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Local intensity variation analysis for iris recognition
Ma, L; Tan, TM; Wang, YH; Zhang, DX
AbstractAs all emerging biometric for human identification, iris recognition has received increasing attention in recent years. This paper makes an attempt to reflect shape information of the iris by analyzing local intensity variations of an iris image. In Our framework, a set of one-dimensional (1D) intensity signals is constructed to contain the most important local variations of the original 2D iris image. Gaussian-Hermite moments of Such intensity signals reflect to a large extent their various spatial modes and are used as distinguishing features. A resulting high-dimensional feature vector is mapped into a low-dimensional subspace using Fisher linear discriminant, and then the nearest center classifier based on cosine similarity measure is adopted for classification. Extensive experimental results show that the proposed method is effective and encouraging. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
KeywordIris Recognition Local Intensity Variations Gaussian-hermite Moments Fisher Linear Discriminant Biometrics
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000221553100015
Citation statistics
Cited Times:138[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
AffiliationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Ma, L,Tan, TM,Wang, YH,et al. Local intensity variation analysis for iris recognition[J]. PATTERN RECOGNITION,2004,37(6):1287-1298.
APA Ma, L,Tan, TM,Wang, YH,&Zhang, DX.(2004).Local intensity variation analysis for iris recognition.PATTERN RECOGNITION,37(6),1287-1298.
MLA Ma, L,et al."Local intensity variation analysis for iris recognition".PATTERN RECOGNITION 37.6(2004):1287-1298.
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