Optimized pre-processing input plane GPU implementation of an optical face recognition technique using a segmented phase only composite filter

The key outcome of this work is to propose and validate a fast and robust correlation scheme for face recognition applications. The robustness of this fast correlator is ensured by an adapted pre-processing step for the target image allowing us to minimize the impact of its (possibly noisy and varyi...

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Bibliographic Details
Published in:Optics communications 2013-02, Vol.289, p.33-44
Main Authors: Ouerhani, Y., Jridi, M., Alfalou, A., Brosseau, C.
Format: Article
Language:English
Subjects:
Computer Science
Correlation
Correlators
Embedded Systems
Engineering Sciences
Face recognition
Frames per second
Microprocessors
Optical engineering
Phase-only filters
Recognition
Robustness
Signal and Image processing
Tracking
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Summary:The key outcome of this work is to propose and validate a fast and robust correlation scheme for face recognition applications. The robustness of this fast correlator is ensured by an adapted pre-processing step for the target image allowing us to minimize the impact of its (possibly noisy and varying) amplitude spectrum information. A segmented composite filter is optimized, at the very outset of its fabrication, by weighting each reference with a specific coefficient which is proportional to the occurrence probability. A hierarchical classification procedure (called two-level decision tree learning approach) is also used in order to speed up the recognition procedure. Experimental results validating our approach are obtained with a prototype based on GPU implementation of the all-numerical correlator using the NVIDIA GPU GeForce 8400GS processor and test samples from the Pointing Head Pose Image Database (PHPID), e.g. true recognition rates larger than 85% with a run time lower than 120ms have been obtained using fixed images from the PHPID, true recognition rates larger than 77% using a real video sequence with 2 frame per second when the database contains 100 persons. Besides, it has been shown experimentally that the use of more recent GPU processor like NVIDIA-GPU Quadro FX 770M can perform the recognition of 4 frame per second with the same length of database.
ISSN:0030-4018
1873-0310
DOI:10.1016/j.optcom.2012.09.074