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A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network
Open accessAbstract
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.
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Motoyoshi, I., Nishida, S., Sharan, L., & Adelson, E. H. (2007) · Nature · doi:10.1038/nature05724 · Cited by 588
Probabilistic neural networks for classification, mapping, or associative memory
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Leaf shape based plant species recognition
Du, J., Wang, X.-F., & Zhang, G.-J. (2006) · Applied Mathematics and Computation · doi:10.1016/j.amc.2006.07.072 · Cited by 359
Shape based leaf image retrieval
Wang, Z., Chi, Z., & Feng, D. D. (2003) · IEE Proceedings - Vision Image and Signal Processing · doi:10.1049/ip-vis:20030160 · Cited by 239
Interactive venation‐based leaf shape modeling
Hong, S. M., Simpson, B., & Baranoski, G. V. G. (2005) · Computer Animation and Virtual Worlds · doi:10.1002/cav.88 · Cited by 43
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Metadata
- Authors
- Wu, S. G., Bao, F. S., Xu, E. Y., Wang, Y.-X., Chang, Y.-F., & Xiang, Q.-L.
- Venue
- 2007 IEEE International Symposium on Signal Processing and Information Technology
- Publisher
- IEEE
- Published
- 2007-12
- Pages
- 11-16
- OpenAlex
- W1968896562
- Cited by
- 935
- References
- 10
- FWCI
- 3.83
- Type
- conference paper
- Language
- en
- Open access
- green
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- Wu, S. G., Bao, F. S., Xu, E. Y., Wang, Y.-X., Chang, Y.-F., & Xiang, Q.-L. (2007). A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network. 2007 IEEE International Symposium on Signal Processing and Information Technology. https://doi.org/10.1109/isspit.2007.4458016
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