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All Journal International Journal of New Media Technology
Irham Surya Pratama
Tanri Abeng University
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Ethnicity Classification Based On Facial Features Using Viola-Jones Algorithm Irham Surya Pratama; Felix Indra Kurniadi
IJNMT (International Journal of New Media Technology) Vol 7 No 1 (2020): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (434.759 KB) | DOI: 10.31937/ijnmt.v6i2.917

Abstract

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.
Co-Authors Felix Indra Kurniadi