Shape matching and recognition base on genetic algorithm and application to plant species identification

Authors:
Ji-Xiang Du;Xiao-Feng Wang;Xiao Gu
Affiliations:
Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China;Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China;Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China
Venue:
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
Year:
2005

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Abstract

In this paper an efficient shape matching and recognition approach based on genetic algorithm is proposed and successfully applied to plant special identification. Firstly, a Douglas-Peucker approximation algorithm is adopted to the original shape and a new shape representation is used to form the sequence of invariant attributes. Then a genetic algorithm for shape matching is proposed to do the shape recognition. Finally, the superiority of our proposed method over traditional approaches to plant species identification is demonstrated by experiment. The experimental result showed that our proposed genetic algorithm for leaf shape matching is much suitable for the recognition of not only intact but also blurred, partial, distorted and overlapped plant leaves due to its robustness.