opencv中集成了很多好用的函数，比如霍夫变换检测直线的函数，当然，考虑到看我文章的人水平，我这里只讲讲如何使用这个函数，和怎么调节其中的参数
先把运行效果PO出来吧
#include "CV_ERROR.h"
#include "MCV_funs.hpp"#include <opencv2/opencv.hpp>
#include <iostream>int main() {cv::utils::logging::setLogLevel(cv::utils::logging::LOG_LEVEL_ERROR);// 读取PNG图像//cv::Mat image = cv::imread("lines.png", cv::IMREAD_COLOR);cv::Mat image = cv::imread("PIC.jpg", cv::IMREAD_COLOR);if (image.empty()) {std::cerr << "无法读取图像文件" << std::endl;return -1;}showimageWin(image);// 转换为灰度图像cv::Mat gray;cv::cvtColor(image, gray, cv::COLOR_BGR2GRAY);// 应用边缘检测（Canny）cv::Mat edges;cv::Canny(gray, edges, 150, 200, 3);showimageWin(edges);// 使用霍夫变换检测直线std::vector<cv::Vec2f> lines;cv::HoughLines(edges, lines, 0.5, CV_PI / 360, 200);// 在原图上绘制检测到的直线cv::Mat result = image.clone();for (size_t i = 0; i < lines.size(); i++) {float rho = lines[i][0], theta = lines[i][1];cv::Point pt1, pt2;double a = cos(theta), b = sin(theta);double x0 = a * rho, y0 = b * rho;pt1.x = cvRound(x0 + 1000 * (-b));pt1.y = cvRound(y0 + 1000 * (a));pt2.x = cvRound(x0 - 1000 * (-b));pt2.y = cvRound(y0 - 1000 * (a));cv::line(result, pt1, pt2, cv::Scalar(0, 255, 0), 15, cv::LINE_AA);}// 显示结果图像showimageWin(result);cv::waitKey();return 0;
}
下面是原理类的讲解，本鼠懒得重复做笔记了，直接PO在下面吧ψ(｀∇´)ψ
