Skip to main content

Construction of Color Network Model of Folk Painting Based on Machine Learning

  • Conference paper
  • First Online:
Machine Learning for Cyber Security (ML4CS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13657))

Included in the following conference series:

  • 548 Accesses

Abstract

In order to more accurately explore and reflect the color design thinking of folk paintings, and provide more reference and inspiration for the current design with Chinese characteristics and ethnic characteristics, a research on the construction of color network model of folk paintings based on machine learning was proposed. By calculating the folk painting color feature point set, the concentric circles coordinate system, constructing the corresponding feature points according to the folk painting color main curvature, the tectonic pattern of folk painting color description factor, combined with folk drawing design of color invariants, matching the folk painting color, the introduction of image histogram constraint, nonlinear histogram transformation model is set up, According to the contrast distortion adjustment algorithm, the model is solved, and the folk painting color network model is constructed. The case shows that the color network model can accurately reflect the color characteristics and color matching design logic of Ansai folk paintings.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Liu, S., Liu, D., Muhammad, K., Ding, W.: Effective template update mechanism in visual tracking with background clutter. Neurocomputing 458, 615–625 (2021)

    Article  Google Scholar 

  2. Yan, Y., et al.: Research on the construction of Ansai folk painting color network model. J. Silk 57(11), 120–125 (2020)

    Google Scholar 

  3. Mei, Y., Jin-song, L., Yi-yan, W.: Construction and application of color network model of Dunhuang traditional fresco. Packag. Eng. 41(18), 22–228 (2020)

    Google Scholar 

  4. Kim, M., Kang, D., Lee, N.: Feature extraction from oriental painting for wellness contents recommendation services. IEEE Access 7, 59263–59270 (2019)

    Article  Google Scholar 

  5. Jiang, Y., Zheng, L.-B.: Application research of chinese traditional painting coloring mode in poster design. Packaging Eng. 42(18), 321–325 (2021)

    Google Scholar 

  6. Liu, S., Wang, S., Liu, X., Lin, C.-T., Lv, Z.: Fuzzy detection aided real-time and robust visual tracking under complex environments. IEEE Trans. Fuzzy Syst. 29(1), 90–102 (2021). https://doi.org/10.1109/TFUZZ.2020.3006520

    Article  Google Scholar 

  7. Qian, W., et al.: Artistic paintings classification based on information entropy. J. Graph. 40(6), 991–999 (2019)

    Google Scholar 

  8. Zhu, M., Jiao, H., Zhao, X.: A color transfer method based on neighborhood-first searching and texture similarity matching. Imaging Sci. Photochem. 38(6), 935–940 (2020)

    Google Scholar 

  9. Weiwei, C., Yan, C.: Color space matching analysis of clothing colors and clothing styles based on PCCS color system. J. Silk 56(1), 66–72 (2019)

    Google Scholar 

  10. Shuai, L., et al.: Human memory update strategy: a multi-layer template update mechanism for remote visual monitoring. IEEE Trans. Multimedia 23, 2188–2198 (2021)

    Article  Google Scholar 

  11. Wen, M.Y., Liao, W.G.: Incremental mining algorithm for uncertain data based on machine learning. Comput. Simul. 38(11), 290–294 (2021)

    Google Scholar 

Download references

Acknowledgement

“A study on the cultural and creative design and artistic creation of the unique landscape resources in Weizhou Island” by Professor 2021 of Nanning University, project number: 2021 JSGC22.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bomei Tan .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yu, R., Tan, B. (2023). Construction of Color Network Model of Folk Painting Based on Machine Learning. In: Xu, Y., Yan, H., Teng, H., Cai, J., Li, J. (eds) Machine Learning for Cyber Security. ML4CS 2022. Lecture Notes in Computer Science, vol 13657. Springer, Cham. https://doi.org/10.1007/978-3-031-20102-8_20

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-20102-8_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20101-1

  • Online ISBN: 978-3-031-20102-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics