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基于模糊保險箱的人臉-人耳融合模板保護

Face and ear fusion template protection based on fuzzy vaults

  • 摘要: 鑒于人臉與人耳兩種生物特征在圖像獲取上的相似性以及生理位置上的互補性,提出一種人臉-人耳多模態融合模板保護方法,將兩者在特征層進行融合,然后利用模糊保險箱算法對融合模板進行保護.該方案基本流程分為五部分:圖像預處理、Gabor-PCA特征提取、特征融合、融合模板加密以及融合模板解密.在由ORL人臉庫和USTB人耳庫3構成的人臉-人耳多模態圖像庫上的認證實驗結果表明所提模板防護方法的有效性,且基于融合模板保護的認證結果比基于單模板保護的認證結果在識別率和誤識率上均有所優化.

     

    Abstract: Due to biological characteristic similarity in image acquisition and physiological complementarity of the face and the ear, a face and ear multimodal fusion template protection method was proposed, in which the face and the ear were combined in the feature level and then a fuzzy vault was utilized to protect the fusion feature template. The basic flow of the scheme was divided into 5 parts:image preprocessing, Gabor-PCA feature extraction, feature fusion, fusion template encryption, and fusion template decryp-tion. On the multimodal image dataset consisted of the ORL face dataset and the USTB ear dataset 3, authentication experimental re-sults show the effectiveness of the proposed fusion template protection method. Also the fusion template protection method outperforms the unimodal template protection method on both genuine accept rate and false accept rate.

     

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