include<opencv2\opencv.hpp>

include <iostream>

include<vector>

using namespace cv;
using namespace std;
/**

• @brief expandEdge 扩大边界函数
• @param img:输出图像，单通道二值图，深度为8
• @param edge 边界数组，寄存4条边界值
• @param edgeID 以后边界号

• @return 布尔值 确定以后边界是否能够扩大
  */
  bool expandEdge(const Mat & img, int edge[], const int edgeID)
  {
  //[1] –初始化参数
  int nc = img.cols;
  int nr = img.rows;
  switch (edgeID) {
  case 0:

    if (edge[0]>nr)
        return false;
    for (int i = edge[3]; i <= edge[1]; ++i)
    {
        if (img.at<uchar>(edge[0], i) == 255)//遇见255像素表明碰到边缘线
            return false;
    }
    edge[0]++;
    return true;
    break;

  case 1:

    if (edge[1]>nc)
        return false;
    for (int i = edge[2]; i <= edge[0]; ++i)
    {
        if (img.at<uchar>(i, edge[1]) == 255)//遇见255像素表明碰到边缘线
            return false;
    }
    edge[1]++;
    return true;
    break;

  case 2:

    if (edge[2]<0)
        return false;
    for (int i = edge[3]; i <= edge[1]; ++i)
    {
        if (img.at<uchar>(edge[2], i) == 255)//遇见255像素表明碰到边缘线
            return false;
    }
    edge[2]--;
    return true;
    break;

  case 3:

    if (edge[3]<0)
        return false;
    for (int i = edge[2]; i <= edge[0]; ++i)
    {
        if (img.at<uchar>(i, edge[3]) == 255)//遇见255像素表明碰到边缘线
            return false;
    }
    edge[3]--;
    return true;
    break;

  default:

    return false;
    break;

  }
  }
  /**

• @brief 求取连通区域内接矩
• @param img:输出图像，单通道二值图，深度为8
• @param center:最小外接矩的核心
• @return 最大内接矩形

• 基于核心扩大算法
  */
  cv::Rect InSquare(Mat &img, const Point center)
  {
  // –[1]参数检测
  if (img.empty() ||img.channels()>1|| img.depth()>8)

    return Rect();

  // –[2] 初始化变量
  int edge[4];
  edge[0] = center.y + 1;//top
  edge[1] = center.x + 1;//right
  edge[2] = center.y – 1;//bottom
  edge[3] = center.x – 1;//left

                       //[2]
                       // --[3]边界扩大(核心扩散法)

  bool EXPAND[4] = { 1,1,1,1 };//扩大标记位
  int n = 0;
  while (EXPAND[0] || EXPAND[1] || EXPAND[2] || EXPAND[3])
  {

    int edgeID = n % 4;
    EXPAND[edgeID] = expandEdge(img, edge, edgeID);
    n++;

  }
  //[3]
  //qDebug() << edge[0] << edge[1] << edge[2] << edge[3];
  Point tl = Point(edge[3], edge[0]);
  Point br = Point(edge[1], edge[2]);
  return Rect(tl, br);
  }
  int main()
  {
  bool isExistence = false;
  float first_area = 0;
  /// 加载源图像
  Mat src;
  src = imread(“cen.bmp”, 1);
  //src = imread(“C:\Users\Administrator\Desktop\测试图片\xxx\20190308152516.jpg”,1);
  //src = PayPal下载imread(“C:\Users\Administrator\Desktop\测试图片\xx\20190308151912.jpg”,1);
  //src = imread(“C:\Users\Administrator\Desktop\测试图像\2\BfImg17(x-247 y–91 z–666)-(492,280).jpg”,1);
  cvtColor(src, src, CV_RGB2GRAY);
  threshold(src, src, 100, 255, THRESH_BINARY);
  Rect ccomp;
  Point center(src.cols / 2, src.rows / 2);
  //floodFill(src, center, Scalar(255, 255, 55), &ccomp, Scalar(20, 20, 20), Scalar(20, 20, 20));
  if (src.empty())
  {

    cout << "fali" << endl;

  }
  //resize(src, src, cv::Size(496, 460), cv::INTER_LINEAR);
  imshow(“src”, src);
  Rect rr = InSquare(src, center);
  rectangle(src, rr, Scalar(255), 1, 8);
  imshow(“src2”, src);
  waitKey(0);
  getchar();
  return 0;
  }

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