Age Classification using Fuzzy Lattice Neural Network

This paper presents an age classification of a person from the gray scale facial images using Fuzzy Lattice Neural (FLN) model. The FLN model is a combination of fuzzy set theory, lattice theory and Adaptive Resonance Theory Neural model. The proposed system comprises of three sections, namely, location, feature extraction and age classification. From each facial image, three areas are located and three wrinkle features extracted from each location. The extracted nine (3x3) features are applied to FLN model. The FLN model trains the input and classifies the age of a person from the facial image. The proposed system is developed on MATLAB 6p1 and object oriented programming language C++. The success rate of the age classification is about 95% over Kwon and Lobo model and Wen, Chung and Chun model.