# Copy Detection Pattern
> Source: https://docs.barcoder.ai/docs/standards/copy-detection-pattern
> research date 2026-06-04 · extracted at 2026-10-03
> Publisher: Barcoder — encyclopedia of QR, barcode and payment-code standards
Specifications:
- [Copy detection pattern — Wikipedia](https://en.wikipedia.org/wiki/Copy_detection_pattern)
- [Digital authentication with copy-detection patterns — Picard, SPIE 2004](https://www.researchgate.net/publication/253088312_Digital_authentication_with_copy-detection_patterns)
## Overview
A **Copy Detection Pattern (CDP)** is a small **random (maximum-entropy) digital image** printed on a document, label, or product so that **copies can be told apart from originals** [1][1]. It works on an **information-loss principle**: each print-and-scan cycle degrades fine detail, and because making a counterfeit requires an *extra* scan-and-print pass, a copied CDP carries measurably less information than a genuine first-generation print [1][1]. Authentication is performed by scanning the CDP with an image scanner or an ordinary **smartphone camera** and measuring how much detail survives [1][1]. CDPs are frequently embedded inside or alongside a [QR Code](https://docs.barcoder.ai/docs/standards/qr-code) so that a single scan both reads the product identifier and authenticates the print [1][1].
## History
Copy Detection Patterns were introduced by **Justin Picard around 2004**, notably in the paper **"Digital authentication with copy-detection patterns"** (SPIE, 2004) [1][1]. Earlier related patent work on visible authentication patterns for printed documents (J. Picard and J. Zhao) dates to about **2002** [2][2]. The underlying insight — that the print-scan channel is a lossy, hard-to-invert process and that copying compounds that loss — became the foundation for a class of anti-counterfeiting graphics [1][1].
CDPs were deployed early in security documents, including **identity-style credentials and event badges** (e.g. 2006 FIFA World Cup badges), and later moved into **pharmaceutical and product packaging** [1][1]. The technology was commercialised most prominently by **Scantrust**, which prints a CDP inside a secure QR code so brands can verify authenticity with a phone [3][3], [1][1].
Security research has continued to probe CDPs: from 2019 onward, studies (Taran, Yadav, and others) examined **machine-learning "clonability" attacks** that attempt to reconstruct the digital CDP from a scan and reprint a higher-fidelity copy, prompting work on stronger detection metrics and provable guarantees [1][1], [4][4].
## Technical specification
A CDP is engineered to be **hard to reproduce and easy to verify** [1][1]:
- **Maximum-entropy image** — a small random or pseudo-random pattern (e.g. a dense field of black/white pixels) designed to pack the maximum amount of fine detail, so that any loss of detail is conspicuous [1][1].
- **Information-loss detection** — every print or scan loses information about the original digital image; a counterfeit needs an additional capture-and-reprint cycle, so it is **further** from the digital original and measurably lower in information content [1][1].
- **Verification metric** — the detector compares the scanned pattern against the known digital reference (or a derived statistic) and computes a similarity/correlation score; a genuine first-generation print scores high, a copy scores low [1][1].
- **Public algorithm, secret reference** — the detection algorithm can be public; security rests on keeping the **digital CDP itself (or its generation key)** secret, since an attacker who lacks the high-resolution digital original must work from a degraded scan [1][1].
- **Smartphone-readable** — modern CDPs are tuned so a consumer-grade phone camera can capture enough detail to authenticate, not just a flatbed scanner [1][1], [3][3].
- **QR integration** — high-entropy secure graphics are commonly embedded **within a standard QR code** (e.g. inside the finder/data zone), so one scan yields both the identifier and the authenticity verdict [1][1], [3][3].
## Use cases
- **Brand protection / anti-counterfeit** — the core use: proving a label or package is a genuine first-generation print rather than a scanned-and-reprinted copy [1][1], [3][3].
- **Pharmaceutical packaging** — authenticating medicine packs against counterfeits [1][1].
- **Secure documents and credentials** — identity documents and access badges (e.g. 2006 FIFA World Cup badges) [1][1].
- **Product authentication via IoT / track-and-trace** — combined with serialized QR for both identity and authenticity in supply-chain systems [1][1], [3][3].
## Implementations
CDPs are mostly delivered through **commercial platforms**, with academic datasets available [1][1], [3][3]:
- **Scantrust** — the leading commercial provider; prints a CDP inside a **secure QR code** and authenticates via a mobile app/SDK and cloud verification [3][3].
- **Academic datasets / tooling** — research groups (and Scantrust-shared datasets) publish CDP image sets for studying detection and clonability, but these are research artifacts rather than a turnkey open standard [1][1], [4][4].
State honestly: there is no single open CDP standard; generation, the secret digital reference, and the verification service are typically held by the vendor. The general *principle* is public, but production-grade CDP authentication is a proprietary/managed offering.
## Comparison
**vs. [QR Code](https://docs.barcoder.ai/docs/standards/qr-code) alone** — a plain QR carries an identifier but is trivially photocopied; the symbol scans identically whether genuine or copied. A CDP embedded in or beside the QR adds a *copy-resistance* layer the QR lacks, so the same scan can both identify and authenticate [1][1].
**vs. holograms** — holograms are overt, visually striking deterrents but are themselves widely counterfeited and require human inspection. A CDP is a flat printed graphic verified automatically by a camera + algorithm, giving an objective genuine/copy decision rather than relying on a person to judge a hologram's quality [3][3].
**vs. serialization (unique serial numbers / track-and-trace)** — serialization proves an item's *identity* and detects duplicates only if the back-end sees the same serial twice; it does not, by itself, prove the *physical print* is original. A CDP complements serialization by detecting that a given printed instance is a scanned copy even if the serial looks valid [1][1], [3][3].
## Fun facts
The security model is unusual: the **detection algorithm can be completely public** — secrecy lives only in the high-resolution **digital original** of the random pattern. A counterfeiter who can only photograph or scan a genuine label is already working from a degraded copy and cannot recover the full-detail digital source, which is exactly what the detector checks for [1][1].
CDPs were used on **2006 FIFA World Cup badges**, an early high-profile deployment of the print-and-scan information-loss idea in a real-world security-credential setting [1][1].
## Status
**Active and commercially deployed**, with an ongoing security arms race [1][1], [3][3]. CDPs are in production use for brand protection, pharma, and secure documents, most visibly through Scantrust's secure-QR product [3][3]. Academic work continues on **machine-learning attacks** that try to clone CDPs and on stronger, provable detection guarantees, so the technology is evolving rather than static [1][1], [4][4].
## Sources
[1]: https://en.wikipedia.org/wiki/Copy_detection_pattern
[2]: https://www.academia.edu/43083433/Digital_authentication_with_copy_detection_patterns
[3]: https://blog.scantrust.com/anti-counterfeiting-in-2021-from-blockchain-and-holograms-to-copy-detection-patterns/
[4]: https://arxiv.org/pdf/2409.17649
[5]: https://dl.acm.org/doi/10.1145/3469096.3474924
1. [Copy detection pattern — Wikipedia][1]
2. [Digital authentication with copy-detection patterns — Picard, SPIE 2004][2]
3. [Anti-counterfeiting in 2021: QR codes and copy detection patterns — Scantrust, 2021][3]
4. [Provable Performance Guarantees of Copy Detection Patterns — Tutt et al., arXiv 2024][4]
5. [Counterfeit detection with QR codes — ACM DocEng 2021][5]
## Deployments
_No country reports mention this standard by name._
## Regions / aggregations not mapped to a single country
- Universal