A constrained genetic algorithm for line labelling of line drawings with shadows and table-lines

Abstract

Line drawings are well known to exhibit geometric ambiguities, resulting in, drawings that can have

multiple interpretations. However, drawings are used to present design concepts to peers in fields such

as engineering design, where it is imperative that the observer interprets the drawing in the same way

as the designer for effective communication. Designers therefore use cues, prompting the observer to

resolve the geometric ambiguities and achieve the desired interpretation. In this paper, we identify the

cues introduced in drawings and focus on two cues, namely table-lines (which convey information

about the position of the object in space) and shadows (which convey information about the geometry

of the object). These cues can be used in a line-labelling context to allow a line-labelling algorithm to

overcome the geometric ambiguities of the drawing. For this purpose, we propose a cue-constrained

genetic algorithm that takes the vectorized line drawing and the identified cues attached to each edge,

and uses these cues as constraints on the edge labels, thus distinguishing between different object- background interactions. We show that the proposed algorithm can be used to successfully label

intentionally ambiguous line drawings according to some desired interpretation as specified by the

additional cues present in the drawing.