Title
A New Fast Facial Recognition Algorithm Applicable To Large Databases
Abstract
In this contribution, a Transform Domain Two-Dimensional Principal Component Analysis algorithm employing Vector Quantization (TD2DPCA/VQ) is presented for facial recognition, particularly for large databases. The algorithm has attractive properties with respect to storage requirements in the training mode and the computational complexity in the testing mode. The experimental results obtained by applying the new algorithm to the ORL database confirmed the significant reduction in the storage and computational requirements while improving the excellent recognition accuracy of the spatial 2DPCA method. © 2006 IEEE.
Publication Date
12-1-2006
Publication Title
4th International IEEE North-East Workshop on Circuits and Systems, NEWCAS 2006 - Conference Proceedings
Number of Pages
193-196
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/NEWCAS.2006.250916
Copyright Status
Unknown
Socpus ID
34250711281 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/34250711281
STARS Citation
Abdelwahab, Moataz M. and Mikhael, Wasfy B., "A New Fast Facial Recognition Algorithm Applicable To Large Databases" (2006). Scopus Export 2000s. 7713.
https://stars.library.ucf.edu/scopus2000/7713