The decline in the working population due to falling birth rates and an aging population is a pressing issue. Convenience stores, in particular, have become part of the social infrastructure; however, their operations are diverse, and labor shortages are becoming increasingly acute. Therefore, automating display operations is necessary to reduce workloads. However, existing methods pose several challenges, such as loss of visual appeal and the high costs associated with developing deep learning models. This study focuses on information-hiding technology and proposes an invisible QR code that embeds information into product packaging in an imperceptible manner. Because it is invisible, it does not detract from the package’s appearance and can be detected by image processing, thereby eliminating computational learning costs. In this study, we evaluated the proposed method through experiments on image quality degradation, recognition accuracy, and the position and orientation estimation accuracy of the invisible QR codes.

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