How to detect a pattern of dark/bright bands in an image?

I'm trying to detect a pattern like this in some images

Pattern (ideal)

The actual image looks something like this

It could be scaled and/or rotated . Is there a way to do that efficiently without resorting to neural nets or some learning algorithm? Can some detection be done based on the value gradient for example (dark-bright-dark-bright-dark)?

Answer 1

[Image Analyst]

Can you just threshold and locate centroids? What are you really interested in? The centroids, the widths of the bars (as if they were bars), or both?

[Mohamed]

I extracted this from a larger image. So I can't just threshold because there are other parts in the image that may saturate as much. I'm interested in the centroids only.

[Image Analyst]

You aren't giving us much to work with. Somehow you narrowed down your image to that rectangle. How did you do that? Well somehow you did it, so why can't we just proceed from that point onwards?

[Mohamed]

I have manually cropped it from the image below.

[Image Analyst]

If you can locate the dark ring, and if you know the bright dots are always within that, then you can just locate the 4 brightest white spots of a certain size, and then get rid of the pair closest to each other or the center of the dark ring. Hard to tell the most robust algorithm after looking at just one image, but that's what I'd do given what I see so far.

[Mohamed]

That's actually a good idea. Thanks!

[Mert Su]

Not an image analyst. How do you detect centroids?

[Image Analyst]

@Mert Su to detect centroids first segment the image to get a binary image mask, then use the regionprops function.

props = regionprops(mask, 'Centroid');
xy = vertcat(props.Centroid)

For a full demo see my Image Processing Tutorial in my File Exchange:

Image Analyst's File Exchange