A Framework For Combination Of Sequential Architecture And Soft Biometrics In Multibiometric Scores Fusion

Sobabe, Abdou-Aziz; Djara, Tahirou; Vianou, Antoine

doi:10.1109/biosmart.2019.8734247

Cited by 3 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another field of investigation will be the design of a system capable of circumventing the limitations related to the influence of external factors such as lighting conditions in order to improve skin detection. Once the skin color authentication system is in place, the next step in this work will be the implementation of the face and contactless fingerprint before combining the three modalities using the adapted sequential fusion algorithm proposed by Sobabe et al (2019) in 2019. It will thus be possible to assess the level of contribution of skin color in improving the performance of the face and contactless fingerprint authentication system.…”

Section: Discussionmentioning

confidence: 99%

Soft Biometrics Authentication

Sobabe

Djara

Blochaou

et al. 2022

Journal of Information Technology Research

Self Cite

View full text Add to dashboard Cite

This manuscript presents the design of a new approach of human skin color authentication. Skin color is one of the most popular soft biometric modalities. Since a soft biometric modality alone cannot reliably authenticate an individual, this new system is designed to combine skin color results with other pure biometric modalities to increase recognition performance. In the classification process, we first perform facial skin detection by segmentation using the thresholding method in the HSV color space. Then, the K-means algorithm of the clustering method is used to determine the dominant colors on the skin pixels in the RGB model. Variations according to the R, G and B components are recorded in a reference model to enable an individual’s identity to be predicted on the basis of 30 clusters. Experimental results are promising and give a false acceptance rate (FAR) of 29.47% and a false rejection rate (FRR) of 70.53%.

show abstract

Section: Discussionmentioning

confidence: 99%

Soft Biometrics Authentication

Sobabe

Djara

Blochaou

et al. 2022

Journal of Information Technology Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…Sobabe et al [39] presented a new framework for score-level fusion. The principle developed is presented with more details.…”

Section: Extension Of the Adapted Sequential Fusion Approachmentioning

confidence: 99%

“…10). In [39], authors have considered hypothesis and and the two species errors and are computed as follows:…”

Section: Extension Of the Adapted Sequential Fusion Approachmentioning

confidence: 99%

See 1 more Smart Citation

Incorporating Metadata in Multibiometric Score-Level Fusion: an Optimized Architecture

2019

IJITEE

View full text Add to dashboard Cite

 This manuscript presents a review on multibiometrics using ancillary information, in addition to the main biometric data. The proposed method involves taking non-biometric information into account in the biometric recognition process to improve system performance. This ancillary information can come from the user (the skin color), the sensor (the camera flash, etc.) or the operating environment (the ambient noise). Moreover, the paper presents an extension of the adapted sequential fusion framework through a complete description of the method used for the score-level fusion architecture presented at the IEEE BioSmart 2019 Proceedings. An optimized score-level fusion architecture is proposed. An introduction of new concepts (namely "biochemical features" and "multi origin biometrics") is also made. The first part of the paper highlights the various biometric systems developed up to now, their architecture and characteristics. Then, the manuscript discussed about multibiometrics through its advantages, its diversity and the different levels of fusion. An attention was paid to the score-level fusion before addressing the consideration of ancillary information (or metadata) in multibiometrics. Dealing with the affective computing, the influence of emotion on the performance of biometric systems is explored. Finally, a typology of biometric adaptation is discussed.As an application, the proposed methodology will implement a multibiometric system using the face, contactless fingerprint and skin color. A single sensor will be used (a camera) with two shots while the skin color will be extracted automatically from the facial image.

show abstract