Fast and effective retrieval of plant leaf shapes

Authors:
Bin Wang;Yongsheng Gao
Affiliations:
Key Laboratory of Electronic Business, Nanjing University of Finance and Economics, Nanjing, China,School of Engineering, Griffith University, QLD, Australia;School of Engineering, Griffith University, QLD, Australia
Venue:
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part II
Year:
2012

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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 different length of shape contour to describe the shape. This method not only finely captures the global and local features, but also is very compact and has very low computational complexity. 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.