Hybrid approaches to frontal view face recognition using the neural network
Kang Sik Yoon, Young Kug Ham, Rae‐Hong Park · Proceedings of International Conference on Neural Networks (ICNN'97) · 2002
In this paper, for frontal view face recognition hybrid approaches using neural networks (NNs) and hidden Markov models (HMMs) 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.