Copy Detection Pattern Optimization for Counterfeit Resistance
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Solution Overview
Problem
Existing copy detection patterns (CDPs) are ineffective in reliably distinguishing original prints from sophisticated copies, particularly when high-pass filters or deep learning techniques are used by counterfeiters to pre-compensate for printing and scanning variations, leading to difficulties in discerning originals from copies with high reliability.
Innovation Solution
A method for generating CDPs that involves simulating printing and copying processes using mathematical models to optimize CDP structures, employing iterative optimization processes to enhance the detection performance by maximizing the difference between original and copied images, utilizing Gaussian filters and unsharp filters to simulate printing and scanning conditions, and adjusting pixel modifications based on detection performance scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional CDPs are used, then the detection process is simple, but the ability to distinguish originals from sophisticated copies is insufficient
Solution Approach 1:
The patent applies preliminary action by pre-optimizing CDP structures through iterative simulation of printing and copying processes before actual deployment. The optimization process models the complete chain from original printing to copying to scanning, adjusting CDP parameters in advance to maximize detection performance against anticipated copy methods including sophisticated techniques like high-pass filtering and deep learning-based reconstruction.
Solution Approach 2:
The patent implements feedback through an iterative optimization loop that evaluates detection performance and uses the results to refine CDP structures. The system simulates the entire printing-copying-scanning chain, measures detection scores, and adjusts CDP parameters based on performance feedback, continuing iterations until optimal detection reliability is achieved.
2Reliability
If high-pass filters or deep learning techniques are used by counterfeiters, then copy quality improves, but the ability to detect copies deteriorates
Solution Approach 1:
The patent applies preliminary anti-action by designing CDP structures that are inherently resistant to sophisticated copying techniques before copies are even made. The optimization process specifically models and counteracts copy methods including high-pass filtering, deep learning-based image reconstruction, and other advanced techniques, embedding anti-copy properties directly into the CDP design to prevent successful forgery.
Solution Approach 2:
The patent uses parameter changes by adjusting CDP structural parameters through iterative optimization to maximize detection performance. The system varies parameters such as pattern density, contrast, and spatial distribution, evaluating each configuration's resistance to sophisticated copying methods, and converges on parameter sets that maintain high detectability even against advanced copy techniques.
3Reliability
If printing quality is reduced to optimize CDP detection, then copy detection performance improves, but the original document quality deteriorates
Solution Approach 1:
The patent applies parameter changes by optimizing CDP structural parameters rather than printing quality parameters. The system adjusts properties such as pattern geometry, pixel distribution, and contrast ratios to enhance detection performance while maintaining standard printing quality specifications, avoiding the need to degrade original print quality for security purposes.
Solution Approach 2:
The patent uses segmentation by separating the CDP into distinct structural components that can be independently optimized. The CDP is divided into pattern elements, transition zones, and reference regions, each optimized for specific detection functions while maintaining overall visual quality, allowing detection performance enhancement without compromising original document appearance.
Data Source
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AI summary
Method of generating a copy detection pattern (CDP), or a portion of a CDP, for printing on a substrate, comprising: - generating a plurality of digital files, each of an image comprising an at least partially random two dimensional (2D) distribution of dark and light pixels, and - applying an optimization process configured to increase a copy detection performance of a resultant digital file output by the method, said optimization process comprising a) comparing a copy detection performance of a first of said plurality of digital files, which constitutes a test digital file, with a copy detection performance of another of said plurality of digital files modified with respect to said test digital file, which constitutes a modified digital file, b) replacing the test digital file with said modified digital file, if the copy detection performance of said modified digital file is greater than the copy detection performance of the test digital file, in which case the modified digital file becomes the test digital file, and c) repeating steps a) and b) until a termination condition is met.