Plant Leaf Classification Based on Deep Learning

摘要

In the plant leaf classification, leaf representation with traditionally handcrafted features is difficult to reveal its complex shape and texture. In this paper, we proposed a novel plant leaf classification method based on convolutional neural network (CNN) due to its powerful capability of feature extraction and classification. In our method, a ten-layer CNN was constructed for plant leaf classification. In order to improve the classification, sample augment for leaf was applied to the images to enlarge the database. The visualization was utilized for analyzing the factors influencing the accuracy rate. The experimental results on leaf database Flavia with 4,800 leaf images and 32 kinds of leaf showed that the proposed method achieved a high overall accuracy with 87.92%.