A method for brand image recognition for ordering payment in supermarket

This paper presents a product brand recognition method based on the YOLOv8 algorithm. The performance evaluation of the proposed method is conducted on two datasets consisting of GroZi-120 and GroZi-3.2K. The results show that the proposed method can achieve high accuracy. The precision and F1-score on the GroZi-120 and GroZi-3.2K datasets reach of {74.77%, 80%} and {99.86%, 100%}, respectively. The comparison with previous studies shows that the precision and F1-score obtained by the YOLOv8 method outperform some previous studies. Additionally, the effectiveness of the proposed method is also evaluated on a dataset of 6,170 images for twelve real products collected from supermarkets for use in order payment. The results show that the proposed method can be applied in single-order payment as well as multiple simultaneous orders with high accuracy in product recognition ranging from 94% to 98%. Therefore, the proposed method can be applied in order quick payment at supermarkets.