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AuthorBoukabou W.R.
AuthorBouridane A.
AuthorAl-Maadeed, Somaya
Available date2022-05-19T10:23:15Z
Publication Date2013
Publication NameDigital Signal Processing: A Review Journal
ResourceScopus
Identifierhttp://dx.doi.org/10.1016/j.dsp.2012.04.005
URIhttp://hdl.handle.net/10576/31162
AbstractFace recognition is an increasingly important problem in biometric applications; consequently many recognition algorithms have been proposed during the last three decades. It is accepted that the use of a pre-processing step can extract more discriminating features and increase the classification rates. Although, Gabor filters have been widely employed they do not provide satisfying classification results. This paper proposes the use of directional filters as a pre-processing step to demonstrate that a Directional Filter Bank is capable of enhancing existing face recognition classifiers such as PCA, ICA, LDA and SDA. The proposed method is tested using two different databases: the Yale face database and the FERET database. Experimental results demonstrate that the pre-processing phase enhances the classification rates. A comparative study has also been carried out to demonstrate that a DFB based classification outperforms a Gabor type one.
Languageen
PublisherElsevier Inc.
SubjectDatabase systems
Discriminant analysis
Filter banks
Gabor filters
Image coding
Image retrieval
Independent component analysis
Principal component analysis
Biometric applications
Classification results
Directional filter bank(DFB)
Directional filter banks
Independent component analyses (ICA)
Linear discriminant analyses (LDA)
Recognition algorithm
Subclass discriminant analyses (SDA)
Face recognition
TitleEnhancing face recognition using Directional Filter Banks
TypeArticle
Pagination586-594
Issue Number2
Volume Number23
dc.accessType Abstract Only


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