Age Classification using Facial Feature Extraction on Female and Male Images

Abstract

This paper presents age classification on facial images using subpattern-based Local Binary Patterns (LBP) method. Classification of age intervals are conducted separately on female and male facial images since the aging process for female and male is different for human beings in real life. The age classification performance of the holistic approaches is compared with the performance of subpattern-based LBP approach in order to demonstrate the performance differences between these two types of approaches. To be consistent with the research of others, our work has been tested on two publicly available databases namely FGNET and MORPH. The experiments are performed on these aging databases to demonstrate the age classification performance on female and male facial images of human beings using subpattern-based LBP method with several parameter settings. The results are then compared with the results of age classification of the holistic PCA and holistic subspace LDA methods.