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


Keles H., TARI Z. S.

PATTERN RECOGNITION, vol.48, no.1, pp.140-155, 2015 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 48 Issue: 1
  • Publication Date: 2015
  • Doi Number: 10.1016/j.patcog.2014.07.005
  • Journal Name: PATTERN RECOGNITION
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.140-155
  • Keywords: Line drawings, Varying brush characteristics, Curvature, Intersection points, Computational design, DOMINANT POINT DETECTION, DIGITAL PLANAR CURVES, POLYGONAL-APPROXIMATION, DETECTION ALGORITHM, DIGITIZED-CURVES, REPRESENTATION, RECOGNITION, SHAPES, CODE
  • Hacettepe University Affiliated: No

Abstract

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. (C) 2014 Elsevier Ltd. All rights reserved.