Abstract: In this paper,a plant leaf image set identification approach was proposed based on non-linear reconstruction models.This approach initializes the parameters of model by performing unsupervised pre-training using Gaussian restricted Boltzmann machines(GRBMs).Then,the pre-initialized model is separately trained for images of each plant set and class-specific models are learnt.At last,based on the minimum reconstruction error from the learnt class-specific models,majority voting strategy is used for classification.Besides,in order to avoid occurring deformation during the image scaled,this paper normalized plant image by image preprocessing and a method of feature extraction was used based on k-means.The experimental results show that this approach can accurately classify the class of plant image set.

Key words: Non-linear reconstruction models,Gaussian restricted Boltzmann machines,K-means feature extract,Image preprocessing