Face Recognition Based on Hybrid Binary Pattern
Fei Zhou · Journal of Information and Computational Science · 2014
In view of the fact that information which only contained in global or local features is insufficient, this paper proposes a novel face recognition method based on Hybrid Binary Pattern (HBP). In this paper, we expect better performance of face recognition by combining global and local features. On the one hand, we introduce a new rotation invariant texture representation method to extract the BGP feature of the face image. On the other hand, we extract the Multi-scale LBP (MSLBP) feature by using Wavelet Transform (WT) and LBP. Finally, we can combine the BGP feature and MSLBP feature to form a HBP feature. In the face recognition process, we adopt the Nearest Neighbor (NN) classifier for its simplicity. The experiment results show that the proposed method integrates different features efficiently and has better robustness to variations of lighting, expression and pose.