Template representativeness is a fundamental problem in a biometric recognition system. The performance of the system degrades if the enrolled templates are un-representative of the substantial intra-class variations encountered in the input biometric samples. Recently, several template updates methods based on supervised and semi-supervised learning have been proposed in the literature with an aim to update the enrolled templates to the intra-class variations of the input data. However, the state of art related to template update is still in its infancy. This paper presents a critical review of the current approaches to template updating in order to analyze the state of the art in terms of advancement reached and open issues r© Springer-Verlag Berlin Heidelberg 2009.
CITATION STYLE
Rattani, A., Freni, B., Marcialis, G. L., & Roli, F. (2009). Template update methods in adaptive biometric systems: A critical review. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5558 LNCS, pp. 847–856). https://doi.org/10.1007/978-3-642-01793-3_86
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