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