I would like to know how to make straight textures using 2D noise, to make stone squares of irregular sizes all jointed together (same as pic1): If there is a mathematical way to quantize 2D noise into orthogonal straight noise or jointed stone squares, please tell me the trick! (for a graphics shader brick wall texture generator)
if it is a mathematical impossibility, please tell me why?
You could try using 2D noise, but sampling adjacent points as though it was 1D noise, getting a series of strips of values. Then break those values into discrete groups, and whenever you run into a difference in group number, there's your break between bricks. And you would always have breaks between each horizontal strips.
To make a procedural 2d/3d similar to square stones, it would be easier to use a voronoi base, because it is already the concept of cells... if each cell has square borders it will make 2d/3d square cells.
voronoi compares the proximity of pixels to central points around it, it makes lines tangent to the points, as cell borders. i am not sure how to make them 90 degrees, but there must be a way.
Related
I have a situation where I have a set of pixels that make up the border of a quadrilateral (very close to square). I'm trying to determine the location of the corners as best as possible and have been struggling for a while now. My first thought was to determine the straight lines of the border and then calculate the corner points, but I don't have access to OpenCV or other image processing libraries, unfortunately.
Below are three cases where the black outline is the image boundary and the red outline is the quadrilateral boundary. I have a list of all of the pixels that make up the red boundary and the red boundary thickness may vary.
My initial thought was that I could just find the pixel that is closest to each of the four image boundaries, however this won't quite work for the first case where the inner quadrilateral isn't tilted.
Any thoughts on how to tackle this problem would be great. I'm coding in dart, but am looking for a psuedocode answer that I can implement myself.
(I have seen this post, which is similar to my problem, but I think there should be a simpler solution for my problem since I have access to all of the boundary points of the quadrilateral)
Having a list of all rectangle boundary pixels, you can use simple methods like this:
Calculate gravity center of rectangle (just sum X- and Y- coordinates of pixels and divide by their number) - it is diagonal intersection.
Find the farthest pixels - they are corners.
In case of bad quality of data set (empty places, excessive pixels) center calculation might be inexact. So you can apply Hough transform to extract sides (as lines) and calculate their intersections.
Triangles, squares and hexagons can all be used to fill a surface (tessellation).
For now let's assume the surface has a limited number of tiles (triangles, squares or hexagons)
The goal is to define a line that touches each tile so that points that are close to each other or the line (1D) are also close to each other on the surface (2D).
The solution for a square based tesselation you have the (Pseudo)-Hillbert curve. Below is an example of a second order pseado-hillbert curve.
Explained in this fantastic video
I was wondering what the equivalent (if any) of the pseudo-hillbert curve for tesselations based on triangles or hexagons are. I am looking for a full tesselation so no holes as in a Sierpinsky Triangle.
I found this great resource
And for triangles using a Peano curve.
I've done a lot of reading on the two subjects, and I still cannot quite figure it out. From what I understand Perlin Noise (in 2D) generates a square grid, and you get the value of a point from that grid by calculating the contribution of each corner of the square you are in.
Simplex noise would be, from what I understand, also a square grid (in 2D). Instead of getting the value by calculating the contribution of the surrounding four corners, you split the square into two parts, and get the contribution from the three corners of the triangle you are currently in.
Do I understand this correctly? If so, isn't this just another way to calculate the contribution of the corners, and not another way of generating noise?
Half right.
Simplex noise is also summing contributions from corners, but in 2D the actual shape being used is the equilateral triangle. (That bit about half squares in Gustavson's 2005 paper was in skewed space... just a way for the computer to figure out which triangle a point is in.)
Because the corners are now in different places and blended differently, the resulting noisy image will have different visual properties, and is thus considered a different type of noise.
In particular, one will find triangular 60 degree artifacts in simplex noise that the eye is not trained to notice (as demonstrated in formal gardening) instead of the right angles in classic Perlin noise. The circular kernel also adds lumpiness to the image.
I am interested in using shapes like these:
Usually a tangram is made of 7 shapes(5 triangles, 1 square and 1 parallelogram).
What I want to do is fill a shape only with tangram shapes, so at this point,
the size and repetition of shapes shouldn't matter.
Here's something I manually tried:
I am a bit lost on how to approach this.
Assuming I have a path (an ordered list/array of points of the outline),
I imagine I should try to do some sort of triangulation.
Is there such a thing as Deulanay triangulation with triangles constrained to 45 degrees
right angled triangles ?
A more 'brute' approach would be to add a bunch of triangles(45 degrees) and use SAT
for collision detection to 'fix' overlaps, and hopefully gaps will be avoided.
Since the square and parallelogram can be made of triangles(45 degrees) too, I imagine there
would be a nice clean geometric solution, right ?
How do I pack triangles(45 degrees) inside an arbitrary shape ?
Any ideas are welcome.
A few random thoughts (maybe they help you find a better solution) if you're using only the original sizes of the shapes:
as you point out, all shapes in the tangram can be made composed of e.g. the yellow or pink triangle (d-g-c), so try also thinking of a bottom-up approach such as first trying to place as many yellow triangles into your shape and then combine them into larger shapes if possible. In the worst case, you'll end up with a set of these smallest triangles.
any kind triangulation of non-polygons (such as the half-moon in your example) probably does not work very well...
It looks like you require that the shapes can only have a few discrete orientations. To find the best fit of these triangles into the given shape, I'd propose the following approximate solution: draw a grid of triangles (i.e. a square grid with diagonal lines) across the shape and take those triangles which are fully contained. This most likely will not give you the optimal coverage but then you could repeatedly shift the grid by a tenth of the grid size in horizontal and vertical direction and see whether you'll find something which covers a larger fraction of the original shape (or you could go in steps of 1/2 then 1/4 etc. of the original grid size in the spirit of a binary search).
If you allow any arbitrary scaling of the shapes you could approximate any (reasonably smooth ?) shape to arbitrary precision by adding smaller and smaller shapes. E.g. if you have a raster image, you can e.g. choose the size of the yellow triangle such that two of them make a pixel on the image and then you can represent any such raster image.
Starting with a 3D mesh, how would you give a rounded appearance to the edges and corners between the polygons of that mesh?
Without wishing to discourage other approaches, here's how I'm currently approaching the problem:
Given the mesh for a regular polyhedron, I can give the mesh's edges a rounded appearance by scaling each polygon along its plane and connecting the edges using cylinder segments such that each cylinder is tangent to each polygon where it meets that polygon.
Here's an example involving a cube:
Here's the cube after scaling its polygons:
Here's the cube after connecting the polygons' edges using cylinders:
What I'm having trouble with is figuring out how to deal with the corners between polygons, especially in cases where more than three edges meet at each corner. I'd also like an algorithm that works for all closed polyhedra instead of just those that are regular.
I post this as an answer because I can't put images into comments.
Sattle point
Here's an image of two brothers camping:
They placed their simple tents right beside each other in the middle of a steep walley (that's one bad place for tents, but thats not the point), so one end of each tent points upwards. At the point where the four squares meet you have a sattle point. The two edges on top of each tent can be rounded normally as well as the two downward edges. But at the sattle point you have different curvature in both directions and therefore its not possible to use a sphere. This rules out Svante's solution.
Selfintersection
The following image shows some 3D polygons if viewed from the side. Its some sharp thing with a hole drilled into it from the other side. The left image shows it before, the right after rounding.
.
The mass thats get removed from the sharp edge containts the end of the drill hole.
There is someething else to see here. The drill holes sides might be very large polygons (lets say it's not a hole but a slit). Still you only get small radii at the top. you can't just scale your polygons, you have to take into account the neighboring polygon.
Convexity
You say you're only removing mass, this is only true if your geometry is convex. Look at the image you posted. But now assume that the viewer is inside the volume. The radii turn away from you and therefore add mass.
NURBS
I'm not a nurbs specialist my self. But the constraints would look something like this:
The corners of the nurbs patch must be at the same position as the corners of the scaled-down polygons. The normal vectors of the nurb surface at the corners must be equal to the normal of the polygon. This should be sufficent to gurarantee that the nurb edge will be a straight line following the polygon edge. The normals also ensure that no visible edges will result at the border between polygon and nurbs patch.
I'd just do the math myself. nurbs are just polygons. You'll have some unknown coefficients and your constraints. This gives you a system of equations (often linear) that you can solve.
Is there any upper bound on the number of faces, that meet at that corner?
You might you might employ concepts from CAGD, especially Non-Uniform Rational B-Splines (NURBS) might be of interest for you.
Your current approach - glueing some fixed geometrical primitives might be too inflexible to solve the problem. NURBS require some mathematical work to get used to, but might be more suitable for your needs.
Extrapolating your cylinder-edge approach, the corners should be spheres, resp. sphere segments, that have the same radius as the cylinders meeting there and the centre at the intersection of the cylinders' axes.
Here we have a single C++ header for generating triangulated rounded 3D boxes. The code is in C++ but also easy to transplant to other coding languages. Also it's easy to be modified for other primitives like quads.
https://github.com/nepluno/RoundCornerBox
As #Raymond suggests, I also think that the nepluno repo provides a very good implementation to solve this issue; efficient and simple.
To complete his answer, I just wrote a solution to this issue in JS, based on the BabylonJS 3D engine. This solution can be found here, and can be quite easily replaced by another 3D engine:
https://playground.babylonjs.com/#AY7B23