Halcon实例转OpenCV：计算回形针方向

    Halcon中有一个计算回形针方向的实例clip.hdev，可以在例程中找到。原图如下：

    处理后的结果图：

    代码整理之后，核心部分如下：

dev_close_window ()
dev_open_window (0, 0, 700, 700, 'black', WindowHandle)
dev_clear_window ()
dev_set_color ('green')
read_image(Image, 'clip')
threshold(Image, Region, 0, 56)
connection(Region, ConnectedRegions)
select_shape (ConnectedRegions, SelectedRegions, 'area', 'and', 3161.4, 6315.4)
orientation_region(SelectedRegions, Phi)
area_center(SelectedRegions, Area, Row, Column)

query_font (WindowHandle, Font)
*FontWithSize := Font[0]+'-18'
*set_font(WindowHandle, FontWithSize)
set_display_font (WindowHandle, 15, 'mono', 'true', 'true')

Length := 80
for index := 0 to |Phi|-1 by 1
    set_tposition(WindowHandle, Row[index], Column[index])
    dev_set_color ('black')
    write_string(WindowHandle, deg(Phi[index])$'3.1f' + 'deg') 
    dev_set_color ('blue')
    dev_set_line_width(3)
    disp_arrow(WindowHandle, Row[index], Column[index],Row[index]-Length*sin(Phi[index]), Column[index]+Length*cos(Phi[index]), 4)
endfor

    思路步骤：

    ① 读取图像 

    ② 二值化 

    ③ 根据面积剔除非回形针的region 

    ④ 计算每个region的方向和中心 

    ⑤ 结果输出 

    转到OpenCV时，主要有几个小问题需要理清：

    ① 轮廓的方向怎么计算？直线拟合？还是计算轮廓中心和回形针端点来算角度？

    ② 回形针的端点坐标如何计算？

    ③ 绘制箭头?

    如下是OpenCV实现的部分代码和效果图 :

void drawArrow(cv::Mat& img, cv::Point pStart, cv::Point pEnd, int len, int alpha, cv::Scalar& color, int thickness, int lineType)
{
  //const double PI = 3.1415926;
  Point arrow;
  //计算 θ 角（最简单的一种情况在下面图示中已经展示，关键在于 atan2 函数，详情见下面）   
  double angle = atan2((double)(pStart.y - pEnd.y), (double)(pStart.x - pEnd.x));

  line(img, pStart, pEnd, color, thickness, lineType);

  //计算箭角边的另一端的端点位置（上面的还是下面的要看箭头的指向，也就是pStart和pEnd的位置） 
  arrow.x = pEnd.x + len * cos(angle + PI * alpha / 180);

  arrow.y = pEnd.y + len * sin(angle + PI * alpha / 180);

  line(img, pEnd, arrow, color, thickness, lineType);

  arrow.x = pEnd.x + len * cos(angle - PI * alpha / 180);

  arrow.y = pEnd.y + len * sin(angle - PI * alpha / 180);

  line(img, pEnd, arrow, color, thickness, lineType);
}

double CalLineAngle(Point &ptStart, Point &ptEnd)
{
  double angle = 0.0;
  if (ptStart.x == ptEnd.x)
    angle = 90;
  else if (ptStart.y == ptEnd.y)
    angle = 0;
  else
  {
    angle = atan(double(ptEnd.y - ptStart.y) / (ptEnd.x - ptStart.x)) * (180 / PI);
    if (angle < 0)
      angle = abs(angle);
    else if (angle > 0)
      angle = 180 - angle;
    if (ptEnd.y - ptStart.y > 0 && ptEnd.x - ptStart.x)
      angle = angle - 180;
  }
  return angle;
}


int main()
{
  Mat img = imread("./clip.png");
  if (img.empty())
  {
    cout << "Read image error, please check again!" << endl;
    return 1;
  }
  imshow("src", img);

  Mat gray;
  cvtColor(img, gray, CV_BGR2GRAY);
  threshold(gray, gray, 85, 255, CV_THRESH_BINARY_INV); //二值化
  imshow("threshold", gray);

  vector<vector<Point>> contours;
  vector<Vec4i> hierarcy;

  findContours(gray, contours, hierarcy, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
  cout << "num=" << contours.size() << endl;
  vector<Rect> boundRect(contours.size());  //定义外接矩形集合
  vector<RotatedRect> box(contours.size()); //定义最小外接矩形集合

  Point2f rect[4];
  for (int i = 0; i<contours.size(); i++)
  {
    box[i] = minAreaRect(Mat(contours[i]));  //计算每个轮廓最小外接矩形
                         //boundRect[i] = boundingRect(Mat(contours[i]));
    if (box[i].size.width < 50 || box[i].size.height < 50)
      continue;
    ......
   }

    二值化效果：

    结果图：