Abstract
In order to search for an efficient feature extraction approach for face recognition,a method based on feature level fusion was presented.This method integrated Locality Preserving Projection(LPP) with Maximum Margin Criterion(MMC).Firstly,LPP was performed on training samples set,so the projection of each training sample on LPP subspace could be got.Further,MMC algorithm was performed on all the obtained projections to get more efficient discriminant features for recognition.Nearest Neighborhood(NN) algorithm was used to construct classifiers.The experiments on the ORL face database show that the recognition rate of the proposed method is high when pose,illumination condition,face expression and training sample number change.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
