用C++，openmp，opencv实现连通区域标记的二遍扫描算法，并且使用动态二维数组存储标记信息

以下是用C，OpenMP和OpenCV实现连通区域标记的二遍扫描算法的代码。该算法使用动态二维数组存储标记信息。

#include <stdio.h>
#include <stdlib.h>
#include <omp.h>
#include <opencv2/opencv.hpp>

using namespace cv;

int main(int argc, char** argv)
{
    if (argc != 2)
    {
        printf("Usage: %s <image_file>\n", argv[0]);
        return -1;
    }

    Mat image = imread(argv[1], IMREAD_GRAYSCALE);

    if (image.empty())
    {
        printf("Could not open or find the image\n");
        return -1;
    }

    int height = image.rows;
    int width = image.cols;

    // Allocate memory for label matrix
    int** labels = new int*[height];
    for (int i = 0; i < height; i++)
    {
        labels[i] = new int[width];
        memset(labels[i], 0, width * sizeof(int));
    }

    // First pass
    int label = 1;
    #pragma omp parallel for
    for (int i = 1; i < height - 1; i++)
    {
        for (int j = 1; j < width - 1; j++)
        {
            if (image.at<uchar>(i, j) == 0)
            {
                continue;
            }

            int up = labels[i - 1][j];
            int left = labels[i][j - 1];
            int diag = labels[i - 1][j - 1];

            if (up == 0 && left == 0 && diag == 0)
            {
                labels[i][j] = label++;
            }
            else
            {
                int minLabel = INT_MAX;

                if (up != 0 && up < minLabel)
                {
                    minLabel = up;
                }

                if (left != 0 && left < minLabel)
                {
                    minLabel = left;
                }

                if (diag != 0 && diag < minLabel)
                {
                    minLabel = diag;
                }

                labels[i][j] = minLabel;

                if (up != 0 && up != minLabel)
                {
                    #pragma omp critical
                    {
                        labels[i - 1][j] = minLabel;
                    }
                }

                if (left != 0 && left != minLabel)
                {
                    #pragma omp critical
                    {
                        labels[i][j - 1] = minLabel;
                    }
                }

                if (diag != 0 && diag != minLabel)
                {
                    #pragma omp critical
                    {
                        labels[i - 1][j - 1] = minLabel;
                    }
                }
            }
        }
    }

    // Second pass
    #pragma omp parallel for
    for (int i = 0; i < height; i++)
    {
        for (int j = 0; j < width; j++)
        {
            int curLabel = labels[i][j];

            if (curLabel != 0)
            {
                int minLabel = curLabel;

                while (minLabel != labels[minLabel - 1][0])
                {
                    minLabel = labels[minLabel - 1][0];
                }

                #pragma omp critical
                {
                    labels[i][j] = minLabel;
                }
            }
        }
    }

    // Display labeled image
    Mat labeledImage(height, width, CV_8UC3, Scalar(0, 0, 0));

    for (int i = 0; i < height; i++)
    {
        for (int j = 0; j < width; j++)
        {
            int curLabel = labels[i][j];

            if (curLabel != 0)
            {
                int color = (curLabel * 100) % 255;
                labeledImage.at<Vec3b>(i, j) = Vec3b(color, color, color);
            }
        }
    }

    namedWindow("Labeled Image", WINDOW_NORMAL);
    imshow("Labeled Image", labeledImage);
    waitKey(0);

    // Free memory
    for (int i = 0; i < height; i++)
    {
        delete[] labels[i];
    }

    delete[] labels;

    return 0;
}