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首页> 外文会议>International Conference on Artificial Intelligence and Evolutionary Algorithms in Engineering Systems >Multimodal Biometric Authentication System Based on Score-Level Fusion of Palmprint and Finger Vein
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Multimodal Biometric Authentication System Based on Score-Level Fusion of Palmprint and Finger Vein

机译：基于Palmprint和手指静脉的分数级融合的多模态生物识别系统

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摘要

Multimodal biometrics plays a major role in our day-to-day life to meet the requirements with the well-grown population. In this paper, palmprint and finger vein images are fused using normalization scores of the individual traits. Palmprint features extracted from the discrete cosine transform (DCT) are classified by using multi-class linear discriminant analysis (LDA) and self-organizing maps (SOM). Finger vein identification is designed and developed by using repeated line tracking method to extract the patterns. A multimodal biometric authentication system integrates information from multiple biometric sources to compensate for the limitations in performance of each individual biometric system. These systems can significantly improve the recognition performance of a biometric system apart from catalyzing population coverage, impeding spoof attacks, increasing the degrees of freedom, and reducing the failure rates.
机译：多式化生物识别学在日常生活中发挥着重要作用，以满足人口良好的人口的要求。在本文中，使用各个特征的标准化分数融合了棕榈纹和手指静脉图像。通过使用多级线性判别分析（LDA）和自组织地图（SOM）来分类从离散余弦变换（DCT）中提取的掌纹特征。通过使用重复的线路跟踪方法来提取图案来设计和开发手指静脉识别。多模式生物识别身份验证系统将来自多个生物识别源的信息集成，以补偿每个单独的生物识别系统的性能的限制。除了催化群体覆盖范围内，这些系统可以显着提高生物识别系统的识别性能，妨碍欺骗攻击，增加自由度，降低故障率。

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