Skip to main content
SpringerLink
Log in

Vectorization of line drawing image based on junction analysis

基于交叉点分析的线条画矢量化

  • Research Paper
  • Published:
Science China Information Sciences Aims and scope Submit manuscript

Abstract

Converting a scanned or shot line drawing image into a vector graph can facilitate further editand reuse, making it a hot research topic in computer animation and image processing. Besides avoiding noiseinfluence, its main challenge is to preserve the topological structures of the original line drawings, such as linejunctions, in the procedure of obtaining a smooth vector graph from a rough line drawing. In this paper, wepropose a vectorization method of line drawings based on junction analysis, which retains the original structureunlike done by existing methods. We first combine central line tracking and contour tracking, which allowsus to detect the encounter of line junctions when tracing a single path. Then, a junction analysis approachbased on intensity polar mapping is proposed to compute the number and orientations of junction branches.Finally, we make use of bending degrees of contour paths to compute the smoothness between adjacent branches,which allows us to obtain the topological structures corresponding to the respective ones in the input image.We also introduce a correction mechanism for line tracking based on a quadratic surface fitting, which avoidsaccumulating errors of traditional line tracking and improves the robustness for vectorizing rough line drawings.We demonstrate the validity of our method through comparisons with existing methods, and a large amount ofexperiments on both professional and amateurish line drawing images.

创新点

本文提出一种基于交叉点分析的线条矢量化方法, 克服了现有方法难以保持拓扑结构的不足。通过中心路径跟踪和轮廓路径跟踪相结合的方式, 准确检测交叉点的出现提出一种基于极坐标亮度映射的交叉点分析方法, 计算交叉点的分支数量和朝向; 利用轮廓路径的弯曲角度判断交叉点相邻分支间的光顺度, 从而获得与原图一致的拓扑结构。

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Chen T, Cheng M M, Tan P, et al. Sketch2Photo: Internet image montage. ACM Trans Graph, 2009, 28: 1–10

    Google Scholar 

  2. Xu K, Chen K, Fu H B, et al. Sketch2Scene: sketch-based co-retrieval and co-placement of 3D models. ACM TransGraph, 2013, 32: 1–12

    Google Scholar 

  3. Lai Y K, Hu S M, Martin R R, et al. Automatic and topology-preserving gradient mesh generation for image vectorization. ACM Trans Graph, 2009, 28: 1–8

    Article  Google Scholar 

  4. Lee B S, Kazi R H, Smith G. SketchStory: telling more engaging stories with data through freeform sketching. IEEETrans Vis Comput Graph, 2013, 19: 2416–2425

    Article  Google Scholar 

  5. Yoo I, Vank J, Nizovtseva. Sketching human character animations by composing sequences from large motion database. Vis Comput, 2014, 30: 213–227

    Article  Google Scholar 

  6. Fu H B, Zhou S Z, Liu L G, et al. Animated construction of line drawings. ACM Trans Graph, 2011, 30: 1–10

    Article  Google Scholar 

  7. Zhang T, Suen C Y. A fast parallel algorithm for thinning digital patterns. Commun ACM, 1984, 27: 236–239

    Article  Google Scholar 

  8. Hilaire X, Tombre K. Improving the accuracy of skeleton-based vectorization. Graphics recognition algorithms andapplications. Berlin/Heidelberg: Springer, 2002. 273–288

    Chapter  Google Scholar 

  9. Sezgin T M, Davis R. Handling overtraced strokes in hand-drawn sketches. In: Proceedings of Making Pen-BasedInteraction Intelligent and Natural. New York: AAAI Fall Symposium, 2004. 1–4

    Google Scholar 

  10. Hilaire X, Tombre K. Robust and accurate vectorization of line drawings. IEEE Trans Patt Anal Mach Intell, 2006,28: 890–904

    Article  Google Scholar 

  11. Bonnici A, Camilleri K P. Scribble vectorization using concentric sampling circles. In: Proceedings of InternationalConference on Advanced Engineering Computing and Applications in Sciences. Los Alamitos: IEEE Computer Society,2009. 89–94

    Google Scholar 

  12. Bonnici A, Camilleri K. A circle-based vectorization algorithm for drawings with shadows. In: Proceedings of theInternational Symposium on Sketch-Based Interfaces and Modeling. New York: ACM, 2013. 69–77

    Chapter  Google Scholar 

  13. Zou J J, Yan H. Line image vectorization based on shape partitioning and merging. In: Proceedings of InternationalConference on Pattern Recognit, Barcelona, 2000. 994–997

    Google Scholar 

  14. Zou J J, Yan H. Cartoon image vectorization based on shape subdivision. In: Proceedings of Computer GraphicsInternational. Los Alamitos: IEEE Computer Society, 2001. 225–231

    Google Scholar 

  15. Wenyin L, Dori D. Sparse pixel tracking: a fast vectorization algorithm applied to engineering drawings. In: Proceedingsof International Conference on Pattern Recognit, Vienna, 1996. 808–812

    Google Scholar 

  16. Dori D, Liu W. Sparse pixel vectorization: an algorithm and its performance evaluation. IEEE Trans Patt Anal MachIntell, 1999, 21: 202–215

    Article  Google Scholar 

  17. Whited B, Rossignac J, Slabaugh G, et al. Pearling: stroke segmentation with crusted pearl strings. IEEE Trans PattAnal Mach Intell, 2009, 19: 277–283

    Google Scholar 

  18. Noris G, Hornung A, Sumner R W, et al. Topology-driven vectorization of clean line drawings. ACM Trans Graph,2013, 32: 1–11

    Article  Google Scholar 

  19. Sun J, Liang L, Wen F, et al. Image vectorization using optimized gradient meshes. ACM Trans Graph, 2007, 26:1–11

    Google Scholar 

  20. Xia T, Liao B, Yu Y. Patch-based image vectorization with automatic curvilinear feature alignment. ACM TransGraph, 2009, 28: 1–10

    Article  Google Scholar 

  21. Chiang J Y, Tue S, Leu Y. A new algorithm for line image vectorization. Patt Recog, 1998, 31: 1541–1549

    Article  Google Scholar 

  22. Chang H H, Yan H. Vectorization of hand-drawn image using piecewise cubic B´ezier curves fitting. Patt Recog, 1998,31: 1747–1755

    Article  Google Scholar 

  23. Liu K, Huang Y S, Suen C Y. Identification of fork points on the skeletons of handwritten Chinese characters. IEEETrans Patt Anal Mach Intell, 1999, 21: 1095–1100

    Article  Google Scholar 

  24. Rajan P, Hammond T. From paper to machine: extracting strokes from images for use in sketch recognition. In:Proceedings of the 5th Eurographics conference on Sketch-Based Interfaces and Modeling, Annecy, 2008. 41–48

    Google Scholar 

  25. Yang Y, Zhu C, Sun Q. Vectorization of linear features on color scanning topographic maps (in Chinese). J ComputAid Des Comput Graph, 2009, 21: 533–541

    Google Scholar 

  26. Song J, Su F, Cai S. The segmentation of text from line based on the line recognition in scanning engineering drawings(in Chinese). J Nanjing Univ, 2001, 37: 535–541

    Google Scholar 

  27. Wong J, Guo C. An improved image template thinning algorithm (in Chinese). J Image Graph, 2004, 9: 297–301

    Google Scholar 

  28. Liu R, Li Y. Study of auto-vectorization based on scan-thinning algorithm (in Chinese). Acta Geodaetica et CartographicaSinica, 2012, 41: 309–314

    Google Scholar 

  29. Lu Z, Zhang Q. Line contour tracking in engineering drawing vectorization (in Chinese). J Image Graph, 1997, 2:878–882

    Google Scholar 

  30. Bartolo A, Camilleri K P, Fabri S G, et al. Scribbles to vectors: preparation of scribble drawings for CAD interpretation.In: Proceedings of the 4th Eurographics workshop on Sketch-based interfaces and modeling. New York: ACM, 2007.123–130

    Chapter  Google Scholar 

  31. Nieuwenhuizen P R, Kiewiet O, Bronsvoort W F. An integrated line tracking and vectorization algorithm. ComputGraph Forum, 1994, 13: 349–359

    Google Scholar 

  32. Kyprianidis J E, Kang H. Image and video abstraction by coherence-enhancing filtering. Comput Graph Forum, 2011,30: 593–602

    Article  Google Scholar 

  33. Bartolo A, Camilleri K P, Fabri S G, et al. Line tracking algorithm for scribbled drawings. In: Proceedings ofInternational Symposium on Communications, Control and Signal Processing, St Julians, 2008. 554–559

    Google Scholar 

  34. Wang S D, Ma Z Y, Liu X H, et al. Coherence-enhancing line drawing for color images. Sci China Inf Sci, 2013, 56:110903

  35. Pham T A, Delalandre M, Barrat S, et al. Accurate junction detection and characterization in line-drawing images. Patt Recog, 2014, 47: 282–295

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Computer Science, Zhejiang University of Technology, Hangzhou, 310023, China

    JiaZhou Chen & YongWei Miao

  2. State Key Laboratory of CAD&CG, Zhejiang University, Hangzhou, 310058, China

    Qi Lei & QunSheng Peng

Authors
  1. JiaZhou Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Qi Lei
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. YongWei Miao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. QunSheng Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to JiaZhou Chen.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Chen, J., Lei, Q., Miao, Y. et al. Vectorization of line drawing image based on junction analysis. Sci. China Inf. Sci. 58, 1–14 (2015). https://doi.org/10.1007/s11432-014-5246-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11432-014-5246-x

Keywords

关键词

Search

Navigation