2026-06-30T05:21:55Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/112342026-01-17T01:05:32Zcom_10259_5377com_10259_5086com_10259_2604col_10259_5378

Ahmadi, Kavan Latorre Carmona, Pedro Javidi, Bahram Carnicer, Artur 2026-01-16T12:38:23Z 2026-01-16T12:38:23Z 2020-04 https://hdl.handle.net/10259/11234 10.1109/JPHOT.2020.2987484 1943-0655 1943-0647 Document signature is a powerful technique used to determine whether a message is tampered or valid. Recently, this concept was extended to optical codes: we demonstrated that the combined use of optical techniques and machine learning algorithms might be able to distinguish among different classes of samples. In the present work, we produce nano particle encoded optical codes with predetermined designs synthesized with a 3D printer. We used conventional polylactic acid filament filled with metallic powder to include the effect of nano-encoding for unique polarimetric signatures. We investigated an interesting real-world scenario, that is, we demonstrate how a single class of codes is distinguished among a group of samples to be rejected. This is a difficult unbalanced problem since the number of polarimetric signatures that characterize the true class is small compared to the complete dataset. Each sample is characterized by analyzing the polarization state of the emerging light. Using the one class-support vector machine algorithm we found high accuracy figures in the recognition of the true class codes. To the best of our knowledge, this is the first report on implementing optical codes with nano particle encoded materials using 3D printing technology. Funding Agency: 10.13039/100000181-Air Force Office of Scientific Research 10.13039/501100003329-Ministerio de Economía y Competitividad (Grant Number: FIS2016-75147-C3-1-P) application/pdf eng Institute of Electrical and Electronics Engineers IEEE Photonics Journal. 2020, V. 12, n. 3, p. 6500810 https://doi.org/10.1109/JPHOT.2020.2987484 Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Optical authentication and security Optical polarization Speckle noise Óptica Aprendizaje automático Impresión 3D Optics Machine learning Three-dimensional printing Polarimetric Identification of 3D-Printed Nano Particle Encoded Optical Codes info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion IEEE Photonics Journal 12 3 6500810