A venation-based leaf image classification scheme

Jin Kyu Park, Een Jun Hwang, Yunyoung Nam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)


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.

Original languageEnglish
Title of host publicationInformation Retrieval Technology - Third Asia Information Retrieval Symposium, AIRS 2006, Proceedings
PublisherSpringer Verlag
Number of pages13
ISBN (Print)3540457801, 9783540457800
Publication statusPublished - 2006
Event3rd Asia Information Retrieval Symposium, AIRS 2006 - Singapore, Singapore
Duration: 2006 Oct 162006 Oct 18

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4182 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other3rd Asia Information Retrieval Symposium, AIRS 2006

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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