Phase-eigen subspace based illumination invariant face recognition using associative memory

Phase eigen subspace based face recognition under varying lighting conditions is proposed. Universal subspace analysis is exploited in frequency domain and phase spectrum is extracted instead of using raw spatial data of face images. Improved results are obtained when simplified bi-directional assoc...

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Bibliographic Details
Published in2012 NATIONAL CONFERENCE ON COMPUTING AND COMMUNICATION SYSTEMS pp. 1 - 5
Main Authors Banerjee, P., Banerjee, P. K.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2012
Subjects
Face
Face recognition
Frequency domain analysis
Lighting
Training
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Summary:Phase eigen subspace based face recognition under varying lighting conditions is proposed. Universal subspace analysis is exploited in frequency domain and phase spectrum is extracted instead of using raw spatial data of face images. Improved results are obtained when simplified bi-directional associative memory neural network is used as classifier. The proposed scheme is experimented over two standard databases like YaleB and PIE and the promising recognition accuracy is achieved while comparing to standard subspace methods.
ISBN:9781467319522
146731952X
DOI:10.1109/NCCCS.2012.6413023