A robust method for scale independent detection of curvature-based criticalities and intersections in line drawings

•The method detects curvature based criticalities and intersections efficiently.•The method is effective for the noisy and disconnected line drawings.•The method is effective for line drawings with a variety of brush characteristics.•The method is utilized to represent shapes in a design grammar interpreter.•Features in varying scales can be detected in digital drawings.

A novel two-phase iterative method is proposed to identify curvature based criticalities and intersections in line drawings. The method is based on evaluating a field obtained from the image via diffusion using adaptively changing ellipse-shaped analysis windows. The deviation of the average field strength values within the analysis windows from that of an external reference field is used as a metric to evaluate the criticality of a region. The external reference field is computed from an image of a straight line. The experimental results depict that the method is effective in detecting curvature based criticalities and intersections, even for noisy and disconnected drawings as well as drawings drawn with a variety of brush characteristics, such as glass, ocean, ripple, scatter, stamp, strokes effects. Our method can be employed as a part of a design grammar interpreter.