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Activity Number: 337
Type: Topic Contributed
Date/Time: Tuesday, August 6, 2013 : 10:30 AM to 12:20 PM
Sponsor: Committee of Representatives to AAAS
Abstract - #309317
Title: A Quality Metric for Assessing Quality of Individual Minutiae in Latent Fingerprints
Author(s): Karen Kafadar*+ and Adele Peskin and Elham Tabassi
Companies: Indiana University and NIST-Boulder and NIST-Gaithersburg
Keywords: image quality ; gradient ; fingerprint database ; classification ; resolution

We have developed a new measurement to quantify the quality of individual features ("minutiae") in a latent ?ngerprint. Currently minutiae quality is based on an overall score for an entire print. However, minutiae of sufficiently high quality can be useful for identification, even in prints having large sections of low resolution. We develop a score with a scale of 0-100 (low to high quality) that characterizes (via gradients) the clarity of a feature, and then show results of quality scores on minutiae from NIST's public SD27a latent fingerprint database containing prints judged by "experts" as "good," "bad," or "ugly." The scores correlate well with the general classification and serve as objective, versus subject, measures of minutiae quality.

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