Plant classification based on multilinear independent component analysis

Authors:
Shan-Wen Zhang;Min-Rong Zhao;Xiao-Feng Wang
Affiliations:
Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, P.R. China;Missile Institute, Air-Force Engineering University, Sanyuan, P.R. China;Hefei Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, P.R. China
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

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Abstract

Plant classification is very important and necessary with respect to agricultural informization, ecological protection and plant automatic classification system. In this paper, we present a multilinear independent component analysis (MICA) algorithm and apply it to a multimodal plant leaf recognition problem involving multiple leaves imaged in different periods and illuminations. To show the validity of the method, we apply it to a plant leaf image dataset. The experimental results show that the method is efficient and feasible.