Multispectral Embedding of Security Codes in Nature Inspired Textile Designs

This paper explores a novel approach to integrating machine-readable security elements into textile product design by embedding OCR-B codes within floral graphic patterns intended for cotton tote bags. The concept relies on the aesthetic use of dark leaf motifs, which naturally provide regions of high absorption suitable for concealing information in the visible spectrum. The embedded OCR-B code remains visually imperceptible to the human observer, while becoming detectable under near-infrared (NIR) imaging due to the differential spectral response of the code and surrounding texture. Using multispectral image acquisition, we evaluate the visibility, contrast, and machine readability of the hidden code across selected wavelengths. The study demonstrates that natural pattern structures can serve as an effective substrate for embedding security identifiers without compromising the artwork’s visual integrity. This concept highlights an emerging direction in design-driven protection of textile products, where aesthetic motifs inspired by nature can simultaneously function as carriers of covert authentication data.