A computer vision system for identification of granite-forming minerals based on RGB data and artificial neural networks

Abstract

[Abstract]: Granitic stones are widely used in the field of Cultural Heritage in the north-western Iberian Peninsula. In some activities regarding conservation, such as the laser cleaning, it is of great interest the identification of the minerals on the granitic stone surface in order to improve the treatment and to avoid damages by means of the adaption of the fluence to each different forming mineral. The aim of this work is the optimization of a back propagation artificial neural network (ANN) in order to obtain the rapid and reliable identification of forming minerals in granitic rocks by means of RGB images. Our goal is, eventually, in situ monitoring the laser cleaning of granitic stonework. The results obtained, though preliminary, led a high degree of correct identification of the forming minerals for three different granitic types.