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- Fingerprint recognition : contributions to latent matching and 3D fingerprint target generation
- Arora, Sunpreet Singh
- Electronic Theses & Dissertations
Automatic fingerprint capture and comparison methods have led to the ubiquitous use of fingerprint-based person recognition in applications ranging from law enforcement and border control to national identification and smartphone unlock. However, despite tremendous advancements in the state-of-the-art, improvements are still needed in case of some challenging applications, e.g, to recognize poor quality and distorted fingerprints acquired from non-cooperative users, improve fingerprint reader...
Show moreAutomatic fingerprint capture and comparison methods have led to the ubiquitous use of fingerprint-based person recognition in applications ranging from law enforcement and border control to national identification and smartphone unlock. However, despite tremendous advancements in the state-of-the-art, improvements are still needed in case of some challenging applications, e.g, to recognize poor quality and distorted fingerprints acquired from non-cooperative users, improve fingerprint reader fidelity, and determine anti-spoofing capability of different fingerprint readers. In this thesis, we address two such impending challenges: (i) comparison of latent prints found at crime scenes to large collections of reference prints (rolled tenprints or slap fingerprints) in law enforcement databases, and (ii) operational evaluation of fingerprint recognition systems prior to large scale deployment.We develop a feedback paradigm that uses reference print features to dynamically select latent features during matching. The paradigm automatically determines if dynamic latent feature selection would improve recognition performance using a statistical hypothesis test and qualitatively decides the regions in latent and reference prints for applying feedback. The paradigm when used in conjunction with a state-of-the-art latent matcher demonstrates marked improvement (0.5-3.5%) in latent matching accuracy.Further, we develop a framework for crowdsourcing latent print feature markup to a pool of fingerprint examiners. The framework uses a statistical criterion to automatically determine when crowdsourcing is required, and a method to dynamically determine the number of examiners needed for latent feature markup. Significant recognition performance improvements (2.5-11.5%) are obtained using crowdsourced markups in conjunction with a state-of-the-art latent matcher.Finally, we design and fabricate single-finger and whole hand 3D targets for operational evaluation of optical and capacitive fingerprint readers as well as for end-to-end evaluation of fingerprint recognition systems. 2D calibration patterns with known characteristics (e.g. synthetic fingerprints with known features, sine gratings with known orientation and spacing) are projected onto electronic 3D finger and hand surfaces to create electronic 3D single-finger and whole hand targets. A high-resolution 3D printer is used to manufacture physical 3D single-finger and whole hand targets from electronic targets. Other contributions include: (i) a method to chemically clean the 3D printed targets without impacting the engraved target patterns, (ii) a procedure to apply conductive coating of metal/metal oxides on the surface of 3D targets using DC sputtering, (iii) fidelity measurement techniques using optical microscopy to assess the 3D target generation process, and (iv) methods to evaluate fingerprint readers using the fabricated 3D targets. We demonstrate that the 2D calibration pattern features are reproduced with high fidelity both on the electronic and physical 3D single-finger and whole hand targets and that the intra-class variations between images of the 3D targets do not degrade matching accuracy (at 0.01% false accept rate). We evaluate several commercially available single-finger and slap contact-based and contactless optical readers as well as capacitive readers using the generated 3D targets.