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OpenCV图像匹配算法之sift

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    //utils.h  
    #ifndef _UTILS_H  
    #define _UTILS_H  

    #include <opencv2/opencv.hpp>  
    #include <opencv2/features2d/features2d.hpp>  
    #include <opencv2/core/core.hpp>  
    #include <opencv2/imgproc/imgproc.hpp>  
    #include <opencv2\nonfree\nonfree.hpp>  
    using namespace cv;  

    // ORB settings  
    const int ORB_MAX_KPTS = 1500;  
    const float ORB_SCALE_FACTOR = 1.5;  
    const int ORB_PYRAMID_LEVELS = 3;  
    const float ORB_EDGE_THRESHOLD = 31.0;  
    const int ORB_FIRST_PYRAMID_LEVEL = 0;  
    const int ORB_WTA_K = 2;  
    const int ORB_PATCH_SIZE = 31;  

    // BRISK settings  
    const float BRISK_HTHRES = 10.0;  
    const int BRISK_NOCTAVES = 6;  

    const float DRATIO = 0.8f;                          // NNDR Matching value  
    const float MIN_H_ERROR = 2.50f;            // Maximum error in pixels to accept an inlier  

    void matches2points_nndr(const std::vector<cv::KeyPoint>&amp; train,  
                             const std::vector<cv::KeyPoint>&amp; query,  
                             const std::vector<std::vector<cv::DMatch> >&amp; matches,  
                             std::vector<cv::Point2f>&amp; pmatches, float nndr);  
    void compute_inliers_ransac(const std::vector<cv::Point2f>&amp; matches,  
                                std::vector<cv::Point2f>&amp; inliers,  
                                float error, bool use_fund);  
    void draw_inliers(const cv::Mat&amp; img1, const cv::Mat&amp; img2, cv::Mat&amp; img_com,  
                      const std::vector<cv::Point2f>&amp; ptpairs, int color);  

    typedef struct info  
    {  
        double t;  
        int n1;  
        int n2;  
        int m;  
        int rm;  
    }INFO;  

    void sift(char* path1, char* path2, INFO&amp; info, bool show);  
    void surf(char* path1, char* path2, INFO&amp; info, bool show);  
    void orb(char* path1, char* path2, INFO&amp; info, bool show);  
    void brisk(char* path1, char* path2, INFO&amp; info, bool show);  
    void freak(char* path1, char* path2, INFO&amp; info, bool show);  
    void showInfo(INFO info);  

    #endif  
    //utils.cpp  
    #include "stdafx.h"  
    #include "utils.h"  
    #include <iostream>  
    using namespace std;  

    /** 
     * @brief This function converts matches to points using nearest neighbor distance 
     * ratio matching strategy 
     * @param train Vector of keypoints from the first image 
     * @param query Vector of keypoints from the second image 
     * @param matches Vector of nearest neighbors for each keypoint 
     * @param pmatches Vector of putative matches 
     * @param nndr Nearest neighbor distance ratio value 
     */  
    void matches2points_nndr(const std::vector<cv::KeyPoint>&amp; train,  
                             const std::vector<cv::KeyPoint>&amp; query,  
                             const std::vector<std::vector<cv::DMatch> >&amp; matches,  
                             std::vector<cv::Point2f>&amp; pmatches, float nndr) {  

      float dist1 = 0.0, dist2 = 0.0;  
      for (size_t i = 0; i < matches.size(); i++) {  
        DMatch dmatch = matches[i][0];  
        dist1 = matches[i][0].distance;  
        dist2 = matches[i][1].distance;  

        if (dist1 < nndr*dist2) {  
          pmatches.push_back(train[dmatch.queryIdx].pt);  
          pmatches.push_back(query[dmatch.trainIdx].pt);  
        }  
      }  
    }  

    /** 
     * @brief This function computes the set of inliers estimating the fundamental matrix 
     * or a planar homography in a RANSAC procedure 
     * @param matches Vector of putative matches 
     * @param inliers Vector of inliers 
     * @param error The minimum pixelic error to accept an inlier 
     * @param use_fund Set to true if you want to compute a fundamental matrix 
     */  
    void compute_inliers_ransac(const std::vector<cv::Point2f>&amp; matches,  
                                std::vector<cv::Point2f>&amp; inliers,  
                                float error, bool use_fund) {  

      vector<Point2f> points1, points2;  
      Mat H = Mat::zeros(3,3,CV_32F);  
      int npoints = matches.size()/2;  
      Mat status = Mat::zeros(npoints,1,CV_8UC1);  

      for (size_t i = 0; i < matches.size(); i+=2) {  
        points1.push_back(matches[i]);  
        points2.push_back(matches[i+1]);  
      }  

      if (use_fund == true){  
        H = findFundamentalMat(points1,points2,CV_FM_RANSAC,error,0.99,status);  
      }  
      else {  
        H = findHomography(points1,points2,CV_RANSAC,error,status);  
      }  

      for (int i = 0; i < npoints; i++) {  
        if (status.at<unsigned char>(i) == 1) {  
          inliers.push_back(points1[i]);  
          inliers.push_back(points2[i]);  
        }  
      }  
    }  

    //*******************************************************************************  
    //*******************************************************************************  

    /**  
     * @brief This function draws the set of the inliers between the two images  
     * @param img1 First image  
     * @param img2 Second image  
     * @param img_com Image with the inliers  
     * @param ptpairs Vector of point pairs with the set of inliers  
     * @param color The color for each method  
     */  
    void draw_inliers(const cv::Mat&amp; img1, const cv::Mat&amp; img2, cv::Mat&amp; img_com,  
                      const std::vector<cv::Point2f>&amp; ptpairs, int color) {  

      int x1 = 0, y1 = 0, x2 = 0, y2 = 0;  
      float rows1 = 0.0, cols1 = 0.0;  
      float rows2 = 0.0, cols2 = 0.0;  
      float ufactor = 0.0, vfactor = 0.0;  

      rows1 = img1.rows;  
      cols1 = img1.cols;  
      rows2 = img2.rows;  
      cols2 = img2.cols;  
      ufactor = (float)(cols1)/(float)(cols2);  
      vfactor = (float)(rows1)/(float)(rows2);  

      // This is in case the input images don't have the same resolution  
      Mat img_aux = Mat(Size(img1.cols,img1.rows),CV_8UC3);  
      resize(img2,img_aux,Size(img1.cols,img1.rows),0,0,CV_INTER_LINEAR);  

      for (int i = 0; i < img_com.rows; i++) {  
        for (int j = 0; j < img_com.cols; j++) {  
          if (j < img1.cols) {  
            *(img_com.ptr<unsigned char>(i)+3*j) = *(img1.ptr<unsigned char>(i)+3*j);  
            *(img_com.ptr<unsigned char>(i)+3*j+1) = *(img1.ptr<unsigned char>(i)+3*j+1);  
            *(img_com.ptr<unsigned char>(i)+3*j+2) = *(img1.ptr<unsigned char>(i)+3*j+2);  
          }  
          else {  
            *(img_com.ptr<unsigned char>(i)+3*j) = *(img_aux.ptr<unsigned char>(i)+3*(j-img_aux.cols));  
            *(img_com.ptr<unsigned char>(i)+3*j+1) = *(img_aux.ptr<unsigned char>(i)+3*(j-img_aux.cols)+1);  
            *(img_com.ptr<unsigned char>(i)+3*j+2) = *(img_aux.ptr<unsigned char>(i)+3*(j-img_aux.cols)+2);  
          }  
        }  
      }  

      for (size_t i = 0; i < ptpairs.size(); i+= 2) {  
        x1 = (int)(ptpairs[i].x+.5);  
        y1 = (int)(ptpairs[i].y+.5);  
        x2 = (int)(ptpairs[i+1].x*ufactor+img1.cols+.5);  
        y2 = (int)(ptpairs[i+1].y*vfactor+.5);  

        if (color == 0) {  
          line(img_com,Point(x1,y1),Point(x2,y2),CV_RGB(255,255,0),1);  
        }  
        else if (color == 1) {  
          line(img_com,Point(x1,y1),Point(x2,y2),CV_RGB(255,0,0),1);  
        }  
        else if (color == 2) {  
          line(img_com,Point(x1,y1),Point(x2,y2),CV_RGB(0,0,255),1);  
        }  
      }  
    }  

    void showInfo(INFO info)  
    {  
        printf("%-40s%d\n","The keypoints number of src image is :", info.n1);  
        printf("%-40s%d\n","The keypoints number of dst image is : ", info.n2);  
        printf("%-40s%d\n","The matching number is : ", info.m);  
        printf("%-40s%d\n","The right result number is : ", info.rm);  
        printf("%-40s%.2fs\n","The total time is : ", info.t);  
        return ;  
    }  
    //sift.cpp  
    #include "stdafx.h"  
    #include <cv.hpp>  
    #include <highgui.h>  
    #include "utils.h"  
    #include <iostream>  
    using namespace std;  

    void sift(char* path1, char* path2, INFO&amp; info, bool show)  
    {  
        double t1,t2;  
        t1=cvGetTickCount();  

        initModule_nonfree();  

        Mat img1, img2;   
        img1=imread(path1,0);  
        img2=imread(path2,0);  
        if(img1.data==NULL)  
        {  
            cout<<"The image can not been loaded: "<<path1<<endl;  
            system("pause");  
            exit(-1);  
        }  
        if(img2.data==NULL)  
        {  
            cout<<"The image can not been loaded: "<<path2<<endl;  
            system("pause");  
            exit(-1);  
        }     

        Ptr<FeatureDetector> sift_detector = FeatureDetector::create( "SIFT" );  
        Ptr<DescriptorExtractor> sift_descriptor = DescriptorExtractor::create( "SIFT" );    
        vector<KeyPoint> kpts1_sift, kpts2_sift;  
        Mat desc1_sift, desc2_sift;  
        Ptr<DescriptorMatcher> matcher_l2 = DescriptorMatcher::create("BruteForce");      //欧氏距离匹配  
        vector<vector<DMatch> > dmatches_sift;  
        vector<Point2f> matches_sift, inliers_sift;  

        sift_detector->detect(img1,kpts1_sift);  
        sift_detector->detect(img2,kpts2_sift);  
        info.n1=kpts1_sift.size();  
        info.n2=kpts2_sift.size();  
        sift_descriptor->compute(img1,kpts1_sift,desc1_sift);  
        sift_descriptor->compute(img2,kpts2_sift,desc2_sift);  
        matcher_l2->knnMatch(desc1_sift,desc2_sift,dmatches_sift,2);                                     //匹配  
        matches2points_nndr(kpts1_sift,kpts2_sift,dmatches_sift,matches_sift,DRATIO);  
        info.m=matches_sift.size()/2;  
        compute_inliers_ransac(matches_sift,inliers_sift,MIN_H_ERROR,false);  
        info.rm=inliers_sift.size()/2;  

        t2=cvGetTickCount();  
        info.t=(t2-t1)/1000000.0/cvGetTickFrequency();  

        Mat img1_rgb_sift = imread(path1,1);  
        Mat img2_rgb_sift = imread(path2,1);  
        Mat img_com_sift = Mat(Size(img1.cols*2,img1.rows),CV_8UC3);  

        if(show == true)  
        {  
            draw_inliers(img1_rgb_sift,img2_rgb_sift,img_com_sift,inliers_sift,2);  
            imshow("sift",img_com_sift);  
            waitKey(0);  
        }  

        return;  
    }  

使用cpp INFO sift_info; sift(path1,path2,sift_info,true); showInfo(sift_info);

标签:c/c++

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