(六)OpenCV视频分析与对象跟踪_07_视频中移动对象统计

基于BSM模型
提取前景ROI区域对象轮廓
排除干扰与统计

#include <opencv2/opencv.hpp>
#include <iostream>
//#define _CRT_SECURE_NO_WARNINGS

using namespace cv;
using namespace std;

int main(int argc, char** argv)
{
	VideoCapture capture;
	capture.open("../path.avi");
	if (!capture.isOpened())
	{
		cout << "could not load video..." << endl;
		return -1;
	}

	//初始BS模型
	//图像分割(GMM - 高斯混合模型)
	Ptr<BackgroundSubtractor> pMOG2 = createBackgroundSubtractorMOG2();
	Mat fgmask;

	Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));//形态学操作kernel

	//定义轮廓
	vector<vector<Point>> contours;
	vector<Vec4i> hierarchy;

	Mat frame;
	namedWindow("Video_demo", WINDOW_AUTOSIZE);
	while (capture.read(frame))
	{
		pMOG2->apply(frame, fgmask);//BS
		threshold(fgmask, fgmask, 0, 255, THRESH_BINARY);//二值化
		morphologyEx(fgmask, fgmask, MORPH_OPEN, kernel, Point(-1, -1));//形态学操作
		
		findContours(fgmask, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point());//查找轮廓

		int count_contours = 0;//用于计算轮廓数
		char numText[16];//buffer
		for (size_t i = 0; i < contours.size(); i++)
		{
			double area = contourArea(contours[i]);
			if (area < 10) continue;//面积太小就抛弃
			Rect ROI = boundingRect(contours[i]);//获取轮廓(最小外包围矩形框)
			if (ROI.width < 3 || ROI.height < 3)continue;//ROI区域太小也抛弃
			count_contours++;
			rectangle(frame, ROI, Scalar(255, 0, 255), 2, 8);//绘制轮廓外包围最小矩形框
			sprintf(numText, "%d", count_contours);//把count_contours格式化存放到numText中
			putText(frame, numText, Point(ROI.x, ROI.y), FONT_HERSHEY_PLAIN, 1, Scalar(255, 0, 0), 1, 8);
		}

		imshow("Video_demo", frame);
		char c = waitKey(100);
		if (c == 27)
		{
			break;
		}
	}

	capture.release();
	waitKey(0);
	return 0;
}

输出结果: