Performance of Multimodal Biometric Systems at Score Level Fusion

2015 ◽  
pp. 903-913 ◽  
Author(s):  
Harbi AlMahafzah ◽  
Ma’en Zaid AlRawashdeh
Keyword(s):  
Score Level Fusion ◽  
Biometric Systems ◽  
Level Fusion ◽  
Multimodal Biometric Systems

Performance evaluation of score level fusion in multimodal biometric systems

2010 ◽  
Vol 43 (5) ◽  
pp. 1789-1800 ◽  
Author(s):  
Mingxing He ◽  
Shi-Jinn Horng ◽  
Pingzhi Fan ◽  
Ray-Shine Run ◽  
Rong-Jian Chen ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Score Level Fusion ◽  
Biometric Systems ◽  
Level Fusion ◽  
Multimodal Biometric Systems

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

2019 ◽  
Vol 9 (1) ◽  
pp. 5290-5305
Keyword(s):  
Skin Color ◽  
Affective Computing ◽  
Biometric Data ◽  
Score Level Fusion ◽  
New Concepts ◽  
Biometric Systems ◽  
The Face ◽  
Ancillary Information ◽  
Biometric Information ◽  
Level Fusion

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.

Score-Based Fusion in Multi-Unit Biometric Recognition System

2011 ◽  
Vol 48-49 ◽  
pp. 1010-1013 ◽  
Author(s):  
Yong Li ◽  
Jian Ping Yin ◽  
En Zhu
Keyword(s):  
Recognition System ◽  
Fingerprint Recognition ◽  
Fusion Model ◽  
Biometric Recognition ◽  
Score Level Fusion ◽  
Fusion Rules ◽  
Biometric Systems ◽  
Score Fusion ◽  
Multiple Units ◽  
Level Fusion

The performance of biometric systems can be improved by combining multiple units through score level fusion. In this paper, different fusion rules based on match scores are comparatively studied for multi-unit fingerprint recognition. A novel fusion model for multi-unit system is presented first. Based on this model, we analyze the five common score fusion rules: sum, max, min, median and product. Further, we propose a new method: square. Note that the performance of these strategies can complement each other, we introduce the mixed rule: square-sum. We prove that square-sum rule outperforms square and sum rules. The experimental results show good performance of the proposed methods.

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