Facial expression recognition using weber discrete wavelet transform

In this paper, a novel descriptor called Weber Discrete Wavelet Transform (WDWT) is proposed. It effectively recognizes facial expressions. WDWT uses unique combination of Weber Local Descriptor (WLD) and Discrete Wavelet Transform (DWT) for efficient extraction of illumination invariant features from multi scale images. The proposed descriptor's effectiveness is evaluated under different challenges on facial expression recognition problem. Experiments are performed on the standard face databases and results show that the proposed technique performs better than traditional LBP and WLD over a range of low resolution images. A significant decrease in the feature dimensions and substantial increase in recognition accuracy rate has been observed.