  Automatic marbles classification based on their visual appearance is an
important industrial issue. However, there is no definitive solution to the
problem mainly due to the presence of randomly distributed high number of
different colours and its subjective evaluation by the human expert. In this
paper we present a study of segmentation techniques, we evaluate they overall
performance using a training set and standard quality measures and finally we
apply different clustering techniques to automatically classify the marbles.
KEYWORDS: Segmentation, Clustering, Quadtrees, Learning Vector Quantization
(LVQ), Simulated Annealing (SA).
