Point spread function engineering for iris recognition system design

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

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 subpixel 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 to that of the conventional imager without undersampling. Further, the ZPEL imager design using 16 frames yields a FRR that is actually 15% lower than that obtained with the conventional imager without undersampling.

Original languageEnglish (US)
JournalApplied Optics
Volume49
Issue number10
DOIs
StatePublished - Apr 1 2010

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Optical transfer function
point spread functions
Image sensors
systems engineering
rejection
Systems analysis
engineering
lenses
Lenses
engineers
masks
Imaging systems
modules
Masks
optics
Optics
optimization
Detectors
detectors
Engineers

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics

Cite this

Point spread function engineering for iris recognition system design. / Ashok, Amit; Neifeld, Mark A.

In: Applied Optics, Vol. 49, No. 10, 01.04.2010.

Research output: Contribution to journalArticle

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