Liong, Sze-Teng and Wu, Yi-Liang and Liong, Gen-Bing and Gan, Y. S. (2023) Moving towards agriculture 4.0: An AI-AOI carrot inspection system with accurate geometric properties. Journal of Food Engineering, 357. ISSN 0260-8774, DOI https://doi.org/10.1016/j.jfoodeng.2023.111632.
Full text not available from this repository.Abstract
This paper aims to give a new impetus to the development of automated inspection systems in the food industry, specifically by examining the geometric properties of agricultural products using computer vision technology. The proposed framework is designed to replicate the conditions of a manufacturing industry, in which a roller conveyor transports randomly arranged products. Despite this challenging environment, the proposed framework is able to accurately identify the geometric properties of each product, including width, length, area, and volume. Succinctly, a suite of novel image processing is introduced such as the techniques of object detection, semantic segmentation, and object tracking. Particularly, the use of a depth sensor allows for the enhancement of image information by providing a corresponding depth matrix for each RGB image. The agricultural product experimented with herein is the carrot, which has a range of sizes/ shapes and is widely produced in many countries. Through extensive experimentation and analysis, the proposed framework demonstrated high accuracy in estimating the length, width, and volume of carrots, with average errors of 1.85%, 2.51%, and 5.35% when tested on a sample of 20 carrots and a total of 3120 images. This work offers promising potential for improving food production efficiency in the manufacturing industry and should inspire further research in this area.
| Item Type: | Article |
|---|---|
| Funders: | Ministry of Science and Technology (MOST) , Taiwan, ROC [Grant No: MOST 111-2221-E-035-059-MY3] |
| Uncontrolled Keywords: | Carrot; Inspection; Volume; Deep learning; Industry 4; 0 |
| Subjects: | T Technology > T Technology (General) T Technology > TP Chemical technology |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Ms. Juhaida Abd Rahim |
| Date Deposited: | 10 Nov 2025 02:45 |
| Last Modified: | 10 Nov 2025 02:45 |
| URI: | http://eprints.um.edu.my/id/eprint/49718 |
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