Hologram Detection for Identity Document Authentication

Kada, Oumayma; Kurtz, Camille; van Kieu, Cuong; Vincent, Nicole

doi:10.1007/978-3-031-09037-0_29

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…In [3], a hologram detection approach for ID verification is proposed. The approach is based on the shape and the color analysis thanks to the pixel properties to extract the hologram for a given ID and decide the presence of the hologram in a given ID or not.…”

Section: Literature Reviewmentioning

confidence: 99%

Guilloche Detection for ID Authentication: A Dataset and Baselines

Al-Ghadi,

Ming,

Gomez-Krämer

et al. 2023

2023 IEEE 25th International Workshop on Multimedia Signal Processing (MMSP)

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In cases of digital enrolment via mobile and online services, identity documents (IDs) verification is critical to efficiently detect forgery and therefore build user trust in the digital world. In this paper, we propose a copy-move public dataset, called FMIDV (forged mobile ID video dataset) containing forged IDs with respect to guilloche patterns. Also, we propose two fraud detection models on guilloche patterns of IDs, which are based on contrastive and adversarial learning. In the sequel, each proposed model manages to read the entire ID and to recognize the guilloche pattern to check its similarity to the pattern of an authentic ID. The objective of the similarity check is to validate its authenticity or its rejection. Experiments are conducted on MIDV and FMIDV datasets to analyze and identify the most proper parameters to achieve higher authentication performance. The code and the dataset are available at https: //github.com/malghadi/CheckID.

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Section: Literature Reviewmentioning

confidence: 99%

Guilloche Detection for ID Authentication: A Dataset and Baselines

Al-Ghadi,

Ming,

Gomez-Krämer

et al. 2023

2023 IEEE 25th International Workshop on Multimedia Signal Processing (MMSP)

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“…Moreover, this study is limited when the structure and metadata are altered. Kada et al (2022) proposed a way to identify fake identity documents based on the reconstruction of holograms. Unlike ours, this proposal considers general holograms and therefore lacks precision.…”

Section: Comparison With Similar Workmentioning

confidence: 99%

Fals-Ism: A Graph Isomorphism Framework for Multi-Level Detection of Falsified PDF Documents

Nguinabe,

Tchakounte,

Tchakounte

et al. 2023

Journal of Computer Science

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Fake Portable Document Format (PDF) documents are disseminated in an incredible rhythm across social media. Negative incidences are obvious but effective solutions identifying falsified items in the PDF are still in need. Unlike determining malicious scripts inserted into the file, this research aims at identifying falsified objects from different layers of the document. Specifically, we introduce Fals-Ism, a novel approach to detect falsified PDF documents based on graph isomorphism. Each document is transformed and characterized by metadata, structure, and content required to build the corresponding graph such that any alteration is reflected on the complete graph. The graph is input to the isomorphism search algorithm namely; VF2 to verify if there is a similarity-based isomorphism. Experiments are conducted on (36) PDF documents considering metadata, structure, and content modifications. The results show that Fals-Ism (i) Is efficient to detect forgery at metadata level, structure, and content; (ii) Is robust and resistant to forgery attacks such as insertion, deletion, and modification of information; (iii) Does not require certain information about the PDF documents beforehand to perform the detection. Fals-Ism can detect different types of falsifications in PDF (version 1.7 or higher) with an accuracy of 90%. A comparison with similar work confirms that Fals-Ism could be a complementary tool for fake news detection.

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“…For example, modern systems are tasked with verifying the authenticity of the presented document. Among different approaches there are checking the presence of the holograms [1], the conformance of the used fonts to the government standards [2], etc.…”

Section: Introductionmentioning

confidence: 99%

Screen recapture detection based on color-texture analysis of document boundary regions

Kunina,

Sher,

Nikolaev

2023

Computer Optics

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This paper examines a presentation attack detection when a document recaptured from a screen is presented instead of the original document. We propose an algorithm based on analyzing a moiré pattern within document boundary regions as a distinctive feature of the recaptured image. It is assumed that the pattern overlapping the document boundaries is a recapture artifact, not a match between document and background textures. To detect such a pattern, we propose an algorithm that employs the result of the fast Hough transform of the document boundary regions with enhanced pattern contrast. The algorithm performance was measured for the open dataset DLC-2021, which contains images of mock documents as originals and their screen recaptures. The precision of the proposed solution was evaluated as 95.4 %, and the recall as 90.5 %.

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Hologram Detection for Identity Document Authentication

Cited by 6 publications

References 6 publications

Guilloche Detection for ID Authentication: A Dataset and Baselines

Guilloche Detection for ID Authentication: A Dataset and Baselines

Fals-Ism: A Graph Isomorphism Framework for Multi-Level Detection of Falsified PDF Documents

Screen recapture detection based on color-texture analysis of document boundary regions

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