Human face conveys substantial amount of information. It plays a central role in social interaction which contains information related to personal characteristics, including age, gender, emotion, ethnicity and identification. This paper will present an approach in age estimation of a person.
Age estimation systems are commonly designed to use two steps: an aging feature extraction and feature classification. The extracted features affect largely the performance of the age prediction process, which is then a key success to the classification stage. Facial aging effects show some unique characteristics: aging progress is uncontrollable, individual and time dependent. Different people undergo different aging rate not only by the human gene, but also other external factors which influence the aging process such as health conditions, life style and geographical location.