Personal authentication using finger vein pattern and finger-dorsa texture fusion

Personal authentication has attracted great attention due to its large potential of security application, and many researches have shown that fusion of features or decisions obtained from various single-modal biometrics verification systems can enhance the overall performance of system. In this paper, we proposed a novel multimodal biometric approach fusing finger vein pattern with finger-dorsa texture. Firstly, Finger Vein image and finger-dorsa image from the same finger are captured simultaneously, and a method is designed to segment Regions Of Interest(ROI) of vein image and dorsal image. Secondly, two strategies are designed to extract finger vein pattern and finger-dorsa texture respectively. Vein extraction strategy consists of four steps: local thresholding, modified line tracking, thorough probability map creating and directional neighbor analysis. Gray normalization is performed on finger-dorsa image to extract main finger-dorsa texture. Thirdly, the binarized vein pattern and normalized dorsal texture are fused into one feature image. Finally, a block-based texture feature is proposed for personal authentication. Experimental results showed that the proposed fusion method outperforms any one of finger-dorsa and finger vein methods.