Introduction - If you have any usage issues, please Google them yourself
Plant based on digital image recognition is a hotspot of research on automatic classification.But with the increase of plant species, the traditional classification method by the extraction of characteristics or more single classifier structure is too simple, leading to a lower leaf recognition rate.To this end, this paper proposes using the texture characteristics in combination with characteristics of shape, which can identify the belief network architecture and using the depth as a classifier.Texture characteristics by local binary pattern, Gabor filter and gray level co-occurrence matrix method.And shape characteristic vector by Hu s invariant and the Fourier descriptor.In order to avoid over fitting phenomenon, dropout method is used to train deep belief networks.This belief network based on feature fusion depth plant identification method