Abstract: Due to the representation difficulty of a face image by a single type feature used in face recognition， a MBC feature and POEM feature-based face recognition scheme was proposed. Firstly，MBC and POEM coding patterns were extracted from normalized face images. Secondly， feature vector of every block was generated by dividing the MBC and POEM coding patterns into blocks. Finally， the classification capacity of features was enhanced by using weighted piecewise LDA algorithm. Recognition and verification test were carried out using the proposed algorithm on Dup1，Dup2， Fb and Fc， respectively， which were the four subsets of FERET. The recognition rates were 93.77%， 90.60%， 99.58%， and 99.49%， respectively， and the verification rates(false accepted rate is 0.1%) were 95.70%， 92.31%， 99.75%， and 100% ， respectively. All these results indicated the effectiveness of the proposed algorithm.

Key words: face recognition, MBC feature, POEM feature, feature fusion, weighted piecewise LDA