How to find opposing triangle pairs in triangulated objects?

1 visualización (últimos 30 días)
Andre Lutz
Andre Lutz el 9 de Jun. de 2021
Comentada: Andre Lutz el 27 de Jul. de 2021
Hi,
I want to find opposing triangle pairs in triangulated objects like shown in the example picture. The example data is attached with variables F and V for faces and vertices.
The interesting areas are marked in the pictures.
The requirements for a match of my choice would be:
  1. distance of triangles lower than threshold, e.g. 3mm
  2. triangles should be close to parallel. This could be set by a threshold of the "degree of parallelism". However a good measurement could be defined.
  3. "correct" spatial orientation would be great, but is a bonus.
How I started:
  • calculate center of gravity of all triagles
  • calculate each of the distances (pdist2)
  • remove triangle pairs with too high distances
  • calculate normal vectors of remaining triangles
  • check "parallelism" of triangles by dot product of normal vectors (dot product >0.9)
  • remove adjacent triangle pairs that are "parallel" according to above definition
This is not very robust and leads to following issue:
  • second neighbors are still found (neighbors of the adjacent triangles)
Is there a smart way to remove 2nd or 3rd neighbors or neighbors in general (neighborhood matrix/tree?!?)
Is there in general a smarter and more robust way to do that? It seems I ran into a direction where I have to exclude a lot of undesired cases....
Any help is welcome :-)
  2 comentarios
darova
darova el 24 de Jul. de 2021
Is the area of interest always vertical?
Andre Lutz
Andre Lutz el 26 de Jul. de 2021
mostly yes, but not in general :-/

Iniciar sesión para comentar.

Respuestas (1)

darova
darova el 26 de Jul. de 2021
Here is an idea or finding neigbour points;
% some data
x0 = rand(40,1);
y0 = rand(40,1);
s1 = max(max(x0)-min(x0),max(y0)-min(y0)); % scale factor (max value)
% scale the data
x1 = round((x0-min(x0))/s1*39)+5;
y1 = round((y0-min(y0))/s1*39)+5;
A = zeros(50);
ind = sub2ind(size(A),y1,x1); % indices
A(ind) = 1:40; % write into matrix numbers of points
A1 = A*0;
A1(y1(5)-4:y1(5)+4,x1(5)-4:x1(5)+4) = 1; % region around 5th point
A1 = A.*A1; % select points in region
imshow([A A(:,1)+1 A1])
  • Is there a smart way to remove 2nd or 3rd neighbors or neighbors in general (neighborhood matrix/tree?!?)
I don't understand. Why can't you just select max value of dot product?
  1 comentario
Andre Lutz
Andre Lutz el 27 de Jul. de 2021
2 neighboring triangles might be fully parallel. Therefore the dot product of there normal vectors might be 1 (or -1).
If I just check the dot product of the normal vectors, I'll also find the neighboring triangles. Therefore I want to find a way to exclude them. The direct neighbors are easy to exclude as the share nodes with my triangle. The second and third neigbors are not so easy to find.

Iniciar sesión para comentar.

Categorías

Más información sobre Delaunay Triangulation en Help Center y File Exchange.

Productos


Versión

R2019b

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by