Leaf Recognition for Plant Classification Based on Wavelet Entropy and Back Propagation Neural Network

In this paper, we proposed a method for plant classification, which aims to recognize the type of leaves from a set of image instances captured from same viewpoints. Firstly, for feature extraction, this paper adopted the 2-level wavelet transform and obtained in total 7 features. Secondly, the leaves were automatically recognized and classified by Back-Propagation neural network (BPNN). Meanwhile, we employed K-fold cross-validation to test the correctness of the algorithm. The accuracy of our method achieves 90.0%. Further, by comparing with other methods, our method arrives at the highest accuracy.

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