ORB 特征检测与匹配

来源：互联网发布：macbook air必备软件编辑：程序博客网时间：2024/06/05 14:37

#include <opencv2/opencv.hpp>#include <opencv2/xfeatures2d.hpp>#include <opencv2/xfeatures2d/nonfree.hpp>#include <iostream>using namespace cv::xfeatures2d;using namespace std;using namespace cv;// 计算图像的ORB特征及匹配cv::Mat cacORBFeatureAndCompare(cv::Mat srcImage1,cv::Mat srcImage2){CV_Assert(srcImage1.data != NULL && srcImage2.data != NULL);// 转换为灰度cv::Mat grayMat1, grayMat2;cv::cvtColor(srcImage1, grayMat1, CV_RGB2GRAY);cv::cvtColor(srcImage2, grayMat2, CV_RGB2GRAY);// 关键点检测std::vector<KeyPoint> keyPoints1, keyPoints2;// 描述特征向量cv::Mat descriptorMat1, descriptorMat2;// 初始化ORB检测描述子cv::Ptr<Feature2D> orb = cv::ORB::create();// 计算兴趣点orb->detectAndCompute(grayMat1, Mat(), keyPoints1, descriptorMat1,false);orb->detectAndCompute(grayMat2, Mat(), keyPoints2, descriptorMat2,false);// 特征匹配BFMatcher matcher(NORM_HAMMING);std::vector<DMatch> mathces;matcher.match(descriptorMat1, descriptorMat2, mathces);// 绘制匹配点集Mat matchMat;drawMatches(srcImage1, keyPoints1,srcImage2, keyPoints2, mathces, matchMat);//cv::imshow("Mathces", matchMat);return matchMat;}int main(){// 读取源图像及待匹配图像cv::Mat srcImage1 =cv::imread("..\\images\\hand1.jpg", 1);if (srcImage1.empty())return -1;cv::Mat srcImage2 =cv::imread("..\\images\\hand3.jpg", 1);if (srcImage2.empty())return -1;cv::Mat  matchMat = cacORBFeatureAndCompare(srcImage1, srcImage2);cv::imshow("matchMat", matchMat);cv::waitKey(0);return 0;}

转载：http://blog.csdn.net/zhuwei1988

0 0