描述和匹配

#include <stdio.h>#include <iostream>#include "opencv2/core/core.hpp"#include "opencv2/features2d/features2d.hpp"#include "opencv2/highgui/highgui.hpp"#include <opencv2/nonfree/features2d.hpp>#include<opencv2/legacy/legacy.hpp>using namespace cv;using namespace std;void readme();/** @function main */int main(int argc, char** argv){Mat img_1 = imread("color52.bmp", CV_LOAD_IMAGE_GRAYSCALE);Mat img_2 = imread("color51.bmp", CV_LOAD_IMAGE_GRAYSCALE);if (!img_1.data || !img_2.data){return -1;}//-- Step 1: Detect the keypoints using SURF Detectorint minHessian = 400;SurfFeatureDetector detector(minHessian);//定义最大特征数400std::vector<KeyPoint> keypoints_1, keypoints_2;//OpenCV里为角点检测提供了统一的接口，通过类下面的detect方法来检测对应的角点，而输出格式都是vector<KeyPoint>detector.detect(img_1, keypoints_1);//特征检测detector.detect(img_2, keypoints_2);//-- Step 2: Calculate descriptors (feature vectors)SurfDescriptorExtractor extractor;Mat descriptors_1, descriptors_2;extractor.compute(img_1, keypoints_1, descriptors_1);//提取SURF特征点以及其描述extractor.compute(img_2, keypoints_2, descriptors_2);//-- Step 3: Matching descriptor vectors with a brute force matcher计算匹配点数BruteForceMatcher< L2<float> > matcher;std::vector< DMatch > matches;matcher.match(descriptors_1, descriptors_2, matches);/*void match(const Mat& queryDescriptors, const Mat& trainDescriptors,CV_OUT vector<DMatch>& matches, const Mat& mask = Mat()) const;*///匹配点向量和画图int w = img_1.cols;int h = img_1.rows;Mat showImg(h, 2*w, CV_8UC1, Scalar(0, 0, 0));img_1.copyTo(showImg(Rect(0, 0, w,h)));img_2.copyTo(showImg(Rect(w, 0, w,h)));vector<Point2f> feture_matche[2];for (int i = 0; i < matches.size(); ++i){Point2f p1 = keypoints_1[matches[i].queryIdx].pt;//matches[i].queryIdx第i个匹配的特征点的索引，通过索引获得这个特征点在图一特征向量中的坐标Point2f p2 = keypoints_2[matches[i].trainIdx].pt;p2.x += w;CvScalar color = CV_RGB(rand() % 255, rand() % 255, rand() % 255);line(showImg, p1, p2, color);//int g = matches[i].distance;//将匹配点保存在feture_mache2维向量中feture_matche[0].push_back(p1);//未分配内存所以不能使用feture_matche[0][i]=p1feture_matche[1].push_back(p2);}for (int i = 0; i < feture_matche[0].size(); i++)cout << "图1已经匹配的特征点坐标p1" << i << "=" << feture_matche[0][i] << "  " << "图2已经匹配的特征点坐标p2" << i << "=" << feture_matche[1][i] << endl;cout << matches.size() << " " << feture_matche[0].size() << "  " << feture_matche[1].size() << endl;//这三个数是相等的imshow("match", showImg);//只提取25个匹配点并画出std::nth_element(matches.begin(), matches.begin() + 24, matches.end());matches.erase(matches.begin() + 25, matches.end());//-- Draw matchesMat img_matches;drawMatches(img_1, keypoints_1, img_2, keypoints_2, matches, img_matches,Scalar(255, 0, 0));//未定义颜色则将画出不同颜色匹配线条//-- Show detected matchesimshow("Matches", img_matches);waitKey(0);return 0;}/** @function readme */