GENDER CLASSIFICATION FROM FACE IMAGES

Year 2017, Volume: 13 Issue: 1, 31 - 42, 28.04.2017

Eyyüp Yıldız Tolga Ensari

Abstract

In
this article, we study on gender classification which is one of the important
issue in security, statistics and related commercial areas. In the study, FEI
face data set has been used that has 200 female and 200 male frontal face
images. Principal component analysis (PCA) has been used for feature extraction
process. We use all part of the face images instead of taking some part of
them. Support Vector Machine (SVM) and k-nearest neighbor algorithms used for
classification test phases. We compare the results which obtained in our
experiments and give them in tables and graphs. According to the experiments,
defined as hybrid method principal component analysis with k-nearest neighbor
method gives better recognition accuracy then defined as hybrid method
principal component analysis with support vector machine method.

Keywords

Gender classification, face recognition, principal component analysis, k-nearest neighbor

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