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Latent fingerprints are one of the most crucial sources of evidence in forensic investigations. As such, development of automatic latent fingerprint recognition systems to quickly and accurately identify the suspects is one of the most pressing problems facing fingerprint researchers. One of the first steps in manual latent processing is for a fingerprint examiner to perform a triage by assigning...
Latent fingerprints are the most frequently encountered and reliable crime scene evidence used in forensics investigations. Automatic methods for quantitative assessment of a latent in terms of (i) value for individualization (VID), (ii) value for exclusion only (VEO), and (iii) no value (NV), are needed to minimize the workload of latent examiners so that they can pay more attention to challenging...
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...
Extracting reliable fingerprint orientation over low quality fingerprints is still a challenging problem. In this paper, we analyze the distribution of divergence and curl of fingerprint orientation vector field. Then a div-curl regularization model is proposed to minimize the combination of weighted divergence, curl and data fidelity term. This model yields a new nonlinear partial differential equation...
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