Computational Visual Media

, Volume 3, Issue 2, pp 177–188 | Cite as

User-guided line abstraction using coherence and structure analysis

  • Hui-Chi Tsai
  • Ya-Hsuan Lee
  • Ruen-Rone LeeEmail author
  • Hung-Kuo ChuEmail author
Open Access
Research Article


Line drawing is a style of image abstraction where the perceptual content of the image is conveyed using distinct straight or curved lines. However, extracting semantically salient lines is not trivial and mastered only by skilled artists. While many parametric filters have successfully extracted accurate and coherent lines, their results are sensitive to parameter choice and easily lead to either an excessive or insufficient number of lines. In this work, we present an interactive system to generate concise line abstractions of arbitrary images via a few user specified strokes. Specifically, the user simply has to provide a few intuitive strokes on the input images, including tracing roughly along edges and scribbling on the region of interest, through a sketching interface. The system then automatically extracts lines that are long, coherent and share similar textural structures to form a corresponding highly detailed line drawing. We have tested our system with a wide variety of images. Our experimental results show that our system outperforms state-of-the-art techniques in terms of quality and efficiency.


line abstraction interactive drawing coherence strokes structure strokes stroke matching 



We are grateful to the anonymous reviewers for their comments and suggestions. The work was supported in part by the “Ministry of Science and Technology of Taiwan” (Nos. 103-2221-E-007-065-MY3 and 105-2221-E-007-104-MY2).

Supplementary material

41095_2016_76_MOESM1_ESM.pdf (1.1 mb)
User-guided line abstraction using coherence and structure analysis


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© The Author(s) 2016

Open Access The articles published in this journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  1. 1.Department of Computer Science“National Tsing Hua University”Hsinchu, TaiwanChina
  2. 2.Information and Communications Research LaboratoriesIndustrial Technology Research InstituteChutung, Hsinchu, TaiwanChina

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