skip navigation

CrimeSolutions.gov

Add your conference to our Justice Events calendar

PUBLICATIONS

NCJRS Abstract

The document referenced below is part of the NCJRS Library collection.
To conduct further searches of the collection, visit the NCJRS Abstracts Database.

How to Obtain Documents
 
NCJ Number: NCJ 235577     Find in a Library
Title: Automatic Fingerprint Matching Using Extended Feature Set
Author(s): Anil K. Jain
Date Published: 08/2011
Page Count: 66
Sponsoring Agency: National Institute of Justice
US Department of Justice
Office of Justice Programs
United States of America
Grant Number: 2007-RG-CX-K183
Sale Source: National Institute of Justice/NCJRS
Box 6000
Rockville, MD 20849
United States of America

NCJRS Photocopy Services
Box 6000
Rockville, MD 20849-6000
United States of America
Document: PDF 
Type: Report (Study/Research)
Language: English
Country: United States of America
Annotation: This study developed algorithms for encoding and matching extended fingerprint features, created fusion algorithms to combine extended features with minutiae information so as to improve fingerprint matching accuracy, and examined the contributions of various extended features in latent fingerprint matching.
Abstract: Fingerprint friction-ridge features are generally described in a hierarchical order at three different levels: 1evel 1 (ridge flow), 1evel 2 (minutiae points), and 1evel 3 (pores and ridge shape, etc.). Current automated fingerprint Identification Systems (AFIS) generally rely only on a subset of level 1 and level 2 features for matching. On the other hand, latent print examiners often take advantage of a much richer set of features that naturally occur in fingerprints. Fingerprint features, other than minutiae and core/delta, are also referred to as the extended feature set. The experiments conducted determined that almost all the extended features of fingerprints produce some improvement in latent matching accuracy. In addition, extended features at a higher level are more effective in improving latent match accuracy than those at a lower level. Another finding is that high image resolution (at least 1,000 ppi) is necessary, but not sufficient for reliably capturing level 3 features. Based on study findings, the author recommends that extended features at level 1 and level 2 be incorporated into AFIS. Another recommendation is that GUI tools be developed in order to help fingerprint examiners manually mark extended features (especially ridge skeleton) at level 1 and level 2 in latent prints. The author also advises that it is critical to improve the quality of enrolled fingerprints so that a sufficient number of level 3 features can be extracted before level 3 features can have an important role in AFIS. 8 figures and 11 references
Main Term(s): Police policies and procedures
Index Term(s): Fingerprints ; Automated fingerprint processing ; Suspect identification ; Latent fingerprints ; Investigative techniques ; NIJ final report
   
  To cite this abstract, use the following link:
https://www.ncjrs.gov/App/Publications/abstract.aspx?ID=257558

* A link to the full-text document is provided whenever possible. For documents not available online, a link to the publisher's web site is provided.