The problem of finding minimum bounding spheres (aka minimum enclosing spheres) is frequently encountered in a number of applications, including computer graphics and patter recognition. While a number of relatively simple algorithms exist for finding such spheres, there are no robust implementations of these algorithms in Matlab that can be readily found on-line. Functions contained in this submission are meant to fill this void.
Exact minimum bounding spheres and circles can be computed using the functions titled ExactMinBoundSphere3D.m
and ExactMinBoundCircle.m, both implementing Wezlz’s algorithm [1]. Approximate minimum bounding
spheres in any dimension can be computed using ApproxMinBoundSphereND.m function, which implements Ritter’s
algorithm [2].
For convenience, I also included functions VisualizeBoundSphere.m and VisualizeBoundCircle.m that allow you to
visualize input point clouds (or meshes) with their respective minimum bounding sphere/circle (see demo pic).
For demonstration on how to use the functions, add this repository to your Matlab path and enter MinBoundSphereDemo into
command window.
[1] Welzl, E. (1991), 'Smallest enclosing disks (balls and ellipsoids)', Lecture Notes in Computer Science, Vol. 555, pp. 359-370
[2] Ritter, J. (1990), 'An efficient bounding sphere', in Graphics Gems, A. Glassner, Ed. Academic Press, pp.301-303
MIT © 2019 Anton Semechko a.semechko@gmail.com