用C++和opencv实现连通区域标记的二次扫描算法

以下是使用C和OpenCV实现连通区域标记的二次扫描算法的示例代码：

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

using namespace cv;
using namespace std;

int main(int argc, char** argv)
{
    // Load the input image
    Mat image = imread("input_image.jpg", IMREAD_GRAYSCALE);

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

    // Threshold the image to create a binary image
    Mat binary_image;
    threshold(image, binary_image, 128, 255, THRESH_BINARY);

    // Create a label matrix to store the connected component labels
    Mat label_matrix(binary_image.size(), CV_32SC1);

    // Initialize the label matrix to -1
    label_matrix.setTo(-1);

    // Define a label variable to assign to connected components
    int label = 0;

    // Perform the first pass of the algorithm to assign labels to connected components
    for (int i = 0; i < binary_image.rows; i++)
    {
        for (int j = 0; j < binary_image.cols; j++)
        {
            if (binary_image.at<uchar>(i, j) == 255)
            {
                // Check the neighboring pixels for labels
                int left_label = (j > 0) ? label_matrix.at<int>(i, j - 1) : -1;
                int top_label = (i > 0) ? label_matrix.at<int>(i - 1, j) : -1;

                if (left_label == -1 && top_label == -1)
                {
                    // If there are no labels in the neighboring pixels, assign a new label
                    label_matrix.at<int>(i, j) = label;
                    label++;
                }
                else if (left_label != -1 && top_label == -1)
                {
                    // If there is a label in the left pixel, assign it to the current pixel
                    label_matrix.at<int>(i, j) = left_label;
                }
                else if (left_label == -1 && top_label != -1)
                {
                    // If there is a label in the top pixel, assign it to the current pixel
                    label_matrix.at<int>(i, j) = top_label;
                }
                else if (left_label != -1 && top_label != -1)
                {
                    // If there are labels in both neighboring pixels, assign the minimum label to the current pixel
                    int min_label = min(left_label, top_label);
                    label_matrix.at<int>(i, j) = min_label;

                    // Update the equivalence table
                    if (left_label != top_label)
                    {
                        for (int k = 0; k < j; k++)
                        {
                            if (label_matrix.at<int>(i, k) == left_label)
                            {
                                label_matrix.at<int>(i, k) = top_label;
                            }
                        }
                    }
                }
            }
        }
    }

    // Perform the second pass of the algorithm to update the labels based on the equivalence table
    for (int i = 0; i < binary_image.rows; i++)
    {
        for (int j = 0; j < binary_image.cols; j++)
        {
            if (label_matrix.at<int>(i, j) != -1)
            {
                label_matrix.at<int>(i, j) = label_matrix.at<int>(i, label_matrix.at<int>(i, j));
            }
        }
    }

    // Draw the labeled regions on the original image
    Mat result_image = image.clone();
    for (int i = 0; i < binary_image.rows; i++)
    {
        for (int j = 0; j < binary_image.cols; j++)
        {
            if (label_matrix.at<int>(i, j) != -1)
            {
                Scalar color = Scalar(rand() % 256, rand() % 256, rand() % 256);
                rectangle(result_image, Point(j, i), Point(j, i), color, 2);
            }
        }
    }

    // Display the result image
    imshow("Result Image", result_image);
    waitKey(0);

    return 0;
}

此代码使用OpenCV库加载输入图像，并将其阈值化为二进制图像。然后，它使用二次扫描算法将标签分配给连通组件，并更新标签以考虑等价性。最后，它在原始图像上绘制标记的区域，并显示结果图像。