Supervised locally linear embedding for plant leaf image feature extraction

Authors:
Youqian Feng;Shanwen Zhang
Affiliations:
The Science Institute, Air-Force Engineering University, Xi'an, China;Intelligent Computation Lab, Hefei Institute of Intelligent Machines, Chinese Academy of Science, Hefei, Anhui, P.R. China
Venue:
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Year:
2009

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Abstract

The objects of traditional plant identification were too broad and the classification features of it were usually not synthetic and the recognition rate was always slightly low. This paper gives one recognition approach based on supervised locally linear embedding (LLE) and K-nearest neighbors. The recognition results for thirty kinds of broad-leaved trees were realized and the average correct recognition rate reached 98.3%. Comparison with other recognition method demonstrated the proposed method is effective in advancing the recognition rate.