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Plant species identification is one of the most important research branches of botanical science. In this paper, a novel shape descriptor, namely Periodic Wavelet Descriptor (PWD) of plant leaf, is firstly presented. Then based on the PWDs of the leaves of different plant species, we constructed a database of PWDs. At last, a Back Propagation Neural Network (BPNN) is trained to fulfill the experiment of plant species identification. The experimental results show that the proposed algorithm combined the PWD of plant leaf with BPNN is effective with a correct identification rate about 90 %.
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Subject
Classification
Title
Using the periodic wavelet descriptor of plant leaf to identify plant species
Author
Zeng, Qingmao 1 ; Zhu, Tonglin 1 ; Zhuang, Xueying 2 ; Zheng, Mingxuan 2 ; Guo, Yubin 3
1 College of Mathematics and Informatics, South China Agricultural University, Guangzhou, Guangdong, People's Republic of China; Institute of Agricultural Multimedia Technology, South China Agricultural University, Guangzhou, Guangdong, People's Republic of China
2 College of Forestry and Landscape Architecture, South China Agricultural University Guangzhou, Guandong, People's Republic of China
3 College of Mathematics and Informatics, South China Agricultural University, Guangzhou, Guangdong, People's Republic of China; Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation, Guangzhou, Guandong, People's Republic of China; Guangdong Province Key Laboratory for Land Use and Consolidation, Guangzhou, Guandong, People's Republic of China
1 College of Mathematics and Informatics, South China Agricultural University, Guangzhou, Guangdong, People's Republic of China; Institute of Agricultural Multimedia Technology, South China Agricultural University, Guangzhou, Guangdong, People's Republic of China
2 College of Forestry and Landscape Architecture, South China Agricultural University Guangzhou, Guandong, People's Republic of China
3 College of Mathematics and Informatics, South China Agricultural University, Guangzhou, Guangdong, People's Republic of China; Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation, Guangzhou, Guandong, People's Republic of China; Guangdong Province Key Laboratory for Land Use and Consolidation, Guangzhou, Guandong, People's Republic of China
Multimedia Tools and Applications; Dordrecht
Volume
76
Issue
17
Pages
17873-17890
Publication year
2017
Publication date
Sep 2017
Place of publication
Dordrecht
Country of publication
Netherlands
Publication subject
ISSN
13807501
e-ISSN
15737721
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
ProQuest document ID
1923215818
Document URL
https://www.proquest.com/scholarly-journals/using-periodic-wavelet-descriptor-plant-leaf/docview/1923215818/se-2?accountid=40258
Copyright
Multimedia Tools and Applications is a copyright of Springer, 2017.
Last updated
2024-11-29
Database
ABI/INFORM Collection