CLOVER: a mobile content-based leaf image retrieval system

Authors:
Yunyoung Nam;Eenjun Hwang;Dongyoon Kim
Affiliations:
Graduate School of Information and Communication, Ajou University, Suwon, Korea;Department of Electronics and Computer Engineering, Korea University, Seoul, Korea;Graduate School of Information and Communication, Ajou University, Suwon, Korea
Venue:
ICADL'05 Proceedings of the 8th international conference on Asian Digital Libraries: implementing strategies and sharing experiences
Year:
2005

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Abstract

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.