Plant Leaf Identification Using Multi-scale Fractal Dimension

  • André R. Backes
  • Odemir M. Bruno
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5716)


Taxonomical classification of plants is a very complex and time-consuming task. This is mostly due to the great biodiversity of species and the fact of most measures extracted from plants are traditionally performed manually. This paper presents a novel approach to plant identification based on leaf texture. Initially, the texture is modelled as a surface, so complexity analysis using Multi-scale fractal dimension can be performed over the generated surface, resulting in a feature vector which represents texture complexity in terms of the spatial scale. Yielded results show the potential of the approach, which overcomes traditional texture analysis methods, such as Co-occurrence matrices, Gabor filters and Fourier descriptors.


plant identification complexity multi-scale fractal dimension texture analysis 


  1. 1.
    Judd, W., Campbell, C., Kellog, E., Stevens, P.: Plant Systematics: A Phylogenetic Approach. Sinauer Associates, Massachusetts (1999)Google Scholar
  2. 2.
    Kurmann, M.H., Hemsley, A.R.: The Evolution of Plant Architecture. Royal Botanic Gardens, Kew (1999)Google Scholar
  3. 3.
    Hickey, L.R.: Classification of archictecture of dicotyledonous leaves. Amer. J. Bot. 60(1), 17–33 (1973)CrossRefGoogle Scholar
  4. 4.
    Haralick, R.M.: Statistical and structural approaches to texture. Proc. IEEE 67(5), 786–804 (1979)CrossRefGoogle Scholar
  5. 5.
    Murino, V., Ottonello, C., Pagnan, S.: Noisy texture classification: A higher-order statistics approach. Pattern Recognition 31(4), 383–393 (1998)CrossRefGoogle Scholar
  6. 6.
    Shen, L., Bai, L.: A review on gabor wavelets for face recognition. Pattern Anal. Appl. 9(2-3), 273–292 (2006)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Bianconi, F., Fernández, A.: Evaluation of the effects of gabor filter parameters on texture classification. Pattern Recognition 40(12), 3325–3335 (2007)CrossRefzbMATHGoogle Scholar
  8. 8.
    Jain, A.K., Farrokhnia, F.: Unsupervised texture segmentation using Gabor filters. Pattern Recognition 24(12), 1167–1186 (1991)CrossRefGoogle Scholar
  9. 9.
    Daugman, J., Downing, C.: Gabor wavelets for statistical pattern recognition. In: Arbib, M.A. (ed.) The Handbook of Brain Theory and Neural Networks, pp. 414–419. MIT Press, Cambridge (1995)Google Scholar
  10. 10.
    Manjunath, B.S., Ma, W.-Y.: Texture features for browsing and retrieval of image data. IEEE Trans. Pattern Anal. Mach. Intell 18(8), 837–842 (1996)CrossRefGoogle Scholar
  11. 11.
    Azencott, R., Wang, J.-P., Younes, L.: Texture classification using windowed fourier filters. IEEE Trans. Pattern Anal. Mach. Intell 19(2), 148–153 (1997)CrossRefGoogle Scholar
  12. 12.
    Bajcsy, R.K.: Computer identification of visual surfaces. Computer Graphics Image Processing 2, 118–130 (1973)CrossRefGoogle Scholar
  13. 13.
    Sengür, A., Türkoglu, I., Ince, M.C.: Wavelet packet neural networks for texture classification. Expert Syst. Appl. 32(2), 527–533 (2007)CrossRefGoogle Scholar
  14. 14.
    Unser, M.: Texture classification and segmentation using wavelet frames. IEEE Trans. Image Processing 4(11), 1549–1560 (1995)CrossRefGoogle Scholar
  15. 15.
    Huang, P.W., Dai, S.K., Lin, P.L.: Texture image retrieval and image segmentation using composite sub-band gradient vectors. J. Visual Communication and Image Representation 17(5), 947–957 (2006)CrossRefGoogle Scholar
  16. 16.
    Kaplan, L.M.: Extended fractal analysis for texture classification and segmentation. IEEE Transactions on Image Processing 8(11), 1572–1585 (1999)CrossRefGoogle Scholar
  17. 17.
    Schroeder, M.: Fractals, Chaos, Power Laws: Minutes From an Infinite Paradise. W.H. Freeman, New York (1996)zbMATHGoogle Scholar
  18. 18.
    Tricot, C.: Curves and Fractal Dimension. Springer, Heidelberg (1995)CrossRefzbMATHGoogle Scholar
  19. 19.
    Backes, A.R., Bruno, O.M.: A new approach to estimate fractal dimension of texture images. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds.) ICISP 2008 2008. LNCS, vol. 5099, pp. 136–143. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  20. 20.
    Chen, Y.Q., Bi, G.: On texture classification using fractal dimension. IJPRAI 13(6), 929–943 (1999)Google Scholar
  21. 21.
    de O. Plotze, R., Falvo, M., Pádua, J.G., Bernacci, L.C., Vieira, M.L.C., Oliveira, G.C.X., Bruno, O.M.: Leaf shape analysis using the multiscale minkowski fractal dimension, a new morphometric method: a study with passiflora (passifloraceae). Canadian Journal of Botany 83(3), 287–301 (2005)CrossRefGoogle Scholar
  22. 22.
    Li, J., Sun, C., Du, Q.: A new box-counting method for estimation of image fractal dimension. In: International Conference on Image Processing, pp. 3029–3032 (2006)Google Scholar
  23. 23.
    da F. Costa, L., Cesar Jr., R.M.: Shape Analysis and Classification: Theory and Practice. CRC Press, Boca Raton (2000)CrossRefzbMATHGoogle Scholar
  24. 24.
    Carlin, M.: Measuring the complexity of non-fractal shapes by a fractal method. PRL: Pattern Recognition Letters 21(11), 1013–1017 (2000)CrossRefzbMATHGoogle Scholar
  25. 25.
    Bruno, O.M., de O. Plotze, R., Falvo, M., de Castro, M.: Fractal dimension applied to plant identification. Information Sciences 178, 2722–2733 (2008)MathSciNetCrossRefGoogle Scholar
  26. 26.
    Emerson, C.W., Lam, N.N., Quattrochi, D.A.: Multi-scale fractal analysis of image texture and patterns. Photogrammetric Engineering and Remote Sensing 65(1), 51–62 (1999)Google Scholar
  27. 27.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentic-Hall, New Jersey (2002)Google Scholar
  28. 28.
    Everitt, B.S., Dunn, G.: Applied Multivariate Analysis, 2nd edn. Arnold (2001)Google Scholar
  29. 29.
    Fukunaga, K.: Introduction to Statistical Pattern Recognition, 2nd edn. Academic Press, London (1990)zbMATHGoogle Scholar
  30. 30.
    Smith, G.D.: Numerical Solution of Partial Differential Equations: Finite Difference Methods, 3rd edn., Oxford (1986)Google Scholar
  31. 31.
    Idrissa, M., Acheroy, M.: Texture classification using gabor filters. Pattern Recognition Letters 23(9), 1095–1102 (2002)CrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • André R. Backes
    • 1
  • Odemir M. Bruno
    • 2
  1. 1.Instituto de Ciências Matemáticas e de Computação (ICMC)Universidade de São Paulo (USP)São CarlosBrazil
  2. 2.Instituto de Física de São Carlos (IFSC)Universidade de São Paulo (USP)São CarlosBrazil

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