opencv c++ 摄像头移动物体追踪 [待完善, API版本有兼容问题]

OpencvBackSport.cpp

#include "stdafx.h"
#include "OpenTest1.h"

#include<iostream>
#include<opencv2/core/core.hpp>
#include<opencv2/imgproc/imgproc.hpp>
#include<opencv2/highgui/highgui.hpp>
#include <opencv2\opencv.hpp>


using namespace std;
using namespace cv;



//----------------------------------------------------------------MOG2 algorithm  MOG2 背景减法
//https://www.youtube.com/user/feelmare
//http://study.marearts.com/2014/04/opencv-study-background-subtraction-and.html

void InitData3() {
	//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;
	}
}






//---------------------------------------------------------------目标追踪之前景建模(定期背景更新模型)
//https://blog.csdn.net/smuevian/article/details/70215946



void process(Mat& frame, Mat &background, Mat &backImage, Mat &foreground, Mat &output, int threshold, double learningRate) {
	//当前灰度图像
	Mat gray;
	//将读取的帧图像转化为灰度图像
	cvtColor(frame, gray, CV_BGR2GRAY);
	if (background.empty())
		//第一帧  
		gray.convertTo(background, CV_32F);
	//背景转为CV_8U格式以便求取和当前帧差的绝对值  
	background.convertTo(backImage, CV_8U);
	//求当前帧与背景的差别  
	absdiff(backImage, gray, foreground);
	//过滤掉前景中与背景差别不大的扰动点  [二值化]
	cv::threshold(foreground, output, threshold, 255, THRESH_BINARY_INV);
	//更新背景，output作为掩码  
	accumulateWeighted(gray, background, learningRate, output);

	imshow("testBack", background / 255);

}
void InitData2() {
	//视频路径
	//string FilePath = "E:/study/book/opencv/opencv-2-cookbook-src-master/images/bike.avi";
	//读取视频
	VideoCapture capture(0);
	if (!capture.isOpened()) {
		//cout << "Can't open the video!" << endl;
		return;
	}
	//读取帧率
	double rate = capture.get(CV_CAP_PROP_FPS);
	rate = 25;

	bool stop(false);
	namedWindow("Extracted Frame");
	Mat frame;
	int delay = 1000 / rate;
	Mat gray;	//当前灰度图像
	Mat background;//累积的背景图像
	Mat backImage;	//背景图像
	Mat foreground;//前景图像
	Mat output;
	double learningRate = 0.5;
	int threshold = 10;
	while (!stop) {
		if (!capture.read(frame))
			break;
		//处理的程序应该放在这里...
		process(frame, background, backImage, foreground, output, threshold, learningRate);
		//imshow("Extracted Frame", frame);
		imshow("Extracted Frame", output);
		if (waitKey(delay) > 0)
			stop = true;

	}
	capture.release();
	waitKey();
}




//---------------------------------------------------------------最简单的实现差值运算显示内容

Mat background;
int count3 = 0;

//最简单的差值处理
void displayImage(Mat src) {

	Mat resultx = src.clone();
	Mat gray1, gray2;
	Mat diff;

	cvtColor(background, gray1, CV_BGR2GRAY);
	cvtColor(src, gray2, CV_BGR2GRAY);

	absdiff(gray1, gray2, diff);
	imshow("DiffImag", diff);

	medianBlur(diff, diff, 5);//中值滤波
	imshow("medianBlurImag", diff);

	Mat element = getStructuringElement(MORPH_RECT, Size(3, 3));
	dilate(diff, diff, element);
	imshow("dilateImag", diff);

	//threshold(diff, diff, 50, 255, CV_THRESH_BINARY);//灰度二值化
	//imshow("thresholdImag", diff);
}

void InitData() {
	Mat frame;
	VideoCapture cap(0);

	if (!cap.isOpened())
	{
		return;
	}

	while (true)
	{
		cap >> frame;

		if (!frame.empty())
		{
			count3++;
			if (count3 < 10)
			{
				waitKey(10);
				continue;
			}

			if (count3 == 10) {
				background = frame.clone(); //提取第一帧为背景帧
			}

			displayImage(frame);
			
			imshow("nowImage", frame);
			waitKey(10);

		}
	}
	cap.release();


}



OpenTest1::OpenTest1()
{
	//InitData();
	InitData2();
}


OpenTest1::~OpenTest1()
{
}