(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:

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