Redundant DWT based translation invariant wavelet feature extraction for face recognition

Discrete wavelet transform (DWT) is sensitive to the translation/shift of input signals, so its effectiveness could be negatively impacted when we encounter translation among signals. To deal with such drawbacks, this paper proposes redundant DWT(RDWT) based method to achieve image registration, translation invariant wavelet feature extraction and face recognition. We select a representative face from each person to form a reference face set and perform DWT on it. For each test face, we perform RDWT and compare its redundant horizontal and vertical details with the corresponding details obtained from the reference face. The reference face that is the most similar to the test face is determined to be the recognized face. Experiments on Yaleface database prove the effectiveness of our RDWT based method.