Fast and effective retrieval of plant leaf shapes

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Author(s)
Wang, B
Gao, Y
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Lee, K.M.; Matsushita, Y.; Rehg, J.M.; Hu, Z.

Date
2013
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4600168 bytes

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application/pdf

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Daejeon, Korea

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Abstract

In this paper, a novel shape description and matching method based on multi-level curve segment measures (MLCSM) is proposed for plant leaf image retrieval. MLCSM extracts the statistical features of shape contour via measuring the curve bending, convexity and concavity of the curve segments with dient length of shape contour to describe the shape. This method not only ﮥly captures the global and local features, but also is very compact and has very low computational com- plexity. The performance of the proposed method is evaluated on the widely used Swedish leaf database and the leaf databases collected by ourselves which contains 1200 images and 100 plant leaf species. All the experiments show the superiority of our method over the state-of-the-art shape retrieval methods.

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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7725 LNCS

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PART 2

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© 2013 Springer-Verlag Berlin Heidelberg. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com

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Computer vision

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