Projects
VISUAL-ID – Unique Visual Identities in Graphics, Images and Faces
The Visual-ID project emerge in the context of the partnership between the Imprensa Nacional-Casa da...
ICAO compliant Dataset
(ENGLISH VERSION) This ICAO Compliant Dataset project is part of the FACING2 project. The FACI...
FACING2 – Face Image Understanding
The FACING-2 project aims to study and develop methods that allow exploring facial biometrics of hum...
TruIM – Trust Image Understanding
TruIm Project aims at developing technologies to authenticate objects in certified images, encoded u...
Publications
Noise simulation for the improvement of training deep neural network for printer-proof steganography
In the modern era, images have emerged as powerful tools for concealing information, giving rise to innovative methods like watermarking and steganography, with end-to-end steganography solutions emerging in recent years. However, these new methods presented some issues regarding the hidden message and the decreased quality of images. This paper investigates the efficacy of noise simulation methods and deep learning methods to improve the resistance of steganography to printing. The research develops an end-to-end printer-proof steganography solution, with a particular focus on the development of a noise simulation module capable of overcoming distortions caused by the transmission of the print-scan medium. Through the development, several approaches are employed, from combining several sources of noise present in the physical environment during printing and capture by image sensors to the introduction of data augmentation techniques and self- supervised learning to improve and stabilize the resistance of the network. Through rigorous experimentation, a significant increase in the robustness of the network was obtained by adding noise combinations while maintaining the performance of the network. Thereby, these experiments conclusively demonstrated that noise simulation can provide a robust and efficient method to improve printer-proof steganography.
- Date: 24/02/2024
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- Featured In: 13th International Conference on Pattern Recognition Application and Methods (ICPRAM). Rome, Italy
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- Publication Type: Conference Papers
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- Author(s): Telmo Cunha, Luiz Schirmer, João Marcos and Nuno Gonçalves
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- DOI: 10.5220/0012272300003654
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Automatic Validation of ICAO Compliance Regarding Head Coverings: (…) Religious Circumstances
This paper contributes with a dataset and an algorithm that automatically veri es the compliance with the ICAO requirements related to the use of head coverings on facial images used on machine-readable travel documents. All the methods found in the literature ignore that some coverings might be accepted because of religious or cultural reasons, and basically only look for the presence of hats/caps. Our approach speci cally includes the religious cases and distinguishes the head coverings that might be considered compliant. We built a dataset composed by facial images of 500 identities to accommodate these type of accessories. That data was used to ne-tune and train a classi cation model based on the YOLOv8 framework and we achieved state of the art results with an accuracy of 99.1% and EER of 5.7%.
- Date: 22/09/2023
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- Featured In: 2023 International Conference of the Biometrics Special Interest Group (BIOSIG)
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- Publication Type: Conference Papers
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- Author(s): Carla Guerra, João Marcos, Nuno Gonçalves
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- DOI: 10.1109/BIOSIG58226.2023.10345995
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