Palmprint verification using complex wavelet transform

Palmprint is a unique and reliable biometric characteristic with high usability. With the increasing demand of automatic palmprint authentication systems, the development of accurate and robust palmprint verification algorithms has been attracting a lot of interests. The relative translation, rotation and distortion between two palmprint images will introduce much error in palmprint matching. However, an accurate registration of palmprint images is too time-consuming. In this paper, we propose a modified complex wavelet structural similarity index (CW-SSIM) to compute the matching score and hence identify the input palmprint. Since CW-SSIM is robust to translation, small rotation and distortion, a fast rough alignment of palmprint images is sufficient. CW-SSIM is also insensitive to luminance and contrast changes. Our experimental results show that the proposed scheme outperforms the state-of-the-art methods by achieving a higher genuine acceptance rate and a lower false acceptance rate simultaneously.