Marble slabs quality classification system using texture recognition and neural networks methodology

This article describes the use of an LVQ neural network for the clustering and classification of marble slabs according to their texture. The method used for the recognition of textures is based on the Sum and Difference Histograms, a faster version of the Co-occurrence Matrices. The input of the network is a vector of statistical parameters which characterize the pattern shown to the net, and the desired output is the class to which the pattern belongs (supervised learning). The samples chosen for testing the algorithms have been marble slabs of type “Crema Marfil Sierra de la Puerta”. The neural network has been implemented using MATLAB.