Title
A Quantized/Truncated Transform Domain Technique (Qtd) For Fast Facial Recognition
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. © 2011 IEEE.
Publication Date
10-13-2011
Publication Title
Midwest Symposium on Circuits and Systems
Number of Pages
-
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/MWSCAS.2011.6026329
Copyright Status
Unknown
Socpus ID
80053631806 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/80053631806
STARS Citation
Alrasheed, Waleed and Mikhael, Wasfy B., "A Quantized/Truncated Transform Domain Technique (Qtd) For Fast Facial Recognition" (2011). Scopus Export 2010-2014. 2974.
https://stars.library.ucf.edu/scopus2010/2974