Plant classification using leaf image based on 2D linear discriminant analysis

Authors:
Minggang Du;Shanwen Zhang
Affiliations:
School of Urban and Environment Science, Shanxi Normal University, Linfen, Shanxi, P.R. China;Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, P.R. China
Venue:
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Year:
2010

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Abstract

The 2D-LDA algorithm operates on data represented as 2D matrices, instead of 1D vectors, so that the dimensionality of the data representation can be kept small as a way to alleviate the SSS problem. Given a set of samples of each class, the 2D-LDA extracts most informative features which could establish a high degree of similarity between samples of the same class and a high degree of dissimilarity between samples of two classes. In this paper, we apply 2D-LDA to plant leaf classification. The experiments on the real plant leaf database demonstrate that 2D-LDA is effective and feasible for plant leaf classification.