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This type of problem is known as blob detection. There are some good
free machine vision libraries for doing this including opencv.
There's quite a lot of samples included with these libraries. I
played with some edge detection stuff in python a while ago and got
it working with a web cam without too much hassle. Also Beth has
some some recent experience with machine vision stuff in C so she
might be able to give you some code to get you started.<br>
<br>
P.S. hope those lasers are Class I so we don't blind anybody<br>
<br>
On 30/05/13 10:40, Andy S wrote:<br>
<span style="white-space: pre;">><br>
><br>
> On 29 May 2013 17:42, Mick Fuzz
<<a class="moz-txt-link-abbreviated" href="mailto:mickfuzz@clearerchannel.org">mickfuzz@clearerchannel.org</a>
<a class="moz-txt-link-rfc2396E" href="mailto:mickfuzz@clearerchannel.org"><mailto:mickfuzz@clearerchannel.org></a>> wrote:<br>
><br>
> On 29/05/13 17:25, Gareth Coleman wrote:<br>
> ><br>
> > You could call out for a vote at specific times, and it
would take<br>
> > just a few seconds for everyone to get their spot on
target and then<br>
> > the results would be visible. Each vote is equal, unlike
our voices<br>
> > which have a certain 'power' despite all our efforts to
consciously<br>
> > equalize them.<br>
> I love this idea! Let's do it.<br>
><br>
><br>
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><br>
><br>
> B<br>
> e interesting to see how you count the laser spots especially
when they are spread evenly across the selection as they will all
be moving quite a lot, unless people have very steady hands.
Obviously the more people involved, the harder this gets, unless
you have an automated process to count them (well lets face it, a
photo would do!)<br>
><br>
> A<br>
><br>
><br>
> -- <br>
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