Paper Info
Title
Illumination invariant face recognition system
Abstract
One of the main issues that degrades the performance of a face recognition system is the illumination problem. In this paper, we investigated different algorithms as a preprocessing step to overcome the illumination problem. Histogram equalization, discrete cosine transforms and steerable Gaussian filters were applied to face images from Yale face database B for illumination normalization. PCA algorithm was used as a feature extractor. Using this preprocessing step the performance of the system shows significant improvements.
Year
DOI
Venue
2013
10.1109/SIU.2013.6531374
Signal Processing and Communications Applications Conference
Keywords
Field
DocType
Gaussian processes,discrete cosine transforms,face recognition,filtering theory,lighting,principal component analysis,visual databases,PCA algorithm,Yale face database B,discrete cosine transforms,face images,feature extractor,histogram equalization,illumination invariant face recognition system,illumination normalization,illumination problem,performance degradation,preprocessing,steerable Gaussian filters,Face recognition,discrete cosine transform,principal component analysis,steerable Gaussian filters
Facial recognition system,Computer vision,Normalization (statistics),Pattern recognition,Computer science,Discrete cosine transform,Illumination problem,Gaussian,Preprocessor,Gaussian process,Artificial intelligence,Histogram equalization
Conference
ISSN
ISBN
Citations 
2165-0608
978-1-4673-5561-2
0
PageRank 
References 
Authors
0.34
6
3
Name
Order
Citations
PageRank
Cemil Tosik100.34
Alaa Eleyan2515.64
Mohammad Shukri Salman3339.09