OpenCV4入门教程149：背景前景提取

本文介绍如何将背景和前景分割开来。

MOG2版


//---------------------------------【头文件、命名空间包含部分】----------------------------
//      描述：包含程序所使用的头文件和命名空间
//------------------------------------------------------------------------------------------------
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/video/background_segm.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <stdio.h>
using namespace std;
using namespace cv;

static void help()
{
    printf("\n\n\t此程序展示了视频前后背景分离的方法,采用cvUpdateBGStatModel()方法.\n"
        "\n\n\t程序首先会“学习背景”，然后进行分割。\n"
        "\n\n\t可以用过【Space】空格进行功能切换。\n\n");
}


//-----------------------------------【main( )函数】--------------------------------------------
//      描述：控制台应用程序的入口函数，我们的程序从这里开始
//-------------------------------------------------------------------------------------------------
int main(int argc, const char** argv)
{
    help();
    VideoCapture cap;
    bool update_bg_model = true;

    cap.open(0);

    if( !cap.isOpened() )
    {
        printf("can not open camera or video file\n");
        return -1;
    }

    namedWindow("image", WINDOW_AUTOSIZE);
    namedWindow("foreground mask", WINDOW_AUTOSIZE);
    namedWindow("foreground image", WINDOW_AUTOSIZE);
    namedWindow("mean background image", WINDOW_AUTOSIZE);

    Ptr<BackgroundSubtractorMOG2> bg_model = createBackgroundSubtractorMOG2();//(100, 3, 0.3, 5);

    Mat img, fgmask, fgimg;

    for(;;)
    {
        cap >> img;

        if( img.empty() )
            break;

        //cvtColor(_img, img, COLOR_BGR2GRAY);

        if( fgimg.empty() )
            fgimg.create(img.size(), img.type());

        //更新模型
        bg_model->apply(img, fgmask, update_bg_model ? -1 : 0);

        fgimg = Scalar::all(0);
        img.copyTo(fgimg, fgmask);

        Mat bgimg;
        bg_model->getBackgroundImage(bgimg);

        imshow("image", img);
        imshow("foreground mask", fgmask);
        imshow("foreground image", fgimg);
        if(!bgimg.empty())
            imshow("mean background image", bgimg );

        char k = (char)waitKey(1);
        if( k == 27 ) break;
        if( k == ' ' )
        {
            update_bg_model = !update_bg_model;
            if(update_bg_model)
                printf("\t>背景更新(Background update)已打开\n");
            else
                printf("\t>背景更新(Background update)已关闭\n");
        }
    }

    return 0;
}

效果为

background

KNN版

#include "opencv2/opencv.hpp"

using namespace std;
using namespace cv;

int main() {
    VideoCapture cam(0);
    if (!cam.isOpened())
        return -1;

    int                          history        = 500;
    double                       dist2Threshold = 400.0;
    bool                         detectShadows  = true;
    Ptr<BackgroundSubtractorKNN> bgs =
        createBackgroundSubtractorKNN(history, dist2Threshold, detectShadows);

    while (true) {
        Mat frame;
        cam >> frame;
        if (frame.empty())
            break;

        Mat fgMask;
        bgs->apply(frame, fgMask);

        medianBlur(fgMask, fgMask, 3);

        Mat fg;
        bitwise_and(frame, frame, fg, fgMask);

        Mat bg;
        bgs->getBackgroundImage(bg);

        imshow("Video", frame);
        imshow("Background", bg);
        imshow("Foreground Mask", fgMask);
        imshow("Foreground Image", fg);

        int key = waitKey(10);
        if (key == 27) // escape key
            break;
    }

    cam.release();

    return 0;
}