ISSN 1292-862

TIMA Lab. Research Reports

CNRS INPG UJF

TIMA Laboratory, 46 avenue Félix Viallet, 38000 Grenoble France

1

Abstract— We report recent advances in the development of a tactile fingerprint sensor made by a CMOS compatible front side bulk micromachining technology. This device enables the measurement of a fingerprint by the way of a mechanical scanning principle of the finger roughness. While this sensing principle has shown good results on a first prototype of reduced width, we present here the design, fabrication and test of a new sensor. This sensor contains 256 pressure sensitive microbeams for a total length of 1.28 cm and is fully integrated with analog and mixed signal electronics. In this paper we will detail the general working principle of the tactile fingerprint sensor and the two prototypes that have been manufactured and tested with a special focus on the electronic architecture and the test results of the second prototype.

I. INTRODUCTION

Biometrics are the techniques used to identify an individual by the extraction of physical or behavioural parameters peculiar to him. Biometric recognition is envisaging new solutions using constant features of the users body with the convenience that they cannot be lost, forgotten or stolen.

Nowadays the need for identifying users is becoming more and more necessary for several typical operations such as access control, workstation login or electronic banking. Recent laws will make compulsory the presence of some biometric recordings in passports. Biometric techniques are for example the recognition of the human speech; the characteristics of the face or the hand palm, the pattern of the iris and of course the fingerprints.

The recent emergence of integrated biometric devices with small volumes and small costs will help biometrics to reach the market of portable devices such as credit cards, mobile phones or PDAs to replace traditional alphanumeric passwords.

Fingerprint recognition is the oldest biometric technique. Criminal science has been using it for more than 150 years. This technique may be included in the next generation of passports as one of several electronic biometric records required.

A typical fingerprint includes several singular points so called minutiae (generally a number from 12 to 30). These specific points correspond to the places of ending, bifurcation or crossover of ridges and valleys of the finger (see Figure 1). Extraction of the relative positions and orientations of these minutiae allows creating a specific signature for each user guaranteeing a secured identification.

Fig. 1. Typical fingerprint showing the place of the main type of minutiae: ending ! and bifurcation ". Typical fingerprint recognition systems are based on an optical measurement of the finger. In these systems, the finger is placed on a transparent prism and the image is taken through a camera. The major problem of these systems is the volume and the cost that does not allow any integration in mobile devices. Recently, some solid-state sensors have shown great potential in terms of cost, volume, reliability and integration. Most integrated solid-state fingerprint sensors are based on a capacitive principle [3]- [9]. The measurement principle is the detection of a difference of electrical capacity between contact and non contact parts of the finger on the device. Figure 2 shows a cross section schematic of such a system. They are fabricated, for most of them, with CMOS technologies. Some alternative techniques using optoelectronic [10] [11], pyroelectric [12], thermal [13] or ultrasonic [16] transduction mechanisms have also shown interesting results.

Finger surface

Silicon substrate

Pixel

Transistor Electrodes Fig. 2. Cross section of an integrated capacitive fingerprint sensor. The system detects the difference of capacity between a fixed electrode and the surface of the skin.

AN INTEGRATED MEMS FINGERPRINT SENSOR Benoît CHARLOT1, Fabien PARRAIN2, Nicolas GALY1, Skandar BASROUR1 and Bernard COURTOIS1

1 TIMA Laboratory, 46 Avenue Felix VIALLET 38031 Grenoble, France

2 IEF, Institut dElectronique Fondamentale, Orsay, France

2

A typical fingerprint covers an area of about 100 mm². Solid state fingerprint sensors that require direct contact with the finger must be of large surface which is a disadvantage in terms of cost. Sweeping mode fingerprint sensors, like the sensor presented in this paper, are a good solution to create some compact and low cost devices. Most sweeping mode sensors [3] [12] use a partial matrix containing a reduced number of lines (typically 40 lines). The final image is then recomposed using a superposition technique. The cost is lower for the sensor but an important extra computation process is needed

(a) (b) (c)

Fig. 3. Schematic of the measurement principle and resulting image for three types of fingerprint sensor: full matrix (a), partial matrix (b) and one line sensor (c). Resulting image are respectively: the full scale image, the superposed image and the squeezed or stretched image.

Our sensor contains only one line of sensing elements (actually three rows on the sensor but only one is used at a time). Figure 3 shows a schematic and the output images of these three working principles. This architecture gives the minimum surface but induces some problems on the measurement when the finger speed is not constant. This feature will be discussed in chapter IV.

II. TACTILE FINGERPRINT SENSOR The sensor presented here has two main features with

respect to standard industrial solutions: it is a sweeping sensor and it is a tactile, e.g. mechanical sensor. The tactile measurement is based on the use of piezoresistive microbeams (cantilevers). Such microbeams has been successfully employed in several applications such as magnetic field sensing [14] or gaseous chemical species detection [15].

Figure 4(a) shows a schematic of our sensor. It contains three lines of sensing elements placed besides the electronic parts and the bonding pads. The process of fingerprint acquisition with this sensor is presented in Figure 5. First, the user sweeps its finger along the sensor, placed perpendicularly to the direction of the movement. During this step, the ridges and the valleys that compose the fingerprint will induce deflections in the different microbeams of each line of the sensor. The resistance variation of each piezoresistive gauge is transformed into a voltage variation. A shift register placed on top of each row will switch the signal produced by the microbeams to a transmission line that feeds the analog amplification chain. After this the signal is converted to an 8 bit parallel output. A more detailed description of the internal circuits of the sensor will be given in § IV-B.

Analog

and digital

electronics

CMOS Substrate

Scan electronics

Micromachined

cavity

Connexion pads

Piezoresistive

microbeams

Fig. 4. Schematic view of the tactile fingerprint sensor.

Unlike many other integrated fingerprint sensors, the device presented here uses a mechanical measurement principle. Some previous works have shown tactile fingerprint sensors using an array of capacitive pressure sensors [17] or tactile sensors [18].

3

The transduction mechanism used here for measuring the finger surface involves different elements represented in Figure 6. The finger is pressed and swept along the sensor with user defined pressure and speed. A thin polymer film is laid on the surface of the sensor for protection against pollution and corrosion. This film plays an important role in the transduction since it will smooth the profile of the finger. Elasticity, thickness and the nature of polymer/skin contact will affect the global sensitivity of the device. Some static experiments with a given hydrostatic pressure applied on the surface of the sensor shown allowed us to determine the global sensitivity (see Table 1). It is also shown that a 12µm thick PVC film does not blur significantly the signal [2].

The micromachined cavity width has also an important role since it acts as a displacement limiter and avoids a too important incursion of the skin in the cavity, limiting the microbeams displacement. Some experiments on several cavity widths allowed us to choose the value (see Table 1) that gives the best sensitivity [2].

Fig. 6. Schematic of the tactile measurement of the fingerprint with the piézorésistives microbeams. The figure represents a cross section of the stack of the sensor, the polymer protective sheet and the finger.

At the end of the transduction chain, the microbeams stiffness and the gauge sensitivity (discussed in § II-C) will take an important part in the global sensitivity. The resulting image given by the sensor will be the convolution of the real finger surface through this transduction chain

The sensor is made by means of CMOS-compatible front-

side bulk micromachining (FSBM) technology via the Circuit-Multi-Projects (CMP) service [19]. The Standard CMOS is an Austriamicrosystems 0.6 µm triple metal process. The FSBM technique consists in designing openings through the different CMOS layers so as to obtain naked silicon areas. The passivation layer acts as a mask for the post process etching. After the fabrication of the microelectronic layers, a TMAH anisotropic wet etching post-process allows suspending microstructures by creating a cavity on the silicon substrate, without the need of any additional lithographic step (Figure 7).

The microbeam itself is then composed of a sandwich of all the layers present in the CMOS technology: the LOCOS layer (wet oxide), the gate oxide (wet oxide), and the polysilicon of the grids, the deposited interlevel oxides, the interconnection metallic layers and the silicon nitride passivation.

This stable low cost MEMS technology allows integrating the sensor part and electronic circuits in the same chip. Figure 8 shows SEM micrographs of the chip after TMAH release. We can easily see one end of the micromachined cavity, the microbeams and part of the electronic circuit.

MOS Transistor

Micromachined cavity

Suspended microstructure

Openings

Silicon

Fig. 7. Cross section schematic of the CMOS compatible front side bulk micromachining technology employed for the fingerprint sensor.

Amplifier

Vin VoutVin ADCVoutIb

The user sweeps its finger

along the sensor Scanning of the

microbeams ∆R/R measurement Amplification and

filtering Analog to digital

conversion

Fig. 5. Fingerprint sensor working principle.

4

Fig. 8. SEM photo of the microbeams.

The microbeams, detailed in Figures 6 and 8, are

composed of a sandwich of different oxides, polysilicon and metal layers available in the CMOS process. Design parameters of the microbeams are shown in Table 1.

The design of the microbeams has been carried out by analytical modelling and Finite Element Analysis (FEA). Fixed specifications were the pitch and numbers of microbeams, the materials and thicknesses of the microbeams and the piezoresistive coefficients of the gauges. The models have taken into account the different layers, their mechanical parameters and the topology of the microbeam.

The shape of the stress gauges, i.e. number of bends, total resistance and place and length of the gauge at the clamped end of the beam, has been chosen in order to maximise the relative resistance variation for a given force at the end of the beam.

The sensitivity (∆R/R for a given force at the end of the microbeam) has been extrapolated from both the hydrostatic measurements and the microbeam simulation.

The natural resonance frequency of the microbeams was computed around 690 kHz. It allows a very fast mechanical reading of each microbeam and thus high line scanning frequency (up to 200 kHz).

Some experiments on large deformations of such microbeams have shown that no plastic deformations occur during load cycling. Unfortunately, we do not have any fine characterization of the force/displacement/gauge response behaviour of the microbeams without the polymer film. Tests have been conducted in real working conditions, e.g. with a finger swept along the sensor and these results will be presented in the next chapters for both fabricated prototypes.

TABLE I MICROBEAM PARAMETERS

Microbeam parameters value Length 100µm Widths 30µm Thickness ~4µm Pitch 50µm Out of plane stiffness (computed) 186Nm-1 In plane Stiffness (computed) 10075Nm-1 Sensitivity 171 295 N-1

Natural frequency 690kHz Width of the micromachined cavity 210µm

Polysilicon gauge parameters value Width 1.2µm Length 8x28µm Nominal resistance 6.5kΩ Nominal resistance mismatch 1.73% Longitudinal piezoresistive coefficient -1.3 10-10 Pa-1 Transverse piezoresistive coefficient 7.6 10-11 Pa-1

III. FIRST PROTOTYPE A first reduced prototype of reduced length has been made

for the validation of the sensing principle. This first chip contains only 38 microbeams and a simple analog amplifier and output. The measurement of the fingerprint has been performed with a thin polymer sheet lied over the sensor to protect it from pollution and corrosion. Measurement of the sensor in real working configuration (e.g. with a finger on it) has been performed by capturing the analog output with a data acquisition card. Figure 9 shows a comparison between a references ink fingerprint and the output of the sensor. Because of the reduced length, the scanning zone is only 2mm wide. However we can notice the excellent matching of the results with the presence of the same 3 minutiae in each image. The maximum resistance variation is about 6%. We can notice the high contrast of the image. The data acquisition process removes the offsets of each microbeam by removing the background image measured previously without the finger. More details about this first device can be found in [1] and [2].

38 µbeams

120 scanned lines

0

1

2

3

4

5

6

Resistance Variation (%)

Ink Reference Sensor image

Fig. 9. Test results of the first prototype. The fingerprint on the left is the ink reference and the image on the right is the output of the sensor.

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IV. SECOND PROTOTYPE The second prototype has a full length, containing 256

microbeams for a total scanning zone of 1.28 cm which is enough for the measurement of most fingerprints. Except some changes in the analog circuits, the global architecture, the technology and the microbeams are the same as the first prototype. Figure 10 shows the general electronic architecture and the pin-out of the chip. Figure 11 shows the layout of the second prototype. The whole chip contains about 53,000 transistors.

The circuitry embedded in our sensor is made up of three main blocks: a shift register allowing the scanning of the row of microstructures, the piezoresistive gauge resistance readout circuit and an 8 bit successive-approximation A/D converter.

The new analog section architecture has been redesigned with respect to prototype 1.

This has been done in order to improve the signal/noise ratio but mostly to have an offset cancelling circuit, thus avoiding the use of a calibration step during the operation.

The sequential measurement of each piezoresistive gauge placed at the base of each microbeam is controlled by a simple shift-register composed by D flip-flop cells (one by pixel). Following a clock signal (from 20 to 200 kHz), a single bit at high level will activate the pixels one by one.

When a pixel is not selected, analog electronics are turned off in order to minimize the power consumption (i.e. the different current mirrors employed are turned off).

The gauge resistance readout circuit uses a correlated double sampling switch capacitor architecture driven by a pair of non-overlapping clocks (φ1 and φ2). This architecture makes possible to cancel the DC offset signal due to the electronics included in each pixel, the DC input offset of the different op-amps and at the same time reduces low frequency noise. A simplified view of the entire readout circuit schematics is shown in figure 12.

Row 3

Row 2

Row 1

S/H

ADC8 bits

output registry

MUX

Ampli.

drivinglogic

Bias circuit

Clk, Reset ...

GainTest

VshVampVtrans1Vtrans2Vtrans3

Vbias

8 bits //

transimpedance amplifier

Testwrapper

VrefpVrefn

Digital signals Analog signals Fig. 10. Schematic of the global electronic architecture of the chip.

2 mm256 microbeams Fig. 11. Layout of the chip.

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The single ended pixel electronic allows performing a

differential measurement between the gauge and a reference resistor placed above the bulk where the mechanical strains are nonexistent. The gauge and the reference resistor have the same orientation, the same geometry and are placed very close so as to match technological dispersions. The gauge resistance change is transformed into current signal and feeds a transresistance amplifier through the transmission line that is polarized at a constant voltage Vpol. In this way it is possible to get rid of parasitic capacitance of this very long analog interconnect line (in the case of the first pixel, this line has a length of about 1.28 cm).

With respect to the size of the different transistors (T1, T2 and T3), following the active phase φ 1 or φ 2 we can show that the current Ip through the transmission line can be written as:

++=

+−=

I)R(fI)(II)R(fI)(I

b2p

b1p

∆∆φ

∆∆φ (1)

when 2..13 L

W2L

W

=

Where Ib is the bias current, f a linear function that

depends on the bias current and the transistors sizes [A], and W and L the width and lengths of the transistors. The quantity ∆I depends on the transistors mismatching. Notice that a common centroid layout configuration has been used to realize T1 and T2 so as to minimize ∆I. The current source present at the input of the transresistance amplifier allows subtracting the DC current Ib from Ip. Consequently, the output voltage Va of the transresistance amplifier is given by:

++−=

++=

1offGG2a

1offGG1a

VIR)R(fR)(VVIR)R(fR)(V

∆∆φ

∆∆φ (2)

where Voff1 is the input offset voltage of the first op-amp. The last element of the resistance readout circuit is a

typical switch capacitor amplifier. This amplifier works as follows: during phase φ the expression of the electrical charge at node A is given by:

( ) ( )( ) 2off11a2off11A VCVVCQ +−= φφ (3)

where Voff2 is the input offset voltage of the second op-

amp. During phase φ 2 the charge at node A becomes:

( ) ( )( ) ( )S2off22a2off12A VVCVVCQ −+−= φφ (4)

For charge conservation at node A (QA(φ )=QA(φ 2)) using the two last equations we can give the expression of the amplifier output voltage VS during phase φ 2:

( ) ( )

( ) ( ) ( )[ ]2a1a2

12S

2a2a

VVCCV

QQ

φφφ

φφ

−=⇒

= (5)

This last expression shows that the amplifier input offset has been cancelled. It is now possible to determinate VS(φ 2) in function of the gauge resistance change :

( ) )R(fRCC2V G

2

12S ∆φ = (6)

This relationship shows that the output voltage of the readout circuit is totally independent of the different offset DC signals but also independent of the mismatching of the two transistors T1..2 employed within the pixels. Using the size of the different transistors and the characteristics of the employed technology (Austriamicrosystems CUP 0.6 µm) the expression of VS(φ 2) can be written as :

( ) RICµL

WL

WCC

RV 2/3boxp

2/1

2..132

1G2S ∆φ

=

−

(7)

Here, Cox is the transistor gate capacitance per unit area and µp the mobility of holes for the given technology.

The analog signal from the readout circuit is digitalized

using an 8 bit converter so as to provide the value of the gauge resistance change by the way of a digital parallel bus. The implemented A/D converter uses a successive-approximation architecture that is one of the most popular approaches due to the moderate circuit complexity. In order to achieve the A/D conversion following the given algorithm, this kind of converter employs a D/A converter and a comparator. The converter uses a simple folded resistor ladder. The comparator is based on an offset cancelled switch capacitor architecture. The ADC can work up to 1 MSamples/s with a precision of 7.7 effective bits.

7

φ1φ2

φ1φ2

φ2

φ2φ1

φ1

φ1φ1

φ2

φ2

φ1

φ2

φ1

Rg

C1

C2

C3

C4Vb

Vb Vpol

R R+DR

e

e e

e

Vdd

Gnd Analog GND

Vs

T1 T2

T1

T3T4

T5 T6

DC R

Q

Q e

D

ClkReset

Next (e)Prev

Pixel level electronics Transimpedance amplifier Amplifier Sample and hold

Ip

Ip

Ib

Im

VaVb

Current mode transmission line (fixed potential)

NextPrev

Pixel line scanning

PixelNextPrev

PixelNextPrev

Pixel

VsAmpli S/H

Digital signals (clk, reset, f1, f2 ...)Analog signals (Vb ...)

Fig. 12. Simplified schematic of the global electronic architecture of the chip.

V. FINGERPRINT MEASUREMENT Since the second chip embeds an analog to digital

converter, it can be digitally controlled. The measurement setup employs a development card, an ALTERA NIOS Excalibur apex 20k that drives the sensor by supplying digital signals and clock. The controller records the 8 bit output but does not make any signal treatment at the moment. The sensor is mounted on a ceramic board, with protection resin on connection pads as shown in Figure 13. This ceramic board is mounted on a larger PCB that includes an oscillator for the ADC clock (1.8 MHz) and several components for providing different voltage references and switches. The chip is covered with a polymer thin film for protection against pollution. Different films such as polyester (MYLAR) with various thicknesses (from 6 to 20µm) have been tested. The best results have been obtained with Polyethylene films. Lubrication (soap) is used to produce a viscous contact between the finger and the polymer sheet and avoid sticking.

Fig. 13. Fingerprint sensor on board with protective resin on bonding wires.

The card records an image of 640 pixels of length and 256 pixels of width, with a scan clock frequency of 150 kHz so that the capture duration is about 1s. The finger is placed on the sensor and swept along the sensor at the start signal.

Figure 14 shows the sensor card connected to the NIOS card. Measured data are collected with a PC.

8

Fig. 14. Test setup composed of the ALTERA NIOS Excalibur apex 20k card connected to the sensor card.

Figure 15 shows the experimental results for all the fingers (except the thumb) of the authors. A first analysis of these images shows the high contrast (nearly black and white) obtained with the sensor.

Forefinger Middle finger Ring finger Little finger

Fig. 15. Rough images measured from the sensor for the fingers of one of the authors.

We can see on from Figure 16 the presence of vertical black lines that corresponds to broken microbeams. The fracture of a microbeam may occur during the fabrication process, mainly in the anisotropic etching post process or during the operation when the protective film is removed from the surface.

Another point is that the offset and mismatch cancellation technique used gives good results since the background is white (except for those broken lines). The sensor does not require any background cancellation procedure or calibration step.

Another point that appears on these images is the non-uniformity of the movement of the finger that is the main problem of one row sensors. This non-uniformity is more important when the capture duration is low and when there is solid contact of the finger on the polymer film rather than a viscous contact (with lubrication).

Local variation of the finger speed will deform the fingerprint and change the related biometric signature. This problem can be solved by performing a measurement of the finger speed either by including a specific device on the sensor or by using the three rows and an additional computing step to rebuild the image.

VI. CONCLUSIONS We have presented in this paper the design and test of an

integrated tactile fingerprint sensor made with a CMOS compatible bulk micromachining technology. The monolithic nature of this sensor allows the integration in the same silicon substrate of MEMS microstructures and the signal conditioning analog interfaces together with digital cores. This high level of integration provides many advantages such as low prize, reproducibility and miniaturization.

The main problems of our sensor are finger speed control and reliability. We will address these issues in the near future. A finger measurement technique will be developed. Some other protection film materials such as fluorocarbon (TEFLON) will be considered. Alternative protection technique based on filling the cavity with a silicon gel will also be evaluated.

Further works will target the driving of the sensor by a microcontroller and the implementation of the dedicated algorithms for the signal conditioning, fingerprint recognition, enrolment and matching that are in development at the lab.

ACKNOWLEDGMENT The authors want to thank Robin Rolland of the Centre

Inter Universitaire de Microélectronique (CIME) for its help in testing and programming.

Fingerprint sensor

9

Fig. 16. Measured fingerprint of the forefinger.

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Micromachined Tactile Fingerprint Sensor", Symposium on Design, Integration and Test of MEMS/MOEMS, 6-8 Mai 2002, Cannes - Mandelieu, France.

[2] F.Parrain, Capteur intégré tactile d'empreintes digitales à microstructures piezorésistives, Ph.D thesis, INPG, 2002.

[3] STMicroelectronis Touchip fingerprint sensors http://us.st.com/stonline/products/support/touchip/

[4] J.W. Lee, D.J. Min, J. Kim and W. Kim, "A 600-dpi Capacitive Fingerprint Sensor Chip and Image-Synthesis Technique", IEEE Journal of Solid-State Circuits, Vol. 34, No. 4, pp. 469-475, April 1999.

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[8] J.W. Lee, D.J Min, J. Kim, and W. Kim, A 600-dpi Capacitive Fingerprint Sensor Chip and Image-Synthesis Technique, IEEE Journal of Solid-State Circuits, Vol. 34, No. 4, pp. 469-475, April 1999.

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[12] Atmel FingerChip www.atmel.com/products/Biometrics. [13] J.S. Han, T. Kadowaki, K. Sato and M. Shikida, "Thermal

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[14] V. Beroulle, Y. Bertrande, L.Latorre and P.Nouet, "Monolithic Piezoresistive CMOS Magnetic Field Sensors, Sensors and Actuators A: Physical, Vol. 103, 1-2, pp. 23-32, 2003.

[15] D. Lange, C. Hagleitner, A. Hierlemann, O. Brand and H. Baltes, "Complementary Metal Oxide Semiconductor Cantilever Arrays on a Single Chip: Mass-Sensitive Detection of Volatile Organic Compounds", Anal. Chem, Vol 74, pp. 3084-3095, 2002.

[16] Z. Gumienny, M. Pluta, W. Bicz and D. Kosz, "Ultrasonic Setup for Fingerprint Patterns Detection and Evaluation", Acoustical Imaging, Vol. 22, 1996.

[17] P. Rey, P. Charvet, M.T. Delaye, S. Abou Hassan, "A High Density Capacitive Pressure Sensor Array For Fingerprint Sensor Application", TRANSDUCERS '97, 1997 International Conference on Solid-State Sensors and Actuators, Chicago, June 16-19 1997.

[18] R.J. De Souza and K.D. Wise, "A Very High Density Bulk Micromachined Capacitive Tactile Imager", TRANSDUCERS '97, 1997 International Conference on Solid-State Sensors and Actuators, Chicago, June 16-19 1997.

[19] CMP IC and MEMS prototyping service : http://cmp.imag.

640 pixels

256

pixe

ls

Broken microbeams Finger speed non-uniformities

Reaction time