The purpose of this paper is to incorporate a multimodal biometric system, which plays a major role in improving the accuracy and reducing FAR and FRR performance metrics. Biometrics plays a major role in several areas including military applications because of robustness of the system. Speech and face data are considered as key elements that are commonly used for multimodal biometric applications, as they are simultaneously acquired from camera and microphone.

    Design/methodology/approach

    In this proposed work, Viola‒Jones algorithm is used for face detection, and Local Binary Pattern consists of texture operators that perform thresholding operation to extract the features of face. Mel-frequency cepstral coefficients exploit the performances of voice data, and median filter is used for removing noise. KNN classifier is used for fusion of both face and voice. The proposed method produces better results in noisy environment with better accuracy. In this proposed method, from the database, 120 face and voice samples are trained and tested with simulation results using MATLAB tool that improves performance in better recognition and accuracy.

    Findings

    The algorithms perform better for both face and voice recognition. The outcome of this work provides better accuracy up to 98 per cent with reduced FAR of 0.5 per cent and FRR of 0.75 per cent.

    Originality/value

    The algorithms perform better for both face and voice recognition. The outcome of this work provides better accuracy up to 98 per cent with reduced FAR of 0.5 per cent and FRR of 0.75 per cent.


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    Titel :

    Implementing and analysing FAR and FRR for face and voice recognition (multimodal) using KNN classifier


    Weitere Titelangaben:

    Implementing and analysing FAR and FRR


    Beteiligte:
    D.S., Dinesh Kumar (Autor:in) / Rao, P.V. (Autor:in)


    Erscheinungsdatum :

    2019-10-03


    Format / Umfang :

    13 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Schlagwörter :


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    A Gabor Feature Classifier for Face Recognition

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    A Gabor feature classifier for face recognition

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    2D and 3D Multimodal Hybrid Face Recognition

    Mian, Ajmal / Bennamoun, Mohammed / Owens, Robyn | Springer Verlag | 2006

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