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Touchless fingerprint recognition systems do not require contact of the finger with any acquisition surface and thus provide an increased level of hygiene, usability, and user acceptability of fingerprint-based biometric technologies. The most accurate touchless approaches compute 3-D models of the fingertip. However, a relevant drawback of these systems is that they usually require constrained and...
In this paper, we present a complete virtual environment for the computation of synthetic three-dimensional samples representing free falling wood strands.The proposed method permits to simulate acquisitions performed by real multiple view setups in which the stream of strands falling out of a conveyor belt is analyzed with image processing techniques in order to compute the particle size distribution...
Three-dimensional models of fingerprints obtained from contactless acquisitions have the advantages of reducing the distortion present in traditional contact-based samples and the effects of dirt on the finger and the sensor surface. Moreover, they permit to use a greater area for the biometric recognition.
Contactless fingerprint recognition systems are being researched in order to reduce intrinsic limitations of traditional biometric acquisition technologies, encompassing the release of latent fingerprints on the sensor platen, non-linear spatial distortions in the captured samples, and relevant image differences with respect to the moisture level and pressure of the fingertip on the sensor surface.
Current contactless fingertip recognition systems based on three-dimensional finger models mostly use multiple views (N > 2) or structured light illumination with multiple patterns projected over a period of time. In this paper, we present a novel methodology able to obtain a fast and accurate three-dimensional reconstruction of the fingertip by using a single two-view acquisition and a static...
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