This study examines the use of the NIST Spectral Image Validation and Verification (SIVV) metric for the application of detecting the sample rate of a given fingerprint digital image. SIVV operates by reducing an input image to a 1-dimensional power spectrum that makes explicit the characteristic ridge structure of the fingerprint that on a global basis differentiates it from most other images. The magnitude of the distinctive spectral feature, which is related directly to the distinctness of the level 1 ridge detail, provides a primary diagnostic indicator of the presence of a fingerprint image. The location of the detected peak corresponding to the level 1 ridge detail can be used as an estimator of the original sampling frequency of that image given the behavior of this peak at known sampling frequencies a priori versus the calculated shift of this peak on an image of unknown sampling rate. A statistical model is fit to frequency measurements of a sample of images scanned at various sample rates from 10-print fingerprint cards such that the model parameters can be applied to SIVV frequency values of a digital fingerprint of unknown sample rate to estimate the sample rate. Uncertainty analysis is used to compute 95 % confidence intervals for predictions of sample rate from frequency. The model is tested against sets of cardscan and livescan images.
Citation: NIST Interagency/Internal Report (NISTIR) - 7968Report Number:
NIST Pub Series: NIST Interagency/Internal Report (NISTIR)
Pub Type: NIST Pubs
fingerprint, sample rate estimation, SIVV, spectral analysis, Spectral Image Validation and Verification