3D Positioning Method for Pineapple Eyes Based on Multiangle Image Stereo-Matching

Anwen Liu, Yang Xiang (), Yajun Li, Zhengfang Hu, Xiufeng Dai, Xiangming Lei and Zhenhui Tang
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Anwen Liu: College of Mechanical and Electrical Engineering, Hunan Agriculture University, Changsha 410128, China
Yang Xiang: College of Mechanical and Electrical Engineering, Hunan Agriculture University, Changsha 410128, China
Yajun Li: College of Mechanical and Electrical Engineering, Hunan Agriculture University, Changsha 410128, China
Zhengfang Hu: College of Mechanical and Electrical Engineering, Hunan Agriculture University, Changsha 410128, China
Xiufeng Dai: College of Mechanical and Electrical Engineering, Hunan Agriculture University, Changsha 410128, China
Xiangming Lei: College of Mechanical and Electrical Engineering, Hunan Agriculture University, Changsha 410128, China
Zhenhui Tang: College of Mechanical and Electrical Engineering, Hunan Agriculture University, Changsha 410128, China

Agriculture, 2022, vol. 12, issue 12, 1-17

Abstract: Currently, pineapple processing is a primarily manual task, with high labor costs and low operational efficiency. The ability to precisely detect and locate pineapple eyes is critical to achieving automated pineapple eye removal. In this paper, machine vision and automatic control technology are used to build a pineapple eye recognition and positioning test platform, using the YOLOv5l target detection algorithm to quickly identify pineapple eye images. A 3D localization algorithm based on multiangle image matching is used to obtain the 3D position information of pineapple eyes, and the CNC precision motion system is used to pierce the probe into each pineapple eye to verify the effect of the recognition and positioning algorithm. The recognition experimental results demonstrate that the mAP reached 98%, and the average time required to detect one pineapple eye image was 0.015 s. According to the probe test results, the average deviation between the actual center of the pineapple eye and the penetration position of the probe was 1.01 mm, the maximum was 2.17 mm, and the root mean square value was 1.09 mm, which meets the positioning accuracy requirements in actual pineapple eye-removal operations.

Keywords: pineapple eye; three-dimensional; YOLOv5; stereo-matching (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 references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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