Printing variability of copy detection patterns
Roman Chaban, Olga Taran, Joakim Tutt, Yury Belousov, Brian Pulfer,, Taras Holotyak, Slava Voloshynovskiy

TL;DR
This paper investigates the variability in copy detection pattern (CDP) printing using digital offset printers, highlighting factors affecting authentication performance and providing a new dataset for industrial applications.
Contribution
It offers a comprehensive analysis of how printer type, substrate, and resolution influence CDP variability, introducing a new dataset from industrial HP Indigo printers.
Findings
Printer and substrate choice significantly affect CDP similarity.
Digital offset printing introduces variability impacting authentication.
New dataset enables large-scale industrial evaluation.
Abstract
Copy detection pattern (CDP) is a novel solution for products' protection against counterfeiting, which gains its popularity in recent years. CDP attracts the anti-counterfeiting industry due to its numerous benefits in comparison to alternative protection techniques. Besides its attractiveness, there is an essential gap in the fundamental analysis of CDP authentication performance in large-scale industrial applications. It concerns variability of CDP parameters under different production conditions that include a type of printer, substrate, printing resolution, etc. Since digital off-set printing represents great flexibility in terms of product personalized in comparison with traditional off-set printing, it looks very interesting to address the above concerns for digital off-set printers that are used by several companies for the CDP protection of physical objects. In this paper, we…
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Taxonomy
TopicsIndustrial Vision Systems and Defect Detection · Digital Media Forensic Detection · Generative Adversarial Networks and Image Synthesis
