Glass Patterns and Artistic Imaging

Abstract. The theory of Glass patterns naturally combines three essen-tial aspects of painterly artworks: perception, randomness, and geometric structure. Therefore, it seems a suitable framework for the development of mathematical models of the visual properties that distinguish paint-ings from photographic images. With this contribution, we introduce a simple mathematical operator which transfers the microstructure of a Glass pattern to an input image, and we show that its output is per-ceptually similar to a painting. An efficient implementation is presented. Unlike most of the existing techniques for unsupervised painterly render-ing, the proposed approach does not introduce ’magic numbers ’ and has a nice and compact mathematical description, which makes it suitable for further theoretical analysis. Experimental results on a broad range of input images validate the effectiveness of the proposed method in terms of lack of undesired artifacts, which are present with other existing meth-ods, and easy interpretability of the input parameters.