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Author:

Bai, Xiao-Ming (Bai, Xiao-Ming.) | Wang, Cheng-Zhang (Wang, Cheng-Zhang.) | Shi, Qin (Shi, Qin.)

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EI Scopus PKU CSCD

Abstract:

A novel recognition approach coined two-dimension linear discriminant analysis based color face recognition is proposed in this paper to improve the accuracy of face recognition. A matrix-representation model which encodes the color information directly is employed to represent the color face image. Based on the representation model, two-dimension linear discriminant analysis algorithm is exploited to extract facial features for recognition task. The nearest neighborhood classifier is adopted to identify the color face samples based on the facial feature matrix. Experimental results from CVL and CMU PIE color face databases verify the effectiveness of the proposed approach.

Keyword:

Matrix algebra Face recognition Discriminant analysis Principal component analysis Color

Author Community:

  • [ 1 ] [Bai, Xiao-Ming]Information College, Capital University of Economics and Business, Beijing 100070, China
  • [ 2 ] [Wang, Cheng-Zhang]College of Applied Mathematics, Central University of Finance and Economics, Beijing 100081, China
  • [ 3 ] [Shi, Qin]College of Computer Science, Beijing University of Technology, Beijing 100124, China

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Source :

Journal of Beijing University of Technology

ISSN: 0254-0037

Year: 2010

Issue: 12

Volume: 36

Page: 1717-1721

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 3

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