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pythonopencvmotionthreshold

opencv/python : motion detect weird thresholding

I am trying to make a motion detect program using my webcam, but I'm getting this weird results when thresholding the difference of frames:

When Im moving: (seems okay I guess) ![enter image description here][1]

When Im not moving: ![enter image description here][2]

What can this be? I already ran a couple of programs that got exactly the same algorithm and the thresholding is doing fine..

Heres my code:

import cv2
import random
import numpy as np

# Create windows to show the captured images
cv2.namedWindow("window_a", cv2.CV_WINDOW_AUTOSIZE) 
cv2.namedWindow("window_b", cv2.CV_WINDOW_AUTOSIZE)

# Structuring element
es = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (9,4))
## Webcam Settings
capture = cv2.VideoCapture(0)

#dimensions
frameWidth = capture.get(cv2.cv.CV_CAP_PROP_FRAME_WIDTH)
frameHeight = capture.get(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT)

while True:
    # Capture a frame
    flag,frame = capture.read()
    
    current = cv2.blur(frame, (5,5))
    difference = cv2.absdiff(current, previous) #difference is taken of the current frame and the previous frame

    frame2 = cv2.cvtColor(difference, cv2.cv.CV_RGB2GRAY)
    retval,thresh = cv2.threshold(frame2, 10, 0xff, cv2.THRESH_OTSU)
    dilated1 = cv2.dilate(thresh, es)
    dilated2 = cv2.dilate(dilated1, es)
    dilated3 = cv2.dilate(dilated2, es)
    dilated4 = cv2.dilate(dilated3, es)

    cv2.imshow('window_a', dilated4)
    cv2.imshow('window_b', frame)

    previous = current
    
    key = cv2.waitKey(10) #20
    if key == 27: #exit on ESC
        cv2.destroyAllWindows()
        break

Thanks in advance! [1]: https://i.sstatic.net/hslOs.png [2]: https://i.sstatic.net/7fB95.png

Solution

  • The first thing that you need is a previous = cv2.blur(frame, (5,5)) to prime your previous sample after a frame grab before your while loop.

    This will make the code you posted work, but will not solve your problem.

    I think the issue that you are having is due to the type of thresholding algorithm that you are using. Try a binary, cv2.THRESH_BINARY, instead of Otsu's. It seemed to solve the problem for me.