Prediction of human ethnicity from facial images using neural networks

Abstract

This work attempts to solve the problem of ethnicity prediction of humans based on their facial features. Three major ethnicities were considered for this work: Mongolian, Caucasian and the Negro. A total of 447 image samples were collected from the FERET database. Several geometric features and color attributes were extracted from the image and used for classification problem. The accuracy of the model obtained using an MLP approach was 82.4% whereas the accuracy obtained by using a convolution neural network was a significant 98.6%.