(OpenCV Study) Background subtraction and Draw blob to red rectangle (example source code)

I use MOG2 algorithm to background subtraction.

The process is
resize to small for more fast processing
to blur for avoid noise affection
morphology make blob and remove noise
findContour to draw blob rectangle

Example movie of result.

more detail refer to source code..

#include < stdio.h>
#include < iostream>

#include < opencv2\opencv.hpp>
#include < opencv2/core/core.hpp>
#include < opencv2/highgui/highgui.hpp>
#include < opencv2/video/background_segm.hpp>


#ifdef _DEBUG        
#pragma comment(lib, "opencv_core247d.lib")
#pragma comment(lib, "opencv_imgproc247d.lib")   //MAT processing
#pragma comment(lib, "opencv_objdetect247d.lib") //HOGDescriptor
//#pragma comment(lib, "opencv_gpu247d.lib")
//#pragma comment(lib, "opencv_features2d247d.lib")
#pragma comment(lib, "opencv_highgui247d.lib")
#pragma comment(lib, "opencv_ml247d.lib")
//#pragma comment(lib, "opencv_stitching247d.lib");
//#pragma comment(lib, "opencv_nonfree247d.lib");
#pragma comment(lib, "opencv_video247d.lib")
#else
#pragma comment(lib, "opencv_core247.lib")
#pragma comment(lib, "opencv_imgproc247.lib")
#pragma comment(lib, "opencv_objdetect247.lib")
//#pragma comment(lib, "opencv_gpu247.lib")
//#pragma comment(lib, "opencv_features2d247.lib")
#pragma comment(lib, "opencv_highgui247.lib")
#pragma comment(lib, "opencv_ml247.lib")
//#pragma comment(lib, "opencv_stitching247.lib");
//#pragma comment(lib, "opencv_nonfree247.lib");
#pragma comment(lib, "opencv_video247d.lib")
#endif 

using namespace cv;
using namespace std;



int main()
{

 //global variables
 Mat frame; //current frame
 Mat resize_blur_Img;
 Mat fgMaskMOG2; //fg mask fg mask generated by MOG2 method
 Mat binaryImg;
 //Mat TestImg;
 Mat ContourImg; //fg mask fg mask generated by MOG2 method
 Ptr< BackgroundSubtractor> pMOG2; //MOG2 Background subtractor
 
 pMOG2 = new BackgroundSubtractorMOG2(300,32,true);//300,0.0);
 
 char fileName[100] = "mm2.avi"; //video\\mm2.avi"; //mm2.avi"; //cctv 2.mov"; //mm2.avi"; //";//_p1.avi";
 VideoCapture stream1(fileName);   //0 is the id of video device.0 if you have only one camera   

 //morphology element
 Mat element = getStructuringElement(MORPH_RECT, Size(7, 7), Point(3,3) );   

 //unconditional loop   
 while (true) {   
  Mat cameraFrame;   
  if(!(stream1.read(frame))) //get one frame form video   
   break;
  
  //Resize
  resize(frame, resize_blur_Img, Size(frame.size().width/3, frame.size().height/3) );
  //Blur
  blur(resize_blur_Img, resize_blur_Img, Size(4,4) );
  //Background subtraction
  pMOG2->operator()(resize_blur_Img, fgMaskMOG2, -1);//,-0.5);
  
  ///////////////////////////////////////////////////////////////////
  //pre procesing
  //1 point delete
  //morphologyEx(fgMaskMOG2, fgMaskMOG2, CV_MOP_ERODE, element);
  morphologyEx(fgMaskMOG2, binaryImg, CV_MOP_CLOSE, element);
  //morphologyEx(fgMaskMOG2, testImg, CV_MOP_OPEN, element);

  //Shadow delete
  //Binary
  threshold(binaryImg, binaryImg, 128, 255, CV_THRESH_BINARY);

  //Find contour
  ContourImg = binaryImg.clone();
  //less blob delete
  vector< vector< Point> > contours;
  findContours(ContourImg,
            contours, // a vector of contours
            CV_RETR_EXTERNAL, // retrieve the external contours
            CV_CHAIN_APPROX_NONE); // all pixels of each contours

  vector< Rect > output;
  vector< vector< Point> >::iterator itc= contours.begin();
  while (itc!=contours.end()) {

   //Create bounding rect of object
   //rect draw on origin image
   Rect mr= boundingRect(Mat(*itc));
   rectangle(resize_blur_Img, mr, CV_RGB(255,0,0));
   ++itc;
  }
  

  ///////////////////////////////////////////////////////////////////

  //Display
  imshow("Shadow_Removed", binaryImg);
  imshow("Blur_Resize", resize_blur_Img);
  imshow("MOG2", fgMaskMOG2);

  if (waitKey(5) >= 0)   
   break;   
 }

}