基于位面分解方法的人脸和掌纹多模态生物识别系统

Therry Z. Lee, D. Bong
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引用次数: 9

摘要

介绍了位面分解方法在单特征生物识别系统中的应用,如人脸、掌纹和指纹识别。这种方法能够在降低数据维数的同时提供有希望的高性能。然而,该方法尚未在使用多个生物特征的多模态生物识别系统中进行测试。为此,本文提出了一种基于位面分解方法的人脸与掌纹融合的多模态生物识别系统。在提取位面特征之前,采用简单平均法进行像素级融合。在前馈反向传播神经网络分类之前,对混合面-掌位平面进行主成分分析,进一步降维。实验结果表明,该系统具有较高的识别率。
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Face and palmprint multimodal biometric system based on bit-plane decomposition approach
Bit-plane decomposition approach has been introduced \ate\y for single trait biometric system such as face, palmprint, and fingerprint recognition. This approach is able to provide promising high performance rate while reducing the data dimensionality. However, this approach has not been tested on multimodal biometric system which uses more than one biometric trait. Hence, this paper introduces a new multimodal biometric system based on face and palmprint fusion with bit-plane decomposition approach. Pixel level fusion is applied by using simple averaging method before bit-plane feature extraction. Principal Component Analysis is also used on the hybrid face-palm bit planes for further dimension reduction before being classified by Feedforward Backpropagation Neural Network. The experimental results show that the proposed system is able to provide high recognition rate.
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