Authentication of Copy Detection Patterns via Cross-Camera Dual-Synthetic Referencing

2026-05-29

AI Summary

This work addresses the insufficient robustness of copy detection pattern (CDP) authentication caused by printer stochasticity and camera distortion. To this end, we propose a registration-based cross-camera dual-synthesis reference framework that, for the first time, jointly models printing variability and camera distortion. By fusing a digital template with a registered image, the method leverages deep learning to generate high-quality reference images tailored to the verification camera. Integrating cross-camera domain image translation, information-theoretic analysis, and mobile-oriented optimization, the proposed framework significantly improves authentication accuracy for small-region CDPs on heterogeneous low-end devices and effectively resists machine learning–based replication attacks.

Abstract

Copy Detection Patterns (CDPs) are structures printed on physical objects to enable cost-effective authentication. Verification is achieved by comparing a captured image with the digital template from which the CDP was printed. In practice, printer stochasticity and camera distortions hinder this comparison, limiting robustness against counterfeiting. Prior work addressed camera effects by synthesising reference images in the verification camera domain, but it ignored printing variability. We introduce an enrolment-based cross-camera dual-synthetic referencing framework. Each printed CDP is first captured by a controlled enrolment camera, and a deep-learning-based translator jointly exploits the digital template and the enrolled capture to generate a high-quality reference for the verification image. We provide an information-theoretic justification showing that the dual reference is more informative than template-based references. Experiments on heterogeneous mobile cameras demonstrate improved authentication performance, robustness to machine-learning-based copy attacks, and reliable verification from small CDP regions and on low-end devices.

Problem

• Copy Detection Patterns
• authentication
• printer stochasticity
• camera distortions
• counterfeiting

Innovation

• Copy Detection Patterns
• cross-camera synthesis
• dual-synthetic referencing
• deep-learning-based translation
• authentication robustness