Esto es lo que necesito. Alternatively, we employ a digital camera
mounted directly above the wheel to accurately and
instantaneously measure the various physical parameters.
This second approach is obviously a little
more dicult to implement incognito. Here, we are
more interested in determining how much of an edge
can be achieved under ideal conditions, rather than
the various implementation issues associated with
realising this scheme for personal gain. In all our trials
we use a regulation casino-grade roulette wheel (a
32" \President Revolution" roulette wheel manufacturer
by Matsui Gaming Machine Co. Ltd., Tokyo).
The wheel has 37 numbered slots (1 to 36 and 0)
in the conguration shown in gure 1 and has a radius
of 820 mm (spindle to rim). For the purposes of
data collection we employ a Prosilica EC650C IEEE-
1394 digital camera (1/3" CCD, 659493 pixels at
90 frames per second). Data collection software was
written and coded in C++ using the OpenCV library.
Figure 5 illustrates the results from 700 trials of
the prediction algorithm on independent rolls of a
fair and level roulette wheel. Several things are clear
from Fig. 5. First, for most the wheel, the probability
of the ball landing in a particular pocket | relative
to the predicted destination | does not di er
signicantly from chance: observed populations in
30 of 37 pockets is within the 90% condence interval
for a random process.
Mas info esta en el PDF.
Interesados escribame por email.