Tuesday, January 7, 2014

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E-mail: eduf@cccc.net.cn http://www.dnzs.net.cn Tel:+86-551-5690963 5690964 ISSN 1009-3044 ? 5 ?? 2 w ed and Te hn log ? ) Computer Kno8 l?ge (2009c? o10 y ???? ??? Vol.5,No.28, October 2009, pp.8023 ?? PCA ? LBP ????????? ??? ???? ? ???? ?????? ? ?? ?? 330031 ? ?? ? ??????? (PCA) ????????? (LBP) ? ? ? ? ? ? ? ? ? ? ? ? ? PCA ? ? ? ? ? ? ? ? ? ? ? ? ? LBP ? ????????????? ? ????????????????????? ?SVM ? ????????????? ? ???? ?? LBP ??? ? ???? LBP ?????? ? ???????????? LBP ????? ? ??????? LBP ??? PCA ? ?????? SVM ? ?????? ?LBP ? PCA ?????????? PCA ??? LBP ??????????????? ? ??? ? ?? ? ???? ? ????? ? ?????? ? ????? ????? ?TP391 ????? ?A ???? ?1009-3044(2009)28-8023-03 Gender Classification Based on PCA and LBP LI Kun-lun, WANG Ming-yan (Department of Computer, Nanchang University, Nanchang 330031, China) Abstract: The order which combined the characteristic of principal components boil down (PCA) with local binary material body (LBP)s com bines the advantage in telluric features of PCA with the advantage in Details of local texture of LBP and could create a picture better characteristics from face image for meet vector appliance (SVM) to sex classification.
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Using Cascade method rather than traditional LBP method to ex tract LBP histogram characteristics of images and combine the features of LBP and PCA from extraction for SVM. The experimental results immortalise that the characteristics combined PCA with LBP has obvious advantages than the PCA and LBP apiece in Gender identification. keystone words: texture; gender classification; principal componen ts synopsis; local binary pattern;support v! ector machine ???????????????????????? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ??????????????????? ? ? 20 ?? 90 ?????? ? ????????????????????? ? ?? ? ? ? ? ? ? ? ? ? ? ? ? Adaboost ? ? ? ? ? ? ? ? 1991 ? ?Gollomb ? ? [1] ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 30x30 ???????? ? ? 90 ??????????? 91.9% ? 1995 ? ?Brunelli ?? [2]??? HyperBF ?? ?...
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