Abstract: System and related methods for applying machine learning to the classification of surface materials using images of spots of lights, such as resulting from a laser beam impinging the surface. A classifier trained using such spot images, resulting from light beams imping the surface, achieves excellent classification results, in spite of a lack of fine surface details in these images as compared to a more uniformly lit larger scene that would appear to contain more information on the surface type. Classifiers can achieve classification accuracies on biological tissues significantly above 90% using a number of well-known classifier architectures. The classification results can be used to generate a map of classified surface types and the combination of such with a three-dimensional model of a surface having classified surface portions reconstructed from a pattern of spots projected onto the surface.