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Random local region descriptor (RLRD): A new method for fixed-length feature representation of fingerprint image and its application to template protection
Liu, Eryun1,2; Zhao, Heng1; Liang, Jimin1; Pang, Liaojun1; Chen, Hongtao1,2; Tian, Jie1,3
Source PublicationFUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF GRID COMPUTING AND ESCIENCE
2012
Volume28Issue:1Pages:236-243
SubtypeArticle
AbstractMinutia 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.
KeywordFixed-length Feature Cancelable Biometric Fingerprint Recognition Random Local Region Descriptor (Rlrd)
WOS HeadingsScience & Technology ; Technology
WOS KeywordKEY GENERATION ; RANDOM NUMBER ; MINUTIAE ; SIMILARITY ; ALGORITHM
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Theory & Methods
WOS IDWOS:000295947900027
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Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/4056
Collection中国科学院分子影像重点实验室
Corresponding AuthorLiang, Jimin
Affiliation1.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
Recommended Citation
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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