The BioSecure Benchmarking Methodology for Biometric Performance Evaluation

Petrovska‐Delacrétaz, Dijana; Mayoue, Aurélien; Dorizzi, Bernadette

doi:10.1007/978-1-84800-292-0_2

Cited by 4 publications

(5 citation statements)

References 7 publications

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“…A well defined evaluation methodology allows measuring real progress achieved with new research methods as well as pinpointing unsolved problems [22]. For this reason, a technology evaluation protocol based on the definitions suggested by the ISO/IDE 19795 norm [16], [17] and the guidelines provided in [22] has been applied for evaluation purposes. This evaluation protocol is composed of three parts:…”

Section: A Methodologymentioning

confidence: 99%

Analysis of local binary patterns and uniform local binary patterns for palm vein biometric recognition

Aglio-Caballero

Rios-Sanchez

Ávila

et al. 2017

2017 International Carnahan Conference on Security Technology (ICCST)

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Palm vein recognition has emerged as a novelty highly invariant biometric technique that is difficult to forge due to their internal nature. In this work the texture descriptors Local Binary Patterns (LBP) and Uniform Local Binary Patterns (LBPU) are analyzed as feature extraction methods for biometric verification based on palm veins. Their performance and efficiency has been studied through a multivariate analysis including the impact of different wavelengths and the parameters of the texture descriptor number of neighboors and radio. CASIA Multi-Spectral Palmprint Image Database V1.0 has been used for the evaluation of the system.

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Section: A Methodologymentioning

confidence: 99%

Analysis of local binary patterns and uniform local binary patterns for palm vein biometric recognition

Aglio-Caballero

Rios-Sanchez

Ávila

et al. 2017

2017 International Carnahan Conference on Security Technology (ICCST)

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“…In [47], models of legal regulation pertaining to biometric identification and authentication utilizing facial recognition technology were delineated with the intention of formulating proposals to enhance the data security of individuals. The biometric technology system, its design, and its performance evaluation were defined in [48][49][50][51][52]. These devices ensure that employees are unable to sign in for one another, preventing employee time theft.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Aggregation Operators for Optimal Biometric-Based Attendance Device Selection Under Complex Fermatean Fuzzy Environment

Alghazzawi,

Razaq,

Komal

et al. 2024

IEEE Access

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Selecting the right Biometric-Based Attendance Device (BBAD) is pivotal for enhancing security, operations, and compliance in today's dynamic environment of identity authentication. Addressing the complexities arising from uncertainty and periodicity, the Complex Fermatean Fuzzy Set (CFFS) theory emerges as adept, encapsulating comprehensive problem specifications. This study introduces two innovative aggregation operators within the CFFS framework: the Complex Fermatean Fuzzy Dynamic Weighted Averaging (CFFDWA) and the Complex Fermatean Fuzzy Dynamic Weighted Geometric (CFFDWG) operators. Some important characteristics of the newly defined operators are established. The shortcomings in the existing score function are rectified along with the introduction of a novel enhanced score function under complex Fermatean fuzzy environment. Moreover, these operators contribute to a methodical framework for managing Multiple Attribute Decision Making (MADM) problems that involve complex Fermatean fuzzy information. The article exemplifies their application in resolving a MADM problem, determining the optimal model of BBAD. Finally, to validate the derived methodologies, a thorough comparison study is carried out, demonstrating the superiority of the presented operators against various existing operators.

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“…With the recent advances in acquisition systems, impressive face recognition systems have been deployed in real-world applications [1], [10], [14]- [16], [18], [21]. In particular, 3D sensors played an important role in making these advances thanks to the rich geometrical information and their robustness to multiple real-world constraints (e.g., pose variations, illumination changes, etc) [19].…”

Section: Introductionmentioning

confidence: 99%

Disentangled Face Identity Representations for Joint 3D Face Recognition and Neutralisation

Kacem

Cherenkova

Aouada

2022

2022 8th International Conference on Virtual Reality (ICVR)

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In this paper, we propose a new deep learning based approach for disentangling face identity representations from expressive 3D faces. Given a 3D face, our approach not only extracts a disentangled identity representation, but also generates a realistic 3D face with a neutral expression while predicting its identity. The proposed network consists of three components; (1) a Graph Convolutional Autoencoder (GCA) to encode the 3D faces into latent representations, (2) a Generative Adversarial Network (GAN) that translates the latent representations of expressive faces into those of neutral faces, (3) and an identity recognition sub-network taking advantage of the neutralized latent representations for 3D face recognition. The whole network is trained in an end-to-end manner. Experiments are conducted on three publicly available datasets showing the effectiveness of the proposed approach.

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The BioSecure Benchmarking Methodology for Biometric Performance Evaluation

Cited by 4 publications

References 7 publications

Analysis of local binary patterns and uniform local binary patterns for palm vein biometric recognition

Analysis of local binary patterns and uniform local binary patterns for palm vein biometric recognition

Dynamic Aggregation Operators for Optimal Biometric-Based Attendance Device Selection Under Complex Fermatean Fuzzy Environment

Disentangled Face Identity Representations for Joint 3D Face Recognition and Neutralisation

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