Clustering Techniques for Marbles Classification
  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). 
J.R. Caldas-Pinto, Pedro Pina, Vitorino Ramos, Mario Ramalho