CASIA OpenIR  > 09年以前成果
Global texture analysis of iris images for ethnic classification
Qiu, XC; Sun, Z; Tan, T; Zhang, D; Jain, AK
Source PublicationADVANCES IN BIOMETRICS, PROCEEDINGS
2006
Volume3832Pages:411-418
SubtypeArticle
AbstractIris pattern is commonly regarded as a kind of phenotypic feature without relation to the genes. In this paper, we propose a novel ethnic classification method based on the global texture information of iris images. So we would argue that iris texture is race related, and its genetic information is illustrated in coarse scale texture features, rather than preserved in the minute local features of state-of-the-art iris recognition algorithms. In our scheme, a bank of multichannel 2D Gabor filters is used to capture the global texture information and AdaBoost is used to learn a discriminant classification principle from the pool of the candidate feature set. Finally iris images are grouped into two race categories, Asian and non-Asian. Based on the proposed method, we get an encouraging correct classification rate (CCR) of 85.95% on a mixed database containing 3982 iris samples in our experiments.
WOS HeadingsScience & Technology ; Technology
WOS KeywordRECOGNITION ; FEATURES
Indexed ByISTP ; SCI
Language英语
WOS Research AreaComputer Science
WOS SubjectComputer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS IDWOS:000235768300055
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/9264
Collection09年以前成果
AffiliationChinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Ctr Biometr & Secur Res, Beijing 100080, Peoples R China
Recommended Citation
GB/T 7714
Qiu, XC,Sun, Z,Tan, T,et al. Global texture analysis of iris images for ethnic classification[J]. ADVANCES IN BIOMETRICS, PROCEEDINGS,2006,3832:411-418.
APA Qiu, XC,Sun, Z,Tan, T,Zhang, D,&Jain, AK.(2006).Global texture analysis of iris images for ethnic classification.ADVANCES IN BIOMETRICS, PROCEEDINGS,3832,411-418.
MLA Qiu, XC,et al."Global texture analysis of iris images for ethnic classification".ADVANCES IN BIOMETRICS, PROCEEDINGS 3832(2006):411-418.
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