A Venation-Based Leaf Image Classification Scheme

  • Jin-Kyu Park
  • EenJun Hwang
  • Yunyoung Nam
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4182)


Most content-based image retrieval systems use image features such as textures, colors, and shapes. However, in the case of leaf image, it is not appropriate to rely on color or texture features only because such features are similar in most leaves. In this paper, we propose a novel leaf image retrieval scheme which first analyzes leaf venation for leaf categorization and then extracts and utilizes shape feature to find similar ones from the categorized group in the database. The venation of a leaf corresponds to the blood vessel of organisms. Leaf venations are represented using points selected by the curvature scale scope corner detection method on the venation image, and categorized by calculating the density of feature points using non-parametric estimation density. We show its effectiveness by performing several experiments on the prototype system.


Feature Point Image Retrieval Query Image Secondary Vein Leaf Image 
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.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jin-Kyu Park
    • 1
  • EenJun Hwang
    • 1
  • Yunyoung Nam
    • 2
  1. 1.School of Electrical EngineeringKorea UniversitySeoulKorea
  2. 2.Graduate School of Information and CommunicationAjou UniversitySuwon, Kyunggi-DoKorea

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