【OpenCV学习笔记】三十七、特征检测与匹配(二)——SIFT特征点匹配

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特征检测与匹配(二)——SIFT特征点匹配

1.SIFT特征点提取

2.绘制特征点

3.特征点描述符(特征向量)提取

4.使用暴力匹配器进行暴力匹配

5.对匹配结果进行筛选（依据DMatch结构体中的float类型变量distance进行筛选）

6.绘制匹配结果

先上ppt：

代码：SIFT特征点匹配

///SIFT特征点匹配#include "opencv2/opencv.hpp"using namespace cv;#include "opencv2/nonfree/nonfree.hpp"//SIFT相关#include "opencv2/legacy/legacy.hpp"//匹配器相关#include <iostream>using namespace std;int main(){//1.SIFT特征点提取——detect()方法Mat srcImg1 = imread("1.jpg", CV_LOAD_IMAGE_COLOR);Mat srcImg2 = imread("2.jpg", CV_LOAD_IMAGE_COLOR);Mat dstImg1, dstImg2;SiftFeatureDetector siftDetector;//SiftFeatureDetector是SIFT类的别名  vector<KeyPoint> keyPoints1;vector<KeyPoint> keyPoints2;siftDetector.detect(srcImg1, keyPoints1);siftDetector.detect(srcImg2, keyPoints2);drawKeypoints(srcImg1, keyPoints1, dstImg1);drawKeypoints(srcImg2, keyPoints2, dstImg2);imshow("dstImg1", dstImg1);imshow("dstImg2", dstImg2);//2.特征点描述符(特征向量)提取——compute()方法SiftDescriptorExtractor descriptor;//SiftDescriptorExtractor是SIFT类的别名  Mat description1;Mat description2;descriptor.compute(srcImg1, keyPoints1, description1);//注意原图和特征点要对应，不要写错descriptor.compute(srcImg2, keyPoints2, description2);imshow("description1", description1);imshow("description2", description2);//3.使用暴力匹配器进行暴力匹配——BruteForceMatcher类的match()方法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//4.对匹配结果进行筛选（依据DMatch结构体中的float类型变量distance进行筛选）float minDistance = 100;float maxDistance = 0;for (int i = 0; i < matches.size(); i++){if (matches[i].distance < minDistance)minDistance = matches[i].distance;if (matches[i].distance > maxDistance)maxDistance = matches[i].distance;}cout << "minDistance: " << minDistance << endl;cout << "maxDistance: " << maxDistance << endl;vector<DMatch> goodMatches;for (int i = 0; i < matches.size(); i++){if (matches[i].distance < 2 * minDistance){goodMatches.push_back(matches[i]);}}//5.绘制匹配结果——drawMatches()Mat dstImg3;drawMatches(srcImg1, keyPoints1, srcImg2, keyPoints2, goodMatches, dstImg3);imshow("dstImg3", dstImg3);waitKey(0);return 0;}

运行结果：

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