Next Generation Identification system: Latent print matching algorithm and casework practices
2022
Tom, Kyle R. | Knorr, Kathryn B. | Davis, Christine E.
The development of automated fingerprint identification systems (AFIS) revolutionized casework in the friction ridge community. Through the evolution of AFIS development, algorithms have become increasingly sensitive and specific. Internal validation studies conducted by the Federal Bureau of Investigation Laboratory Division’s Latent Print Units (LPU) assessed the performance of the Next Generation Identification (NGI) system’s latent print matching algorithm under the various encoding methods of the Multi-Biometric Identification System (MBIS) platform for the purpose of casework implementation. Based on the results of these studies, casework practices in the LPU have become more streamlined and efficient. The increase in accuracy of the latent print matching algorithm has reduced the number of candidates compared per search. For fingerprints, the results showed the best indicator for the correct mate being the number one candidate was the difference in score between the first and second candidate. When the score difference was 1200 or higher, the first candidate was mated in 99.3% of the trials. This understanding may allow for additional quality assurance measures to be implemented in casework.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par National Agricultural Library
Découvrez la collection de ce fournisseur de données dans AGRIS