Object Detection for Cargo Unloading System Based on Fuzzy C Means

With the recent increase in the utilization of logistics and courier services, it is time for research on logistics systems fused with the fourth industry sector. Algorithm studies related to object recognition have been actively conducted in convergence with the emerging artificial intelligence fie...

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Vydané v:Computers, materials & continua Ročník 71; číslo 2; s. 4167 - 4181
Hlavní autori: Hwang, Sunwoo, Park, Jaemin, Won, Jongun, Kwon, Yongjang, Kim, Youngmin
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Henderson Tech Science Press 2022
Predmet:
Algorithms
Artificial intelligence
Cargo handling
Convergence
Courier services
Frames per second
Logistics
Object recognition
ISSN:1546-2226, 1546-2218, 1546-2226
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Shrnutí:With the recent increase in the utilization of logistics and courier services, it is time for research on logistics systems fused with the fourth industry sector. Algorithm studies related to object recognition have been actively conducted in convergence with the emerging artificial intelligence field, but so far, algorithms suitable for automatic unloading devices that need to identify a number of unstructured cargoes require further development. In this study, the object recognition algorithm of the automatic loading device for cargo was selected as the subject of the study, and a cargo object recognition algorithm applicable to the automatic loading device is proposed to improve the amorphous cargo identification performance. The fuzzy convergence algorithm is an algorithm that applies Fuzzy C Means to existing algorithm forms that fuse YOLO(You Only Look Once) and Mask R-CNN(Regions with Convolutional Neuron Networks). Experiments conducted using the fuzzy convergence algorithm showed an average of 33 FPS(Frames Per Second) and a recognition rate of 95%. In addition, there were significant improvements in the range of actual box recognition. The results of this study can contribute to improving the performance of identifying amorphous cargoes in automatic loading devices.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:1546-2226
1546-2218
1546-2226
DOI:10.32604/cmc.2022.023295