Genetic programming for multibiometrics
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- @Article{Giot20121837,
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author = "Romain Giot and Christophe Rosenberger",
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title = "Genetic programming for multibiometrics",
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journal = "Expert Systems with Applications",
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volume = "39",
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number = "2",
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pages = "1837--1847",
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year = "2012",
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ISSN = "0957-4174",
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DOI = "doi:10.1016/j.eswa.2011.08.066",
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URL = "http://www.sciencedirect.com/science/article/pii/S095741741101178X",
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keywords = "genetic algorithms, genetic programming,
Multibiometrics, Score fusion, Authentication",
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abstract = "Biometric systems suffer from some drawbacks: a
biometric system can provide in general good
performances except with some individuals as its
performance depends highly on the quality of the
capture One solution to solve some of these problems is
to use multibiometrics where different biometric
systems are combined together (multiple captures of the
same biometric modality, multiple feature extraction
algorithms, multiple biometric modalities). In this
paper, we are interested in score level fusion
functions application (i.e., we use a multibiometric
authentication scheme which accept or deny the claimant
for using an application). In the state of the art, the
weighted sum of scores (which is a linear classifier)
and the use of an SVM (which is a non linear
classifier) provided by different biometric systems
provide one of the best performances. We present a new
method based on the use of genetic programming giving
similar or better performances (depending on the
complexity of the database). We derive a score fusion
function by assembling some classical primitives
functions (+, ., -, a ). We have validated the proposed
method on three significant biometric benchmark
datasets from the state of the art.",
- }
Genetic Programming entries for
Romain Giot
Christophe Rosenberger
Citations