CODEWITHSUNDEEP
image-processingopencvpixelmotion-detection
Horizon1710
Horizon1710

Reputation: 822

Idea needed about vehicle counting by analysing the white pixels of the binary foreground image

I am a bit new to image processing so I'd like to ask you about finding the optimal solution for my problem, not help for code. I couldn't think of a good idea yet so wanted to ask for your advices. Hope you can help.

I'm working on a project under OpenCV which is about counting the vehicles from a video file or a live camera. Other people working on such a project generally track the moving objects then count them but instead of it, I wanted to work with a different viewpoint; asking user to set a ROI(Region of interest) on the video window and work only for this region(for some reasons, like to not deal with the whole frame and some performance increase), as seen below.(btw, user can set more than one ROI and user is asked to set the height of the ROI about 2 times of a normal car by sense of proportion )

1..

I've done some basic progress so far, like backgound updating, morphological filters, threshoulding and getting the moving object as a binary image something like below.

2.

After doing them, I tried to count the white pixels of the final threshoulded foreground frame and estimate whether it was a car or not by checking the total white pixels number(I set a lower bound by a static calculation by knowing the height of ROI). To illustrate, I drew a sample graphic:

3.

As you can see from the graphic, it was easy to calculate the white pixels and checking if it draws a curve by the time and determining whether a car or something like noise.

I was quite successful until two cars passed through my ROI together at the same time. My algorithm crashed by counting them as one car as you can guess :/ I tried different approaches for this problem and similar to this like long vehicles but I couldn't get an optimum solution up to now.

My question is: is it impossible to handle this task by this approach of pixel value counting? If it is possible, what would be your suggestion? I wish you also faced something similar to this before and can help me.

All ideas are welcome, thanks in advance friends.

Upvotes: 2

Views: 2790

Answers (2)

KevinM
KevinM

Reputation: 577

In answer to your question "Is it possible to do this using pixel counting?" The short answer is "No", for the very reason your quoting: mere pixel counting of static images is not enough.

If you are limited to pixel counting, you can try looking at pixel count velocity (change of pixel counts between success frames) and you might pick out different "velocity" shapes when 1 car, 2 cars or trucks pass.

But just plain pixel counting? No. You need shape (geometric) information as well.

If you apply any kind of thresholding algorithm (e.g. for background subtraction), don't forget to update the background whenever light levels change (e.g. day and night). Also consider the grief when it is a partly cloudy with sharp cloud shadows that move across your image.

Upvotes: 2

web_bod
web_bod

Reputation: 5758

Isolate the traffic from the background - take two images, run high pass filter on one of them, convert the other to a binary image - use the binary image to mask the filtered one, you should be able to use edge detection to identify the roof of each vehicle as a quadrilateral and you should then be able to compute a relative measure of it.

You then have four scenarios:

  1. no quadrilaterals - no cars
  2. large quadrilaterals - trucks
  3. multiple small quadrilaterals - several cars
  4. single quadrilaterals - one car

Upvotes: 2

Related Questions