关键词: 人脸识别特征提取, 小波包分解, 图像金字塔, 方向梯度直方图

Abstract: Face recognition technology can be applied in the field of monitoring and security, which involves key technologies such as feature extraction and recognition model. The feature extraction method has a direct influence on the recognition effect. At present, the feature extraction method has the problems of incomplete expression and high computational complexity. For solving this problem, this paper proposes a kind of facial feature extraction method：WPD-HOG pyramid. The WPD-HOG pyramid feature extraction method combines the Wavelet Packet Decomposition（WPD）, image pyramid and Histograms of Oriented Gradients（HOG） together to characterize the face image feature. Finally, the WPD-HOG pyramid features are identified by the SVM classifier for face recognition. Experiments are conducted over ORL data set to demonstrate the proposed approach. Compared with the four benchmark methods：HOG, HOG pyramid, FWPD-HOG and FWPD-HOG pyramid, the experimental results show that the recognition performance, computation complexity and noise robustness of the proposed method are the best.

Key words: face recognition feature extraction, Wavelet Packet Decomposition（WPD）, image pyramid, Histograms of Oriented Gradients（HOG）