Back to Search Start Over

Dual imaging technique for a real-time inspection system of foreign object detection in fresh-cut vegetables

Authors :
Hary Kurniawan
Muhammad Akbar Andi Arief
Santosh Lohumi
Moon S. Kim
Insuck Baek
Byoung-Kwan Cho
Source :
Current Research in Food Science, Vol 9, Iss , Pp 100802- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Fresh-cut vegetables are a food product susceptible to contamination by foreign materials (FMs). To detect a range of potential FMs in fresh-cut vegetables, a dual imaging technique (fluorescence and color imaging) with a simple and effective image processing algorithm in a user-friendly software interface was developed for a real-time inspection system. The inspection system consisted of feeding and sensing units, including two cameras positioned in parallel, illuminations (white LED and UV light), and a conveyor unit. A camera equipped with a long-pass filter was used to collect fluorescence images. Another camera collected color images of fresh-cut vegetables and FMs. The feeding unit fed FMs mixed with fresh-cut vegetables onto a conveyor belt. Two cameras synchronized programmatically in the software interface simultaneously collected fluorescence and color image samples based on the region of interest as they moved through the conveyor belt. Using simple image processing algorithms, FMs could be detected and depicted in two different image windows. The results demonstrated that the dual imaging technique can effectively detect potential FMs in two types of fresh-cut vegetables (cabbage and green onion), as indicated by the combined fluorescence and color imaging accuracy. The test results showed that the real-time inspection system could detect FMs measuring 0.5 mm in fresh-cut vegetables. The results showed that the combined detection accuracy of FMs in the cabbage (95.77%) sample was superior to that of green onion samples (87.89%). Therefore, the inspection system was more effective at detecting FMs in cabbage samples than in green onion samples.

Details

Language :
English
ISSN :
26659271
Volume :
9
Issue :
100802-
Database :
Directory of Open Access Journals
Journal :
Current Research in Food Science
Publication Type :
Academic Journal
Accession number :
edsdoj.3b74622f23ef4871b620cd0af2c8fc09
Document Type :
article
Full Text :
https://doi.org/10.1016/j.crfs.2024.100802