opencv三帧差、帧差

//三帧差

#include "stdafx.h"
#include "highgui.h"  
#include "cxcore.h"  
#include "ml.h"  
#include "cv.h"  

using namespace std;
using namespace cv;

#define thresholded 15 //设置简单帧差法阈值

int main(int argc,unsigned char* argv[])
{
	Mat img,img1,img2,img3;//3帧法需要3帧图片

	Mat imgGray;
	Mat result1,result2,result;//存储2次相减的图片
	VideoCapture vido_file("C:/Users/acer/Desktop/cut/车辆.avi");//在这里改相应的文件名
	int frameCount = vido_file.get(CV_CAP_PROP_FRAME_COUNT);//获取帧数  
	cout<>img;
	  cvtColor(img,img,CV_BGR2GRAY);
	  ++count;
	  if(count%3==1)
	  {
		  if(count==1)
			  goto L;  
		  img1=img;
		  result1=abs(img1-img3);
		  threshold(result1,result1,thresholded,255,cv::THRESH_BINARY);		  
		  imshow("result1",result1);
	  }

	  if(count%3==2)
	  {
		  img2=img;
		  result2=abs(img2-img1);
		  threshold(result2,result2,thresholded,255,cv::THRESH_BINARY); 
		  imshow("result2",result2);
	  }

	  if(count%3==0)
	  {
		  img3=img;
		  if(count==3)
			  goto L;
		  bitwise_and(result1,result2,result);
		  //threshold(result,result,thresholded,255,cv::THRESH_BINARY);  
		  Mat kernel_dilate = getStructuringElement(MORPH_RECT, Size(6, 6));  
		  dilate(result, result, kernel_dilate); 
		  //dilate(gray,gray,Mat());
		  //erode(gray,gray,Mat());
		  imshow("foreground",result);
	  }
  }
  if( cvWaitKey(33) >= 0 )
	  break;
	}
	return 0;
}

//帧差

while（1）
{
if (img.empty())//对帧进行异常检测  
			{  
			cout << "frame is empty!" << endl;  
			break;  
			}
			if (i == 0)// 
			{  
			result = MoveDetect(img, img);
			}  
			else//若不是第一帧（temp有值了）  
			{  
			result = MoveDetect(temp, img);

			}  			
			imshow("result", result);  

if (waitKey(1000.0 / FPS) == 27)//按原FPS显示  
			{  cout << "ESC退出!" << endl;  
			break;}  
			temp = img.clone(); 
}
Mat MoveDetect(Mat temp, Mat frame)  
{  
	Mat result = frame.clone();  
	//1.将background和frame转为灰度图  
	Mat gray1, gray2;  
	cvtColor(temp, gray1, CV_BGR2GRAY);  
	cvtColor(frame, gray2, CV_BGR2GRAY);  
	//2.将background和frame做差  
	Mat diff;  
	absdiff(gray1, gray2, diff);  
	//imshow("diff", diff);  
	//3.对差值图diff_thresh进行阈值化处理  
	Mat diff_thresh;  
	threshold(diff, diff_thresh, 80, 255, CV_THRESH_BINARY);  
	//imshow("diff_thresh", diff_thresh);  
	//4.腐蚀  
	 Mat kernel_erode = getStructuringElement(MORPH_RECT, Size(3, 3));  
	  Mat kernel_dilate = getStructuringElement(MORPH_RECT, Size(18, 18));  


	 erode(diff_thresh, diff_thresh, kernel_erode);  
  //imshow("erode", diff_thresh);  
	//5.膨胀  
	   dilate(diff_thresh, diff_thresh, kernel_dilate);  
	  imshow("dilate", diff_thresh);  
	//6.查找轮廓并绘制轮廓  
	vector > contours;  
	findContours(diff_thresh, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);  
	drawContours(result, contours, -1, Scalar(0, 0, 255), 2);//在result上绘制轮廓  
	//7.查找正外接矩形  
	vector boundRect(contours.size());  
	for (int i = 0; i < contours.size(); i++)  
	{  
	boundRect[i] = boundingRect(contours[i]);  
	rectangle(result, boundRect[i], Scalar(0, 255, 0), 2);//在result上绘制正外接矩形  
	}  
	return diff_thresh;
	// return result;//返回result  
}