Paper Info
Title
Supervised facial recognition based on multiresolution analysis with radon transform
Abstract
A new supervised facial recognition approach based on the integration of Two Dimensional Discrete Multiwavelet Transform (2D DMWT), 2D Radon Transform (2D RT), and 3D DWT is proposed. In the feature extraction step, 2D DMWT is used to extract the useful information from the image. The extracted features are then aligned using 2D RT and localized in one single band using 3D DWT. The resulting features are fed into a Neural Network for both training and testing. The proposed algorithm is tested on different databases, namely, ORL, YALE, and subset fc of FERET. It is shown that the proposed approach can significantly improve the recognition rate and the storage requirements of the overall recognition system.
Year
DOI
Venue
2014
10.1109/ACSSC.2014.7094589
ACSSC
Keywords
Field
DocType
feret,neural network,multiresolution analysis,face recognition,2d rt,discrete multiwavelet transform,yale database,image resolution,2d dmwt,3d dwt,feature extraction,orl database,supervised facial recognition approach,radon transforms,2d radon transform,discrete wavelet transforms,neural nets
Computer vision,Facial recognition system,Pattern recognition,Recognition system,Computer science,FERET,Multiresolution analysis,Feature extraction,Artificial intelligence,Artificial neural network,Radon transform
Conference
ISSN
Citations 
PageRank 
1058-6393
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Ahmed Aldhahab122.72
G. Atia226541.37
Wasfy B. Mikhael37676.27