Skip to main content
SpringerLink
Log in

Textile image recoloring by polarization observation

  • Original article
  • Published:
The Visual Computer Aims and scope Submit manuscript

Abstract

In this paper, a novel method for recoloring a textile image with polarization observation is proposed. By polarization image analysis, the proposed method can easily catch the specular reflection of yarns. Polarization image analysis also contributes to highly accurate region segmentation of warp and weft yarns. The conventional method using convex-hull assumes that an image is composed of at least four color elements. Our proposed method can overcome the limitations of too few textile colors. Our method can process textile images composed of only two color elements while existing methods struggle. In addition, we show how to generate images recolored both correctly and naturally through interactive alpha-matting, instead of aiming only at efficiency in recoloring, which sometimes results in unnatural images. A user study is performed to test the GUI indicators and the naturalness of the recoloring results. Extensive experiments show that the proposed method generates far better textile recoloring results compared to existing approaches.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25
Fig. 26
Fig. 27
Fig. 28

Similar content being viewed by others

References

  1. Tan, J., Echevarria, J.: Efficient palette-based decomposition and recoloring of images via RGBXY-space geometry. ACM Trans. Graph. (TOG) 262, 1–10 (2018)

    Article  Google Scholar 

  2. Zhao, S., Luan, F., Bala, K.: Fitting procedural yarn models for realistic cloth rendering. ACM Trans. Graph. (TOG) 35(4), 1–11 (2016)

    Google Scholar 

  3. Leaf, J., Wu, R., Schweickart, E., James, D.L., Marschner, S.: Interactive design of periodic yarn-level cloth patterns. ACM Trans. Graph. (TOG) 37(6), 1–15 (2018)

    Article  Google Scholar 

  4. Donashi, Y., Iwasaki, K., Okabe, M., Ijiri, T., Todo, H.: Inverse appearance modeling of interwoven cloth. Vis. Comput. 35(2), 175–190 (2019)

    Article  Google Scholar 

  5. Bueno, B., Wilson, H.R., Sunkara, S., Able, S., Tilmann, E.K.: Simulation-based design of an angle-selective and switchable textile shading system. Build. Environ. 184, 107–227 (2020)

    Article  Google Scholar 

  6. Monzon, M.D., Paz, R., Verdaguer, M., Suárez, L., Badalló, P., Ortega, Z., Diaz, N.: Experimental analysis and simulation of novel technical textile reinforced composite of banana fibre. Materials 12(7), 1134 (2019)

    Article  Google Scholar 

  7. Huang, Y., Wang, C., Li, C.: Translucent image recoloring through homography estimation. Comput. Graph. Forum 37(7), 421–432 (2018)

    Article  Google Scholar 

  8. Musialski, P., Cui, M., Ye, J., Razdan, A., Wonka, P.: A framework for interactive image color editing. Vis. Comput. 29(11), 1173–1186 (2013)

    Article  Google Scholar 

  9. Zhu, Z., Mao, X.: Image recoloring for color vision deficiency compensation: a survey. Vis. Comput. 37(12), 2999–3018 (2021)

    Article  Google Scholar 

  10. Du, Z.J., Lei, K.X., Xu, K., Tan, J., Gingold, Y.: Video recoloring via spatial-temporal geometric palettes. ACM Trans. Graph. (TOG) 40(4), 1–16 (2021)

    Article  Google Scholar 

  11. Zou, Z., Shen, H.L., Du, X., Shao, S., Xin, J.H.: Recoloring textile fabric images based on improved fuzzy clustering in wiley. Color Res. Appl. 42(1), 115–123 (2019)

    Article  Google Scholar 

  12. Kand, J.M., Hwang, Y.: Hierarchical palette extraction based on local distinctiveness and cluster validation for image recoloring. In: 2018 25th IEEE International Conference on Image Processing (ICIP), IEEE, pp. 2252–2256 (2018)

  13. Tsekouras, G.E., Rigos, A., Chatzistamatis, S., Tsimikas, J., Kotis, K., Caridakis, G., Anagnostopoulos, C.N.: A novel approach to image recoloring for color vision deficiency. Sensors 21(8), 2740 (2021)

    Article  Google Scholar 

  14. Afifi, M., Price, B.L., Cohen, S., Brown, M.S.: Image Recoloring Based on Object Color Distributions. In: Eurographics (Short Papers), pp. 33–36 (2019)

  15. Nguyen, R.M.H., Kim, S.J., BROWN, M.S.: Illuminant aware gamut-based color transfer. Comput. Graph. Forum 33(7), 319–328 (2015)

    Article  Google Scholar 

  16. Xiao, X., Ma, L.: Color transfer in correlated color space. In: Vrcia Acm International Conference on Virtual Reality Continuum & Its Applications. DBLP, pp. 305–309 (2006)

  17. Pitié, F., Kokaram, A.: The linear monge–kantorovitch linear colour mapping for example-based colour transfer. Vis. Media Prod. 23 (2007)

  18. Reinhard, E., Adhikhmin, M., Gooch, B., Shirley, P.: Color transfer between images. IEEE Comput. Graph. Appl. 21(5), 34–41 (2001)

    Article  Google Scholar 

  19. He, M., Liao, J., Chen, D., Yuan, L., Sander, P.V.: Progressive color transfer with dense semantic correspondences. ACM Trans. Graph. (TOG) 38(2), 1–18 (2019)

    Article  Google Scholar 

  20. Luan, F., Paris, S., Shechtman, E., Bala, K.: Deep photo style transfer. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4990–4998 (2017)

  21. Kuo, C.F.J., Jian, B.L., Wu, H.C., Peng, K.C.: Automatic machine embroidery image color analysis system. Part I: using Gustafson–Kessel clustering algorithm in embroidery fabric color separation. Text. Res. J. 82(6), 571–583 (2012)

    Article  Google Scholar 

  22. Liu, S., Chen, D.: Computer simulation of batik printing patterns with cracks. Text. Res. J. 85(18), 1972–1984 (2015)

    Article  Google Scholar 

  23. Postle, R., Dhingra, R.C.: Measuring and interpreting low-stress fabric mechanical and surface properties: part III: optimization of fabric properties for men’s. suiting materials. Text. Res. J. 59(8), 448–459 (1989)

  24. Šomodi, Ž, Rolich, T., Hurse, A., Pavlinić, D.Z.: Micromechanical tensile model of woven fabric and parameter optimization for fit with KES data. Text. Res. J. 80(13), 1255–1264 (2010)

    Article  Google Scholar 

  25. Atkinson, G.A., Hancock, E.R.: Shape estimation using polarization and shading from two views. IEEE Trans. Pattern Anal. Mach. Intell. 29(11), 2001–2017 (2007)

    Article  Google Scholar 

  26. Grant, L., Daughtry, C.S.T., Vanderbilt, V.C.: Polarized and non-polarized leaf reflectances of Coleus blumei. Environ. Exp. Bot. 27(2), 139–145 (1987)

    Article  Google Scholar 

  27. Jacques, S.L., Ramella-Roman, J.C., Lee, K.: Imaging skin pathology with polarized light. J. Biomed. Opt. 7(3), 329–340 (2002)

    Article  Google Scholar 

  28. Li, Z., Li, K., Li, L., Xu, H., Xie, Y., Ma, Y., Li, D., Goloub, P., Yuan, Y., Zheng, X.B.: Calibration of the degree of linear polarization measurements of the polarized Sun-sky radiometer based on the POLBOX system. Appl. Opt. 57(5), 1011–1018 (2018)

    Article  Google Scholar 

  29. Chang, H., Fried, O., Liu, Y., DiVerdi, S., Finkelstein, A.: Palette-based photo recoloring. ACM Trans. Graph 34(4), 139:1-139:11 (2015)

    Article  Google Scholar 

  30. Porter T., Duff T.: Compositing digital images[C]// Proceedings of the 11th Annual Conference on Computer Graphics and Interactive Techniques. 253–259 (1984)

  31. Mokrzycki, W.S., Tatol, M.: Colour difference \(\Delta \) E-A survey. Mach. Graph. Vis. 20(4), 383–411 (2011)

    Google Scholar 

Download references

Acknowledgements

The authors would like to thank the anonymous reviewers for providing constructive suggestions, that contributed to highly improve this work. This work was supported in part by the National Key Research and Development Program of China under Grant 2020YFB 1709402; in part by the NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization under Grant U1909210; in part by the Zhejiang Provincial Science and Technology Program in China under Grant 2021C01108; in part by the China National Natural Science Foundation under Grant 61902099; in part by the Zhejiang Laboratory Tianshu Open Source AI Platform; in part by the Zhejiang Provincial Science and Technology Program in China under Grant LQ22F020026; in part by the Fundamental Research Funds for the Provincial Universities of Zhejiang under Grant GK219909299001-028.

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou, 310018, China

    Haipeng Luan, Renshu Gu, Haiyan Wu & Gang Xu

  2. Department of Computer Science and Engineering, University of Yamanashi, Kofu, Yamanashi, Japan

    Masahiro Toyoura & Takamasa Terada

  3. Nara Institute of Science and Technology, Ikoma, Nara, 630-0192, Japan

    Takuya Funatomi

Authors
  1. Haipeng Luan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Masahiro Toyoura
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Renshu Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Takamasa Terada
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Haiyan Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Takuya Funatomi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Gang Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Masahiro Toyoura or Gang Xu.

Ethics declarations

Conflict of interest

All of the authors declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Luan, H., Toyoura, M., Gu, R. et al. Textile image recoloring by polarization observation. Vis Comput 39, 4351–4370 (2023). https://doi.org/10.1007/s00371-022-02595-y

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00371-022-02595-y

Keywords

Search

Navigation