14-05-2012, 12:02 PM
A Multi Biometric System Using Combined Vein and Fingerprint
Identification
[attachment=21965]
INTRODUCTION
Biometrics technology is based on identification of
individuals by a physical or behavioural characteristic.
Examples of recognition of physical characteristics are:
fingerprints, iris, face or even hand geometry. Behavioural
characteristic can be the voice, signature or other keystroke
dynamics. What make fingerprints idealistic for personal
digital identification is the fact that the fingerprint pattern is
composed of ridges and valleys that form a unique
combination of distinguishing features of each finger (as
shown in Fig. 1); also, fingerprint characteristics do not vary
in time [1]. A comparison of popular biometrics are shown
in Tables I and II. From the comparison, it’s clear to see
why fingerprint and vein biometrics are both an attractive
alternative in comparison to other biometrics.
The fingerprint sensor selection
One of the most important tasks considering an
automatic fingerprint biometric recognition system is the
biometric pattern extraction from the captured image of the
fingerprint. Due to imperfections of the acquired image, in
some cases certain pattern can be missed by the extraction
algorithm. Image imperfections can also generate errors in
determining the coordinates of each true pattern and its
relative orientation of the image. All these facts make
remarkable decrease of the recognition system reliability
[7]. Thus, an efficient and reliable fingerprint scanning
apparatus is an essential component of the whole system.
INCORPORATING FINGER VEIN BIOMETRIC
In visible light, the vein structure on the back
of the hand is not easily discernible. The visibility
of the vein structure varies significantly depending
on factors such as age, levels of subcutaneous fat,
ambient temperature and humidity, physical
activity, and hand position. In addition a multitude
of other factors including surface features such as
moles, warts, scars, pigmentation and hair can also
obscure the image. Fortunately, the use of thermo
graphic imaging in the near IR spectrum exhibit
marked and improved contrast between the
subcutaneous blood vessels and surrounding skin,
and eliminates many of the unwanted surface
features [14].
CONCLUSION
The design of the system uses two biometrics
identifiers, fingerprint and vein patterns. The
fingerprint sensor FPC1011F1 fingerprint is
connected to the FPC2020 fingerprint processor
with a direct interface , as well as to an external PC
for storing templates. The sensor and fingerprint
processor is integrated with a vein pattern
extraction system that consists of a set of LEDs
that generates near infrared light that
penetrates the body Tissue. An image of the
veins pattern is revealed as the near infrared
light is reflected in the haemoglobin in the
blood.
Identification
[attachment=21965]
INTRODUCTION
Biometrics technology is based on identification of
individuals by a physical or behavioural characteristic.
Examples of recognition of physical characteristics are:
fingerprints, iris, face or even hand geometry. Behavioural
characteristic can be the voice, signature or other keystroke
dynamics. What make fingerprints idealistic for personal
digital identification is the fact that the fingerprint pattern is
composed of ridges and valleys that form a unique
combination of distinguishing features of each finger (as
shown in Fig. 1); also, fingerprint characteristics do not vary
in time [1]. A comparison of popular biometrics are shown
in Tables I and II. From the comparison, it’s clear to see
why fingerprint and vein biometrics are both an attractive
alternative in comparison to other biometrics.
The fingerprint sensor selection
One of the most important tasks considering an
automatic fingerprint biometric recognition system is the
biometric pattern extraction from the captured image of the
fingerprint. Due to imperfections of the acquired image, in
some cases certain pattern can be missed by the extraction
algorithm. Image imperfections can also generate errors in
determining the coordinates of each true pattern and its
relative orientation of the image. All these facts make
remarkable decrease of the recognition system reliability
[7]. Thus, an efficient and reliable fingerprint scanning
apparatus is an essential component of the whole system.
INCORPORATING FINGER VEIN BIOMETRIC
In visible light, the vein structure on the back
of the hand is not easily discernible. The visibility
of the vein structure varies significantly depending
on factors such as age, levels of subcutaneous fat,
ambient temperature and humidity, physical
activity, and hand position. In addition a multitude
of other factors including surface features such as
moles, warts, scars, pigmentation and hair can also
obscure the image. Fortunately, the use of thermo
graphic imaging in the near IR spectrum exhibit
marked and improved contrast between the
subcutaneous blood vessels and surrounding skin,
and eliminates many of the unwanted surface
features [14].
CONCLUSION
The design of the system uses two biometrics
identifiers, fingerprint and vein patterns. The
fingerprint sensor FPC1011F1 fingerprint is
connected to the FPC2020 fingerprint processor
with a direct interface , as well as to an external PC
for storing templates. The sensor and fingerprint
processor is integrated with a vein pattern
extraction system that consists of a set of LEDs
that generates near infrared light that
penetrates the body Tissue. An image of the
veins pattern is revealed as the near infrared
light is reflected in the haemoglobin in the
blood.