CODEWITHSUNDEEP
c++opencvcomputer-vision
DouglasAdams
DouglasAdams

Reputation: 490

Remove noise from the computed optical flow

I compute the optical flow on grayscale videos which contains true-white and noisy-black patch besides the useful information. I want to remove those patches because the correspondant optical flow is foolish. Those patches are on the edges of the image and their sizes vary from a video to another. My goal is to extract a bounding box describing the useful information in my video thanks to the optical flow.

How can I compute this bounding box ? Or at least, how can I remove the computed optical flow in those regions ?

Edit : I saw your answers. I'll try that next week end then come back to discuss about that. Tank you !

Upvotes: 1

Views: 916

Answers (3)

Bharat
Bharat

Reputation: 2179

If I understand correctly, you are getting noisy optical flow in patches which are grey/white or basically uniform. A simple approach would be to divide the image into small patches and compute the entropy over each patch. Now, patches which have a very low entropy can be discarded by choosing an appropriate threshold because they do not contain much information.

Upvotes: 0

rockinfresh
rockinfresh

Reputation: 2106

It's a little tough to understand what the problem is, if the noises is true-white and noisy-black patches in a grayscale image as you have said, then I suggest you look at eroding and dilating. More information can be found here: Eroding and Dilating

Should this not be what you are asking, do post some sample images with the patches and comment so that I can have a clearer idea on what the problem is. Cheers.

Upvotes: 1

nkint
nkint

Reputation: 11733

Remove noise from optical flow could be a complicated task. A simple and dummy way could be to use a threshold on the optical flow vector intensity.

But if you only need to find bounding boxes why just do not use a simple background/motion object segmentation? Like MOG, GMG, opencv has nice implementations of them and they works well and are quite fast. See this tutorial.

Upvotes: 1

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