Plant species identification based on modified local discriminant projection

被引:2
|
作者
Zhang, Shanwen [1 ]
Huang, Wenzhun [1 ]
Wang, Zhen [1 ]
机构
[1] Xijing Univ, Dept Informat Engn, Xian 710123, Peoples R China
来源
NEURAL COMPUTING & APPLICATIONS | 2020年 / 32卷 / 21期
基金
中国国家自然科学基金;
关键词
Plant species identification; Maximum margin criterion (MMC); Local discriminant projection (LDP); Modified LDP (MLDP); GENERAL FRAMEWORK; RECOGNITION; FEATURES;
D O I
10.1007/s00521-018-3746-0
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Plant species identification based on plant leaves is important for biological science, ecological science, and agricultural digitization. Because of the complexity and variation of the plant leaves, many classical plant species identification algorithms using plant leaf images are not enough for practical application. A modified local discriminant projection (MLDP) algorithm is proposed for plant species identification. MLDP aims to extract discriminant features for plant species identification by taking class label information into account based on the property of locality preserving. The MLDP can preserve the local geometrical structure of leaves and extract the strong discriminative ability. The experimental results on the public ICL leaf image database show the effectiveness and feasibleness of the proposed method.
引用
收藏
页码:16329 / 16336
页数:8
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