Printer identification from micro-metric scale printing

Nguyen, Quoc-Thông; Delignon, Yves; Chagas, Lionel; Septier, François

doi:10.1109/icassp.2014.6854803

Cited by 8 publications

(8 citation statements)

References 10 publications

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“…Metropolis-Hasting within Gibbs algorithm is conducted with 30000 MCMC iterations with 10000 as burn-in period. The realisation from the Spatial binary model [23] is illustrated to compare the improvement as well. Tab.…”

Section: Estimation Results From Printed Dotsmentioning

confidence: 99%

“…The shape of the profile contains the characteristics of the printed dots, which means the shape of the dots contains the identity of the source printer in some sense. The model in [22,23] introduced the parameters controlling the width of the droplets, the density of the black pixels and the average number of black pixels. However, the interaction with the surrounding pixels was not taken into account.…”

Section: Printed Dots At the Microscopic Scalementioning

confidence: 99%

“…The positive parameter λ characterises the interaction between pixels when the neighbour pixel is black, U i−1 = 0. With λ = 1, the probabilities ( 6) only depend on the relative position to the centres, P (U i | U i−1 ) = P (U i ), which is the approach proposed in [22,23]. In case λ < 1, the smaller λ leads to a higher chance of being black of current pixel U i , since P (U i = 0 | U i−1 = 0) is greater with smaller λ (see Eq.…”

Section: Spatial Interaction Binary Model With Markov Chain 105mentioning

confidence: 99%

“…The accurate and consistent model can help to create an authentic signature to improve the authentication procedure. The model proposed in our previous works [22,23] consists in a spatial distribution model that simulates the randomness of the shape of printed dots. The random shape is manipulated by the parameters in this probabilistic model.…”

Section: Introductionmentioning

confidence: 99%

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Probabilistic modelling of printed dots at the microscopic scale

Nguyen

Delignon

Septier

et al. 2018

Signal Processing: Image Communication

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Microscopic analysis of paper printing shows regularly spaced dots whose random shape depends on the printing technology, the configuration of the printer as well as the paper properties. The modelling and identification of paper and ink interactions are required for qualifying the printing quality, for controlling the printing process and for application in authentication as well. This paper proposes an approach to identify the authentic printer source using micro-tags consisting of microscopic printed dots embedded in the documents. These random shape features are modelled and extracted as a signature for a particular printer. In the paper, we propose a probabilistic model consisting of vector parameters using a spatial interaction binary model with inhomogeneous Markov chain. These parameters determine the location and describe the diverse micro random structures of microscopic printed dots. A Markov chain Monte Carlo (MCMC) algorithm is thus developed to approximate the Minimum Mean Squared Error estimator. The performance is assessed through numerical simulations. The real printed dots from the common printing technologies (conventional offset, waterless offset, inkjet, laser) are used to assess the effectiveness of the model.

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Section: Estimation Results From Printed Dotsmentioning

confidence: 99%

Section: Printed Dots At the Microscopic Scalementioning

confidence: 99%

Section: Spatial Interaction Binary Model With Markov Chain 105mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Probabilistic modelling of printed dots at the microscopic scale

Nguyen

Delignon

Septier

et al. 2018

Signal Processing: Image Communication

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“…Each printed and scanned set of dots (a dot being a binary element) suffers from a stochastic non-invertible noise which makes the reproduction of the original graphical code impossible [12,14,10,9] (see in Fig. 1).…”

Section: Studied Problemmentioning

confidence: 99%

Image model and printed document authentication: A theoretical analysis

Hoang

Sawaya

Bas

2014

2014 IEEE International Conference on Image Processing (ICIP)

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This paper combines the principles of statistical estimation and hypothesis testing to analyze the impact of parameter estimation on an authentication system based on graphical codes. The studied authentication system uses the fact that a code, once printed, undergoes a stochastic and non invertible alteration. A statistical test applies a likelihood ratio between the model of the authentic printed and scanned image and the model of the reproduced one, with the particularity here that the later model is unknown. The proposed solution consists in using an optimal estimation of the image model coming from observed fake codes in order to perform the likelihood test. Using a second order expansion, we derive a linear relation between the quadratic error of the estimated parameters and the probability of type II error. We are then able to formulate analytically and practically the error spread region of the Receiver Operating Characteristic (ROC) curves, and to compute the average authentication performance when the receiver has to estimate the opponent print and scan channel.

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Auto Machine Learning-Based Approach for Source Printer Identification

Dang

Nguyen

et al. 2022

Recent Challenges in Intelligent Information and Database Systems

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Printer identification from micro-metric scale printing

Cited by 8 publications

References 10 publications

Probabilistic modelling of printed dots at the microscopic scale

Probabilistic modelling of printed dots at the microscopic scale

Image model and printed document authentication: A theoretical analysis

Auto Machine Learning-Based Approach for Source Printer Identification

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