如何使用BackgroundSubtractorMOG2的图像 [英] How to use BackgroundSubtractorMOG2 for images

问题描述

我是OpenCV的新手，我现在卡住了。我正在处理图像，而不是视频。因为我在项目中有相同的背景，所以如果我可以删除我的背景，我认为工作会更容易。但首先，我要问一件事。我可以将BackgroundSubtractorMOG2用于图像吗？因为它是在视频分析/运动分析标题下。

I am pretty new to OpenCV and I am stuck at the moment. I am dealing with images, not a video. Since I will have same background in my project, I thought it would be easier to work, if I could remove my background. But first, I have to ask one thing. Can I use BackgroundSubtractorMOG2 for images? Because it is under video analysis/motion analysis title.

我阅读了opencv.org上的文档并浏览了无数的例子/教程，但我仍然难以理解MOG2工作。

I read the documentation on opencv.org and looked through countless examples/tutorials but I am still having difficulty understanding how MOG2 works.

快速提问：参数中的历史记录是什么？

Quick question: What is history that in parameters?

所以，我写了一个简单的代码。我得到了一个前景蒙版。那么，下一步是什么？如何删除背景并仅留下我的对象？我不应该首先加载我的背景，然后加载实际图像，以便MOG2可以进行背景减法吗？

So, I have written a simple code. I get a foreground mask. So, what is the next step? How can I remove the background and left with my object only? Shouldn't I load my background first, then the actual image, so that MOG2 could do the background subtraction?

我正在使用OpenCV 2.4.11。

I am using OpenCV 2.4.11.

代码：

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/video/background_segm.hpp>

using namespace cv;
using namespace std;

//global variables
int history = 1;
float varThreshold = 16;
bool bShadowDetection = true;

Mat src; //source image
Mat fgMaskMOG2; //fg mask generated by MOG2 method
Ptr<BackgroundSubtractor> pMOG2; //MOG2 Background subtractor

int main(int argc, char* argv[])
{
    //create GUI windows
    namedWindow("Source");
    namedWindow("FG Mask MOG 2");

    src = imread("bluePaper1.png", 1);

    //create Background Subtractor objects
    pMOG2 = new BackgroundSubtractorMOG2(history, varThreshold, bShadowDetection); //MOG2 approach
    pMOG2->setInt("nmixtures", 3);
    pMOG2->setDouble("fTau", 0.5);

    pMOG2->operator()(src, fgMaskMOG2);

    imshow("Source", src);
    imshow("FG Mask MOG 2", fgMaskMOG2);

    waitKey(0);

    return 0;
}

源图片：

Source image:

我从MOG2得到的fgMask：

fgMask that I get from MOG2:

推荐答案

高斯混合方法根据固定相机中的帧历史来学习背景，因此您不能仅将其用于一个图像。历史参数显示有多少帧会对背景构造产生影响。

Mixture of Gaussian method learns background according to history of frames in a fixed camera and so you can not use it for only one image. The history parameter shows how many frames would have effect on construction of the background.

阴影检测不是一个依赖于BGS方法的过程，应该同时实现。例如，我们在MOG2文档中有
：

Shadow detection is not a process which depends on BGS method and should be implemented alongside. for example in MOG2 documentation we have:

如果像素是背景的较暗版本，则会检测到阴影。 Tau是定义阴影可以暗多少的阈值。 Tau = 0.5意味着如果一个像素深两倍以上则不是阴影

The shadow is detected if the pixel is a darker version of the background. Tau is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel is more than twice darker then it is not shadow

如果是你的例子，前景很容易通过简单的帧差异获得，您可以通过上述解决方案轻松删除阴影。

In case of your example the foreground could easily be obtained by a simple frame difference and you can easily remove shadows by the mentioned solution.

您可以通过以下步骤获得前景：

you can have the foreground by the following steps:

1. 减去来自已知背景的图像和阈值结果以获取前景蒙版


2. 对前景蒙版和给定图像应用AND操作以使对象具有可能的阴影。


3. 移除比其对应的更暗的像素（应调整的数量）背景中的像素。


4. 进行一些后处理，如形态学和连通分量标记，以获得更好的结果。

1. Subtract given image from known background and threshold the result to obtain the foreground mask
2. Apply AND operation on foreground mask and the given image to get your object with possible shadows.
3. Remove pixels which is darker (amount of it should be adjust) than their corresponding pixel in background.
4. Do some post processing like morphological and connected-component-labeling to have a better result.

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