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Point spread function engineering for iris recognition system design
 

Summary: Point spread function engineering for iris
recognition system design
Amit Ashok1,
* and Mark A. Neifeld1,2
1
Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, 85721 USA
2
College of Optical Sciences, University of Arizona, Tucson, Arizona, 85721 USA
*Corresponding author: ashoka@ece.arizona.edu
Received 3 September 2009; revised 15 January 2010; accepted 22 January 2010;
posted 26 January 2010 (Doc. ID 116358); published 19 February 2010
Undersampling in the detector array degrades the performance of iris-recognition imaging systems.
We find that an undersampling of 8 8 reduces the iris-recognition performance by nearly a factor of
4 (on CASIA iris database), as measured by the false rejection ratio (FRR) metric. We employ optical
point spread function (PSF) engineering via a Zernike phase mask in conjunction with multiple sub-
pixel shifted image measurements (frames) to mitigate the effect of undersampling. A task-specific
optimization framework is used to engineer the optical PSF and optimize the postprocessing parameters
to minimize the FRR. The optimized Zernike phase enhanced lens (ZPEL) imager design with one
frame yields an improvement of nearly 33% relative to a thin observation module by bounded optics
(TOMBO) imager with one frame. With four frames the optimized ZPEL imager achieves a FRR equal

  

Source: Ashok, Amit - Department of Electrical and Computer Engineering, University of Arizona

 

Collections: Engineering