Applications in Image Retrieval and 3D Recognition

  • Matti Pietikäinen
  • Abdenour Hadid
  • Guoying Zhao
  • Timo Ahonen
Part of the Computational Imaging and Vision book series (CIVI, volume 40)


This chapter considers two applications of LBP in spatial domain: Content-based image retrieval and recognition of 3D textured surfaces. Color and texture features are commonly used in retrieval, but usually they have been applied on full images. In the first part of this chapter two block based methods based on LBPs are presented which can significantly increase the retrieval performance. The second part describes a method for recognizing 3D textured surfaces using multiple LBP histograms as object models. Excellent results are obtained in view-based classification of the widely used CUReT texture database. The method performed also well in the pixel-based classification of natural scene images.


Image Retrieval Local Binary Pattern Query Image Image Block Texture Class 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Bülthoff, H.H., Wallraven, C., Graf, A.: View-based dynamic object recognition based on human perception. In: Proc. International Conference on Pattern Recognition, pp. 768–776 (2002) Google Scholar
  2. 2.
    Castano, R., Manduchi, R., Fox, J.: Classification experiments on real-world texture. In: Proc. Workshop on Empirical Evaluation Methods in Computer Vision, pp. 3–20 (2001) Google Scholar
  3. 3.
    Corel Corporation (2005).
  4. 4.
    Cula, O.G., Dana, K.J.: Compact representation of bidirectional texture functions. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, vol. 1, pp. 1041–1047 (2001) Google Scholar
  5. 5.
    Cula, O.G., Dana, K.J.: Recognition methods for 3D texture surfaces. In: Proc. SPIE Conference on Human Vision and Electronic Imaging, pp. 209–220 (2001) CrossRefGoogle Scholar
  6. 6.
    Dana, K.J., van Ginneken, B., Nayar, S.K., Koenderink, J.J.: Reflectance and texture of real-world surfaces. ACM Trans. Graph. 18(1), 1–34 (1999) CrossRefGoogle Scholar
  7. 7.
    Grangier, D., Bengio, S.: A discriminative kernel-based approach to rank images from text queries. IEEE Trans. Pattern Anal. Mach. Intell. 30(8), 1371–1384 (2008) CrossRefGoogle Scholar
  8. 8.
    Huang, J., Kumar, S.R., Mitra, M., Zhu, W.J., Zabih, R.: Image indexing using color correlograms. In: Proc. IEEE Conference on Computer Vision and Pattern Recognition, pp. 762–768 (1997) CrossRefGoogle Scholar
  9. 9.
    Leung, T., Malik, J.: Representing and recognizing the visual appearance of materials using three-dimensional textons. Int. J. Comput. Vis. 43(1), 29–44 (2001) MATHCrossRefGoogle Scholar
  10. 10.
    Malik, J., Belongie, S.J., Leung, T., Shi, J.B.: Contour and texture analysis for image segmentation. Int. J. Comput. Vis. 43(1), 7–27 (2001) MATHCrossRefGoogle Scholar
  11. 11.
    Manjunath, B.S., Ma, W.Y.: Texture features for browsing and retrieval of image data. IEEE Trans. Pattern Anal. Mach. Intell. 18, 837–842 (1996) CrossRefGoogle Scholar
  12. 12.
    Manjunath, B.S., Ohm, J.R., Vinod, V.V., Yamada, A.: Color and texture descriptors. IEEE Trans. Circuits Syst. Video Technol. 11(6), 703–715 (2001). Special Issue on MPEG-7 CrossRefGoogle Scholar
  13. 13.
    Ojala, T., Pietikäinen, M., Harwood, D.: A comparative study of texture measures with classification based on feature distributions. Pattern Recognit. 29(1), 51–59 (1996) CrossRefGoogle Scholar
  14. 14.
    Ojala, T., Pietikäinen, M., Mäenpää, T.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans. Pattern Anal. Mach. Intell. 24(7), 971–987 (2002) CrossRefGoogle Scholar
  15. 15.
    Ojala, T., Mäenpää, T., Pietikäinen, M., Viertola, J., Kyllönen, J., Huovinen, S.: Outex—New framework for empirical evaluation of texture analysis algorithms. In: Proc. International Conference on Pattern Recognition, pp. 701–706 (2002) Google Scholar
  16. 16.
    Park, D.K., Jeon, Y.S., Won, C.S.: Efficient use of local edge histogram descriptor. In: Proc. ACM Workshop on Standards, Interoperability and Practices, pp. 51–54 (2000) Google Scholar
  17. 17.
    Park, S.J., Park, D.K.W.C.: Core experiments on MPEG-7 edge histogram descriptor. Technical report, ISO/IEC JTC1/SC29/WG11-MPEG2000/M5984 (2000) Google Scholar
  18. 18.
    Pietikäinen, M., Nurmela, T., Mäenpää, T., Turtinen, M.: View-based recognition of real-world textures. Pattern Recognit. 37(2), 313–323 (2004) MATHCrossRefGoogle Scholar
  19. 19.
    Puzicha, J., Buhmann, J.M., Rubner, Y., Tomasi, C.: Empirical evaluation of dissimilarity measures for color and texture. In: Proc. International Conference on Computer Vision, vol. 2, p. 1165 (1999) CrossRefGoogle Scholar
  20. 20.
    Sim, D.G., Kim, H.K., Oh, D.I.: Translation, scale, and rotation invariant texture descriptor for texture-based image retrieval. In: Proc. International Conference on Image Processing, vol. 3, pp. 742–745 (2000) Google Scholar
  21. 21.
    Stricker, M., Orengo, M.: Similarity of color images. In: Storage and Retrieval of Image and Video Databases III, vol. 2, pp. 381–392 (1995) CrossRefGoogle Scholar
  22. 22.
    Swain, M., Ballard, D.: Color indexing. In: Proc. International Conference on Computer Vision, pp. 11–32 (1990) Google Scholar
  23. 23.
    Takala, V.: Local Binary Pattern Method in Context-based Image Retrieval. M.Sc. thesis, Department of Electrical and Information Engineering, University of Oulu (2004) (In Finnish) Google Scholar
  24. 24.
    Takala, V., Ahonen, T., Pietikäinen, M.: Block-based methods for image retrieval using local binary patterns. In: Scandinavian Conference on Image Analysis. Lecture Notes in Computer Science, vol. 3540, pp. 882–891. Springer, Berlin (2005) CrossRefGoogle Scholar
  25. 25.
    Tamura, H., Mori, T., Yamawaki, T.: Textural features corresponding to visual perception. IEEE Trans. Syst. Man Cybern. 8, 460–473 (1978) CrossRefGoogle Scholar
  26. 26.
    Turtinen, M., Pietikäinen, M.: Contextual analysis of textured scene images. In: Proc. British Machine Vision Conference, pp. 849–858 (2006) Google Scholar
  27. 27.
    Varma, M., Zisserman, A.: Classifying images of materials: Achieving viewpoint and illumination independence. In: European Conference on Computer Vision. Lecture Notes in Computer Science, vol. 2352, pp. 255–271. Springer, Berlin (2002) Google Scholar
  28. 28.
    Varma, M., Zisserman, A.: Classifying materials from images: To cluster or not to cluster? In: Proc. International Workshop on Texture Analysis and Synthesis, pp. 139–144 (2002) Google Scholar
  29. 29.
    Yao, C.H., Chen, S.Y.: Retrieval of translated, rotated and scaled color textures. Pattern Recognit. 36(4), 913–929 (2003) MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Matti Pietikäinen
    • 1
  • Abdenour Hadid
    • 1
  • Guoying Zhao
    • 1
  • Timo Ahonen
    • 2
  1. 1.Machine Vision Group, Department of Computer Science and EngineeringUniversity of OuluOuluFinland
  2. 2.Nokia Research CenterPalo AltoUSA

Personalised recommendations