LFIQ: Latent fingerprint image quality

Yoon, Soweon; Cao, Kai; Liu, Eryun; Jain, Anil K.

doi:10.1109/btas.2013.6712750

Cited by 42 publications

(21 citation statements)

References 16 publications

(6 reference statements)

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“…• If the pattern I being projected is a synthetic fingerprint image, then reference coordinates [r u , r v ] are extracted from the fingerprint image using the method in [28]. The next step is to determine the one-to-one mapping between the pixel locations (u, v) on I and the vertices V OF on S OF P .…”

Section: Mapping 2d Calibration Pattern To 3d Surfacementioning

confidence: 99%

Design and Fabrication of 3D Fingerprint Targets

Arora

Cao

Jain

et al. 2016

IEEE Trans.Inform.Forensic Secur.

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Standard targets are typically used for structural (white-box) evaluation of fingerprint readers, e.g., for calibrating imaging components of a reader. However, there is no standard method for behavioral (black-box) evaluation of fingerprint readers in operational settings where variations in finger placement by the user are encountered. The goal of this research is to design and fabricate 3D targets for repeatable behavioral evaluation of fingerprint readers. 2D calibration patterns with known characteristics (e.g. sinusoidal gratings of pre-specified orientation and frequency, fingerprints with known singular points and minutiae) are projected onto a generic 3D finger surface to create electronic 3D targets. A state-of-the-art 3D printer (Stratasys Objet350 Connex) is used to fabricate wearable 3D targets with materials similar in hardness and elasticity to the human finger skin. The 3D printed targets are cleaned using 2M NaOH solution to obtain evaluation-ready 3D targets. Our experimental results show that (i) features present in the 2D calibration pattern are preserved during the creation of the electronic 3D target, (ii) features engraved on the electronic 3D target are preserved during the physical 3D target fabrication, and (iii) intra-class variability between multiple impressions of the physical 3D target is small. We also demonstrate that the generated 3D targets are suitable for behavioral evaluation of three different (500/1000 ppi) PIV/Appendix F certified optical fingerprint readers in the operational settings.Keywords-3D fingerprint targets, fingerprint reader evaluation, 2D calibration patterns, 3D printing, 2D pattern to 3D surface projection.

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Section: Mapping 2d Calibration Pattern To 3d Surfacementioning

confidence: 99%

Design and Fabrication of 3D Fingerprint Targets

Arora

Cao

Jain

et al. 2016

IEEE Trans.Inform.Forensic Secur.

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“…• The translation constraint ensures the origin in S * is at a fixed distance d below the reference point detected on the fingerprint image I using the method described in [20]. This distance d is set to 50 pixels in our experiments.…”

Section: Surface Parameterizationmentioning

confidence: 99%

3D Fingerprint Phantoms

Arora

Cao

Jain

et al. 2014

2014 22nd International Conference on Pattern Recognition

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One of the critical factors prior to deployment of any large scale biometric system is to have a realistic estimate of its matching performance. In practice, evaluations are conducted on the operational data to set an appropriate threshold on match scores before the actual deployment. These performance estimates, though, are restricted by the amount of available test data. To overcome this limitation, use of a large number of 2D synthetic fingerprints for evaluating fingerprint systems had been proposed. However, the utility of 2D synthetic fingerprints is limited in the context of testing end-to-end fingerprint systems which involve the entire matching process, from image acquisition to feature extraction and matching. For a comprehensive evaluation of fingerprint systems, we propose creating 3D fingerprint phantoms (phantoms or imaging phantoms are specially designed objects with known properties scanned or imaged to evaluate, analyze, and tune the performance of various imaging devices) with known characteristics (e.g., type, singular points and minutiae) by (i) projecting 2D synthetic fingerprints with known characteristics onto a generic 3D finger surface and (ii) printing the 3D fingerprint phantoms using a commodity 3D printer. Preliminary experimental results show that the captured images of the 3D fingerprint phantoms can be successfully matched to the 2D synthetic fingerprint images (from which the phantoms were generated) using a commercial fingerprint matcher. This demonstrates that our method preserves the ridges and valleys during the 3D fingerprint phantom creation process ensuring that the synthesized 3D phantoms can be utilized for comprehensive evaluations of fingerprint systems.

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“…have proposed a latent matcher for automatic identification of suspects by using the extended features, namely, singularity, ridge quality map, and ridge flow map [17], [18]. The latent fingerprint image quality is measured by Spectral Image Validation and Verification (SIVV)-based metric [19] and the latent fingerprint image quality (LFIQ) metric based on triangulation of minutiae points [20].…”

Section: Introductionmentioning

confidence: 99%

Enhancements to latent fingerprints in forensic applications

Ramaiah

Rao

Mohan

2014

2014 19th International Conference on Digital Signal Processing

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Latent fingerprint identification is a challenging task in criminal investigation due to the poor quality of ridge impressions and less region of interest on the fingerprint. In this paper, we propose a semi-automated latent fingerprint identification to markup fingerprint landmarks manually using the image enhancement filters which will improve the identification performance in lights-out mode. It uses the global and local adaptive binarization, and global minutia features with ISO/IEC 19794-2 standard fingerprint templates. In the latent fingerprint identification, the fingerprints are matched with rolled fingerprint database from standard law enforcement database. Also, the latent fingerprints are matched with the plain fingerprints database from the data collected using three different live-scanners. The efficacy of the proposed latent fingerprint identification systems is demonstrated on the standard NIST SD-27 (special database-27) latent prints database.

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LFIQ: Latent fingerprint image quality

Abstract: Latent fingerprint images are typically obtained under non-ideal acquisition conditions, resulting in incomplete or

Cited by 42 publications

References 16 publications

Design and Fabrication of 3D Fingerprint Targets

Design and Fabrication of 3D Fingerprint Targets

3D Fingerprint Phantoms

Enhancements to latent fingerprints in forensic applications

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