A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network

In this paper, we employ probabilistic neural network (PNN) with image and data processing techniques to implement a general purpose automated leaf recognition for plant classification. 12 leaf features are extracted and orthogonalized into 5 principal variables which consist the input vector of the...

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Bibliographic Details
Published in2007 IEEE International Symposium on Signal Processing and Information Technology pp. 11 - 16
Main Authors Wu, S.G., Bao, F.S., Xu, E.Y., Yu-Xuan Wang, Yi-Fan Chang, Qiao-Liang Xiang
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 01.12.2007
Subjects
Artificial neural networks
Biology computing
Classification algorithms
Computer science
Feature extraction
Humans
leaf recognition
Neural networks
plant classification
Principal component analysis
Probabilstic Neural Network
Shape
Signal processing algorithms
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ISBN9781424418343
1424418348
ISSN2162-7843
DOI10.1109/ISSPIT.2007.4458016

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Summary:In this paper, we employ probabilistic neural network (PNN) with image and data processing techniques to implement a general purpose automated leaf recognition for plant classification. 12 leaf features are extracted and orthogonalized into 5 principal variables which consist the input vector of the PNN. The PNN is trained by 1800 leaves to classify 32 kinds of plants with an accuracy greater than 90%. Compared with other approaches, our algorithm is an accurate artificial intelligence approach which is fast in execution and easy in implementation.
ISBN:9781424418343
1424418348
ISSN:2162-7843
DOI:10.1109/ISSPIT.2007.4458016