CASIA OpenIR  > 09年以前成果
Improving iris recognition accuracy via cascaded classifiers
Sun, ZN; Wang, YH; Tan, TN; Cui, JL
Source PublicationIEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS
2005-08-01
Volume35Issue:3Pages:435-441
SubtypeLetter
AbstractAs a reliable approach to human identification, iris recognition has received increasing attention in recent years. The most distinguishing feature of an iris image comes from the fine spatial changes of the image structure. So iris pattern representation must characterize the local intensity variations in iris signals. However, the measurements from minutiae are easily affected by noise, such as occlusions by eyelids and eyelashes, iris localization error, nonlinear iris deformations, etc. This greatly limits the accuracy of iris recognition systems. In this paper, an elastic iris blob matching algorithm is proposed to overcome the limitations of local feature based classifiers (LFC). In addition, in order to recognize various iris images efficiently a novel cascading scheme is proposed to combine the LFC and an iris blob matcher. When the LFC is uncertain of its decision, poor quality iris images are usually involved in intra-class comparison. Then the iris blob matcher is resorted to determine the input iris' identity because it is capable of recognizing noisy images. Extensive experimental results demonstrate that the cascaded classifiers significantly improve the system's accuracy with negligible extra computational cost.
KeywordBiometrics Blob Matching Cascaded Classifiers Iris Recognition
WOS HeadingsScience & Technology ; Technology
WOS KeywordWAVELET TRANSFORM ; PATTERNS ; PHASE
Indexed BySCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Cybernetics ; Computer Science, Interdisciplinary Applications
WOS IDWOS:000230797600017
Citation statistics
Cited Times:57[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9112
Collection09年以前成果
AffiliationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Ctr Biomet & Secur Res, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Sun, ZN,Wang, YH,Tan, TN,et al. Improving iris recognition accuracy via cascaded classifiers[J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS,2005,35(3):435-441.
APA Sun, ZN,Wang, YH,Tan, TN,&Cui, JL.(2005).Improving iris recognition accuracy via cascaded classifiers.IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS,35(3),435-441.
MLA Sun, ZN,et al."Improving iris recognition accuracy via cascaded classifiers".IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART C-APPLICATIONS AND REVIEWS 35.3(2005):435-441.
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