OpenCv实现两幅图像的拼接

我不是女神ヾ 2021-12-01 19:16 358阅读 0赞

直接贴上源码

来源：[http://www.myexception.cn/image/1498389.html][http_www.myexception.cn_image_1498389.html]

实验效果

Left.jpg

![231401554042390.jpg][]

right.jpg

![231401561231478.jpg][]

ImageMatch.jpg

![231401571393420.jpg][]

#include <iostream>
    #include <iomanip>
    #include "opencv2/core/core.hpp"
    #include "opencv2/objdetect/objdetect.hpp"
    #include "opencv2/features2d/features2d.hpp"
    #include "opencv2/highgui/highgui.hpp"
    #include "opencv2/calib3d/calib3d.hpp"
    #include "opencv2/nonfree/nonfree.hpp"
    #include "opencv2/imgproc/imgproc_c.h"
    #include "opencv2/legacy/legacy.hpp"
    #include "opencv2/legacy/compat.hpp"
    using namespace cv;
    using namespace std;
    
    
    int main()
    {
        Mat leftImg=imread("left.jpg");
        Mat rightImg=imread("right.jpg");
        if(leftImg.data==NULL||rightImg.data==NULL)
            return 0;
    
        //转化成灰度图
        Mat leftGray;
        Mat rightGray;
        cvtColor(leftImg,leftGray,CV_BGR2GRAY);
        cvtColor(rightImg,rightGray,CV_BGR2GRAY);
    
        //获取两幅图像的共同特征点
    
        int minHessian=400;
        SurfFeatureDetector detector(minHessian);
        vector<KeyPoint> leftKeyPoints,rightKeyPoints;
        detector.detect(leftGray,leftKeyPoints);
        detector.detect(rightGray,rightKeyPoints);
        SurfDescriptorExtractor extractor;
        Mat leftDescriptor,rightDescriptor;
        extractor.compute(leftGray,leftKeyPoints,leftDescriptor);
        extractor.compute(rightGray,rightKeyPoints,rightDescriptor);
        FlannBasedMatcher matcher;
        vector<DMatch> matches;
        matcher.match(leftDescriptor,rightDescriptor,matches);    
        int matchCount=leftDescriptor.rows;
    
        if(matchCount>15)
        {
            matchCount=15;
            //sort(matches.begin(),matches.begin()+leftDescriptor.rows,DistanceLessThan);
            sort(matches.begin(),matches.begin()+leftDescriptor.rows);
        }    
    
        vector<Point2f> leftPoints;
        vector<Point2f> rightPoints;
    
        for(int i=0; i<matchCount; i++)
        {
            leftPoints.push_back(leftKeyPoints[matches[i].queryIdx].pt);
            rightPoints.push_back(rightKeyPoints[matches[i].trainIdx].pt);
        }
    
        //获取左边图像到右边图像的投影映射关系
        Mat homo=findHomography(leftPoints,rightPoints);
        Mat shftMat=(Mat_<double>(3,3)<<1.0,0,leftImg.cols, 0,1.0,0, 0,0,1.0);
    
        //拼接图像
        Mat tiledImg;
        warpPerspective(leftImg,tiledImg,shftMat*homo,Size(leftImg.cols+rightImg.cols,rightImg.rows));
        rightImg.copyTo(Mat(tiledImg,Rect(leftImg.cols,0,rightImg.cols,rightImg.rows)));
    
        //保存图像
        imwrite("tiled.jpg",tiledImg);
        //显示拼接的图像
        imshow("tiled image",tiledImg);
        waitKey(0);
        return 0;
    }

转载于:https://www.cnblogs.com/adong7639/p/3988254.html

[http_www.myexception.cn_image_1498389.html]: http://www.myexception.cn/image/1498389.html
[231401554042390.jpg]: /images/20211201/f1b2b036e2434d0480ff3a34358ce520.png
[231401561231478.jpg]: /images/20211201/93ab7b788e9048c09fb99ce7afc7799e.png
[231401571393420.jpg]: /images/20211201/e2b37f69227e47a4a243e32dd0409403.png