3D face recognition using optimised directional faces and fourier transform

This paper proposes an efficient multimodal face recognition method by combining the textural as well as depth features, extracted from directional faces of input image. Directional faces are obtained using filters which are designed using Local Polynomial Approximation (LPA). The efficient modified Local Binary Pattern (mLBP) operator is used for the feature extraction from optimized directional faces. The spectral representation of the concatenated block histogram of mLBP feature image acts as a robust face descriptor. Discrete Fourier Transform (DFT) is used as the transformation tool. The fusion of both modalities is performed at score level. The experimental results shows that the proposed method gives better performance.