2014 2nd International Conference on Electronic Design (ICED) 2014
DOI: 10.1109/iced.2014.7015828
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Investigation of information fusion in face and palmprint multimodal biometrics

Abstract: This paper reviews several information fusion techniques and strategies in the application of multimodal biometrics system using face and palmprint images. Multimodal biometric is able to overcome several limitations in single modal biometric such as intra-class variations, less discriminative power, noise data and redundant features. By consolidating two kinds of modality a better performance can be achieved. Information fusion in multimodal biometrics can be carried out at three possible levels, i.e. feature… Show more

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Cited by 2 publications
(2 citation statements)
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“…Experiments were carried out through a test bed comprising sixty pairs of iris and palmprint images of ten people. Mohamad et al [4] surveyed various data fusion methods and schemes for applying in multimodal biometrics systems through the usage official features and palmprint images. Multimodal biometric systems are capable of overcoming various restrictions which are present in unimodal biometrics systems like intra-class differences, lesser discriminative capacity, noisy data and repetitive attributes.…”
Section: Related Workmentioning
confidence: 99%
“…Experiments were carried out through a test bed comprising sixty pairs of iris and palmprint images of ten people. Mohamad et al [4] surveyed various data fusion methods and schemes for applying in multimodal biometrics systems through the usage official features and palmprint images. Multimodal biometric systems are capable of overcoming various restrictions which are present in unimodal biometrics systems like intra-class differences, lesser discriminative capacity, noisy data and repetitive attributes.…”
Section: Related Workmentioning
confidence: 99%
“…Recent lines of research pertaining to face and fingerprint multimodal biometric systems include investigation into image quality of related systems (palm print and face) [34], [35], privacy preservation [36] and the issue of mutual dependency between face and fingerprint biometric features and its effect on accuracy [37].…”
Section: Face and Fingerprint Multimodal Systemsmentioning
confidence: 99%