|Table of Contents|

Face Recognition Based on Fusion of Multi Features with Multi Scales

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2009年01期
Page:
47-52
Research Field:
Publishing date:

Info

Title:
Face Recognition Based on Fusion of Multi Features with Multi Scales
Author(s):
YAN Yun-yang12GUO Zhi-bo23CHEN Fu-bing2YANG Jing-yu2
1.Department of Computer Engineering,Huaiyin Institute of Technology,Huaian 223001,China;2.School of Computer Science and Technology,NUST,Nanjing 210094,China;3.School of Information Engineering,Yangzhou University,Yangzhou 225009,China
Keywords:
multi scales low frequency singular values feature fusion face recognition
PACS:
TP391.41
DOI:
-
Abstract:
To avoid some influences caused by lighting condition,noise and gesture,modular linear discriminant analysis(MLDA) is developed here for face recognition based on the transform feature of each sub-image after multi-scale division.Using the new LDA,local effective discriminant character is lost little.An image is divided with different scales.The coefficients with low frequency and the singular values of each sub-image are derived respectively.All coefficients or singular values are combined together and used as the feature vector of the image.LDA is implemented based on these feature vectors.In view of the limitations to express a face using only one feature,fusion of low frequency characters with singular values of an image for face recognition is presented.The experimental results performed on ORL or Yale face data set show that the proposed method is obviously superior to corresponding algorithms in terms of recognition rate and generalization ability.

References:

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Last Update: 2012-11-19