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Centrality bias measure for high density QR code module recognition., , , , , and . Sig. Proc.: Image Comm., (2016)Copy Sensitive Graphical Code Quality Improvement Using a Super-Resolution Technique., , , , and . ICIP, page 3808-3812. IEEE, (2018)Rich QR Code for Multimedia Management Applications., , , , , and . ICIAP (2), volume 9280 of Lecture Notes in Computer Science, page 383-393. Springer, (2015)Generation and analysis of graphical codes using textured patterns for printed document authentication. (Génération et analyse des codes graphiques utilisant des motifs texturés pour l'authentification de documents imprimés).. University of Montpellier, France, (2015)Authentication of Medicine Blister Foils: Characterization of the Rotogravure Printing Process., , and . VISIGRAPP (4: VISAPP), page 577-583. SciTePress, (2019)Experimental study of Print-and-Scan impact as random process., , , and . Media Watermarking, Security, and Forensics, page 1-11. Ingenta, (2016)Estimation of Copy-sensitive Codes Using a Neural Approach., , , and . IH&MMSec, page 77-82. ACM, (2019)Authentication of rotogravure print-outs using a regular test pattern., , and . J. Inf. Secur. Appl., (2022)Improving the module recognition rate of high density QR codes (Version 40) by using centrality bias., , , , , and . IPTA, page 155-160. IEEE, (2014)Fighting against forged documents by using textured image., , , , , and . EUSIPCO, page 790-794. IEEE, (2014)