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2017-07-25T20:27:27+00:00
fanfuhan OpenCV 教學087 ~ opencv-087-視頻分析(基於幀差法實現移動對象分析)
資料來源: https://fanfuhan.github.io/
https://fanfuhan.github.io/2019/05/08/opencv-087/
GITHUB:https://github.com/jash-git/fanfuhan_ML_OpenCV
光流跟踪與背景消除都是基於建模方式的視頻分析方法，其實這類方法最原始的一個例子就是對視頻移動對象的幀差法跟踪，這個在視頻分析與處理中也是一種很常見的手段，有時候會取得意想不到的好效果，幀差法進一步劃分有可以分為：
◇兩幀差
◇三幀差
假設有當前幀frame，前一幀prev1，更前一幀prev2
兩幀差方法直接使用前一幀減去當前幀diff = frame – prev1
三幀差方法計算如下：
diff1 = prev2 – prev1
diff2 = frame – prev1
diff = diff1 & diff2
幀差法在求取幀差之前一般會進行高斯模糊，用以減低干擾，通過得到的diff圖像進行形態學操作，用以合併與候選區域，提升效率。
幀差法的缺點有如下：
高斯模糊是高耗時計算
容易受到噪聲與光線干擾
C++
#include
#include
using namespace std;
using namespace cv;
/*
* 视频分析(基于帧差法实现移动对象分析)
*/
int main() {
VideoCapture capture("../images/bike.avi");
if (!capture.isOpened()) {
cout << "could not open video..." << endl;
return -1;
}
// 读取第一帧
Mat preFrame, preGray;
capture.read(preFrame);
cvtColor(preFrame, preGray, COLOR_BGR2GRAY);
GaussianBlur(preGray, preGray, Size(0, 0), 15);
Mat diff;
Mat frame, gray;
// 定义结构元素
Mat k = getStructuringElement(MORPH_RECT, Size(7, 7));
while (true) {
bool ret = capture.read(frame);
if (!ret) break;
cvtColor(frame, gray, COLOR_BGR2GRAY);
GaussianBlur(gray, gray, Size(0, 0), 15);
subtract(gray, preGray, diff);
threshold(diff, diff, 0, 255, THRESH_BINARY | THRESH_OTSU);
morphologyEx(diff, diff, MORPH_OPEN, k);
imshow("input", frame);
imshow("result", diff);
gray.copyTo(preGray);
char c = waitKey(5);
if (c == 27) {
break;
}
}
waitKey(0);
return 0;
}
Python
import numpy as np
import cv2 as cv
cap = cv.VideoCapture("D:/images/video/bike.avi")
ret, prevFrame = cap.read()
prevGray = cv.cvtColor(prevFrame, cv.COLOR_BGR2GRAY)
prevGray = cv.GaussianBlur(prevGray, (0, 0), 15)
k = cv.getStructuringElement(cv.MORPH_RECT, (7, 7))
while True:
ret, frame = cap.read()
if ret is False:
break
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
gray = cv.GaussianBlur(gray, (0, 0), 15)
diff = cv.subtract(gray, prevGray)
t, binary = cv.threshold(diff, 0, 255, cv.THRESH_BINARY | cv.THRESH_OTSU)
binary = cv.morphologyEx(binary, cv.MORPH_OPEN, k)
cv.imshow('input', frame)
cv.imshow('result', binary)
cv.imwrite("D:/result.png", binary)
c = cv.waitKey(50)&0xff
prevGray = np.copy(gray)
if c == 27:
break
cap.release()
cv.destroyAllWindows()
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