检测灰度图中白色和黑色的分界线并拟合直线 c++

好的，以下是使用 C++ 实现检测灰度图中白色和黑色的分界线并拟合直线的代码：

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;

int main()
{
    // 读取灰度图像
    Mat img_gray = imread("gray_image.jpg", IMREAD_GRAYSCALE);

    // 二值化图像
    Mat img_binary;
    threshold(img_gray, img_binary, 127, 255, THRESH_BINARY);

    // Canny边缘检测
    Mat img_edges;
    Canny(img_binary, img_edges, 100, 200);

    // 霍夫直线变换
    vector<Vec2f> lines;
    HoughLines(img_edges, lines, 1, CV_PI/180, 100);

    // 选择斜率最接近水平或垂直的直线，并将其拟合为一条直线
    float max_theta = 0;
    float max_length = 0;
    for (size_t i = 0; i < lines.size(); i++)
    {
        float rho = lines[i][0];
        float theta = lines[i][1];
        float length = abs(rho);
        if (length > max_length && (abs(theta - CV_PI/2) < CV_PI/6 || abs(theta) < CV_PI/6))
        {
            max_length = length;
            max_theta = theta;
        }
    }

    Point2f pt1, pt2;
    if (abs(max_theta - CV_PI/2) < CV_PI/6)
    {
        float line_y = cos(max_theta) / sin(max_theta);
        float y_intercept = img_gray.cols / 2 - line_y * img_gray.rows / 2;
        pt1 = Point2f(0, y_intercept);
        pt2 = Point2f(img_gray.cols, line_y * img_gray.cols + y_intercept);
    }
    else
    {
        float line_x = sin(max_theta) / cos(max_theta);
        float x_intercept = img_gray.rows / 2 - line_x * img_gray.cols / 2;
        pt1 = Point2f(x_intercept, 0);
        pt2 = Point2f(line_x * img_gray.rows + x_intercept, img_gray.rows);
    }

    // 在原始图像上绘制直线
    Mat img_output = imread("gray_image.jpg", IMREAD_COLOR);
    line(img_output, pt1, pt2, Scalar(0, 255, 0), 2);

    // 显示结果
    imshow("Output", img_output);
    waitKey();

    return 0;
}

这里使用了 OpenCV 库中的函数来实现图像的读取、二值化、Canny 边缘检测、霍夫直线变换和直线绘制等操作。希望这份代码能对您有所帮助！