IDENTIFYING FAGACEAE SPECIES IN TAIWAN USING LEAF IMAGES
Journal
TRANSACTIONS OF THE ASABE
Journal Volume
62
Journal Issue
5
Pages
1055
Date Issued
2019
Author(s)
Abstract
Fagaceae is the second-largest woody plant family in Taiwan and has considerable economic and ecological value. Identifying Fagaceae species is essential for forest managers and forestry technical personnel. In this study, ten Fagaceae species were distinguished using image processing and machine learning. For each species, 100 leaf images were collected using flatbed scanners. The morphological, marginal, color, and textural traits of the leaves were then quantified. A genetic algorithm was next applied to identify the traits that are essential for species identification. Support vector machine classifiers were developed to identify the species using the selected traits as the inputs. The results indicated that the proposed approach had an accuracy of 92.8%.
Subjects
Fagaceae; Image processing; Machine learning; Species identification; Trait selection
SDGs
Publisher
AMER SOC AGRICULTURAL & BIOLOGICAL ENGINEERS
Type
journal article
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2019升等_參考著作2_Fagaceae Identification.pdf
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