Multimodal recognition using face and ear
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摘要: 單一模式生物特征識別系統由于存在一些固有的局限性,有時難以滿足實際應用的需求,本文提出了基于正面人臉和人耳信息融合的多模態生物特征識別方法.針對USTB人耳圖像庫和ORL人臉圖像庫,利用核Fisher鑒別分析方法分別進行了人耳識別、人臉識別和人臉人耳融合識別,融合策略包括圖像層融合和特征層融合兩種.識別結果表明基于人臉人耳信息融合的多模態識別的識別率優于單體的人耳或人臉識別.這說明融合多種生物特征的多模態識別可以提高身份認證的準確率,也為實現非打擾式識別提供了一種新的途徑.
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關鍵詞:
- 人耳識別 /
- 人臉識別 /
- 多模態生物特征識別 /
- 核Fisher鑒別分析算法
Abstract: Unimodal biometric systems have to contend with a variety of problems and sometimes cannot satisfy application requirements.In this paper,a novel method of multimodal recognition using frontal face and ear was proposed.Kernel Fisher Discriminant Analysis was used for ear recognition,face recognition and the multimodal recognition.The multimodal recognition was studied on the image level fusion and feature level fusion.The experimental results from using USTB ear database and ORL face database show that the multimodal recognition outperforms the unimodal biometric recognition.This work shows that multibiometric system can increase the accuracy of overall system recognition,and provides an effective approach of non-intrusive biometric recognition. -

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