CONTINUOUS RECONSTRUCTION METHODS IN GENERATIVE ART AND DESIGN

In this paper, we present an original tool for continuous semantic processing of an arbitrary graphic image in the «human–machine» mode. Its essence lies in the automatic smooth rendering of the visual with a tone monoline, with guaranteed progress from random noise to full detail. We show that, having previously been used exclusively for natural science purposes [I. V. Kashin, AIP Conf. Proc. 2313, 030048 (2020)], the algorithm also claims to be authentic in the palette of generative design and generative art methods. The flexibility of its practical implementation suggests that it can be useful for stimulating the possibility of dynamic decomposition of the drawing and its subsequent creative rethinking.