  The performance of a biometric system that relies on a single biometric
modality (e.g., fingerprints only) is often stymied by various factors such as
poor data quality or limited scalability. Multibiometric systems utilize the
principle of fusion to combine information from multiple sources in order to
improve recognition accuracy whilst addressing some of the limitations of
single-biometric systems. The past two decades have witnessed the development
of a large number of biometric fusion schemes. This paper presents an overview
of biometric fusion with specific focus on three questions: what to fuse, when
to fuse, and how to fuse. A comprehensive review of techniques incorporating
ancillary information in the biometric recognition pipeline is also presented.
In this regard, the following topics are discussed: (i) incorporating data
quality in the biometric recognition pipeline; (ii) combining soft biometric
attributes with primary biometric identifiers; (iii) utilizing contextual
information to improve biometric recognition accuracy; and (iv) performing
continuous authentication using ancillary information. In addition, the use of
information fusion principles for presentation attack detection and
multibiometric cryptosystems is also discussed. Finally, some of the research
challenges in biometric fusion are enumerated. The purpose of this article is
to provide readers a comprehensive overview of the role of information fusion
in biometrics.
