Adaptive feature-specific imaging: a face recognition example.
Appl Opt
; 47(10): B21-31, 2008 Apr 01.
Article
in En
| MEDLINE
| ID: mdl-18382548
We present an adaptive feature-specific imaging (AFSI) system and consider its application to a face recognition task. The proposed system makes use of previous measurements to adapt the projection basis at each step. Using sequential hypothesis testing, we compare AFSI with static-FSI (SFSI) and static or adaptive conventional imaging in terms of the number of measurements required to achieve a specified probability of misclassification (Pe). The AFSI system exhibits significant improvement compared to SFSI and conventional imaging at low signal-to-noise ratio (SNR). It is shown that for M=4 hypotheses and desired Pe=10(-2), AFSI requires 100 times fewer measurements than the adaptive conventional imager at SNR= -20 dB. We also show a trade-off, in terms of average detection time, between measurement SNR and adaptation advantage, resulting in an optimal value of integration time (equivalent to SNR) per measurement.
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Collection:
01-internacional
Database:
MEDLINE
Main subject:
Algorithms
/
Pattern Recognition, Automated
/
Image Interpretation, Computer-Assisted
/
Face
Limits:
Female
/
Humans
/
Male
Language:
En
Journal:
Appl Opt
Year:
2008
Document type:
Article
Affiliation country:
Country of publication: