A venation-based leaf image classification scheme

Jin Kyu Park, Een Jun Hwang, Yunyoung Nam

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

    9 Citations (Scopus)

    Abstract

    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
    Pages416-428
    Number of pages13
    ISBN (Print)3540457801, 9783540457800
    DOIs
    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

    Other

    Other3rd Asia Information Retrieval Symposium, AIRS 2006
    Country/TerritorySingapore
    CitySingapore
    Period06/10/1606/10/18

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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