04-05-2012, 12:25 PM
Fingerprint Biometrics via Low-cost Sensors and Webcams
[attachment=21246]
INTRODUCTION
The possibility to obtain fingerprint images by using lowcost
cameras and off-the-shelf webcams has a great practical
importance since nowadays fingerprint biometrics can be
successfully achieved only by using dedicated sensors. The
diffusion of general purpose cameras is rapidly growing, and
they can be found easily on laptops and cellular phones.
Unfortunately, the images of human fingerprints acquired
from these kinds of sensors are very different from the
images obtained by dedicated fingerprint sensors.
CHARACTERISTICS OF THE INPUT IMAGES
Dedicated sensors tend to produce high-contrast image of
the ridge structure of the fingertip (Figure 2, right). The
background of the image tends to be very flat and continuous,
permitting a simple segmentation of the ridge structure.
By using a state-of-the-art sensor, the produced image can
have a very small noise component, and the presence of
artifacts in the final image is rare (presence in the output
image of spurious characteristics which are not present on
the finger surface, such as false bifurcations or ends of
the ridges, as well as deformations of the original ridge
structure). With the dedicated sensor the ridge structure
is produced by the pressure of the friction ridges of the
fingertip on the sensor surface. The noise on the image can
be related to dryness or high humidity of the skin, excessive
or limited pressure of the fingertip on the sensor and bad
condition of the skin surface (e.g., illness, scratches, usage
of abrasive material and other particular working conditions).
The Failure to Acquire/Enroll ration is considered to be few
percents, depending on operational conditions and on the
population.
THE PROPOSED METHOD
In the literature, the interest in low-cost sensors is rapidly
growing and some preliminary methods have been presented
mainly focused on the extraction of the ridge structure
[1], [2]. Similar image processing techniques have been
exploited to cope with the palm image biometrics [3], [4].
This work aims to contribute in a twofold manner: we
propose an innovative complete sequence of modules for
image-based fingertip biometrics and we present the results
of an experimental campaign (Scenario Evaluation [6]). In
our experiments, to compare the proposed approach with the
classical solutions, the fingerprints of the same individuals
have been acquired by using two sensors: webcam and
dedicated sensor.
CONCLUSIONS
This paper presented an innovative composition of techniques
to extract the fingerprint ridge structure by image
processing in images acquired by low-cost cameras and webcams.
The approach we propose aims for allowing the use
of webcams and low-cost cameras as interoperable devices
for fingerprint biometrics when these devices are already
Rate (FNMR) is plotted vs. the False Match Rate (FMR).
or can become easily available while the security level
of the envisioned applications does not need the accuracy
of dedicated devices.
[attachment=21246]
INTRODUCTION
The possibility to obtain fingerprint images by using lowcost
cameras and off-the-shelf webcams has a great practical
importance since nowadays fingerprint biometrics can be
successfully achieved only by using dedicated sensors. The
diffusion of general purpose cameras is rapidly growing, and
they can be found easily on laptops and cellular phones.
Unfortunately, the images of human fingerprints acquired
from these kinds of sensors are very different from the
images obtained by dedicated fingerprint sensors.
CHARACTERISTICS OF THE INPUT IMAGES
Dedicated sensors tend to produce high-contrast image of
the ridge structure of the fingertip (Figure 2, right). The
background of the image tends to be very flat and continuous,
permitting a simple segmentation of the ridge structure.
By using a state-of-the-art sensor, the produced image can
have a very small noise component, and the presence of
artifacts in the final image is rare (presence in the output
image of spurious characteristics which are not present on
the finger surface, such as false bifurcations or ends of
the ridges, as well as deformations of the original ridge
structure). With the dedicated sensor the ridge structure
is produced by the pressure of the friction ridges of the
fingertip on the sensor surface. The noise on the image can
be related to dryness or high humidity of the skin, excessive
or limited pressure of the fingertip on the sensor and bad
condition of the skin surface (e.g., illness, scratches, usage
of abrasive material and other particular working conditions).
The Failure to Acquire/Enroll ration is considered to be few
percents, depending on operational conditions and on the
population.
THE PROPOSED METHOD
In the literature, the interest in low-cost sensors is rapidly
growing and some preliminary methods have been presented
mainly focused on the extraction of the ridge structure
[1], [2]. Similar image processing techniques have been
exploited to cope with the palm image biometrics [3], [4].
This work aims to contribute in a twofold manner: we
propose an innovative complete sequence of modules for
image-based fingertip biometrics and we present the results
of an experimental campaign (Scenario Evaluation [6]). In
our experiments, to compare the proposed approach with the
classical solutions, the fingerprints of the same individuals
have been acquired by using two sensors: webcam and
dedicated sensor.
CONCLUSIONS
This paper presented an innovative composition of techniques
to extract the fingerprint ridge structure by image
processing in images acquired by low-cost cameras and webcams.
The approach we propose aims for allowing the use
of webcams and low-cost cameras as interoperable devices
for fingerprint biometrics when these devices are already
Rate (FNMR) is plotted vs. the False Match Rate (FMR).
or can become easily available while the security level
of the envisioned applications does not need the accuracy
of dedicated devices.