A Quantized/truncated Transform Domain technique (QTD) for fast facial recognition

Author

Alrasheed, Waleed ; Mikhael, Wasfy B.

Author_Institution

Sch. of Electr. Eng. & Comput. Sci., Univ. of Central Florida, Orlando, FL, USA

fYear

2011

fDate

7-10 Aug. 2011

Firstpage

1

Lastpage

3

Abstract

A Quantized/truncated Transform Domain technique (QTD) is presented in this paper for facial recognition, suitable particularly for large data bases. The algorithm has attractive properties with respect to storage requirements and computational complexity in both the training and testing modes. The new algorithm is applied to both ORL and Yale data bases using Discrete Cosine Transform (DCT). The experimental results confirm the significant reduction in the storage and computational requirements while maintaining a high recognition accuracy rate.

Keywords

computational complexity; discrete cosine transforms; face recognition; DCT; ORL; QTD; computational complexity; discrete cosine transform; fast facial recognition; quantized-truncated transform domain technique; storage requirements; yale data bases; Complexity theory; Discrete cosine transforms; Educational institutions; Face recognition; Image recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems (MWSCAS), 2011 IEEE 54th International Midwest Symposium on

Conference_Location

Seoul

ISSN

1548-3746

Print_ISBN

978-1-61284-856-3

Electronic_ISBN

1548-3746

Type

conf

DOI

10.1109/MWSCAS.2011.6026329

Filename

6026329