  An algorithm for identifying rings in Ring Imaging Cherenkov (RICH) detectors
is described. The algorithm is necessarily Bayesian and makes use of a
Metropolis-Hastings Markov chain Monte Carlo sampler to locate the rings. In
particular, the sampler employs a novel proposal function whose form is
responsible for significant speed improvements over similar methods. The method
is optimised for finding multiple overlapping rings in detectors which can be
modelled well by the LHbC RICH toy model described herein.
