Using Facial Features for the Estimation of Age of a Person

Abstract

Age succession is normally indicated by human face structure, skin color and texture. The human facial attributes change with age succession of an individual. This manuscript enables a technique to appraise the exact age of humans by analyzing wrinkle arena of human facial images. Wrinkle arenas are detected and wrinkle attributes are extracted from human facial images. Based on the wrinkle attributes, each human facial image is clustered using c-means clustering procedure for classification. Then, approximated human facial age is determined using their clustering membership value and the average human age of each cluster. The obtained results are outstanding and awesome.