• opencv 最小二乘法拟合曲线


    //-----------------------------------【头文件包含部分】---------------------------------------
    //       描述:包含程序所依赖的头文件
    //----------------------------------------------------------------------------------------------
    #include"opencv2/highgui/highgui.hpp"
    #include"opencv2/imgproc/imgproc.hpp"
    #include <iostream>
    
    //-----------------------------------【命名空间声明部分】--------------------------------------
    //    描述:包含程序所使用的命名空间
    //-----------------------------------------------------------------------------------------------
    using namespace cv;
    
    
    bool polynomial_curve_fit(std::vector<cv::Point>& key_point, int n, cv::Mat& A)
    {
        //Number of key points
        int N = key_point.size();
    
        //构造矩阵X
        cv::Mat X = cv::Mat::zeros(n + 1, n + 1, CV_64FC1);
        for (int i = 0; i < n + 1; i++)
        {
            for (int j = 0; j < n + 1; j++)
            {
                for (int k = 0; k < N; k++)
                {
                    X.at<double>(i, j) = X.at<double>(i, j) +
                        std::pow(key_point[k].x, i + j);
                }
            }
        }
    
        //构造矩阵Y
        cv::Mat Y = cv::Mat::zeros(n + 1, 1, CV_64FC1);
        for (int i = 0; i < n + 1; i++)
        {
            for (int k = 0; k < N; k++)
            {
                Y.at<double>(i, 0) = Y.at<double>(i, 0) +
                    std::pow(key_point[k].x, i) * key_point[k].y;
            }
        }
    
        A = cv::Mat::zeros(n + 1, 1, CV_64FC1);
        //求解矩阵A
        cv::solve(X, Y, A, cv::DECOMP_LU);
        return true;
    }
    
    int main()
    {
        //创建用于绘制的深蓝色背景图像
        cv::Mat image = cv::Mat::zeros(480, 640, CV_8UC3);
        image.setTo(cv::Scalar(0, 0, 100));
    
        //输入拟合点
        std::vector<cv::Point> points;
        points.push_back(cv::Point(100., 58.));
        points.push_back(cv::Point(150., 70.));
        points.push_back(cv::Point(200., 90.));
        points.push_back(cv::Point(252., 140.));
        points.push_back(cv::Point(300., 220.));
        points.push_back(cv::Point(350., 400.));
    
        //将拟合点绘制到空白图上
        for (int i = 0; i < points.size(); i++)
        {
            cv::circle(image, points[i], 5, cv::Scalar(0, 0, 255), 2, 8, 0);
        }
    
        //绘制折线
        cv::polylines(image, points, false, cv::Scalar(0, 255, 255), 1, 8, 0);
    
        cv::Mat A;
    
        polynomial_curve_fit(points, 3, A);
        std::cout << "A = " << A << std::endl;
    
        std::vector<cv::Point> points_fitted;
    
        for (int x = 0; x < 400; x++)
        {
            double y = A.at<double>(0, 0) + A.at<double>(1, 0) * x +
                A.at<double>(2, 0)*std::pow(x, 2) + A.at<double>(3, 0)*std::pow(x, 3);
    
            points_fitted.push_back(cv::Point(x, y));
        }
        cv::polylines(image, points_fitted, false, cv::Scalar(255, 255, 255), 1, 8, 0);
    
        cv::imshow("image", image);
    
        cv::waitKey(0);
        return 0;
    }
    

  • 相关阅读:
    实验二 Nmap的实践
    《网络攻击与防范》第八周学习总结
    《网络攻击与防范》第七周学习总结
    《网络攻击与防范》第六周学习总结
    《网络攻击与防范》第五周学习总结
    《网络攻击与防范》第四周学习总结
    《网络攻击与防范》第三周学习总结
    《网络攻击与防范》第二周学习总结
    Linux 基础入门学习总结
    20169312 2016-2017-2《网络攻防实践》课程总结
  • 原文地址:https://www.cnblogs.com/yanghailin/p/12097913.html
Copyright © 2020-2023  润新知