Opencv分水岭算法学习

#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
#include<iostream>

using namespace cv;
using namespace std;
//宏定义
#define WINDOW_NAME "image[procedure window]"

//全局变量声明
Mat g_srcImage,g_maskImage;
Point prevPt(-1,-1);

//全局函数声明
static void on_Mouse(int event,int x,int y,int flags,void*);

//主函数
int main()
{
  //载入源图像
  g_srcImage=imread("/Users/new/Desktop/1.jpg");
  if(!g_srcImage.data){printf("读取源图像srcImage错误～！\n");return false;}

  //显示源图像
  imshow(WINDOW_NAME,g_srcImage);
  Mat srcImage,grayImage;
  g_srcImage.copyTo(srcImage);
  //灰度化
  cvtColor(srcImage, g_maskImage, COLOR_BGR2GRAY);
  //imshow("image[mask]",g_maskImage);
  cvtColor(g_maskImage, grayImage, COLOR_GRAY2BGR);
  //imshow("image[gray]",grayImage);
  //掩膜图像初始化为0
  g_maskImage=Scalar::all(0);

  //设置鼠标回调函数
  setMouseCallback(WINDOW_NAME, on_Mouse,0);

  //轮询按键处理
  while(1)
  {
    //获取键值
    int c=waitKey(0);
    //若按键为ESC时，退出
    if((char)c == 27)
      break;
    //若按键为2时，恢复原图
    if((char)c=='2')
    {
      g_maskImage=Scalar::all(0);
      srcImage.copyTo(g_srcImage);
      imshow("image",g_srcImage);
    }
    //若按键为1,则进行处理
    if((char)c=='1')
    {
      //定义一些参数
      int i,j,compCount=0;
      vector<vector<Point>>contours;
      vector<Vec4i> hierarchy;
      //寻找轮廓
      findContours(g_maskImage, contours, hierarchy, CV_RETR_CCOMP, CHAIN_APPROX_SIMPLE);
      //轮廓为空时的处理
      if(contours.empty())
        continue;
      //复制掩膜
      Mat maskImage(g_maskImage.size(),CV_32S);
      maskImage=Scalar::all(0);

      //循环绘制轮廓
      for(int index=0;index>=0;index=hierarchy[index][0],++compCount)
        drawContours(maskImage, contours, index, Scalar::all(compCount+1),-1,8,hierarchy,INT_MAX);
        //compCount为零时的处理
        if(compCount==0)
          continue;

        //生成随机颜色
        vector<Vec3b>colorTab;
        for(int i=0;i<compCount;++i)
        {
          int b=theRNG().uniform(0, 255);
          int g=theRNG().uniform(0, 255);
          int r=theRNG().uniform(0, 255);

          colorTab.push_back(Vec3b((uchar)b,(uchar)g,(uchar)r));
        }
        //计算处理时间并输出到窗口中
        double dTime=(double)getTickCount();
        //进行分水岭算法
        watershed(srcImage, maskImage);
        dTime=(double)getTickCount()-dTime;
        printf("\t 处理时间=%gms\n",dTime*1000./getTickFrequency());
        //双层循环，将分水岭图像遍历存入watershedImage中
        Mat watershedImage(maskImage.size(),CV_8UC3);
        for(i=0;i<maskImage.rows;++i)
          for(j=0;j<maskImage.cols;++j)
          {
            int index=maskImage.at<int>(i,j);
            if(index==-1)
              watershedImage.at<Vec3b>(i,j)=Vec3b(255,255,255);//图像变白色
            else if(index<=0||index>compCount)
              watershedImage.at<Vec3b>(i,j)=Vec3b(0,0,0);//图像变黑色
            else
              watershedImage.at<Vec3b>(i,j)=colorTab[index-1];
          }
        //混合灰度图和分水岭效果图并显示最终的窗口
        watershedImage=watershedImage*0.5+grayImage*0.5;
        imshow("image[watershed]",watershedImage);
    }
  }
    return 0;
}

//回调函数定义
void on_Mouse(int event,int x,int y,int flags,void*)
{
  //处理鼠标不在窗口中的情况
  if(x<0||x>=g_srcImage.cols||y<0||y>=g_srcImage.rows)
    return;

  //处理鼠标左键相关消息
  if(event==EVENT_LBUTTONUP||!(flags & EVENT_FLAG_LBUTTON))//按下左键
    prevPt=Point(-1,-1);
  else if(event==EVENT_LBUTTONDOWN)//松开左键
    prevPt=Point(x,y);//鼠标所指的位置

  //鼠标左键按下并移动，绘制出白色线条
  else if(event==EVENT_MOUSEMOVE && (flags & EVENT_FLAG_LBUTTON))
  {
    Point pt(x,y);
    if(prevPt.x<0)//如果指出去了，返回
      prevPt=pt;
    line(g_maskImage, prevPt, pt, Scalar::all(255),2,8,0);//画白线
    line(g_srcImage,prevPt,pt,Scalar::all(255),2,8,0);//画白线
    prevPt=pt;
    imshow(WINDOW_NAME, g_srcImage);

  }
}

//计算处理时间并输出到窗口中
        double dTime=(double)getTickCount();
        //进行分水岭算法
        watershed(srcImage, maskImage);
        dTime=(double)getTickCount()-dTime;
        printf("\t 处理时间=%gms\n",dTime*1000./getTickFrequency());

对于单通道的图像：image.at<uchar>(i, j)
对于RGB通道的图像：image.at<Vec3b>(i, j)[0] 
         image.at<Vec3b>(i, j)[1] 
         image.at<Vec3b>(i, j)[2]