Biometric recognition system can use race classification to identify the human globally with a particular identity. This paper proposes Support Vector Machine and will compare the result with K-Nearest Neighbor for classification of people into two major races namely Indonesian western and eastern races. Firstly, the proposed classification method extracts the distinct primary facial feature and skin color model of the given face with Viola-Jones Algorithm to effectively classify the races. To increase the accuracy, the sample must not contain any background of other people skin, no movement and the pictures were taken from the mobile camera with no beauty filter. ; Biometric recognition system can use race classification to identify the human globally with a particular identity. This paper proposes Support Vector Machine and will compare the result with K-Nearest Neighbor for classification of people into two major races namely Indonesian western and eastern races. Firstly, the proposed classification method extracts the distinct primary facial feature and skin color model of the given face with Viola-Jones Algorithm to effectively classify the races. To increase the accuracy, the sample must not contain any background of other people skin, no movement and the pictures were taken from the mobile camera with no beauty filter.


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    Titel :

    Ethnicity Classification Based On Facial Features Using Viola-Jones Algorithm


    Beteiligte:

    Erscheinungsdatum :

    2020-07-02


    Anmerkungen:

    doi:10.31937/ijnmt.v6i2.917
    IJNMT (International Journal of New Media Technology); Vol 7 No 1 (2020): IJNMT (International Journal of New Media Technology); 39-42 ; 2581-1851 ; 2355-0082 ; 10.31937/ijnmt.v7i1



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch


    Klassifikation :

    DDC:    006 / 629




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