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NCJ Number: NCJ 241242     Find in a Library
Title: Performance Evaluation of Automated Fingerprint Identification Systems for Specific Conditions Observed in Casework Using Simulated Fingermarks
Journal: Journal of Forensic Sciences  Volume:57  Issue:4  Dated:July 2012  Pages:1075 to 1081
Author(s): Arent de Jongh, Ph.D. ; Crystal M. Rodriguez, M.Sc.
Date Published: 07/2012
Page Count: 7
Document: HTML 
Type: Research (Applied/Empirical)
Language: English
Country: United States of America
Annotation: This paper aims to illustrate to fingerprint examiners the relevance of evaluating the AFIS performance under specific conditions by carrying out five types of performance tests.
Abstract: Few studies have been reported on the performance evaluation of automated fingerprint identification systems (AFIS) for fingermark-to-fingerprint comparisons. This paper aims to illustrate to fingerprint examiners the relevance of evaluating the AFIS performance under specific conditions by carrying out five types of performance tests. The conditions addressed are the number of minutiae assigned to a fingermark, manual and automatic assignment of the minutiae, the finger region from which the fingermark originates, the degree of distortion in the fingermark, and the difference in orientation between fingermarks and fingerprints. In these tests, the magnitude of the influence for each condition was quantified. The comparisons were performed using a research AFIS technology with simulated fingermarks. Simulated fingermarks provide a practical way to create fingermarks for specific conditions in large quantities. The results showed that each condition influences the performance significantly, emphasizing the relevance of developing, and applying performance tests for specific conditions. Abstract published by arrangement with John Wiley & Sons.
Main Term(s): Forensics/Forensic Sciences
Index Term(s): Evidence identification and analysis ; Evaluation techniques ; Latent fingerprints ; Evaluation measures ; Fingerprint classification ; Performance Measures
   
  To cite this abstract, use the following link:
https://www.ncjrs.gov/App/Publications/abstract.aspx?ID=263332

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