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Latent Fingerprint Training With NIST Special Database 27 and Universal Latent Workstation



Michael D. Garris


UPDATE: 1/20/2017 It has been determined that this dataset lacks the documentation required by NIST for distribution. This dataset has been withdrawn and is no longer available for purchase or download from NIST. NIST regrets any inconvenience from the withdrawal of this dataset. NIST researchers are working to replace the withdrawn data as quickly as possible. The National Institute of Standards and Technology, in collaboration with the FBI, has published NIST Special Database 27 (SD27) Fingerprint Minutiae from Latent and Matching Tenprint Images. This CD-ROM collection contains images of 258 latent crime scene fingerprints and their matching rolled tenprints. In addition, minutiae features validated by a team of professional latent examiners are provided for each fingerprint. Meanwhile, the FBI has also developed the Universal Latent Workstation (ULW). This workstation has been designed to render and enhance fingerprint images, assist the operator in labeling minutiae and other fingerprint features, and formatting this information into a standard transaction file for searching federal, state, and local law enforcement fingerprint repositories. Using the ULW in conjunction with SD27 poses a powerful and inexpensive training tool for fingerprint examiners. This report documents the steps needed to load SD27 fingerprint images into ULW, and how trainee results can then be overlaid with the validated minutiae in SD27. Given these steps, a variety of training scenarios are possible.
NIST Interagency/Internal Report (NISTIR) - 6799
Report Number


ANSI/NIST, database, FBI, fingerprint, grayscale, IAFIS, image, latent, minutiae


Garris, M. (2001), Latent Fingerprint Training With NIST Special Database 27 and Universal Latent Workstation, NIST Interagency/Internal Report (NISTIR), National Institute of Standards and Technology, Gaithersburg, MD, [online], (Accessed December 5, 2023)
Created September 1, 2001, Updated January 30, 2018