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International Journal of Scientific and Engineering Research
ISSN Online 2229-5518
ISSN Print: 2229-5518 3    
Website: http://www.ijser.org
scirp IJSER >> Volume 3,Issue 3,March 2012
Face Recognition Using Combined Global Local Preserving Projections And Compared With Various Methods
Full Text(PDF, )  PP.227-230  
Nisar Hundewale
— CGLPP, Dimensionality reduction, Face recognition, Locality Preserving Projection, ORL, Principal Component Analysis, UMIST.
In appearance-based methods, we usually represent an image of size n x m pixels by a vector in an n x m - dimensional space. However, these n x m-dimensional spaces are too large to allow robust and fast face recognition. A common way to attempt to resolve this problem is to use dimensionality reduction techniques. The most prominent existing techniques for this purpose are Principal Component Analysis (PCA) and Locality Preserving Projections (LPP). We Propose a new combined approach for face recognition which aims to integrates the advantages of the global feature extraction technique like PCA and the local feature extraction technique LPP .It has been introduced here (CGLPP- Combined Global Local Preserving Projections. Finally, Comparison is done with various recognition methods. Experimental evaluations are performed on the ORL and UMIST data sets with 400 images and 40 subjects
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