Presentation
7 June 2024 Design and preliminary evaluation of a machine vision-based automated sweet potato sorting system
Jiajun Xu, Yuzhen Lu
Author Affiliations +
Abstract
Ensuring the supply of high-quality sweet potatoes to consumers requires efficient sorting of harvested produce, a task made complex by various factors. This paper introduces a prototype of an innovative automated sweet potato sorting system and its preliminary evaluation. The system integrates a machine vision-based grading module and a pneumatic actuation cylinder-based sorting mechanism. The vision system captures multiple views of rotating sweet potatoes on a conveyor, utilizing a deep learning algorithm to track and grade them based on size, shape, and surface defects. The integrated sorting mechanism, activated by a computer-controlled cylinder, automatically segregates the sweet potatoes into designated areas based on quality grades. Future experimentation aims to quantify the efficacy of the integrated system, promising a potentially valuable tool for sweet potato packers.
Conference Presentation
© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiajun Xu and Yuzhen Lu "Design and preliminary evaluation of a machine vision-based automated sweet potato sorting system", Proc. SPIE PC13060, Sensing for Agriculture and Food Quality and Safety XVI, PC1306009 (7 June 2024); https://doi.org/10.1117/12.3013972
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KEYWORDS
Design and modelling

Algorithm development

Image quality

Imaging systems

Computing systems

Detection and tracking algorithms

Machine vision

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