Thought I’d ask for some image analysis advice:
I want to detect the cross points in images of a grid (marked a couple of these in red, just as an example):
(a clean and full resolution of this image is available here)
I need to detect the points where the green ropes intersect. I then use those locations to spatially calibrate the image: each such cross point is on a 5 cm x 5 cm grid in real life (it just looks warped because of the camera lens and other effects).
There are a number of ways to accomplish this:
- FFT: the barrel-distortion obscures the regular grid pattern and the frequencies are not so clean to do that.
- Morphological operations: the images of this grid will have a large variation of backgrounds, so any simple operation (dilate, top hat, etc) might not work in the long run (though, they can be beneficial to pre-process the image).
- Template matching: not sure how to do that.
- Tensor flow: no idea how to do that.
- Hough transform: AFAIK, doesn’t exist in Julia.
I would really appreciate any advice/input you might have.
Thanks in advance!