OpenCV edge enhancement

Question

I am performing background subtraction to obtain a moving car from a video as below ( Running average background modeling)

I am applying findContours() after this to draw a polygon around the car.

As you can see, the quality of the obtained output is not great. Is there any way I can enhance the edges of the car to make it more prominent and cut out the extraneous noise surrounding it. I tried performing morphological closing(dilate -> erode) to fill the gaps, but the output was not as expected.

enter image description here

did you try using morphological operations the other way around -- instead of using closing to enhance the car silhouette, maybe you could try using opening to get rid of the surrounding noise? if you are then left just with an (imperfect) car on the picture, it might be easier to work with if it is left as the *only* object on the picture — penelope, Dec 27 '11 at 09:48
Can you post a sample learned background, and then a sample frame with the car contained in it? — mevatron, Dec 28 '11 at 00:18

score 0 · Answer 1 · answered Jun 04 '12 at 07:41

0

This might be overkill and far from a quick solution but Level Set Methods would be very suited to extract the presegmented car.

answered Jun 04 '12 at 07:41

Herr von Wurst

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score 0 · Answer 2 · answered May 09 '20 at 15:57

You can try to apply background subtraction by using cv2.createBackgroundSubtractorMOG2().

Code:

import cv2
import numpy as np

cap = cv2.VideoCapture(0)
out = cv2.createBackgroundSubtractorMOG2()

fourcc = cv2.VideoWriter_fourcc(*'MJPG')
output = cv2.VideoWriter('output.avi', fourcc, 20.0, (640,480), isColor=False)

while(cap.isOpened()):
    ret, frame = cap.read()

    if ret==True:
        frame = cv2.flip(frame,180)

        outmask = out.apply(frame)
        output.write(outmask)

        cv2.imshow('original', frame)
        cv2.imshow('Motion Tracker', outmask)

        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

    else:
        break


output.release()
cap.release()
cv2.destroyAllWindows()

OpenCV edge enhancement

2 Answers2