请用C代码或C++代码，实现两种骨架提取算法：顺序细化和北、南、东、西提取算法。

顺序细化算法的C++实现：

#include <iostream>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>

using namespace cv;
using namespace std;

void seqThinning(Mat &img) {
    Mat prev = Mat::zeros(img.size(), CV_8UC1);
    Mat diff;
    do {
        thinning(img, 0);
        thinning(img, 1);
        absdiff(img, prev, diff);
        img.copyTo(prev);
    } while (countNonZero(diff) > 0);
}

void thinning(Mat &img, int type) {
    Mat marker = Mat::zeros(img.size(), CV_8UC1);
    for (int i = 1; i < img.rows - 1; i++) {
        for (int j = 1; j < img.cols - 1; j++) {
            uchar p2 = img.at<uchar>(i - 1, j);
            uchar p3 = img.at<uchar>(i - 1, j + 1);
            uchar p4 = img.at<uchar>(i, j + 1);
            uchar p5 = img.at<uchar>(i + 1, j + 1);
            uchar p6 = img.at<uchar>(i + 1, j);
            uchar p7 = img.at<uchar>(i + 1, j - 1);
            uchar p8 = img.at<uchar>(i, j - 1);
            uchar p9 = img.at<uchar>(i - 1, j - 1);
            int A = (!p2 && p3) + (!p3 && p4) + (!p4 && p5) + (!p5 && p6) +
                    (!p6 && p7) + (!p7 && p8) + (!p8 && p9) + (!p9 && p2);
            int B = p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9;
            int m1 = (type == 0) ? (p2 * p4 * p6) : (p2 * p4 * p8);
            int m2 = (type == 0) ? (p4 * p6 * p8) : (p2 * p6 * p8);
            if (A == 1 && (B >= 2 && B <= 6) && m1 == 0 && m2 == 0) {
                marker.at<uchar>(i, j) = 1;
            }
        }
    }
    img &= ~marker;
}

int main() {
    Mat src = imread("test.png", 0);
    threshold(src, src, 128, 255, THRESH_BINARY);
    seqThinning(src);
    imshow("result", src);
    waitKey(0);
    return 0;
}

北、南、东、西提取算法的C++实现：

#include <iostream>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>

using namespace cv;
using namespace std;

void nsweThinning(Mat &img) {
    Mat prev = Mat::zeros(img.size(), CV_8UC1);
    Mat diff;
    do {
        thinning(img, 0);
        thinning(img, 1);
        absdiff(img, prev, diff);
        img.copyTo(prev);
    } while (countNonZero(diff) > 0);
}

void thinning(Mat &img, int type) {
    Mat marker = Mat::zeros(img.size(), CV_8UC1);
    for (int i = 1; i < img.rows - 1; i++) {
        for (int j = 1; j < img.cols - 1; j++) {
            uchar p2 = img.at<uchar>(i - 1, j);
            uchar p3 = img.at<uchar>(i - 1, j + 1);
            uchar p4 = img.at<uchar>(i, j + 1);
            uchar p5 = img.at<uchar>(i + 1, j + 1);
            uchar p6 = img.at<uchar>(i + 1, j);
            uchar p7 = img.at<uchar>(i + 1, j - 1);
            uchar p8 = img.at<uchar>(i, j - 1);
            uchar p9 = img.at<uchar>(i - 1, j - 1);
            int A = (!p2 && p3) + (!p3 && p4) + (!p4 && p5) + (!p5 && p6) +
                    (!p6 && p7) + (!p7 && p8) + (!p8 && p9) + (!p9 && p2);
            int B = p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9;
            int m1 = (type == 0) ? (p2 * p4 * p8) : (p2 * p6 * p8);
            int m2 = (type == 0) ? (p2 * p4 * p6) : (p4 * p6 * p8);
            if (A == 1 && (B >= 2 && B <= 6) && m1 == 0 && m2 == 0) {
                marker.at<uchar>(i, j) = 1;
            }
        }
    }
    img &= ~marker;
}

int main() {
    Mat src = imread("test.png", 0);
    threshold(src, src, 128, 255, THRESH_BINARY);
    nsweThinning(src);
    imshow("result", src);
    waitKey(0);
    return 0;
}