  In this paper, a new method for handwritten signature identification based on
rotated complex wavelet filters is proposed. We have proposed to use the
rotated complex wavelet filters (RCWF) and dual tree complex wavelet
transform(DTCWT) together to derive signature feature extraction, which
captures information in twelve different directions. In identification phase,
Canberra distance measure is used. The proposed method is compared with
discrete wavelet transform (DWT). From experimental results it is found that
signature identification rate of proposed method is superior over DWT
