Abstract
Plant recognition has great potential in forestry research and management. A new method combined back propagation neural network and radial basis function neural network to identify tree species using a few features and samples. The process was carried out in three steps: image pretreatment, feature extraction, and leaf recognition. In the image pretreatment processing, an image segmentation method based on hue, saturation and value color space and connected component labeling was presented, which can obtain the complete leaf image without veins and background. The BP-RBF hybrid neural network was used to test the influence of shape and texture on species recognition. The recognition accuracy of different classifiers was used to compare classification performance. The accuracy of the BP-RBF hybrid neural network using nine dimensional features was 96.2%, highest among all the classifiers.
Highlights
Forest resources play an important role in the development of economies, societies and the environment (Yang and Kan 2020)
The results showed that an accuracy of the GBDT-probabilistic neural network (PNN) model using 12 core features was 92.7%, and the accuracy with all 35 features was 93.5%
This study proposed an image segmentation method based on HSV color space and connected component labeling, which can completely extract leaves without petiole
Summary
Forest resources play an important role in the development of economies, societies and the environment (Yang and Kan 2020). There is a new awareness of the importance of protecting plant species. Recognition of plant species can help understand the forest ecosystem and forest economy (Nevalainen et al 2017); on the other, it helps strengthen the management and protection of forest resources, and improve the public’s awareness of forest protection. Plant recognition and classification based on image features is an important research focus in biodiversity informatics, and it is beneficial to explore the evolutionary rules and relationships of plants and establish a taxonomic database. Based on the above characteristics, leaves are often used for species recognition (Rahman et al 2019)
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