WAPSI: Web Application for Plant Species Identification Using Fuzzy Image Retrieval

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 297)


In this paper, a Web Application for Plant Species Identification (WAPSI) that incorporates content-based image retrieval (CBIR) is described. At the heart of this application is a shape-based leaf image retrieval system which uses a contour descriptor based on the curvature of the leaf contour which reduces the number of points for the shape representation. Futhermore, a two-step algorithm for retrieval is used which in the first step reduces the database using some geometrical features. Secondly, leaf images are ranked using a similarity measure between the contour representations. The similarity function between images uses a variant triangular membership function to calculate the distance between the characteristic points’ vectors. This membership function is the key of the good results obtained. The effectiveness for plant species identification of the method is shown through several experiments using our Web application.


fuzzy logic triangular membership function CBIR web application image processing botany 


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  1. 1.
    Caballero, C., Aranda, M.C.: Plant species identification using leaf image retrieval. In: International Conference on Image and Video Retrieval, pp. 327–334 (2010)Google Scholar
  2. 2.
    Panagiotis, T., Papadakis, S.E., Manolakis, D.: Plant leaves classification based on morphological features and a fuzzy surface selection technique. In: International Conference on Technology and Automation, pp. 365–370 (2005)Google Scholar
  3. 3.
    Wang, Z., Chi, Z., Feng, D.: Fuzzy integral for leaf image retrieval. Fuzzy System 1, 372–377 (2002)Google Scholar
  4. 4.
    Yan, C.Z., Mao, H.P., Hu, B., Li., M.X.: Features selection of cotton diseases leaves image based on fuzzy feature selection techniques. In: The Proceedings of the International Conference on Wavelet Analysis and Pattern Recognition, pp. 124–129 (2007)Google Scholar
  5. 5.
    Liqun, H.: Recognition of the part of growth of flue-cured tabacco leaves based on support vector machine. In: World Congress on Intelligent Control and Automation, pp. 3624–3627 (2008)Google Scholar
  6. 6.
    Liu, J., Zhang, S., Deng, S.: A method of plant classification based on wavelet transforms and support vector machines. In: Emerging Intelligent Computing Technology and Applications, pp. 253–260 (2009)Google Scholar
  7. 7.
    Jiazhi, P., He., Y.: Recognition of plant by leaves digital image and neural network. In: International Conference on Computer Science and Software Engineering, pp. 12–14 (2008)Google Scholar
  8. 8.
    Liu, J., Zhang, S., Liu, J.: A method of plant leaf recognition based on locally linear embedding and moving center hypersphere classifier. In: Emerging Intelligent Computing Technology and Applications, pp. 645–651 (2009)Google Scholar
  9. 9.
    Wang, Z., Chi, Z., Feng, D.: Shape based leaf image retrieval. Image Signa Process 150, 34–43 (2003)Google Scholar
  10. 10.
    Du, J.X., Wang, X.F., Zhang, G.J.: Leaf shape based plant species recognition. Applied Mathematics and Computation 185, 883–893 (2007)zbMATHCrossRefGoogle Scholar
  11. 11.
    Pornpanomchai, C., Rimdusit, S., Tanasap, P., Chaiyod, C.: Thai Herb Leaf Image Recognition System (THLIRS). Kasetsart Journal: Natural Sicence 45(3), 551–562 (2011)Google Scholar
  12. 12.
    Nam, Y., Hwang, E., Byeon, K.: ELIS: An efficient leaf image retrieval system. In: International Pattern Recognition and Image Analysis, pp. 589–597 (2005)Google Scholar
  13. 13.
    White, S., Fenier, S.: Exploring interfaces to botanical species classification. In: International Conference Extended Abstracts on Human Factors in Computing System, pp. 3051–3056 (2010)Google Scholar
  14. 14.
    LeafSnap (2011),
  15. 15.
    Wang, X., Huang, D., Du, J., Xu, H., Heutte, L.: Classification of plant leaf images with complicated background. In: Applied Mathematics and Computation, pp. 916–926 (2008)Google Scholar
  16. 16.
    Papert, S.: Uses of technology to enhance education. Technical Report 298. MIT, AI Lab (1973)Google Scholar
  17. 17.
    Mokhtarian, F., Mackworth, A.: Scaled-based description and recognition of planar curves and two dimensional shapes. IEEE Trans. Pattern Anal. Machine Intell. 8(1), 34–43 (1996)CrossRefGoogle Scholar

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© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of Languages and Computer Science, Engineerings SchoolUniversity of MalagaMálagaEspaña (Spain)

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