Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICASSP.2005.1415345
DC FieldValue
dc.titlePeg-free human hand shape analysis and recognition
dc.contributor.authorXiong, W.
dc.contributor.authorXu, C.
dc.contributor.authorOng, S.H.
dc.date.accessioned2014-06-19T03:23:07Z
dc.date.available2014-06-19T03:23:07Z
dc.date.issued2005
dc.identifier.citationXiong, W.,Xu, C.,Ong, S.H. (2005). Peg-free human hand shape analysis and recognition. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings II : II77-II80. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/ICASSP.2005.1415345" target="_blank">https://doi.org/10.1109/ICASSP.2005.1415345</a>
dc.identifier.isbn0780388747
dc.identifier.issn15206149
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/71382
dc.description.abstractThis work addresses the problem of deformable hand shape recognition in biometric systems without positioning aids. We separate and recognize multiple rigid fingers. An elliptical model is introduced to represent fingers and accelerate the matching of them. Technically, our method bridges the traditional handcrafted-feature methods and the shape-distance methods. We have tested it using our 108-person-540-sample database with significantly increased positive recognition accuracy. © 2005 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICASSP.2005.1415345
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/ICASSP.2005.1415345
dc.description.sourcetitleICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
dc.description.volumeII
dc.description.pageII77-II80
dc.description.codenIPROD
dc.identifier.isiutNOT_IN_WOS
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