Learning compact binary codes for hash-based fingerprint indexing

doi:10.1109/TIFS.2015.2421332

科研成果详情

题名	Learning compact binary codes for hash-based fingerprint indexing
作者	Wang，Yi 1; Wang，Lipeng 2; Cheung，Yiu Ming 3; Yuen，Pong C.3,4
发表日期	2015-08-01
发表期刊	IEEE Transactions on Information Forensics and Security
ISSN/eISSN	1556-6013
卷号	10 期号:8 页码:1603-1616
摘要	Compact binary codes can in general improve the speed of searches in large-scale applications. Although fingerprint retrieval was studied extensively with real-valued features, only few strategies are available for search in Hamming space. In this paper, we propose a theoretical framework for systematically learning compact binary hash codes and develop an integrative approach to hash-based fingerprint indexing. Specifically, we build on the popular minutiae cylinder code (MCC) and are inspired by observing that the MCC bit-based representation is bit-correlated. Accordingly, we apply the theory of Markov random field to model bit correlations in MCC. This enables us to learn hash bits from a generalized linear model whose maximum likelihood estimates can be conveniently obtained using established algorithms. We further design a hierarchical fingerprint indexing scheme for binary hash codes. Under the new framework, the code length can be significantly reduced from 384 to 24 bits for each minutiae representation. Statistical experiments on public fingerprint databases demonstrate that our proposed approach can significantly improve the search accuracy of the benchmark MCC-based indexing scheme. The binary hash codes can achieve a significant search speedup compared with the MCC bit-based representation.
DOI	10.1109/TIFS.2015.2421332
URL	查看来源
语种	英语English
Scopus入藏号	2-s2.0-84933054291
引用统计	被引频次：23[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://repository.uic.edu.cn/handle/39GCC9TT/6447
专题	北师香港浸会大学
作者单位	1.Department of Computer Science, Institute of Computational and Theoretical Studies, Hong Kong Baptist University,Hong Kong 2.Institute of Information Engineering, Chinese Academy of Sciences,Beijing,100093,China 3.Department of Computer Science, Hong Kong Baptist University,Hong Kong 4.United International College, Beijing Normal University-Hong Kong Baptist University,Zhuhai,519085,China
推荐引用方式 GB/T 7714	Wang，Yi,Wang，Lipeng,Cheung，Yiu Minget al. Learning compact binary codes for hash-based fingerprint indexing[J]. IEEE Transactions on Information Forensics and Security, 2015, 10(8): 1603-1616.
APA	Wang，Yi, Wang，Lipeng, Cheung，Yiu Ming, & Yuen，Pong C. (2015). Learning compact binary codes for hash-based fingerprint indexing. IEEE Transactions on Information Forensics and Security, 10(8), 1603-1616.
MLA	Wang，Yi,et al."Learning compact binary codes for hash-based fingerprint indexing". IEEE Transactions on Information Forensics and Security 10.8(2015): 1603-1616.