Is there any methods (like circularity) to decide if the 3D construction close to sphere?
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Hi,
I have got many 3D particles from 2D images and want to get a value to decide if this 3D particles close to perfect sphere. For a 2D shape, I know there is a way to calculate circularity, but is there a similar way for 3D constructions?
Thanks!
4 Comments
Jan
on 3 Feb 2021
Please explain in which format you "have many 3D particles".
You can fit a sphere in a least square sense and measure the maximum or mean deviation of the radius of the partical coordinates. But than 2 circles could be accepted as "perfect sphere", if they are located exactly on the surface. Would this match your needs or do you need a kind of equi-distribution on the surface?
Dongyu Liang
on 3 Feb 2021
Jan
on 4 Feb 2021
Again: How are your input data are represented? As an image, as coordinates of points or edges, as STL-File, as polytops, as point cloud?
So what exactly is "an object" in your case. How can a "hollow sphere" be distinguished from a "not hollow sphere"? Do you expect an equi-distribution of points on the surface, or inside a volume? Is it defined if the obejct is convex at all?
Dongyu Liang
on 4 Feb 2021
Answers (1)
Shubham Rawat
on 3 Feb 2021
0 votes
Hi,
When finding sphericity for a single particle or object, you can define sphericity as the ratio of surface area of a sphere that has the same volume as the particle or object to the surface area of the particle itself.
Put into mathematical terms, the sphericity given by Ψ ("psi") is:
for the volume of the particle or object
and surface area of the particle or object
. You can see why this is the case through a few mathematical steps to derive this formula.
Hope this Helps!
1 Comment
Dongyu Liang
on 3 Feb 2021
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