Softwood ray height based on tangential section images by using YOLOv5

Abstract

Abstract In order to achieve rapid acquisition, identification and measurement of the average ray height of softwood based on tangential section photographs, a new method is proposed. Firstly, labels the digital image of the softwood tangential section with the 100 magnification, that is, mark the rays and scales on the image, and establish the dataset; Secondly, the dataset is randomly divided into training set and validation set. YOLOv5s is used for model training to obtain the best target recognition model of rays and scale. The experimental results show that the model trained with YOLOv5s can achieve 93.5% accuracy, 95.6% recall and 96.7% average accuracy in the validation set; Thirdly, using the YOLOv5s trained model, a visual program for automatically calculating the ray height and obtaining the ray characteristics of softwood is designed, which lowered the threshold for wood identification workers to use such software.