In this paper, we present an alternative procedure for the digital reconstruction of spectral reflectanc curves of oil painting on canvas using multispectral imaging. The technique is based on a combination of the results obtained by pseudo-inverse, principal component analysis and interpolation; these results are the input to a feed-forward back propagation neural network fittin the values of the curves to a target obtained using a spectrophotometer Shimadzu UV2401. Goodness-of-Fit Coefficien (GFC), absolute mean error (ABE) and spectral Root Mean Squared error (RMS) are the metrics used to evaluate the performance of the procedure proposed.