opencv实现两幅图像的极线约束匹配

#include <stdio.h> #include "opencv2/core/core.hpp" #include "opencv2/features2d/features2d.hpp" #include "opencv2/highgui/highgui.hpp" #include "opencv2/nonfree/nonfree.hpp" #include <opencv2/calib3d/calib3d.hpp> #include <iostream> using namespace std; using namespace cv; static void help() { printf("\nThis program demonstrates using features2d detector, descriptor extractor and simple matcher\n" "Using the SURF desriptor:\n" "\n" "Usage:\n matcher_simple <image1> <image2>\n"); } int main(int argc, char** argv) { //if(argc != 3) //{ // help(); // return -1; //} Mat img1 = imread("111.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat img2 = imread("222.jpg", CV_LOAD_IMAGE_GRAYSCALE); if(img1.empty() || img2.empty()) { printf("Can't read one of the images\n"); return -1; } // detecting keypoints SurfFeatureDetector detector(1000); vector<KeyPoint> keypoints1, keypoints2; detector.detect(img1, keypoints1); detector.detect(img2, keypoints2); // computing descriptors SurfDescriptorExtractor extractor; Mat descriptors1, descriptors2; extractor.compute(img1, keypoints1, descriptors1); extractor.compute(img2, keypoints2, descriptors2); // matching descriptors BFMatcher matcher(NORM_L2); vector<DMatch> matches; matcher.match(descriptors1, descriptors2, matches); // drawing the results namedWindow("matches", 1); Mat img_matches0,img_matches1; drawMatches(img1, keypoints1, img2, keypoints2, matches, img_matches0); //for(int i=0;i<matches.size();i++) //{ // //if(abs((keypoints1[matches[i].queryIdx].pt.y-keypoints2[matches[i].trainIdx].pt.y)>5) // //{ // //} // //cout<<keypoints1[matches[i].queryIdx].pt.x<<endl; // Point2f pt1,pt2; // pt1=keypoints1[matches[i].queryIdx].pt; // pt2=keypoints2[matches[i].trainIdx].pt; // if(abs(pt1.y-pt2.y)>5) // { // matches[i].distance=100; // } //} // drawMatches(img1, keypoints1, img2, keypoints2, matches, img_matches1); // 分配空间 int ptCount = (int)matches.size(); Mat p1(ptCount, 2, CV_32F); Mat p2(ptCount, 2, CV_32F); // 把Keypoint转换为Mat Point2f pt; for (int i=0; i<ptCount; i++) { pt = keypoints1[matches[i].queryIdx].pt; p1.at<float>(i, 0) = pt.x; p1.at<float>(i, 1) = pt.y; pt = keypoints2[matches[i].trainIdx].pt; p2.at<float>(i, 0) = pt.x; p2.at<float>(i, 1) = pt.y; } // 用RANSAC方法计算F // Mat m_Fundamental; // 上面这个变量是基本矩阵 vector<uchar> m_RANSACStatus; // 上面这个变量已经定义过，用于存储RANSAC后每个点的状态 //m_Fundamental = findFundamentalMat(p1, p2, m_RANSACStatus, FM_RANSAC); Mat m_Fundamental=findFundamentalMat(p1, p2, m_RANSACStatus, FM_RANSAC); cout<<m_Fundamental<<endl; // 计算野点个数 int OutlinerCount = 0; for (int i=0; i<ptCount; i++) { if (m_RANSACStatus[i] == 0) // 状态为0表示野点 { OutlinerCount++; } } // 计算内点 vector<Point2f> m_LeftInlier; vector<Point2f> m_RightInlier; vector<DMatch> m_InlierMatches; // 上面三个变量用于保存内点和匹配关系 int InlinerCount = ptCount - OutlinerCount; m_InlierMatches.resize(InlinerCount); m_LeftInlier.resize(InlinerCount); m_RightInlier.resize(InlinerCount); InlinerCount = 0; for (int i=0; i<ptCount; i++) { if (m_RANSACStatus[i] != 0) { m_LeftInlier[InlinerCount].x = p1.at<float>(i, 0); m_LeftInlier[InlinerCount].y = p1.at<float>(i, 1); m_RightInlier[InlinerCount].x = p2.at<float>(i, 0); m_RightInlier[InlinerCount].y = p2.at<float>(i, 1); m_InlierMatches[InlinerCount].queryIdx = InlinerCount; m_InlierMatches[InlinerCount].trainIdx = InlinerCount; InlinerCount++; } } // 把内点转换为drawMatches可以使用的格式 vector<KeyPoint> key1(InlinerCount); vector<KeyPoint> key2(InlinerCount); KeyPoint::convert(m_LeftInlier, key1); KeyPoint::convert(m_RightInlier, key2); for(int i=0;i<10;i++) cout<<key1[i].pt<<" "<<key2[i].pt<<" "<<key1[i].pt.x-key2[i].pt.x<<endl; drawMatches(img1, key1, img2, key2, m_InlierMatches, img_matches1); imshow("matches0", img_matches0); imshow("matches1", img_matches1); Mat test(img1.rows,img1.cols,CV_32FC1); float a=0.0105591872,b=0.1024243227,c=10.106085341; for(int i=0;i<test.rows;i++) { float* pt=test.ptr<float>(i); for(int j=0;j<test.cols;j++) { float val=j*a+i*b+c; pt[j]=val; } } //cout<<test<<endl; cv::normalize(test,test,0,1,CV_MINMAX); cv::convertScaleAbs(test,test,255); test.convertTo(test,CV_8UC1); imshow("test",test); waitKey(0); return 0; }