Accurate Recognition Method of Plant Leaves based on Multi-feature Fusion

During the use of a convolutional neural network to train a recognition model of plant leaves, the convolutional layers focus on the appearance of leaves in learning the features of them, while ignoring their internal texture features, thereby resulting in the misclassification of plant leaves with similar appearance. Aiming at this problem, this paper proposes an accurate identification method of plant leaves based on multi-feature fusion, which can be applied to extract the appearance and texture features of leaves simultaneously, and to conduct fusion and summation for these two types of features. The experimental results indicate that compared with the accuracy of the ordinary convolutional neural network recognition method and traditional machine learning method, the accuracy of this method has been improved substantially.