An Enhanced Face Recognition Using Modified Feature Extarction and Sparese Representation
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 6
Abstract
Face recognition system is put-fourth a significant challenge to the pattern recognition researchers. Generally human faces are very similar in structure which is difficult to differentiate. Change of facial expression, pose variation and change of lighting condition makes face recognition more difficult. Recent research shows that sparse representation is successfully used in face recognition problems. Local features extractions have been done in past using statistical feature like Local Binary Pattern (LBP). This paper proposed an adaptive method for face recognition which uses LBP in combination with sparse representation for vigorous face recognition. We also proposed modified feature extraction method to avoid face misalignment. Face recognition model is implemented in MATLAB software. Widespread testing of the proposed model is done using AR database. Result analysis on the AR database shows that proposed model is good performing compared to stat-of-art methods.
Authors and Affiliations
Aadhya Dani, Kapil Nagwanshi
Keywords
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