In this paper, we employ Probabilistic Neural Network (PNN) with image and data processing techniques to implement a general purpose automated leaf recognition algorithm. 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.
@article{arxiv.0707.4289,
title = {A Leaf Recognition Algorithm for Plant Classification Using Probabilistic Neural Network},
author = {Stephen Gang Wu and Forrest Sheng Bao and Eric You Xu and Yu-Xuan Wang and Yi-Fan Chang and Qiao-Liang Xiang},
journal= {arXiv preprint arXiv:0707.4289},
year = {2007}
}