Extracting multiple features in the CID color space for face recognition

Document Type

Article

Publication Date

9-1-2010

Abstract

This correspondence presents a novel face recognition method that extracts multiple features in the color image discriminant (CID) color space, where three new color component images, D1, D2, and D3, are derived using an iterative algorithm. As different color component images in the CID color space display different characteristics, three different image encoding methods are presented to effectively extract features from the component images for enhancing pattern recognition performance. To further improve classification performance, the similarity scores due to the three color component images are fused for the final decision making. Experimental results using two large-scale face databases, namely, the face recognition grand challenge (FRGC) version 2 database and the FERET database, show the effectiveness of the proposed method. © 2010 IEEE.

Identifier

77955789861 (Scopus)

Publication Title

IEEE Transactions on Image Processing

External Full Text Location

https://doi.org/10.1109/TIP.2010.2048963

ISSN

10577149

PubMed ID

20421188

First Page

2502

Last Page

2509

Issue

9

Volume

19

Grant

60632050

Fund Ref

National Natural Science Foundation of China

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