Hit-or-Miss Transform in Multivariate Images

  • Santiago Velasco-Forero
  • Jesús Angulo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6474)


The Hit-or-Miss transform (HMT) is a well-known morphological operator for template matching in binary images. A novel approach for HMT for multivariate images is introduced in this paper. The generic framework is a generalization of binary case based on a h-supervised ordering formulation which leads to reduced orderings. In particular, in this paper we focus on the application of HMT for target detection on high-resolution images. The visual results of the experiments show the performance of proposed approach.


Mathematical Morphology Hyperspectral Imagery Hit-or-Miss Transform Remote Sensing Colour Images 


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  1. 1.
    Sim, D., Kwon, O., Park, R.: Object matching algorithms using robust hausdorff distance measures. IEEE Trans. Image Processing 8, 425–429 (1999)CrossRefGoogle Scholar
  2. 2.
    Zhu, Z., Tang, M., Lu, H.: A new robust circular gabor based object matching by using weighted hausdorff distance. Pattern Recognition Letters 25, 515–523 (2004)CrossRefGoogle Scholar
  3. 3.
    Serra, J.: Image Analysis and Mathematical Morphology. Academic Press, Inc., Orlando (1983)Google Scholar
  4. 4.
    Soille, P.: Morphological Image Analysis. Springer, Heidelberg (1999)CrossRefMATHGoogle Scholar
  5. 5.
    Naegel, B., Passat, N., Ronse, C.: Grey-level hit-or-miss transforms - Part I: Unified theory. Pattern Recognition 40, 635–647 (2007)CrossRefMATHGoogle Scholar
  6. 6.
    Ronse, C.: A lattice-theoretical morphological view on template extraction in images. Journal of Visual Comm. and Image Representation 7, 273–295 (1996)CrossRefGoogle Scholar
  7. 7.
    Aptoula, E., Lefevre, S., Ronse, C.: A hit-or-miss transform for multivariate images. Pattern Recognition Letters 30, 760–764 (2009)CrossRefGoogle Scholar
  8. 8.
    Weber, J., Lefevre, S.: A multivariate Hit-or-Miss transform for conjoint spatial and spectral template matching. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds.) ICISP 2008. LNCS, vol. 5099, pp. 226–235. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  9. 9.
    Velasco-Forero, S., Angulo, J.: Morphological processing of hyperspectral images using kriging-based supervised ordering. In: ICIP (2010)Google Scholar
  10. 10.
    Roman, S.: Lattices and Ordered Sets. Springer, Heidelberg (2008)MATHGoogle Scholar
  11. 11.
    Heijmans, H.: Theoretical aspects of gray-level morphology. IEEE Trans. Pattern Analysis and Machine Intelligence 13, 568–582 (1991)CrossRefGoogle Scholar
  12. 12.
    Goutsias, J., Heijmans, H., Sivakumar, K.: Morphological operators for image sequences. Comput. Vis. Image Underst. 62, 326–346 (1995)CrossRefGoogle Scholar
  13. 13.
    Barnett, V.: The ordering of multivariate data (with discussion). Journal of the Royal Statistical Society Series A 139, 318–354 (1976)MathSciNetCrossRefGoogle Scholar
  14. 14.
    Jolliffe, I.T.: Principal Component Analysis. Springer, Heidelberg (1986)CrossRefMATHGoogle Scholar
  15. 15.
    Lezoray, O., Charrier, C., Elmoataz, A.: Learning complete lattices for manifold mathematical morphology. In: Proc. of the ISMM, pp. 1–4 (2009)Google Scholar
  16. 16.
    Angulo, J.: Morphological colour operators in totally ordered lattices based on distances: Application to image filtering, enhancement and analysis. Comput. Vis. Image Underst. 107, 56–73 (2007)CrossRefGoogle Scholar
  17. 17.
    Cristianini, N., Shawe-Taylor, J.: An Introduction to support vector machines and other kernel based learning methods. Cambridge University Press, Cambridge (2000)CrossRefMATHGoogle Scholar
  18. 18.
    Regazzoni, C., Teschioni, A.: A new approach to vector median filtering based on space filling curves. IEEE Trans. Image Processing 6, 1025–1037 (1997)CrossRefGoogle Scholar
  19. 19.
    Chanussot, J., Lambert, P.: Extending mathematical morphology to color image processing. In: Int. Conf. on Color in Graphics and Image Proc., pp. 158–163 (2000)Google Scholar
  20. 20.
    Serra, J.: Image Analysis and Mathematical Morphology. Academic Press, Inc., Orlando (1982)MATHGoogle Scholar
  21. 21.
    Goutsias, J., Heijmans, H.: Mathematical Morphology. IOS Press, Amsterdam (2000)MATHGoogle Scholar
  22. 22.
    Haralick, R., Sternberg, S., Zhuang, X.: Image analysis using mathematical morphology. IEEE Trans. Pattern Analysis and Machine Intelligence 9, 532–550 (1987)CrossRefGoogle Scholar
  23. 23.
    Aptoula, E., Lefèvre, S.: A comparative study on multivariate mathematical morphology. Pattern Recognition 40, 2914–2929 (2007)CrossRefMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Santiago Velasco-Forero
    • 1
  • Jesús Angulo
    • 1
  1. 1.CMM-Centre de Morphologie Mathématique, Mathématiques et SystèmesFontainebleauFrance

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