Skip to main content
SpringerLink
Log in

Jacquard Image Segmentation Method Based on Fuzzy Optimization Technology

  • Conference paper
Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3642))

Abstract

Automatic pattern segmentation of jacquard images is a challenging task for jacquard pattern analysis. In this paper, the phase field model was introduced to extract specific pattern structures within jacquard images. A novel fuzzy optimization method, namely, Multi-start Fuzzy Optimization Method (MSFOM) was proposed for numerical solving of the phase field model. The proposed method was a hybrid algorithm combining fuzzy logic and genetic algorithms, which was able to find global minimum of the phase field model with low computational cost. Experimental results on synthetic and jacquard images demonstrate the efficacy of the proposed method.

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

Access this chapter

Log in via an institution
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 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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ngan, H.Y.T., Pang, G.K.H., Yung, S.P., Michael, K.N.: Defect detection on patterned jacquard fabric. In: Proceedings of SPIE Conference on Applied Imagery Pattern Recognition, pp. 163–168 (2003)

    Google Scholar 

  2. Bodnarova, A., Bennamoun, M., Latham, S.J.: Flaw detection in jacquard fabrics using Gabor filters. In: Proceedings of SPIE Conference on Intelligent Robots and Computer Vision XVIII: Algorithms, Techniques, and Active Vision, pp. 254–269 (1999)

    Google Scholar 

  3. Unser, M.: Texture classification and segmentation using wavelet frames. IEEE Transaction on Image Processing 4, 1549–1560 (1995)

    Article  Google Scholar 

  4. Soria-Frisch, A., Koppen, M., Nickolay, B.: Aggregation as similarity in a morphological framework for the processing of textile images. In: Proceedings of IEEE International Conference on Fuzzy Systems, pp. 1739–1744 (2004)

    Google Scholar 

  5. Ginneken, B.V., Frangi, A.F., Staal, J.J., Viergever, M.A.: Active shape model segmentation with optimal features. IEEE Transactions on Medical Imaging 21, 924–933 (2002)

    Article  Google Scholar 

  6. Xiao, H., Xu, C.Y.: A topology preserving level set method for deformable models. IEEE Transaction on Pattern Analysis and Machine Intelligence 25, 755–768 (2003)

    Article  Google Scholar 

  7. Kichenassamy, S., Kumar, A., Olver, P.J., Tannenbaum, A., Yezzi, A.: Conformal curvature flows: from phase transitions to active vision. Archive for Rational Mechanics and Analysis 134, 257–301 (1996)

    Article  MathSciNet  Google Scholar 

  8. Nestler, B., Wheeler, A.A.: Phase-field modeling of multi-phase solidification. Computer Physics Communications 147, 230–233 (2002)

    Article  MATH  Google Scholar 

  9. Barles, G., Soner, H.M., Sougandis, P.E.: Front propagation and phase field theory. SIAM Journal on Control and Optimization 31, 439–469 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  10. Capuzzo, D., Finzi, V., March, R.: Area-preserving curve-shortening flows: From phase separation to image processing. Interfaces and Free Boundaries 31, 325–343 (2002)

    Article  Google Scholar 

  11. Gajewski, H., Gartner, K.: On a nonlocal model of image segmentation. Weierstrass Institute for Applied Analysis and Stochastics 762, 87–107 (2002)

    Google Scholar 

  12. Benes, M., Chalupecky, V., Mikula, K.: Geometrical image segmentation by the AllenĺCCahn equation. Applied Numerical Mathematics 51, 187–205 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  13. Zadeh, L.A.: Fuzzy sets. Information and Control 8, 338–353 (1965)

    Article  MATH  MathSciNet  Google Scholar 

  14. Rao, S.S., Sawyer, J.P.: Fuzzy Finite Element Approach for the Analysis of Imprecisely Defined Systems. AIAA Journal 33, 2364–2370 (1995)

    Article  MATH  Google Scholar 

  15. Allen, M., Cahn, W.: A microscopic theory for antiphase boundary motion and its application to antiphase domain coarsening. Applied Physics 27, 1085–1095 (1979)

    Google Scholar 

  16. De Giorgi, E., Carriero, M., Leaci, A.: Existence theorem for a minimum problem with free discontinuity set. Archive for Rational Mechanics and Analysis 1, 291–322 (1990)

    Google Scholar 

  17. Ambrosio, L., Tortorelli, V.M.: Approximation of functionals depending on jumps by elliptic functionals via Γ-convergence. Communications on Pure and Applied Mathematics 43, 999–1036 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  18. Modica, L.: The gradient theory of phase transitions and the minimal interface criterion. Archive for Rational Mechanics and Analysis 98, 123–142 (1987)

    Article  MATH  MathSciNet  Google Scholar 

  19. Kawarada, H., Suito, H.: Fuzzy Optimization Method, Computational Science for the 21st Century. John Wiley & Sons, Chichester (1997)

    Google Scholar 

  20. Kawarada, H., Ohtomo, T., Suito, H.: Multi-Start Fuzzy Optimization Method, GAKUTO International Series. Mathematical Sciences and Applications 11, 26–78 (1997)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. College of Zhijiang, Zhejiang University of Technology, Hangzhou, 310024, China

    Zhilin Feng

  2. State Key Lab of CAD & CG, Zhejiang University, Hangzhou, 310027, China

    Zhilin Feng, Jianwei Yin, Jiong Qiu, Xiaoming Liu & Jinxiang Dong

Authors
  1. Zhilin Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jianwei Yin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jiong Qiu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaoming Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jinxiang Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Regina, Regina, SK, S4S 0A2 Canada, Polish-Japanese Institute of Information Technology, Koszykowa 86, 02-008 Warsaw, P.O. Box, Poland

    Dominik Ślęzak

  2. Department of Computer Science, University of Regina, S4S 0A2, Regina, Saskatchewan, Canada

    JingTao Yao  & Wojciech Ziarko  & 

  3. Department of Electrical and Computer Engineering, University of Manitoba, R3T 5V6, Winnipeg, Manitoba, Canada

    James F. Peters

  4. College of Computer and Information Engineering, Hehan University, Henan, China

    Xiaohua Hu

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Feng, Z., Yin, J., Qiu, J., Liu, X., Dong, J. (2005). Jacquard Image Segmentation Method Based on Fuzzy Optimization Technology. In: Ślęzak, D., Yao, J., Peters, J.F., Ziarko, W., Hu, X. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2005. Lecture Notes in Computer Science(), vol 3642. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11548706_29

Download citation

  • DOI: https://doi.org/10.1007/11548706_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28660-8

  • Online ISBN: 978-3-540-31824-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation