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Biometric Fusion System Using Face and Voice Recognition

A Comparison Approach: Biometric Fusion System Using Face and Voice Characteristics

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 996)


This paper presents a biometric fusion system for human recognition which utilizes voice and face biometric features. The aim of the system is to verify or identify the users by their face and/or voice characteristics. The system allows reliable human recognition based on physiological biometric feature—face, and physiological–behavioral biometric feature—voice. The outcome yields better identification results using voice biometrics and better verification results using face biometrics. The approach used here for face recognition consists of an image processing being histogram equalization and application of Gabor filter, and extracting a feature vector from the image. Such a feature extraction method has been successfully applied in the iris recognition [3]. The speech recognition process uses a recording divided into frames out of which only the frames containing speech are considered. The feature vector is extracted from Mel frequency cepstral coefficient. The classification process is performed by a basic dynamic time warping algorithm. In this paper, evaluation of the above approaches for face and voice recognition is performed.


  • Face recognition
  • Text-dependent voice recognition
  • Biometrics
  • Biometric fusion system
  • Gabor filter
  • Mel frequency cepstral coefficients

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  • DOI: 10.1007/978-981-13-8969-6_5
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Correspondence to Kornel Żaba .

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Kuśmierczyk, A., Sławińska, M., Żaba, K., Saeed, K. (2020). Biometric Fusion System Using Face and Voice Recognition. In: Chaki, R., Cortesi, A., Saeed, K., Chaki, N. (eds) Advanced Computing and Systems for Security. Advances in Intelligent Systems and Computing, vol 996. Springer, Singapore.

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