Automated hedcut illustration using isophotes

Sung Ye Kim, Insoo Woo, Ross MacIejewski, David S. Ebert

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

In this work, we present an automated system for creating hedcut illustrations, portraits rendered using small image feature aligned dots (stipples). We utilize edge detection and shading cues from the input photograph to direct stipple placement within the image. Both image edges and isophotes are extracted as a means of describing the image feature and shading information. Edge features and isophotes are then assigned different priorities, with isophotes being assigned the highest priority to enhance the depth perception within the hedcut portrait. Priority assignment dictates the stipple alignment and spacing. Finally, stipple size is based on the number of points and intensity and the gradient magnitude of the input image.

Original languageEnglish (US)
Title of host publicationSmart Graphics - 10th International Symposium, SG 2010, Proceedings
Pages172-183
Number of pages12
DOIs
StatePublished - Dec 1 2010
Externally publishedYes
Event10th International Symposium on Smart Graphics, SG 2010 - Banff, AB, Canada
Duration: Jun 24 2010Jun 26 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6133 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other10th International Symposium on Smart Graphics, SG 2010
CountryCanada
CityBanff, AB
Period6/24/106/26/10

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Kim, S. Y., Woo, I., MacIejewski, R., & Ebert, D. S. (2010). Automated hedcut illustration using isophotes. In Smart Graphics - 10th International Symposium, SG 2010, Proceedings (pp. 172-183). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6133 LNCS). https://doi.org/10.1007/978-3-642-13544-6_17