Intelligent 3D Potato Cutting Simulation System Based on Multi-View Images and Point Cloud Fusion

Ruize Xu, Chen Chen (), Fanyi Liu and Shouyong Xie
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Ruize Xu: College of Engineering and Technology, Southwest University, Chongqing 400715, China
Chen Chen: College of Engineering and Technology, Southwest University, Chongqing 400715, China
Fanyi Liu: College of Engineering and Technology, Southwest University, Chongqing 400715, China
Shouyong Xie: College of Engineering and Technology, Southwest University, Chongqing 400715, China

Agriculture, 2025, vol. 15, issue 19, 1-21

Abstract: The quality of seed pieces is crucial for potato planting. Each seed piece should contain viable potato eyes and maintain a uniform size for mechanized planting. However, existing intelligent methods are limited by a single view, making it difficult to satisfy both requirements simultaneously. To address this problem, we present an intelligent 3D potato cutting simulation system. A sparse 3D point cloud of the potato is reconstructed from multi-perspective images, which are acquired with a single-camera rotating platform. Subsequently, the 2D positions of potato eyes in each image are detected using deep learning, from which their 3D positions are mapped via back-projection and a clustering algorithm. Finally, the cutting paths are optimized by a Bayesian optimizer, which incorporates both the potato’s volume and the locations of its eyes, and generates cutting schemes suitable for different potato size categories. Experimental results showed that the system achieved a mean absolute percentage error of 2.16% (95% CI: 1.60–2.73%) for potato volume estimation, a potato eye detection precision of 98%, and a recall of 94%. The optimized cutting plans showed a volume coefficient of variation below 0.10 and avoided damage to the detected potato eyes, producing seed pieces that each contained potato eyes. This work demonstrates that the system can effectively utilize the detected potato eye information to obtain seed pieces containing potato eyes and having uniform size. The proposed system provides a feasible pathway for high-precision automated seed potato cutting.

Keywords: potato eye; rotating platform; point cloud; detection and mapping; potato cutting (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: 2025
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