Plant identification using leaf shapes-A pattern counting approach

被引:98
作者
Zhao, Cong [1 ]
Chan, Sharon S. F. [2 ]
Cham, Wai-Kuen [1 ]
Chu, L. M. [2 ]
机构
[1] Chinese Univ Hong Kong, Dept Elect Engn, Sch Engn, Hong Kong, Hong Kong, Peoples R China
[2] Chinese Univ Hong Kong, Sch Life Sci, Hong Kong, Hong Kong, Peoples R China
关键词
Plant identification; Foliage image recognition; Shape matching; Sparse representation; Dictionary learning; LARGE UNDERDETERMINED SYSTEMS; SPARSE REPRESENTATION; EQUATIONS;
D O I
10.1016/j.patcog.2015.04.004
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Plant identification is required by all walks of life, from professionals to the general public. Nevertheless, it is not an easy job but requires specialized knowledge. In this paper, we propose a new method for plant identification using shapes of their leaves. Different from existing studies which target at simple leaves, the proposed method can accurately recognize both simple and compound leaves. In specifics, we propose a novel feature that captures global and local shape information independently so that they can be examined individually during classification. Furthermore, we advocate that when comparing two leaf individuals it is better to "count" the number of certain shape patterns rather than to match the extracted shape features in a point-wise manner. The proposed counting-based shape descriptor is not only discriminative for classification but also computationally fast and storage cheap. Experiments conducted on five leaf image datasets demonstrate that our algorithm significantly outperforms the state-of-the-art methods in terms of recognition accuracy, efficiency and storage requirement. (C) 2015 Elsevier Ltd. All rights reserved.
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页码:3203 / 3215
页数:13
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