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A Spectral Analytic Method for Fingerprint Image Sample Rate Estimation



John M. Libert, Shahram Orandi, John D. Grantham, Michael D. Garris


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.
NIST Interagency/Internal Report (NISTIR) - 7968
Report Number


fingerprint, sample rate estimation, SIVV, spectral analysis, Spectral Image Validation and Verification


Libert, J. , Orandi, S. , Grantham, J. and Garris, M. (2014), A Spectral Analytic Method for Fingerprint Image Sample Rate Estimation, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], (Accessed May 22, 2024)


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Created February 25, 2014, Updated November 10, 2018