使用C++，openmp，opencv实现连通区域标记的二遍扫描算法，将读入需要进行连通区域标记的图像，将其二值化，使用动态二维数组来存储每个像素所属的连通区域标记，将输出图像显示在一个窗口中

#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: ./connected_components <image_path>\n");
return -1;
}

Mat image, gray_image, binary_image;
image = imread(argv[1], IMREAD_COLOR);

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

cvtColor(image, gray_image, COLOR_BGR2GRAY);
threshold(gray_image, binary_image, 128, 255, THRESH_BINARY);

int rows = binary_image.rows;
int cols = binary_image.cols;

int **label = new int*[rows];
for (int i = 0; i < rows; i++)
label[i] = new int[cols];

// Initialize label matrix to all zeros
for (int i = 0; i < rows; i++)
for (int j = 0; j < cols; j++)
label[i][j] = 0;

int label_count = 1;

// First pass
#pragma omp parallel for
for (int i = 1; i < rows-1; i++)
for (int j = 1; j < cols-1; j++)
if (binary_image.at<uchar>(i,j) == 255)
{
int min_label = 255;

if (label[i-1][j-1] != 0 && label[i-1][j-1] < min_label)
min_label = label[i-1][j-1];
if (label[i-1][j] != 0 && label[i-1][j] < min_label)
min_label = label[i-1][j];
if (label[i-1][j+1] != 0 && label[i-1][j+1] < min_label)
min_label = label[i-1][j+1];
if (label[i][j-1] != 0 && label[i][j-1] < min_label)
min_label = label[i][j-1];

if (min_label == 255)
label[i][j] = label_count++;
else
label[i][j] = min_label;

if (label[i-1][j-1] != 0 && label[i-1][j-1] != min_label)
label[label[i-1][j-1]][j-1] = min_label;
if (label[i-1][j] != 0 && label[i-1][j] != min_label)
label[label[i-1][j]][j] = min_label;
if (label[i-1][j+1] != 0 && label[i-1][j+1] != min_label)
label[label[i-1][j+1]][j+1] = min_label;
if (label[i][j-1] != 0 && label[i][j-1] != min_label)
label[label[i][j-1]][j-1] = min_label;
}

// Second pass
#pragma omp parallel for
for (int i = 1; i < rows-1; i++)
for (int j = 1; j < cols-1; j++)
if (label[i][j] != 0)
{
int root = label[i][j];
while (root != label[root/cols][root%cols])
root = label[root/cols][root%cols];

label[i][j] = root;
}

// Color each connected component with a different color
Vec3b colors[label_count];
for (int i = 0; i < label_count; i++)
colors[i] = Vec3b(rand()%256, rand()%256, rand()%256);

Mat output_image(rows, cols, CV_8UC3);
for (int i = 0; i < rows; i++)
for (int j = 0; j < cols; j++)
output_image.at<Vec3b>(i,j) = colors[label[i][j]];

namedWindow("Output Image", WINDOW_AUTOSIZE);
imshow("Output Image", output_image);
waitKey(0);

return 0;
}