Hybrid approaches to frontal view face recognition using the hidden Markov model and neural network

摘要

In this paper, for frontal view face recognition a hidden Markov model (HMM) algorithm and hybrid approaches using the HMM and neural network (NN) are proposed. In the preprocessing stage, edges of a face are detected using the conventional locally adaptive threshold (LAT) scheme and facial features are extracted based on generic knowledge of facial components. In constructing a database with normalized features, we employ HMM parameters of each person computed by the forward-backward algorithm. Computer simulation shows that the proposed HMM-NN algorithm yields higher recognition rate compared with several conventional face recognition algorithms.