Age Group Estimation using Facial Features

Human face is the non-verbal portal into the person. A person’s gender, mood, country of origin, age category, and identity can be identified from the face. There has been a growing interest in automatic age estimation from facial images due to a variety of potential applications in law enforcement, security control, and human computer interaction (HCI). This paper presents a method to improve the accuracy of the estimated age. Apart from geometric shape features, wrinkle analysis is also incorporated in classifying the age. Multiple algorithms are applied for different phases like feature extraction, illumination correction, image fitting and edge detection etc. The main objective of this paper is to present a working model of an age classifier that is more efficient that the existing models. The experimental results show that 93.01% recognition rate can be achieved when applying the proposed system on the images.