P2D Hidden Markov Model-based Face Recognition
Junyong Ye · Jisuanji gongcheng · 2003
A new approach is proposed in this paper, Dauechies orthogonal wavelet transform is used to preprocess the original face image, resulting in its four sub-images belonging to different frequency bands, and the sub-images are used to learn and recognize with HMM. An algorithm is designed to combine the multiple sort results, and the Karhunen Loeve (K-L) transform is used to extract a set of observations to improve the method by Asmaria.