Random local region descriptor (RLRD): A new method for fixed-length feature representation of fingerprint image and its application to template protection

	Random local region descriptor (RLRD): A new method for fixed-length feature representation of fingerprint image and its application to template protection
	Liu, Eryun 1,2; Zhao, Heng 1; Liang, Jimin 1; Pang, Liaojun 1; Chen, Hongtao 1,2; Tian, Jie 1,3
发表期刊	FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING AND ESCIENCE
	2012
卷号	28 期号:1 页码:236-243
文章类型	Article
摘要	Minutia based features are the most widely used features in fingerprint recognition. However, the minutiae based fingerprint matching algorithms have some drawbacks that limit their applications in template protection. Because the minutia sets are unordered, it is difficult to determine the correspondence between two minutia sets and cannot be used in some known template protection schemes directly (e.g., fuzzy commitment, wrap around). In this paper, we propose a new fixed-length feature representation: random local region descriptor (RLRD) feature. The RLRD feature is extracted by randomly and uniformly selecting a set of points, where the order of points is determined by a random seed. For each point, a real fixed-length feature vector is extracted based on Tico's sampling structure. The real RLRD feature vector can be further transformed into a bit vector for secure sketches working in the Hamming space. The experimental results on FVC2002 DB1 and DB2 show the advantages of the RLRD feature over some other fixed-length fingerprint feature vectors in terms of equal error rate (EER), genuine accept rate (GAR) and false accept rate (FAR). (C) 2011 Elsevier B.V. All rights reserved.
关键词	Fixed-length Feature Cancelable Biometric Fingerprint Recognition Random Local Region Descriptor (Rlrd)
WOS标题词	Science & Technology ; Technology
关键词[WOS]	KEY GENERATION ; RANDOM NUMBER ; MINUTIAE ; SIMILARITY ; ALGORITHM
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Theory & Methods
WOS记录号	WOS:000295947900027
引用统计	被引频次：9[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/4056
专题	中国科学院分子影像重点实验室
通讯作者	Liang, Jimin
作者单位	1.Xidian Univ, Sch Life Sci & Technol, Life Sci Res Ctr, Xian 710071, Shaanxi, Peoples R China 2.Xidian Univ, Sch Elect Engn, Xian 710071, Shaanxi, Peoples R China 3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Liu, Eryun,Zhao, Heng,Liang, Jimin,et al. Random local region descriptor (RLRD): A new method for fixed-length feature representation of fingerprint image and its application to template protection[J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING AND ESCIENCE,2012,28(1):236-243.
APA	Liu, Eryun,Zhao, Heng,Liang, Jimin,Pang, Liaojun,Chen, Hongtao,&Tian, Jie.(2012).Random local region descriptor (RLRD): A new method for fixed-length feature representation of fingerprint image and its application to template protection.FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING AND ESCIENCE,28(1),236-243.
MLA	Liu, Eryun,et al."Random local region descriptor (RLRD): A new method for fixed-length feature representation of fingerprint image and its application to template protection".FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING AND ESCIENCE 28.1(2012):236-243.

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