Paper Info
Title
Lfiq: Latent Fingerprint Image Quality
Abstract
Latent fingerprint images are typically obtained under non-ideal acquisition conditions, resulting in, incomplete or distorted impression of a finger; and ridge structure corrupted by background noise. This necessitates involving latent experts in latent fingerprint examination, including assessing the value of a latent print as forensic evidence. However.; it is now generally agreed that human factors (e.g., human visual perception, expertise of latent examiners, workload, etc.) can significantly affect the reliability and consistency of the value determinations made by latent examiners. We propose an objective quality measure for latent,fingerprints, called Latent Fingerprint Image Quality (LFIQ), that can be effectively used to distinguish latent fingerprints of good quality, which do not require any human intervention, and to compensate for the subjective nature of value determination by latent examiners. We investigate several factors that determine the latent quality: (i) ridge quality based on ridge clarity and connectivity of good ridge structures, (ii) minutiae reliability based on a minutiae dictionary learnt from high quality minutia patches, and (iii) position of the finger by detecting a reference point. The proposed LFIQ metric is based on triangulation of minutiae incorporating the above three factors. Experimental results show that (i) the proposed LFIQ is a good predictor of the latent matching performance by AFIS and (ii) it is also correlated with value determination by latent examiners.
Year
DOI
Venue
2013
10.1109/BTAS.2013.6712750
2013 IEEE SIXTH INTERNATIONAL CONFERENCE ON BIOMETRICS: THEORY, APPLICATIONS AND SYSTEMS (BTAS)
Keywords
Field
DocType
fingerprint identification,mesh generation,reliability,human factors
Background noise,Pattern recognition,Human visual perception,Workload,Minutiae,Computer science,Image matching,Fingerprint image,Fingerprint,Triangulation (social science),Artificial intelligence
Conference
Citations 
PageRank 
References 
4
0.56
5
Authors
4
Name
Order
Citations
PageRank
Soweon Yoon1625.69
Kai Cao220718.68
Eryun Liu313811.46
Anil Jain4335073334.84