Detect masonry from an image

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Axel Reyskens
Axel Reyskens on 22 Nov 2020
Edited: Axel Reyskens on 22 Nov 2020
Hi
I'm trying to create a file which detects masonry from walls (eg. facade of a building). So basically this code should detect masonry from an image and isolate it into a 2D model. What's the best way to do this?
Thanks in advance.
-Ax

Answers (1)

Image Analyst
Image Analyst on 22 Nov 2020
Depends on how varied your images are.
  1. If it's any possible kind of building (wood, glass, steel, masonry, etc.) and any possible kind of masonry (brick, blocks, marble, limestone, stucco, cement, tile, different colors, etc.) then I think it could be difficult. You'd probably have to use SegNet to train a deep learning model with thousands of images.
  2. If you have a more limited set of images, like houses made of only red brick, you could possibly get by with traditional methods like a texture filter like stdfilt() or entropyfilt().
  2 Comments
Axel Reyskens
Axel Reyskens on 22 Nov 2020
I think option one applies. It could be any building and any type of masonry. So I'm trying to 'detect' masonry from an image of a facade of a building. So the masonry could be any type and even colours can differ (eg. red masonry vs dark masonry).
Axel Reyskens
Axel Reyskens on 22 Nov 2020
Edited: Axel Reyskens on 22 Nov 2020
Is using image segmentation an option?
Also: if I want to make a 2D model out of it later on, how can I identify length?

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