Advertisement

Implementation of Textile Image Segmentation Using Contextual Clustering and Fuzzy Logic

  • R. Shobarani
  • S. Purushothaman
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 216)

Abstract

This paper presents the segmentation analysis on textile images. These images have innumerable textures. The content of the images are regularly arranged or repeated or random in a tessellated fashion. It is not necessary that the entire image has to be compulsorily segmented. However, at least one full object has to be segmented correctly in an image. In this work, a systematic approach has been developed to extract textures from the given texture images. The features of the textile images are extracted and used for segmenting those images using contextual clustering and fuzzy logic. The proposed methods combine to improve the segmentation accuracies and to analyze the effects of parameters of the proposed algorithms in segmentation of textures.

Keywords

Contextual clustering Segmentation Textile textures Fuzzy logic K-means algorithm 

References

  1. 1.
    Larry, S.Davis: MITES (mit-æs): a model-driven, iterative texture segmentation algorithm. Comput. Graphics Image Process. 19(2), 95–110 (1982)CrossRefGoogle Scholar
  2. 2.
    Conners, R.W., McMillin, C.W., Lin, K., Vasquez-Espinosa, R.E.: Identifying and locating surface defects in wood: part of an automated lumber processing system. IEEE Trans. Pattern Anal. Mach. Intell. PAMI-5(6), 573–583 (1983)Google Scholar
  3. 3.
    Spann, M., Wilson, R.: A quad-tree approach to image segmentation which combines statistical and spatial information. Pattern Recogn. 18(3/4), 257–269 (1985)CrossRefGoogle Scholar
  4. 4.
    Panjwani, D.K., Healey, G.: Markov random-field models for unsupervised segmentation of textured color images. IEEE Trans on PAMI 17(10), 939–954 (1995)Google Scholar
  5. 5.
    Zucker, S.W.: On the structure of texture. 5(4), 419–436 (1976)Google Scholar
  6. 6.
    Cohen, F.S., Fan, Z., Attali, S.: Automated inspection of textile fabrics using textural models. IEEE Trans. Pattern Anal. Mach. Intell. 13(8), 803–808 (1991)CrossRefGoogle Scholar
  7. 7.
    Chen, J., Jain, A. K.: A structural approach to identify defects in textured images. In: Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, Beijing, Las vegas, Nevada, pp. 29–32 (1988)Google Scholar
  8. 8.
    Hanmandlu, M., Madasu, V.K., Vasikarla, S.: A fuzzy approach to texture segmentation. In: Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC’04), 1, 636–642 (2004) Google Scholar
  9. 9.
    Krastev, K., Georgieva, L.: Identification of leather surface defects using fuzzy logic. International Conference on Computer Systems and Technologies – Comp Sys Tech’, Varna, Bulgaria, pp. IIIA. 12-1-12-6 (2005) Google Scholar
  10. 10.
    Arasteh, Sara, Hung, Chih-Cheng: Color and texture image segmentation using uniform local binary patterns. Mach. Graph. Vis. Int. J. 15(3), 265–274 (2006)Google Scholar
  11. 11.
    Allilli, M.S., Ziou, D.: Globally adaptive region information for automatic color-texture image segmentation. Pattern Recogn. Lett. 28(15), 1946–1956 (2007)Google Scholar
  12. 12.
    Houhou, Nawal, Thiran, Jean-Philippe, Bresson, Xavier: Fast texture segmentation based on semi-local region descriptor and active contour. Numer. Math. Theor. Meth. Appl. 2(4), 445–468 (2009)MathSciNetMATHGoogle Scholar
  13. 13.
    Sujaritha, M., Annadurai, S.: A new modified gaussian mixture model for color-texture segmentation. J. Comp. Sci. 7(2), 279–283 (2011)CrossRefGoogle Scholar
  14. 14.
    Law, Yan Nei, Lee, Hwee Kuan, Yip, Andy M.: Subspace learning for Mumford–Shah-model-based texture segmentation through texture patches. Appl. Opt. 50(21), 3947–3957 (2011)CrossRefGoogle Scholar
  15. 15.
    Shaabany, A., Jamshidi, F.: Texture segmentation concept using fuzzy logic. Int. J. Multidiscipl. Sci. Eng. 3(1), 26–29 (2012)Google Scholar
  16. 16.
    Salli, Eero, Aronen, Hannu J., Savolainen, Sauli, Korvenoja, Antti, Visa, Ari: Contextual Clustering for Analysis of Functional MRI Data. IEEE Trans. Med. Imaging 20(5), 403–414 (2001)CrossRefGoogle Scholar

Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Research Scholar, Mother Teresa Women’s UniversityKodaikanalIndia
  2. 2.PET Engineering CollegeTirunelveli DistrictIndia

Personalised recommendations