Advertisement

A Gravitational Model for Plant Classification Using Adaxial Epidermis Texture

  • André R. BackesEmail author
  • Jarbas Joaci de Mesquita Sá Junior
  • Rosana Marta Kolb
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9280)

Abstract

The leaves are very informative plant organs. They are extensively used in plant anatomical studies focusing taxonomy. Their both inner and outer structures provide very discriminant features from vegetal species. In this study, we propose using images from adaxial epidermis for plant classification. The adaxial epidermis is a very variable region in a plant leaf cross-section. It differs in color, number of layers and presence/absence of hypodermis. To accomplish this task, we propose combining complexity analysis methods with a gravitational collapsing system to extract texture features from adaxial epidermis samples. Experimental results show that this combination of techniques surpasses traditional and state-of-the-art methods in both grayscale and color images of adaxial epidermis.

Keywords

Adaxial epidermis Texture analysis Color Gravitational system 

References

  1. 1.
    Plotze, R.O., Pádua, J.G., Falvo, M., Bernacci, L.C., Oliveira, G.C.X., Vieira, M.L.C., 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 - Revue Canadienne de Botanique 83(3), 287–301 (2005)Google Scholar
  2. 2.
    Casanova, D., Sá Junior, J.J.M., Bruno, O.M.: Plant leaf identification using Gabor wavelets. International Journal of Imaging Systems and Technology 19(1), 236–243 (2009)CrossRefGoogle Scholar
  3. 3.
    Sá Junior, J.J.M., Rossatto, D.R., Kolb, R.M., Bruno, O.M.: A computer vision approach to quantify leaf anatomical plasticity: a case study on Gochnatia polymorpha (Less.) Cabrera. Ecological Informatics 15, 34–43 (2013)CrossRefGoogle Scholar
  4. 4.
    Backes, A.R., Casanova, D., Bruno, O.M.: Plant leaf identification based on volumetric fractal dimension. IJPRAI 23(6), 1145–1160 (2009)Google Scholar
  5. 5.
    Kaplan, L.M.: Extended fractal analysis for texture classification and segmentation. IEEE Transactions on Image Processing 8(11), 1572–1585 (1999)CrossRefGoogle Scholar
  6. 6.
    Haralick, R.M.: Statistical and structural approaches to texture. Proc. IEEE 67(5), 786–804 (1979)CrossRefGoogle Scholar
  7. 7.
    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
  8. 8.
    Laine, A., Fan, J.: Texture classification by wavelet packet signatures. IEEE Transactions on Pattern Analysis and Machine Intelligence 15(11), 1186–1191 (1993)CrossRefGoogle Scholar
  9. 9.
    Backes, A.R., Casanova, D., Bruno, O.M.: Color texture analysis based on fractal descriptors. Pattern Recognition 45(5), 1984–1992 (2012)CrossRefGoogle Scholar
  10. 10.
    Liu, G.H., Li, Z., Zhang, L., Xu, Y.: Image retrieval based on micro-structure descriptor. Pattern Recognition 44(9), 2123–2133 (2011)CrossRefGoogle Scholar
  11. 11.
    Backes, A.R., de M. Sá Junior, J.J., Kolb, R.M., Bruno, O.M.: Plant species identification using multi-scale fractal dimension applied to images of adaxial surface epidermis. In: Jiang, X., Petkov, N. (eds.) CAIP 2009. LNCS, vol. 5702, pp. 680–688. Springer, Heidelberg (2009) CrossRefGoogle Scholar
  12. 12.
    Sá Junior, J.J.M., Backes, A.R., Rossatto, D.R., Kolb, R.M., Bruno, O.M.: Measuring and analyzing color and texture information in anatomical leaf cross sections: an approach using computer vision to aid plant species identification. Botany 89(7), 467–479 (2011)CrossRefGoogle Scholar
  13. 13.
    Sá Junior, J.J.M., Backes, A.R.: A simplified gravitational model to analyze texture roughness. Pattern Recognition 45(2), 732–741 (2012)CrossRefGoogle Scholar
  14. 14.
    Sá Junior, J.J.M., Backes, A.R., Cortez, P.C.: A simplified gravitational model for texture analysis. Journal of Mathematical Imaging and Vision 47(1–2), 70–78 (2013)Google Scholar
  15. 15.
    Sá Junior, J.J.M., Backes, A.R., Cortez, P.C.: Color texture classification based on gravitational collapse. Pattern Recognition 46(6), 1628–1637 (2013)CrossRefGoogle Scholar
  16. 16.
    Mandelbrot, B.: The fractal geometry of nature. Freeman & Co. (2000)Google Scholar
  17. 17.
    Tricot, C.: Curves and Fractal Dimension. Springer-Verlag (1995)Google Scholar
  18. 18.
    Allain, C., Cloitre, M.: Characterizing the lacunarity of random and deterministic fractal sets. Phys. Rev. A 44(6), 3552–3558 (1991)CrossRefMathSciNetGoogle Scholar
  19. 19.
    Du, G., Yeo, T.S.: A novel lacunarity estimation method applied to SAR image segmentation. IEEE Trans. Geoscience and Remote Sensing 40(12), 2687–2691 (2002)CrossRefGoogle Scholar
  20. 20.
    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
  21. 21.
    Hoang, M.A., Geusebroek, J.M., Smeulders, A.W.M.: Color texture measurement and segmentation. Signal Processing 85(2), 265–275 (2005)CrossRefzbMATHGoogle Scholar
  22. 22.
    Paschos, G., Petrou, M.: Histogram ratio features for color texture classification. Pattern Recognition Letters 24(1–3), 309–314 (2003)CrossRefGoogle Scholar
  23. 23.
    Bianconi, F., Fernández, A., González, E., Caride, D., Calvino, A.: Rotation-invariant colour texture classification through multilayer CCR. Pattern Recognition Letters 30(8), 765–773 (2009)CrossRefGoogle Scholar
  24. 24.
    Porebski, A., Vandenbroucke, N., Macaire, L.: Haralick feature extraction from LBP images for color texture classification. In: Image Processing Theory, Tools and Applications, pp. 1–8 (2008)Google Scholar
  25. 25.
    Everitt, B.S., Dunn, G.: Applied Multivariate Analysis, 2nd edn. Arnold (2001)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • André R. Backes
    • 1
    Email author
  • Jarbas Joaci de Mesquita Sá Junior
    • 2
  • Rosana Marta Kolb
    • 3
  1. 1.Faculdade de ComputaçãoUniversidade Federal de UberlândiaUberlândiaBrazil
  2. 2.Departamento de Engenharia de Computação, Campus de SobralUniversidade Federal Do CearáSobralBrazil
  3. 3.Departamento de Ciências Biológicas, Faculdade de Ciências E LetrasUniversidade Estadual Paulista, UNESPAssisBrazil

Personalised recommendations