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.
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© 2005 Springer-Verlag Berlin Heidelberg
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Nam, Y., Hwang, E., Kim, D. (2005). CLOVER: A Mobile Content-Based Leaf Image Retrieval System. In: Fox, E.A., Neuhold, E.J., Premsmit, P., Wuwongse, V. (eds) Digital Libraries: Implementing Strategies and Sharing Experiences. ICADL 2005. Lecture Notes in Computer Science, vol 3815. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11599517_16
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DOI: https://doi.org/10.1007/11599517_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30850-8
Online ISBN: 978-3-540-32291-7
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