开源项目(7)Opencv日常之Homography

参考教程 https://blog.csdn.net/liuphahaha/article/details/50719275

什么是Homography 
在图1中有两张书的平面图,两张图分别有四个相对位置相同的点,Homography就是一个变换(3*3矩阵),将一张图中的点映射到另一张图中对应的点 

如何得到一个Homography

要得到两张图片的H,就必须至少知道4个相同对应位置的点,opencv中可以利用findHomography正确得到

//pts_src和pts_dst是源图像和目标图像中的点矢量。它们是vector <Point2f>类型。我们需要至少4个对应点。

Mat h = findHomography(pts_src, pts_dst);

//计算出的单应性可用于将源图像扭曲到目标。 im_src和im_dst属于Mat类型。大小是im_dst的大小(宽度,高度)。

warpPerspective(im_src, im_dst, h, size);

 OpenCV C++ Homography的一个简单例子: 

#include "opencv2/opencv.hpp" 

using namespace cv;
using namespace std;

int main( int argc, char** argv)
{
    // Read source image.
    Mat im_src = imread("book2.jpg");
    // Four corners of the book in source image
    vector<Point2f> pts_src;
    pts_src.push_back(Point2f(141, 131));
    pts_src.push_back(Point2f(480, 159));
    pts_src.push_back(Point2f(493, 630));
    pts_src.push_back(Point2f(64, 601));


    // Read destination image.
    Mat im_dst = imread("book1.jpg");
    // Four corners of the book in destination image.
    vector<Point2f> pts_dst;
    pts_dst.push_back(Point2f(318, 256));
    pts_dst.push_back(Point2f(534, 372));
    pts_dst.push_back(Point2f(316, 670));
    pts_dst.push_back(Point2f(73, 473));

    // Calculate Homography
    Mat h = findHomography(pts_src, pts_dst);

    // Output image
    Mat im_out;
    // Warp source image to destination based on homography
    warpPerspective(im_src, im_out, h, im_dst.size());

    // Display images
    imshow("Source Image", im_src);
    imshow("Destination Image", im_dst);
    imshow("Warped Source Image", im_out);

    waitKey(0);
}

  

Homography应用:图像矫正
假设你有一张如下所示的图片


你想点击图中书的四个顶点,然后得到正放的书:


该如何做? 
利用Homography可以做到这点。 
1.首先获取书本四个顶点的坐标 pts_src 
2.然后我们需要知道书本的宽高比,此书的宽高比是3/4,所以可使输出图像的size 为300*400,就可设其四个点的坐标为(0,0),(299,0),(299,399),(0,399)保存在pts_dst中 
3.通过pts_src和pts_dst 获取homography 
4.对原图应用homography 得到输出

#include <opencv2/opencv.hpp>

using namespace cv;
using namespace std;

struct userdata{
    Mat im;
    vector<Point2f> points;
};


void mouseHandler(int event, int x, int y, int flags, void* data_ptr)
{
    if  ( event == EVENT_LBUTTONDOWN )
    {
        userdata *data = ((userdata *) data_ptr);
        circle(data->im, Point(x,y),3,Scalar(0,0,255), 5, CV_AA);
        imshow("Image", data->im);
        if (data->points.size() < 4)
        {
            data->points.push_back(Point2f(x,y));
        }
    }

}



void main()
{

    // Read source image.
    Mat im_src = imread("book1.jpg");

    // Destination image. The aspect ratio of the book is 3/4
    Size size(300,400);
    Mat im_dst = Mat::zeros(size,CV_8UC3);


    // Create a vector of destination points.
    vector<Point2f> pts_dst;

    pts_dst.push_back(Point2f(0,0));
    pts_dst.push_back(Point2f(size.width - 1, 0));
    pts_dst.push_back(Point2f(size.width - 1, size.height -1));
    pts_dst.push_back(Point2f(0, size.height - 1 ));

    // Set data for mouse event
    Mat im_temp = im_src.clone();
    userdata data;
    data.im = im_temp;

    cout << "Click on the four corners of the book -- top left first and" << endl
        << "bottom left last -- and then hit ENTER" << endl;

    // Show image and wait for 4 clicks. 
    imshow("Image", im_temp);
    // Set the callback function for any mouse event
    setMouseCallback("Image", mouseHandler, &data);
    waitKey(0);

    // Calculate the homography
    Mat h = findHomography(data.points, pts_dst);

    // Warp source image to destination
    warpPerspective(im_src, im_dst, h, size);

    // Show image
    imshow("Image", im_dst);
    waitKey(0);


}

  

Homography应用:虚拟广告牌

在足球或者棒球体育直播中,经常可以看到球场旁边有虚拟广告,并且还会根据地区,国家的不同播放不同的广告,这是如何做到的? 
看完此篇博客,你应该就能知道如何实现了。原理跟前一个差不多,这里直接上代码

#include <opencv2/opencv.hpp>

using namespace cv;
using namespace std;

struct userdata{
    Mat im;
    vector<Point2f> points;
};


void mouseHandler(int event, int x, int y, int flags, void* data_ptr)
{
    if  ( event == EVENT_LBUTTONDOWN )
    {
        userdata *data = ((userdata *) data_ptr);
        circle(data->im, Point(x,y),3,Scalar(0,255,255), 5, CV_AA);
        imshow("Image", data->im);
        if (data->points.size() < 4)
        {
            data->points.push_back(Point2f(x,y));
        }
    }

}



int main( int argc, char** argv)
{

    // Read in the image.
    Mat im_src = imread("first-image.jpg");
    Size size = im_src.size();

    // Create a vector of points.
    vector<Point2f> pts_src;
    pts_src.push_back(Point2f(0,0));
    pts_src.push_back(Point2f(size.width - 1, 0));
    pts_src.push_back(Point2f(size.width - 1, size.height -1));
    pts_src.push_back(Point2f(0, size.height - 1 ));



    // Destination image
    Mat im_dst = imread("times-square.jpg");


    // Set data for mouse handler
    Mat im_temp = im_dst.clone();
    userdata data;
    data.im = im_temp;


    //show the image
    imshow("Image", im_temp);

    cout << "Click on four corners of a billboard and then press ENTER" << endl;
    //set the callback function for any mouse event
    setMouseCallback("Image", mouseHandler, &data);
    waitKey(0);

    // Calculate Homography between source and destination points
    Mat h = findHomography(pts_src, data.points);

    // Warp source image
    warpPerspective(im_src, im_temp, h, im_temp.size());

    // Extract four points from mouse data
    Point pts_dst[4];
    for( int i = 0; i < 4; i++)
    {
        pts_dst[i] = data.points[i];
    }

    // Black out polygonal area in destination image.
    fillConvexPoly(im_dst, pts_dst, 4, Scalar(0), CV_AA);

    // Add warped source image to destination image.
    im_dst = im_dst + im_temp;

    // Display image.
    imshow("Image", im_dst);
    waitKey(0);

    return 0;
}

  

 

结果

原文地址:https://www.cnblogs.com/kekeoutlook/p/11161883.html