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In this paper we introduce a mathematical method to extract similarities between paintings and music tracks. Our approach is based on the digitalization of both paintings and music tracks by means of finite expansions in terms of orthogonal basis functions (with both Fourier and wavelet bases). The best fit between a specific painting and a sample of music tracks from a given composer is achieved via an L2 projection upon a finite dimensional subspace. Several examples are provided for the analysis of a collection of works of art by the Italian artist Marcello Morandini. Finally we have developed an original applet that implements the process above and which can be freely downloaded from the site https://github.com/pgerva/playing-paintings.git.