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Applied Optics

Applied Optics


  • Editor: James C. Wyant
  • Vol. 47, Iss. 10 — Apr. 1, 2008
  • pp: B21–B31

Adaptive feature-specific imaging: a face recognition example

Pawan K. Baheti and Mark A. Neifeld  »View Author Affiliations

Applied Optics, Vol. 47, Issue 10, pp. B21-B31 (2008)

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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 ( P e ) . 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 P e = 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.

© 2008 Optical Society of America

OCIS Codes
(100.5010) Image processing : Pattern recognition
(110.2970) Imaging systems : Image detection systems
(110.1085) Imaging systems : Adaptive imaging
(110.1758) Imaging systems : Computational imaging

Original Manuscript: September 5, 2007
Manuscript Accepted: November 7, 2007
Published: February 6, 2008

Pawan K. Baheti and Mark A. Neifeld, "Adaptive feature-specific imaging: a face recognition example," Appl. Opt. 47, B21-B31 (2008)

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