Glass Patterns and Artistic Imaging

Abstract

Abstract. The theory of Glass patterns naturally combines three essential 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 paintings 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 perceptually similar to a painting. An efficient implementation is presented. Unlike most of the existing techniques for unsupervised painterly rendering, 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 methods, and easy interpretability of the input parameters.

Reduced Inverse Distance Weighting Interpolation for Painterly Rendering

“…5, is first to compute a vector field v(r), which determins the local brush stroke orientation, and then to render elongated curved brush strokes oriented along v(r). Brush strokes are rendered by means of the operator desribed in [16,17], which is based on the theory of Glass patterns. With respect to other algorithms for brush strokes simulation, the one proposed in [16,17] has the advantage to be fast and free from and magic numbers.…”