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ISSN 1009-3044

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Computer Kno8 l?ge (2009c? o10 y ???? ???
Vol.5,No.28, October 2009, pp.8023

?? PCA ? LBP ?????????
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?? ? ??????? (PCA) ????????? (LBP) ? ? ? ? ? ? ? ? ? ? ? ? ? PCA ? ? ? ? ? ? ? ? ? ? ? ? ? LBP ?
????????????? ? ????????????????????? ?SVM ? ????????????? ? ????
?? LBP ??? ? ???? LBP ?????? ? ???????????? LBP ????? ? ??????? LBP ??? PCA ?
?????? SVM ? ?????? ?LBP ? PCA ?????????? PCA ??? LBP ??????????????? ?
??? ? ?? ? ???? ? ????? ? ?????? ? ?????
????? ?TP391

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???? ?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 method which combined the characteristic of principal components psycho analytic thinking (PCA) with local binary pattern (LBP)s com bines the advantage in ball-shaped features of PCA with the advantage in Details of local texture of LBP and could rive better characteristics
from face image for support vector railcar (SVM) to gender classification.



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
see that the characteristics combined PCA with LBP has obvious advantages than the PCA and LBP separately in Gender identification.
name words: texture; gender classification; principal components analysis; local binary pattern;support vector machine
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