Abstract—This paper details with the subjective age prediction of face images using Principal Component Analysis (PCA). The face database is built by the seven individual age groups which are divided from the adult facial images between 10 to 60 years old. An age prediction algorithm is developed for examining the age of individual. Age prediction is concerned with the use of a training set to train a model that can predict the age of the facial images. The facial feature is extracted based on the geometric feature based method and principal component analysis (PCA) method. The accuracy of the system is analyzed by the variation on the range of the age groups. The efficiency of the system can be confirmed through the experimental results.
Index Terms—Age prediction, feature extraction, principal component analysis, age group, geometric feature.
H. H. Khaung Tin is assistant Lecturer in the University of Computer Studies, Loikaw, KaYah State, Myanmar (e-mail:firstname.lastname@example.org).
Cite: Hlaing Htake Khaung Tin, "Subjective Age Prediction of Face Images Using PCA," International Journal of Information and Electronics Engineering vol. 2, no. 3, pp. 296-299, 2012.