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ULTRASONIC
SETUP FOR FINGERPRINT PATTERNS
DETECTION AND EVALUATION |
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Wiesław
Bicz*, Mieczysław
Pluta**
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INTRODUCTION |
The scope of potential use of
identification systems widens, including restricted area or
confidential data access , credit card use etc. Only in 1993
banks lost more than three billions dollars due to credit
cards forgery and misuse [1].
"No two
fingerprints from different fingers have ever been found
identical ..." [2].
That is why
the fingerprint structure is successfully used in
criminology [3] and is one of the
properties that can be used for the person verification
purpose [3]. Any fingerprint can be easily
scanned and the verification process which goes along with
it and lasts within pushing of a button seems natural and
ergonomic. So far , optical sensors for the recognition of
fingerprints, palm of the hand and the structure of eye
blood vessels have been utilized and all of them have some
disadvantages.
The authors
have proposed and have been developing ultrasonic method of
fingertip papillary lines representation acquisition [4].
We have stated that ultrasound is highly sensitive and
brings out high contrast at the subsurface structure of the
finger . One may expect that due to the uniqueness of the
skin structure and its specific physical properties, the
preparation of an artificial finger would be very
complicated .
At the early
stage of the research we concentrated on the far field
diffractive representation (or Fourier transform) of the
fingerprint structure. Now we are able to measure pulse
response representation of the finger-tip and perform
reconstruction of papillary lines from the set of measured
data. Some techniques of reconstruction quality improvements
and results achieved are presented below.
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DETECTION AND RECONSTRUCTION METHODS |
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| Figure
1a. Schema of the data acquisition head |
In all of our
setups finger-tip is applied to a window of ultrasonic head.
The head contains one , two or a ringshaped matrix of
electro-acoustic transducers (Figure 1a). Ultrasonic method
of acquiring fingerprint representation is based on sending
acoustic signals towards the finger and detecting the echo.
Localization
of the sender T 'and receiver T allows us to detect first
diffractive order of the fingerprint structure:
,
(1)
-ultrasound wave length ( 0.25 mm in water by 6 MHz),
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| Figure
1b. Project geometry |
- papillary line distance ( 0.3 - 0.9 mm for most fingers) .
what makes °.
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Reflected pulse model |
To get the data needed for the
reconstruction of the finger-tip structure we apply the
pulse method. The sender generates short acoustic pulses and
the receiver , moving around a circle , detects the
responses sampled then by a 50 MHz scope board. For 3D
object observed by a flat receiver, tilted by angle Q,
space variables p, z and time t are related by
the time of flight relation:
,
(2)
c - sound
velocity
(The same
relation holds for spherical cross-sections of the object
and properly located point transducers.)
By the fixed
angle Q, we can then measure time in millimeters and
use the space variable p paralely with t . For
2-D flat object g(x,y), the receiver rotated by the
angle f observes the scaled projection
(3)
In real case
we have to take into account the shape of voltage spike ,
used to drive the transducer , and time depending transfer
functions of the sender and receiver
, .
The echo e(t) is then described by the multiple
convolution
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| Figure
2. Visual presentation of measured echo matrix e(t,f)
of a fingerprint. |
(4)
where
represents the pulse response of the setup and
set of projections of the object scaled to the time
domain..An example of the echo of a finger tip structure is
presented in the Figure 2.
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| Point
Spread Distribution of reconstruction |
There exist well known methods of reconstruction of the 2D
function g'(x,y) from the set of projections r(p,f).
Back projection algorithm which we use is linear and
stationary , which means that we can analyze the quality of
reconstruction using 2D point spread distribution (PSD). The
projection of a point d(x0,y0) gives a trace in a form of a
sinusoidal line, therefore during the reconstruction we find
the value for every point by integration along such lines.
,
(5)
z -
defocusing parameter,
- echo scaled to the space domein,
For a point
object we get the 2D PSD function of the setup (including
reconstruction algorithm). Due to the rotational symmetry of
the PSD , it is enough to calculate and show its crooss-
section. The shape of PSD depends on the defocusing z, and
thus we get 3D
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| Figure
3a. good quality |
PSD. Now we
can consider transversal and axial resolution of
reconstruction in Reileigh's sense (a distance from the
maximum to the first zero of PSD in p and z direction).
There are
three examples of pulse responses
in Figure 3. We have analyzed narrow band transducer,
transducer with short pulse response and a signal after
deconvolution.
Figure 3 shows
that even using transducers of several periods per one pulse
response we are able to
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| Figure
3b. poor quality |
obtain narrow
central maximum of PSD, due to the suppression of side loops
by the reconstruction
integral (5).
The disadvantage of such transducer is that we can get also
a false reconstruction for another defocusing parameter
(Figure 3 (a)).
Deconvolution
dramatically improves the pulse response of the setup, or
the amplitude and phase of of the signal spectrum specially
at the higher frequencies (Figure3(c)).
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| Figure
3c. poor quality transducer after convolution |
Figure 3.
Examples of pulse responses h(p), its fourier transforms H(v)
and cross-sections of 2D PSD
depending on
defocussing parameter z0, for electronic setup and
transducers of:
good quality -
(a), poor quality - (b), poor quality transducer after
convolution - (c)
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ENHANCEMENTS OF THE RECONSTRUCTION |
Due to the limited quality of transducers , electronic
noises and interference with signals from deeper layers , we
have to use some enhancement techniques to obtain
satisfactorily reconstructed image. The first of them is
deconvolution of the echo. Also three methods of 2D image
processing are used by us: smoothing , directional filtering
in spectral domain and binearization.
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| Figure
4a. |
Figure
4b. |
Figure
4c. |
Figure
4d. |
Figure
4e. |
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| Figure
4f. |
Figure
4g. |
Figure
4h. |
Figure
4i. |
Figure 4.
(a) - optical picture of
a fingerprint,
(b) - optical picture after binearization,
(c) - reconstructed and enhanced acoustic picture of the
same finger,
(d) - acoustic fingerprint reconstruction,
(e) - acoustic fingerprint reconstruction after
directional filtering,
(f) - acoustic fingerprint reconstruction after
deconvolution and directional filtering,
(g) - another acoustic fingerprint reconstruction after
deconvolution and directional filtering,
(h) - binearization of (g),
(i) - 2D Fourier spectrum of (g),
We
see suppresion of the noises after directional filtering (Figure
4e), and appearance of fine detals after deconvolution (Figure
4f).
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| CONCLUSIONS |
Measurements and reconstructions of finger-tips show that
acoustic field diffraction occurs mainly on fingerprint
lines. Quality of the reconstructed images depends on the
bandwidth of the transducer , but may be improved by some
signal and image enhancement methods. Reconstructed images
are so similar in form to the optical ones that one can use
the same classification and recognition methods. The
advantage of the ultrasonic method is the uniqueness of the
acoustic properties of the finger-tip , which means that
preparing its dummy should be very difficult.
Presented
setup may by also used for measuring of other objects and be
treated as synthetic aperture microscope of .14mm resolution.
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| REFERENCES |
[1].
Kriminalität , "Mafia nera" , Der Spiegel, No.11,
p. 81, März 1994.
[2]. A.A. Moenssnens, "Fingerprint
Techniques " , Chilton Company (1971)
[3]. Cz. Grzeszyk , "Daktyloskopia
", PWN, Warszawa, 1994,(in polish)
[4]. R.H. Andersen, P. Jürgensen , "Fingerprint
Verification - For use in Identity Verification Systems",
Aalborg University , (1993)
[5]. W. Bicz, M. Pluta, "Ultrasonic
sensor for fingerprints recognition ", COE '94 Warszawa
, Poland, (to be published by SPIE Vol 2634 / p. 104).
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| Legends |
| * |
Research - Production
Enterprise OPTEL Ltd. ul. Otwarta 10a, 50-212 Wrocław |
| ** |
Institute of Physics,
Technical University of Wrocław, Wybrzeże Wyspiańskiego 27,
50-370 Wrocław, Poland |
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