6,163 research outputs found
Fingerprint Match in Box
We open source fingerprint Match in Box, a complete end-to-end fingerprint
recognition system embedded within a 4 inch cube. Match in Box stands in
contrast to a typical bulky and expensive proprietary fingerprint recognition
system which requires sending a fingerprint image to an external host for
processing and subsequent spoof detection and matching. In particular, Match in
Box is a first of a kind, portable, low-cost, and easy-to-assemble fingerprint
reader with an enrollment database embedded within the reader's memory and open
source fingerprint spoof detector, feature extractor, and matcher all running
on the reader's internal vision processing unit (VPU). An onboard touch screen
and rechargeable battery pack make this device extremely portable and ideal for
applying both fingerprint authentication (1:1 comparison) and fingerprint
identification (1:N search) to applications (vaccination tracking, food and
benefit distribution programs, human trafficking prevention) in rural
communities, especially in developing countries. We also show that Match in Box
is suited for capturing neonate fingerprints due to its high resolution (1900
ppi) cameras
Gender Determination using Fingerprint Features
Several previous studies have investigated the gender difference of the fingerprint features. However, regarding to the statistical significance of such differences, inconsistent results have been obtained. To resolve this problem and to develop a method for gender determination, this work proposes and tests three fingertip features for gender determination. Fingerprints were obtained from 115 normal healthy adults comprised of 57 male and 58 female volunteers. All persons were born in Taiwan and were of Han nationality. The age range was18-35 years. The features of this study are ridge count, ridge density, and finger size, all three of which can easily be determined by counting and calculation. Experimental results show that the tested ridge density features alone are not very effective for gender determination. However, the proposed ridge count and finger size features of left little fingers are useful, achieving a classification accuracy of 75% (P-valu
High accuracy and error analysis of indoor visible light positioning algorithm based on image sensor
In recent years, with the increasing demand for indoor positioning service,
visible light indoor positioning based on image sensors has been widely
studied. However, many researches only put forward the relevant localization
algorithm and did not make a deep discussion on the principle of the visible
light localization. In this paper, we make a deep discussion on the principle
of the two-light positioning algorithm and the three-light positioning
algorithm based on the image sensor, which includes how these positioning
algorithms work and the errors analysis. Based on the discussion above, we
propose two methods to improve the positioning accuracy, which is rotation
method and dispersion circle method respectively. In our experiment, we have
numerically and experimentally verified the two optimization methods and we
obtained good positioning results. Especially, the positioning accuracy of the
dual-lamp positioning algorithm based on dispersion circle optimization is up
to 1.93cm, while the average positioning error is only 0.82cm, which is
state-of-the-art of the same type of positioning system at present.Comment: This paper presents a centimeter-level precise positioning system
based on image sensor and visible light LED. In this paper, the principle of
dual-light positioning algorithm and three-lamp positioning algorithm based
on image sensor is deeply and respectively analyzed. And the error generation
in the algorithm is discusse
MonoStream: A Minimal-Hardware High Accuracy Device-free WLAN Localization System
Device-free (DF) localization is an emerging technology that allows the
detection and tracking of entities that do not carry any devices nor
participate actively in the localization process. Typically, DF systems require
a large number of transmitters and receivers to achieve acceptable accuracy,
which is not available in many scenarios such as homes and small businesses. In
this paper, we introduce MonoStream as an accurate single-stream DF
localization system that leverages the rich Channel State Information (CSI) as
well as MIMO information from the physical layer to provide accurate DF
localization with only one stream. To boost its accuracy and attain low
computational requirements, MonoStream models the DF localization problem as an
object recognition problem and uses a novel set of CSI-context features and
techniques with proven accuracy and efficiency. Experimental evaluation in two
typical testbeds, with a side-by-side comparison with the state-of-the-art,
shows that MonoStream can achieve an accuracy of 0.95m with at least 26%
enhancement in median distance error using a single stream only. This
enhancement in accuracy comes with an efficient execution of less than 23ms per
location update on a typical laptop. This highlights the potential of
MonoStream usage for real-time DF tracking applications
Texture to the Rescue: Practical Paper Fingerprinting based on Texture Patterns
In this paper, we propose a novel paper fingerprinting technique based on
analyzing the translucent patterns revealed when a light source shines through
the paper. These patterns represent the inherent texture of paper, formed by
the random interleaving of wooden particles during the manufacturing process.
We show these patterns can be easily captured by a commodity camera and
condensed into to a compact 2048-bit fingerprint code. Prominent works in this
area (Nature 2005, IEEE S&P 2009, CCS 2011) have all focused on fingerprinting
paper based on the paper "surface". We are motivated by the observation that
capturing the surface alone misses important distinctive features such as the
non-even thickness, the random distribution of impurities, and different
materials in the paper with varying opacities. Through experiments, we
demonstrate that the embedded paper texture provides a more reliable source for
fingerprinting than features on the surface. Based on the collected datasets,
we achieve 0% false rejection and 0% false acceptance rates. We further report
that our extracted fingerprints contain 807 degrees-of-freedom (DoF), which is
much higher than the 249 DoF with iris codes (that have the same size of 2048
bits). The high amount of DoF for texture-based fingerprints makes our method
extremely scalable for recognition among very large databases; it also allows
secure usage of the extracted fingerprint in privacy-preserving authentication
schemes based on error correction techniques.Comment: This manuscript has been accepted for publication in the ACM
Transactions on Privacy and Security (TOPS, formerly TISSEC) in 201
IriTrack: Liveness Detection Using Irises Tracking for Preventing Face Spoofing Attacks
Face liveness detection has become a widely used technique with a growing
importance in various authentication scenarios to withstand spoofing attacks.
Existing methods that perform liveness detection generally focus on designing
intelligent classifiers or customized hardware to differentiate between the
image or video samples of a real legitimate user and the imitated ones.
Although effective, they can be resource-consuming and detection results may be
sensitive to environmental changes. In this paper, we take iris movement as a
significant liveness sign and propose a simple and efficient liveness detection
system named IriTrack. Users are required to move their eyes along with a
randomly generated poly-line, and trajectories of irises are then used as
evidences for liveness detection. IriTrack allows checking liveness by using
data collected during user-device interactions. We implemented a prototype and
conducted extensive experiments to evaluate the performance of the proposed
system. The results show that IriTrack can fend against spoofing attacks with a
moderate and adjustable time overhead
Implementation of FPR for Safe and Secured Internet Banking
In this paper, we present an enhanced approach for fingerprint segmentation based on Canny edge detection technique and Principal Component Analysis (PCA). The performance of the algorithm has been evaluated interms of decision error trade-off curve so fan over all verification system. Experimental results demonstrate the robustness of the system
Design of an embedded iris recognition system for use with a multi-factor authentication system.
This paper describes in detail the design, manufacturing and testing of an embedded iris scanner for use with a multifactor authentication system. The design process for this project included hardware design from part selection to board design to populating. Additionally, this process included the entirety of the software development, though the iris recognition process was largely based on other works. The functional requirements for the overall multi-factor authentication system were to have three authentication methods with a thirty second window to complete all three. The system acceptance accuracy was required to be greater than 75%. Those requirements therefore dictate that the iris scanner module must also have an acceptance accuracy higher than 75% and perform iris recognition in a few seconds so that the user can gain admittance in the allotted window of time. While the hardware has been verified and tested, further development and testing is necessary on the software and image processing. This work is funded by the Department of Energy’s Kansas City National Security Campus, operated by Honeywell Federal Manufacturing & Technologies, LLC under contract number DE-NA0002839
HST ultraviolet spectral energy distributions for three ultraluminous infrared galaxies
We present HST Faint Object Camera ultraviolet (230 nm and 140 nm) images of
three ultraluminous infrared galaxies (ULIG: L_ir > 10^12 L_sun) selected from
the IRAS Revised Bright Galaxy Sample. The purpose is to estimate spectral
energy distributions (SEDs) to facilitate the identification of similar objects
at high redshift in deep optical, infrared, and submm surveys.
All three galaxies (VII Zw031 = IRAS F12112+0305, and IRAS F22491-1808) were
well detected at 230 nm. Two of the three were marginally detected at 140 nm.
The fluxes, together with ground-based optical and infrared photometry, are
used to compute SEDs over a wide wavelength range. The measured SEDs drop from
the optical to the ultraviolet, but the magnitude of the drop ranges from a
factor of ~3 in IRAS F22491-1808 to a factor of ~100 in VIIZw031. This is most
likely due to different internal extinctions. Such an interpretation is also
suggested by extrapolating to ultraviolet wavelengths the optical internal
extinction measured in VIIZw031. K-corrections are calculated to determine the
colors of the sample galaxies as seen at high redshifts. Galaxies like VIIZw031
have very low observed rest-frame UV fluxes which means that such galaxies at
high redshift will be extremely red or even missing in optical surveys. On the
other hand, galaxies like IRAS F12112+0305 and IRAS F22491-1808, if seen at
high redshift, would be sufficiently blue that they would not easily be
distinguished from normal field galaxies, and therefore, identified as ULIGs.
The implication is then that submillimeter surveys may be the only means of
properly identifying the majority of ULIGs at high redshift.Comment: AJ in press, TeX, 23 pages, 7 tab, 17 figs available also (at higher
resolution) from http://www.ast.cam.ac.uk~trentham/ufigs.htm
Enhancing Trust in eAssessment - the TeSLA System Solution
Trust in eAssessment is an important factor for improving the quality of
online-education. A comprehensive model for trust based authentication for
eAssessment is being developed and tested within the score of the EU H2020
project TeSLA. The use of biometric verification technologies to authenticate
the identity and authorship claims of individual students in online-education
scenarios is a significant component of TeSLA. Technical Univerity of Sofia
(TUS) Bulgaria, a member of TeSLA consortium, participates in large-scale pilot
tests of the TeSLA system. The results of questionnaires to students and
teachers involved in the TUS pilot tests are analyzed and summarized in this
work. We also describe the TeSLA authentication and fraud-detection instruments
and their role for enhancing trust in eAssessment.Comment: Presented at the Conference on Technology Enhanced Assessment (TEA),
2018. 18 pages, 2 tables, 3 figure
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