In this paper, we describe the applicability of the K-means clustering
algorithm for locating thresholds in a given histogram. In order to f
ind optimal thresholds a probabilistic method called Multi-state Stoch
astic Connectionist Approach (MSCA) is employed. Mean Field Annealing
(MFA), a deterministic counterpart of MSCA, is also studied in this co
ntext. A parallel model to parallelize the above methods is presented.
Results of MFA and MSCA are compared with that of the K-means algorit
hm.