CLOVER: A mobile content-based leaf image retrieval system

Yunyoung Nam, Eenjun Hwang, Dongyoon Kim

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

15 Citations (Scopus)


In this paper, we present an effective and robust leaf image retrieval system called CLOVER that works especially in the mobile environment, For the inquiry, users sketch or photograph a leaf using a PDA equipped with a digital camera, and then send it to a server. Most leaves tend to have similar color and texture, which makes shape-based image retrieval more effective than color-based image retrieval. In order to improve retrieval performance, we proposed a new shape representation scheme based on the well-known MPP algorithm. The new scheme can reduce the number of points to consider for matching. In addition, we proposed a new dynamic matching algorithm based on the Nearest Neighbor search to reduce the matching time. We implemented a prototype system that supports adaptive transmission of images over 802.11b wireless networks to mobile devices and demonstrate its effectiveness and scalability through various experimental results.

Original languageEnglish
Title of host publicationDigital Libraries
Subtitle of host publicationImplementing Strategies and Sharing Experiences - 8th International Conference on Asian Digital Libraries, ICADL 2005, Proceedings
Number of pages10
Publication statusPublished - 2005
Event8th International Conference on Asian Digital Libraries, ICADL 2005 - Bangkok, Thailand
Duration: 2005 Dec 122005 Dec 15

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3815 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other8th International Conference on Asian Digital Libraries, ICADL 2005

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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