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I am doing a 3D Scan and export the result as a wavefront object (.obj with the mesh, and .mtl and .jpeg for the texture). the link between the faces of the mesh and the texture are in the .obj.

I am trying to detect "circles" for example on the 3D scans which are on the texture. example there is no "3D variation on the mesh specific to the feature that I want to detect. the variation is due to the object on which is set the texture. so I have to detect "only based on the texture".

My problem is that I don't know how to start. the .jpeg is "puzzled". I can do thresholding and " basic pre-processing" on the .jpeg but I don't know how to do the feature detection which need "geodesic distance information" in addition to the texture. at least I don't know an efficient way. I could even detect some of the features directly on the jpeg. some of them are not split on different portion of the jpeg. don't know if it can help...

My first thought was to loop on every vertex (which already doesn't sound very optimized), try to reconstruct a local (approximately the size of the feature I want to detect) not puzzled "jpeg" and do the feature detection on this not puzzled jpeg.

I tried by "attributing" the average "color value" on each vertex but I lose too much of the texture information.

My question, is there any python libraries existing to manipulate this format ? Is there any python libraries to do feature detection on texture on mesh with this kind of texture "puzzled" ?

if not what would be the best way to process ? I guess the loop on all vertex and local jpeg reconstruction is not ideal...

p.deman
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  • If you want to do this in Python, you probably want to look at Python bindings for [CGAL](https://www.cgal.org/). You might be able to do what you want with a dense delaunay retriangulation of the surface, sampling the texture at the new (denser) vertices, though you'd have to invent a way to do the image recognition on a triangle web instead of the usual regular bitmap grid – theodox May 25 '18 at 07:30
  • thanks i am taking a look at the cgal library. for now I find only feature detection based on the mesh geometry and not on the mesh texture but i am still reading the documentation – p.deman May 25 '18 at 08:43
  • You'll probably need it or something like it even to resample the mesh - there's not a lot of pure-Python alternatives – theodox May 25 '18 at 17:51

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