ASIC Design Lab, Department of Electrical Engineering, University of Korea, Seoul 136-701, Korea.
Sensors (Basel). 2013 Feb 28;13(3):2895-910. doi: 10.3390/s130302895.
A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%.
提出了一种基于用户手部几何形状和血管模式测量的手部生物特征认证方法。为了获取手部几何形状，使用了手部侧面厚度、基于手形链码的 K 曲率、手指谷的长度和角度以及手指的长度和轮廓，而对于血管模式，则使用了基于方向的血管模式提取方法，从而提出了一种新的多模态生物识别方法。所提出的多模态生物识别系统仅使用一张图像来提取特征点。该系统可以配置为低成本设备。我们的多模态生物识别方法-手部几何形状（手部侧面和背面）和血管模式识别方法在分数级别上执行。我们的研究结果表明，所提出系统的等错误率为 0.06%。
