opencv用C++语言实现随机游走图像分割

随机游走图像分割是一种基于图论算法的图像分割方法，其基本思想是将图像看作一个图，通过随机游走的方式寻找图像中不同区域的边界。本文将介绍如何使用OpenCV库和C语言实现随机游走图像分割。

1. 图像预处理

首先，需要对输入的图像进行预处理，将其转换为灰度图像，并进行高斯滤波和边缘检测，以便更好地找到图像的边界。这可以通过以下代码实现：

Mat src = imread("input.jpg", IMREAD_GRAYSCALE);
Mat blur;
GaussianBlur(src, blur, Size(5, 5), 0);
Mat edges;
Canny(blur, edges, 50, 200);

2. 构建图像的邻接矩阵

接下来，需要将图像转换为一个邻接矩阵，以便进行随机游走。邻接矩阵中的每个元素表示两个像素之间是否存在边。这里使用4邻域连接，即每个像素与其上下左右四个像素相连。邻接矩阵可以通过以下代码实现：

int rows = edges.rows;
int cols = edges.cols;
int num_vertices = rows * cols;
Mat adj_matrix = Mat::zeros(num_vertices, num_vertices, CV_32F);
for (int i = 0; i < rows; i++) {
  for (int j = 0; j < cols; j++) {
    int vertex = i * cols + j;
    if (i > 0) {
      adj_matrix.at<float>(vertex, (i - 1) * cols + j) = edges.at<uchar>(i - 1, j) / 255.0;
    }
    if (j > 0) {
      adj_matrix.at<float>(vertex, i * cols + (j - 1)) = edges.at<uchar>(i, j - 1) / 255.0;
    }
    if (i < rows - 1) {
      adj_matrix.at<float>(vertex, (i + 1) * cols + j) = edges.at<uchar>(i + 1, j) / 255.0;
    }
    if (j < cols - 1) {
      adj_matrix.at<float>(vertex, i * cols + (j + 1)) = edges.at<uchar>(i, j + 1) / 255.0;
    }
  }
}

3. 随机游走

随机游走的过程中，从图像中随机选取一个像素作为起点，然后根据邻接矩阵中的权重随机选择下一个像素，直至到达一个边界像素。这个过程可以重复多次，以获得更好的分割结果。

int num_walks = 10000; // 随机游走次数
int num_labels = 2; // 分割结果的类别数
vector<int> labels(num_vertices);
for (int i = 0; i < num_walks; i++) {
  int start_vertex = rand() % num_vertices;
  int curr_vertex = start_vertex;
  while (true) {
    vector<int> neighbors;
    for (int j = 0; j < num_vertices; j++) {
      if (adj_matrix.at<float>(curr_vertex, j) > 0) {
        neighbors.push_back(j);
      }
    }
    if (neighbors.empty()) {
      break;
    }
    int next_vertex = neighbors[rand() % neighbors.size()];
    curr_vertex = next_vertex;
    if (edges.at<uchar>(curr_vertex / cols, curr_vertex % cols) > 0) {
      labels[start_vertex] = 1;
      break;
    }
  }
}

4. 显示分割结果

最后，将分割结果显示出来。可以将分割结果中标记为1的像素显示为白色，其他像素显示为黑色。

Mat result = Mat::zeros(rows, cols, CV_8U);
for (int i = 0; i < rows; i++) {
  for (int j = 0; j < cols; j++) {
    int vertex = i * cols + j;
    if (labels[vertex] == 1) {
      result.at<uchar>(i, j) = 255;
    }
  }
}
imshow("result", result);
waitKey(0);

完整代码如下：

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

using namespace std;
using namespace cv;

int main() {
  Mat src = imread("input.jpg", IMREAD_GRAYSCALE);
  Mat blur;
  GaussianBlur(src, blur, Size(5, 5), 0);
  Mat edges;
  Canny(blur, edges, 50, 200);

  int rows = edges.rows;
  int cols = edges.cols;
  int num_vertices = rows * cols;
  Mat adj_matrix = Mat::zeros(num_vertices, num_vertices, CV_32F);
  for (int i = 0; i < rows; i++) {
    for (int j = 0; j < cols; j++) {
      int vertex = i * cols + j;
      if (i > 0) {
        adj_matrix.at<float>(vertex, (i - 1) * cols + j) = edges.at<uchar>(i - 1, j) / 255.0;
      }
      if (j > 0) {
        adj_matrix.at<float>(vertex, i * cols + (j - 1)) = edges.at<uchar>(i, j - 1) / 255.0;
      }
      if (i < rows - 1) {
        adj_matrix.at<float>(vertex, (i + 1) * cols + j) = edges.at<uchar>(i + 1, j) / 255.0;
      }
      if (j < cols - 1) {
        adj_matrix.at<float>(vertex, i * cols + (j + 1)) = edges.at<uchar>(i, j + 1) / 255.0;
      }
    }
  }

  int num_walks = 10000;
  int num_labels = 2;
  vector<int> labels(num_vertices);
  for (int i = 0; i < num_walks; i++) {
    int start_vertex = rand() % num_vertices;
    int curr_vertex = start_vertex;
    while (true) {
      vector<int> neighbors;
      for (int j = 0; j < num_vertices; j++) {
        if (adj_matrix.at<float>(curr_vertex, j) > 0) {
          neighbors.push_back(j);
        }
      }
      if (neighbors.empty()) {
        break;
      }
      int next_vertex = neighbors[rand() % neighbors.size()];
      curr_vertex = next_vertex;
      if (edges.at<uchar>(curr_vertex / cols, curr_vertex % cols) > 0) {
        labels[start_vertex] = 1;
        break;
      }
    }
  }

  Mat result = Mat::zeros(rows, cols, CV_8U);
  for (int i = 0; i < rows; i++) {
    for (int j = 0; j < cols; j++) {
      int vertex = i * cols + j;
      if (labels[vertex] == 1) {
        result.at<uchar>(i, j) = 255;
      }
    }
  }
  imshow("result", result);
  waitKey(0);
  return 0;
}