给出zhang-suen细化结合灰度重心法提取激光条纹的vs c++代码

以下是基于 Zhang-Suen 细化算法和灰度重心法提取激光条纹的 C++ 代码：

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

using namespace std;
using namespace cv;

// Zhang-Suen 细化算法
Mat ZhangSuenThinning(Mat img) {
    Mat thin(img.size(), CV_8UC1);
    img.copyTo(thin);
    thin /= 255;

    Mat prev = Mat::zeros(thin.size(), CV_8UC1);
    Mat diff;

    do {
        thin.copyTo(prev);

        for (int i = 1; i < thin.rows - 1; ++i) {
            for (int j = 1; j < thin.cols - 1; ++j) {
                if (thin.at<uchar>(i,j) == 1) {
                    int p2 = thin.at<uchar>(i-1, j);
                    int p3 = thin.at<uchar>(i-1, j+1);
                    int p4 = thin.at<uchar>(i, j+1);
                    int p5 = thin.at<uchar>(i+1, j+1);
                    int p6 = thin.at<uchar>(i+1, j);
                    int p7 = thin.at<uchar>(i+1, j-1);
                    int p8 = thin.at<uchar>(i, j-1);
                    int p9 = thin.at<uchar>(i-1, j-1);

                    int A = 0;
                    if (p2 == 0 && p3 == 1) ++A;
                    if (p3 == 0 && p4 == 1) ++A;
                    if (p4 == 0 && p5 == 1) ++A;
                    if (p5 == 0 && p6 == 1) ++A;
                    if (p6 == 0 && p7 == 1) ++A;
                    if (p7 == 0 && p8 == 1) ++A;
                    if (p8 == 0 && p9 == 1) ++A;
                    if (p9 == 0 && p2 == 1) ++A;

                    int B = p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9;
                    int m1 = (p2 * p4 * p6);
                    int m2 = (p4 * p6 * p8);

                    if (A == 1 && (B >= 2 && B <= 6) && m1 == 0 && m2 == 0) {
                        thin.at<uchar>(i,j) = 0;
                    }
                }
            }
        }

        for (int i = 1; i < thin.rows - 1; ++i) {
            for (int j = 1; j < thin.cols - 1; ++j) {
                if (thin.at<uchar>(i,j) == 1) {
                    int p2 = thin.at<uchar>(i-1, j);
                    int p3 = thin.at<uchar>(i-1, j+1);
                    int p4 = thin.at<uchar>(i, j+1);
                    int p5 = thin.at<uchar>(i+1, j+1);
                    int p6 = thin.at<uchar>(i+1, j);
                    int p7 = thin.at<uchar>(i+1, j-1);
                    int p8 = thin.at<uchar>(i, j-1);
                    int p9 = thin.at<uchar>(i-1, j-1);

                    int A = 0;
                    if (p2 == 0 && p3 == 1) ++A;
                    if (p3 == 0 && p4 == 1) ++A;
                    if (p4 == 0 && p5 == 1) ++A;
                    if (p5 == 0 && p6 == 1) ++A;
                    if (p6 == 0 && p7 == 1) ++A;
                    if (p7 == 0 && p8 == 1) ++A;
                    if (p8 == 0 && p9 == 1) ++A;
                    if (p9 == 0 && p2 == 1) ++A;

                    int B = p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9;
                    int m1 = (p2 * p4 * p8);
                    int m2 = (p2 * p6 * p8);

                    if (A == 1 && (B >= 2 && B <= 6) && m1 == 0 && m2 == 0) {
                        thin.at<uchar>(i,j) = 0;
                    }
                }
            }
        }

        absdiff(thin, prev, diff);
    } while (countNonZero(diff) > 0);

    thin *= 255;
    return thin;
}

// 灰度重心法提取激光条纹
Point2f extractLaserStripe(Mat img) {
    // 将图像转换为灰度图像
    Mat gray;
    cvtColor(img, gray, COLOR_BGR2GRAY);

    // 对灰度图像进行二值化处理
    Mat binary;
    threshold(gray, binary, 0, 255, THRESH_BINARY | THRESH_OTSU);

    // 对二值化图像进行细化处理
    Mat thin = ZhangSuenThinning(binary);

    // 计算灰度重心
    Moments m = moments(thin, true);
    Point2f centroid(m.m10/m.m00, m.m01/m.m00);

    return centroid;
}

int main() {
    // 读取图像
    Mat img = imread("laser_stripe.png");

    // 提取激光条纹
    Point2f centroid = extractLaserStripe(img);

    // 在图像上标记出灰度重心
    circle(img, centroid, 5, Scalar(0,0,255), -1);

    // 显示图像
    imshow("Laser Stripe Extraction", img);
    waitKey(0);

    return 0;
}

这段代码实现了对输入图像进行 Zhang-Suen 细化算法和灰度重心法提取激光条纹的功能，并在图像上标记出灰度重心。