We present interiqr, a method that utilizes the infill parameter in the 3D printing process to embed information inside the food that is difficult to recognize with the human eye. Our key idea is to utilize the air space or secondary materials to generate a specific pattern inside the food without changing the model geometry. As a result, our method exploits the patterns that appear as hidden edible tags to store the data and simultaneously adds them to a 3D printing pipeline. Our contribution also includes the framework that connects the user with a data-embedding interface through the food 3D printing process, and the decoding system allows the user to decode the information inside the 3D printed food through backlight illumination and a simple image processing technique. Finally, we evaluate the usability of our method under different settings and demonstrate our method through the example application scenarios.
Yamamoto Miyatake, Parinya Punpongsanon, Daisuke Iwai, and Kosuke Sato. interiqr: Unobtrusive Edible Tags using Food 3D Printing. In Proceedings of the ACM Symposium on User Interface Software and Technology (UIST) 2022, pp. 1-11. Bend, USA, October 2022. Acceptance Rate: 26.3%