A Diameter Measurement Method of Red Jujubes Trunk Based on Improved PSPNet

Yichen Qiao, Yaohua Hu, Zhouzhou Zheng, Zhanghao Qu, Chao Wang, Taifeng Guo and Juncai Hou
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Yichen Qiao: College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China
Yaohua Hu: College of Optical, Mechanical and Electrical Engineering, Zhejiang A&F University, Hangzhou 311300, China
Zhouzhou Zheng: College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China
Zhanghao Qu: College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China
Chao Wang: College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China
Taifeng Guo: College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China
Juncai Hou: College of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China

Agriculture, 2022, vol. 12, issue 8, 1-22

Abstract: A trunk segmentation and a diameter measurement of red jujubes are important steps in harvesting red jujubes using vibration harvesting robots as the results directly affect the effectiveness of the harvesting. A trunk segmentation algorithm of red jujubes, based on improved Pyramid Scene Parsing Network (PSPNet), and a diameter measurement algorithm to realize the segmentation and diameter measurement of the trunk are proposed in this research. To this end, MobilenetV2 was selected as the backbone of PSPNet so that it could be adapted to embedded mobile applications. Meanwhile, the Convolutional Block Attention Module (CBAM) was embedded in the MobilenetV2 to enhance the feature extraction capability of the model. Furthermore, the Refinement Residual Blocks (RRBs) were introduced into the main branch and side branch of PSPNet to enhance the segmentation result. An algorithm to measure trunk diameter was proposed, which used the segmentation results to determine the trunk outline and the normal of the centerline. The Euclidean distance of the intersection point of the normal with the trunk profile was obtained and its average value was regarded as the final trunk diameter. Compared with the original PSPNet, the Intersection-over-Union (IoU) value, PA value and Fps of the improved model increased by 0.67%, 1.95% and 1.13, respectively, and the number of parameters was 5.00% of that of the original model. Compared with other segmentation networks, the improved model had fewer parameters and better segmentation results. Compared with the original network, the trunk diameter measurement algorithm proposed in this research reduced the average absolute error and the average relative error by 3.75 mm and 9.92%, respectively, and improved the average measurement accuracy by 9.92%. To sum up, the improved PSPNet jujube trunk segmentation algorithm and trunk diameter measurement algorithm can accurately segment and measure the diameter in the natural environment, which provides a theoretical basis and technical support for the clamping of jujube harvesting robots.

Keywords: red jujube tree; PSPNet; MobilenetV2; trunk segmentation; trunk diameter measurement (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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