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Efficient Search and Retrieval in Biometric Databases

机译:生物特征数据库中的有效搜索和检索

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Biometric identification has emerged as a reliable means of controlling access to both physical and virtual spaces. Fingerprints, face and voice biometrics are being increasingly used as alternatives to passwords, PINs and visual verification. In spite of the rapid proliferation of large-scale databases, the research has thus far been focused only on accuracy within small databases. In larger applications, response time and retrieval efficiency also become important in addition to accuracy. Unlike structured information such as text or numeric data that can be sorted, biometric data does not have any natural sorting order. Therefore indexing and binning of biometric databases represents a challenging problem. We present results using parallel combination of multiple biometrics to bin the database. Using hand geometry and signature features we show that the search space can be reduced to just 5% of the entire database.
机译:生物识别技术已经成为控制对物理和虚拟空间访问的可靠手段。指纹,面部和语音生物识别技术正越来越多地用作密码,PIN和视觉验证的替代方法。尽管大规模数据库迅速发展,但迄今为止,研究仅集中在小型数据库的准确性上。在较大的应用中,响应时间和检索效率除精度外也很重要。与可以排序的文本或数字数据等结构化信息不同,生物识别数据没有任何自然的排序顺序。因此,生物特征数据库的索引和装箱是一个具有挑战性的问题。我们使用多个生物特征的并行组合来对数据库进行分类,从而得出结果。使用手的几何形状和签名功能,我们表明搜索空间可以减少到整个数据库的5%。

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