Newsgroups: sci.engr.advanced-tv,sci.image.processing,comp.graphics.algorithms,comp.graphics,comp.lang.postscript
Path: cantaloupe.srv.cs.cmu.edu!das-news2.harvard.edu!news2.near.net!news.mathworks.com!news.kei.com!simtel!harbinger.cc.monash.edu.au!bunyip.cc.uq.oz.au!marlin.jcu.edu.au!mccane
From: mccane@cs.jcu.edu.au (Brendan McCane)
Subject: Re: Best fit sphere to cloud of points
Message-ID: <mccane.801556244@reef.cs.jcu.edu.au>
Sender: news@marlin.jcu.edu.au (USENET News System)
Organization: James Cook University
X-Newsreader: NN version 6.5.0 #4
References: <Poynton-1705951718580001@ts2-03.inforamp.net> <D93Kpv.4LD@wti.com> <3q248c$p4f@bbs.pnl.gov> <19950525.185949.10@cromer.demon.co.uk>
Date: 27 May 95 06:30:44 GMT
Lines: 22
Xref: glinda.oz.cs.cmu.edu sci.engr.advanced-tv:2963 sci.image.processing:14895 comp.graphics.algorithms:17272 comp.graphics:77278 comp.lang.postscript:33014

>>>Given a cloud of points, I want to know if 
>>>those points are on a (fuzzy) sphere, and
>>>if so, where the center of the sphere is.
>>>
>>>I say fuzzy because some tolerance
>>>off the sphere is acceptable.
>      ^^^^^^^^^^

As a starting point you could try performing a least squares fit of a
sphere onto the data points. The sum of the squared errors could then
indicate how close the fit is to the points. I have a feeling that
unless you have a lot of data points, this method probably won't work
too well. It's worth a try though since it's quite a simple procedure.

Cheers,

Brendan.
--
----------------------------------------------------------------------------
Brendan McCane                            Email:  mccane@coral.cs.jcu.edu.au
C.S. Dept., James Cook University,        Phone:  (077) 815849.
Townsville, QLD, 4811.  Australia.        There's only one catch - Catch 22.
