Title
A Transform Domain Modular Approach For Facial Recognition Using Different Representations And Windowing Techniques
Abstract
A face recognition algorithm based on a newly developed Transform Domain Modular (TDM) approach is proposed. In this approach, the spatial faces are divided into smaller sub-images, which are processed using non-overlapping and overlapping windows. Each image is subsequently transformed using a compressing transform such as the two dimensional discrete cosine transform. This produces the TDM-2D and the TDM-Dia based on two-dimensional and diagonal representations of the data, respectively. The performance of this approach for facial image recognition is compared with the state of the art successful techniques. The test results, for noise free and noisy images, yield higher than 97.5% recognition accuracy. The improved recognition accuracy is achieved while retaining comparable or better computation complexity and storage savings.
Publication Date
9-23-2014
Publication Title
Midwest Symposium on Circuits and Systems
Number of Pages
817-820
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/MWSCAS.2014.6908540
Copyright Status
Unknown
Socpus ID
84908494366 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84908494366
STARS Citation
Chehata, Ramy C.G.; Mikhael, Wasfy B.; and Atia, George, "A Transform Domain Modular Approach For Facial Recognition Using Different Representations And Windowing Techniques" (2014). Scopus Export 2010-2014. 8048.
https://stars.library.ucf.edu/scopus2010/8048