opencv 背景消除

Opencv–背景消除建模（BSM）

---

在opencv中有两种方法可以进行背景消除：

• 其一、基于机器学习(Knn–K个最近邻)背景消除建模
• 其二、于图像分割(GMM，抗干扰图像分割)背景消除建模
  BS ,Background Subtraction

c版

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

using namespace std;
using namespace cv;

int main(int argc, char** argv) {
    VideoCapture capture;
    capture.open("D:/software/opencv1/picture/vtest.avi");
    if (!capture.isOpened()) {
        printf("could not load the video!");
        return -1;
    }
    Mat frame;
    Mat bsmaskMOG2,bsmaskKNN;
    namedWindow("input video", CV_WINDOW_AUTOSIZE);
    namedWindow("MOG2 Model",CV_WINDOW_AUTOSIZE);
    namedWindow("kKNNoutput Model", CV_WINDOW_AUTOSIZE);
    Mat kernel = getStructuringElement(MORPH_RECT,Size(3,3),Point(-1,-1));
    //初始化BS
    Ptr<BackgroundSubtractor> pMOG2 = createBackgroundSubtractorMOG2();
    Ptr<BackgroundSubtractor> pKNN = createBackgroundSubtractorKNN();

    
    while (capture.read(frame))
    {
        imshow("input video", frame);
        // MOG BS
        pMOG2->apply(frame, bsmaskMOG2);
        //形态学操作--开操作，去除小的噪声morphologyEx()
        morphologyEx(bsmaskMOG2, bsmaskMOG2, MORPH_OPEN, kernel, Point(-1, -1));
        imshow("MOG2 Model", bsmaskMOG2);
        // KNN BS mask
        pKNN->apply(frame, bsmaskKNN);
        imshow("KNNoutput Model", bsmaskKNN);
        char c = waitKey(100);
        if (c == 27) {
            break;
        }

    }

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

}

python

python代码1

#!/usr/bin/python3.6
# -*- coding: utf-8 -*-
# @Time : 2020/11/17 19:06
# @Author : ptg
# @Email : zhxwhchina@163.com
# @File : 去背景.py
# @Software: PyCharm

import cv2 as cv
import numpy as np
from cv2 import cv2

image = cv2.imread("mabaoguo2.jpg",cv2.IMREAD_GRAYSCALE)
binary = cv2.adaptiveThreshold(image,255,
        cv2.ADAPTIVE_THRESH_GAUSSIAN_C,cv2.THRESH_BINARY_INV,25,15)
se = cv2.getStructuringElement(cv2.MORPH_RECT,(1,1))
se = cv2.morphologyEx(se, cv2.MORPH_CLOSE, (2,2))
mask = cv2.dilate(binary,se)
cv2.imshow("image",image)

mask1 = cv2.bitwise_not(mask)
binary =cv2.bitwise_and(image,mask)
result = cv2.add(binary,mask1)
cv2.imshow("reslut",result)
cv2.imwrite("reslut00.jpg",result)
cv2.waitKey(0)
cv2.destroyAllWindows()

import cv2
import numpy as np
 
 
#读入图像
video = cv2.VideoCapture("E:\\video.avi")
videoIsOpen=video.isOpened
print(videoIsOpen)
width=int(video.get(cv2.CAP_PROP_FRAME_WIDTH))#宽度
height=int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))#高度
fps=video.get(cv2.CAP_PROP_FPS)#获取帧率
print(fps,width,height)
#创建窗口
cv2.namedWindow('MOG2')
cv2.namedWindow('MOG22')
cv2.namedWindow('input video')
#cv2.namedWindow('KNN')
bsmaskMOG2 = np.zeros([height,width],np.uint8)
bsmaskKnn = np.zeros([height,width],np.uint8)
#两种消除的方案
pMOG2 = cv2.createBackgroundSubtractorMOG2(detectShadows=True)
PKNN = cv2.createBackgroundSubtractorKNN(detectShadows=True)
#形态学处理
kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(3, 3))
 
while videoIsOpen:
    (flag,frame)=video.read()
    if not flag:
        break
    cv2.imshow('input video',frame)
    # bsmaskKnn= PKNN.apply(frame)
    # cv2.imshow('KNN',bsmaskKnn)
    bsmaskMOG2 = pMOG2.apply(frame)
    cv2.imshow('MOG22',bsmaskMOG2)
    OPEND=cv2.morphologyEx(bsmaskMOG2,cv2.MORPH_OPEN,kernel)
    cv2.imshow('MOG2',OPEND)
    
    c = cv2.waitKey(40)
    if c==27:
        break
video.release()
 
cv2.waitKey(0)