Абстрактный

Motif Patterns Based Age Group Classification on LDP

D Sandhya Rani*, Dr. P V Ramana Murthy, Dr. U Ravi Babu

Facial expression recognition is a research issue. An Age classification is one of a facial expression recognition system and it is based on facial representation from human face images. In this paper we are using classification system for gray-scale facial images. The present paper proposes procedure for extracting the local texture features on a facial image. In this paper, the Motif Patterns are used for extracting the texture features which are identified on a Local Directional Pattern (LDP) values. The present paper uses seven (7) different motif patterns and the patterns starting from the top left corner pixel and scan is should be related to the incremental order. Based on the patterns count the facial image is classified into one of the five categories. i.e. Child (0 to 10years), Young (11 to 25 years), Adult (26-40), senior (41 to 60 years) and Senior adult Age (>60 years). It shows high rate of classification when compare with the other existing methods.