DocumentCode :
2306695
Title :
Linear Discriminant Analysis and Its Application in Plant Classification
Author :
Du, Minggang ; Wang, Xianfeng
Author_Institution :
Sch. of Urban & Environ. Sci., Shanxi Normal Univ., Linfen, China
fYear :
2011
fDate :
25-27 April 2011
Firstpage :
548
Lastpage :
551
Abstract :
The most common organisms on Earth are plants, which are crucial to the maintenance of atmospheric composition, nutrient cycling and other ecosystem processes. The classification of plants is vital to the study of plant genetic diversity and ecological sensitivity, which is also helpful for many problems such as feeding the population and fighting disease. In this paper, we firstly discuss the shortages of LDA, then classify the plant by using PCA+LDA. The experiments show that it is effective and feasible for plant classification.
Keywords :
diseases; ecology; genetic engineering; horticulture; image classification; principal component analysis; production engineering computing; atmospheric composition; common organisms; disease; ecological sensitivity; ecosystem processes; linear discriminant analysis; nutrient cycling; plant classification; plant genetic diversity; principal component analysis; Algorithm design and analysis; Classification algorithms; Feature extraction; Pattern recognition; Personal digital assistants; Shape; Support vector machines; Dimension reduction; LDA; Plant classification; Small-sample-size problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information and Computing (ICIC), 2011 Fourth International Conference on
Conference_Location :
Phuket Island
Print_ISBN :
978-1-61284-688-0
Type :
conf
DOI :
10.1109/ICIC.2011.147
Filename :
5954627
Link To Document :
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