Open AccessComputational workload in biometric identification systems: an overview
Author(s) -
Drozdowski Pawel,
Rathgeb Christian,
Busch Christoph
Publication year - 2019
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
eISSN - 2047-4946
pISSN - 2047-4938
DOI - 10.1049/iet-bmt.2019.0076
Subject(s) - workload , computer science , biometrics , identification (biology) , data science , field (mathematics) , software , key (lock) , perspective (graphical) , artificial intelligence , data mining , computer security , botany , pure mathematics , biology , programming language , operating system , mathematics
The computational workload is one of the key challenges in biometric identification systems. The naïve retrieval method based on an exhaustive search becomes impractical with the growth of the number of the enrolled data subjects. Consequently, in recent years, many methods with the aim of reducing or optimising the computational workload, and thereby speeding‐up the identification transactions, in biometric identification systems have been developed. In this article, taxonomy for conceptual categorisation of such methods is presented, followed by a comprehensive survey of the relevant academic publications, including computational workload reduction and software/hardware‐based acceleration. Lastly, the pertinent technical considerations and trade‐offs of the surveyed methods are discussed, along with an industry perspective, and open issues/challenges in the field.