Finger-vein network enhancement and segmentation

Recently, an emerging biometric recognition based on human finger-vein patterns has received considerable attention. Due to light attenuation in imaging finger tissues, the finger-vein imagery is often seriously degraded. This makes network-based finger-vein feature representation greatly difficult in practice. In order to obtain perfect finger-vein networks, in this paper, we propose a novel scheme for venous region enhancement and finger-vein network segmentation. First, a method aimed at scattering removal, directional filtering and false vein information suppression is put forward to effectively enhance finger-vein images. Then, to achieve the high-fidelity extraction of finger-vein networks in an automated manner, a matting-based segmentation approach is presented considering the variations of veins in intensity and diameter. Extensive experiments are finally conducted to validate the proposed method.