A visible image-based face recognition system can be seriously degraded in real-life environments by various factors including illumination changes, expression changes, occlusion, and disguise. In this paper, a novel feature descriptor for robust face recognition, Eigen Directional Bit-Plane (EDBP), is introduced to address these issues. It is observed that Local Binary Pattern (LBP) can be decomposed into 8 directional bit-planes (DBP), each of which represents certain directional information of the facial image. Principal Component Analysis (PCA) is then applied to the DBP space to obtain a more compact feature, the EDBP. For face recognition, the proposed EDBP is integrated into conventional state-of-the-art classification methods. Simulation results demonstrate that classifiers with EDBP outperform those with existing feature descriptors under illumination changes, expression changes, occlusion, and disguise.
- Eigen Directional Bit-Plane (EDBP)
- Face Recognition
- Local Binary Pattern (LBP)
- Principal Component Analysis (PCA)
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Media Technology