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Hand Biometric Recognition Based on Fused Hand Geometry and Vascular Patterns

机译:基于融合手部几何和血管模式的手部生物特征识别

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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%.
机译:提出了一种基于用户手部几何形状和血管图案测量的手部生物特征认证方法。为了获得手的几何形状,使用了手的侧视图的厚度,带有手形链码的K曲率,手指谷的长度和角度以及手指的长度和轮廓,并且血管模式,采用基于方向的血管模式提取方法,因此,提出了一种新的多峰生物特征识别方法。所提出的多峰生物特征识别系统仅使用一张图像来提取特征点。可以为低成本设备配置此系统。我们的多模式生物特征手形(手和手背的侧视图)和血管模式识别方法在得分级别上表现出色。我们的研究结果表明,该系统的均等错误率为0.06%。

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