Component-Based Ethnicity Identification from Facial Images

Abstract

This paper presents an exhaustive component-based analysis to identify the ethnicity from facial images. The different ethnic groups identified are Asian, African, African American, Asian Middle East, Caucasian and Other. The classification techniques investigated include Decision Trees, Naive Bayes, Random Forest and K-Nearest Neighbor. Naive Bayes achieved 84.7 % and 85.6 % accuracy rates for African ethnicity and Asian ethnicity identification, respectively. The Decision Trees achieved 85.8 % for African American ethnicity identification rate, while K-Nearest Neighbor achieved 86.8 % for Asian Middle East ethnicity and Random Forest achieved 90.8 % for Caucasian ethnicity identification rate. This research work achieved an overall ethnicity identification rate of 86.6 %.