Face Recognition using Dual-Tree Wavelet Transform
This paper introduces a face recognition method based on the Dual-Tree Complex Wavelet Transform (DT-CWT), which is used to extract features from face images. DT-CWT uses similar kernels with Gabor wavelets and is a computationally cheaper way of extracting Gabor-like features. Principal Component Analysis (PCA) which is a linear dimensionality reduction technique, that attempts to represent data in lower dimensions, is used to perform the face recognition. The results demonstrate that using DT-CWT in the preprocessing phase and then applying PCA on the features extracted from the DT-CWT instead of raw face images, improves the recognition performance.