Patent Publication Number: US-2023140424-A1

Title: Fingerprint sub-image capture

Description:
TECHNICAL FIELD 
     The present disclosure relates to a method of a fingerprint sensing system arranged in a smartcard configured to acquire fingerprint data of a user with a fingerprint sensor for biometric authentication, and a fingerprint sensing system performing the method. 
     BACKGROUND 
     In a fingerprint sensing system, a fingerprint sensor of the system must be initialized with correct settings in order to be able to acquire fingerprint images of high quality to be used by a device being equipped with the fingerprint sensor for authenticating an individual to which the fingerprint belongs. Parameters of the fingerprint sensor to be initialized included e.g. sensor gain, offset of an analogue-to-digital converter (ADC) of the sensor, pixel sensitivity, etc. 
     This initialization is undertaken upon the fingerprint sensor detecting a finger touching a sensing area of the sensor, where the sensor transits from a sleep mode to an active mode. When transiting to the active mode, the sensor captures a sub-image of the finger touching the sensing area whereupon the sub-image is evaluated for determining whether it is of sufficient quality. A sub-image is a fingerprint image associated with a relatively small section of the sensing area of the sensor. 
     If not, the sensor settings are slightly changed, and a new sub-image is captured, and so on, until a sub-image is captured which is considered to be of sufficiently high quality. The sensor settings applied when capturing this image will as a result be the settings used for capturing one or more full fingerprint images from which the individual may be authenticated. 
     However, this initialization process is time consuming and processing-heavy, in particular if the fingerprint sensor in implemented in a device such as a smart card where timing restrictions are harsh. 
     SUMMARY 
     One object is to solve, or at least mitigate this problem in that art, and thus provide an improved method of acquiring fingerprint data of a user with a fingerprint sensor in a smartcard for biometric authentication. 
     This object is attained in a first aspect by a method of a fingerprint sensing system arranged in a smartcard, the fingerprint sensing system being configured to acquire fingerprint data of a user with a fingerprint sensor for biometric authentication. The method comprising detecting a finger of the user contacting a sensing area of the fingerprint sensor, initializing the fingerprint sensor with a predetermined sensor setting, acquiring, for the finger being detected to contact the sensing area of the fingerprint sensor, a calibration sub-image which is confined in size to a subarea of the sensing area, determining whether or not a quality criterion is met for the acquired calibration sub-image, and if so acquiring (S505) one or more further sub-images confined in size to a subarea of the sensing area, and combining a plurality of the acquired further sub-images into a representation of a fingerprint of the user, wherein the further sub-images are acquired during a time period when the smartcard is not engaged in waiting time extension (WTX) request signalling with a card reader with which the smartcard performs contactless communication. 
     This object is attained in a second aspect by a fingerprint sensing system arranged in a smartcard, the fingerprint sensing system comprising a fingerprint sensor being configured to acquire fingerprint data of a user for biometric authentication, and a processing unit being configured to cause the fingerprint system to be operative to detect a finger of the user contacting a sensing area of the fingerprint sensor, initialize the fingerprint sensor with a predetermined sensor setting, acquire, for the finger being detected to contact the sensing area of the fingerprint sensor, a calibration sub-image which is confined in size to a subarea of the sensing area, determine whether or not a quality criterion is met for the acquired calibration sub-image, and if so to acquire one or more further sub-images confined in size to a subarea of the sensing area, and to combine a plurality of the acquired further sub-images into a representation of a fingerprint of the user, wherein the further sub-images are acquired during a time period when the smartcard is not engaged in WTX request signalling with a card reader with which the smartcard performs contactless communication. 
     Thus, the fingerprint sensor detects that a finger contacts a sensing area of the sensor. Thereafter, or even before, the fingerprint sensor is initialized with a predetermined sensor setting. This may be a default setting which empirically may have proven to result in captured images of a high quality. 
     Then, a calibration sub-image is acquired by the fingerprint sensor being initialized with the default settings, which is used for determining whether or not the sensor settings are adequate or if they need to be adjusted. In order to be able to use a fingerprint image for biometric authentication of the user, the quality of the image must be sufficiently high. 
     If not, it is not feasible to match the captured fingerprint image to previously enrolled fingerprint templates of the fingerprint sensing system. Hence, the processor determines whether or not the quality of the captured calibration sub-image complies with a predetermined quality criterion. For instance, the perceived quality of the image must be sufficiently high. 
     If so, the processor proceeds with controlling the fingerprint sensor to capture further sub-images using the default sensor settings. 
     It should be noted that the calibration sub-image typically is smaller than the further sub-images subsequently being captured for the purpose of performing authentication of the fingerprint of the user, which further sub-images in their turn are smaller than a full fingerprint image. For instance, if the size of the sensing area of the sensor is 160 × 160 pixels, the further sub-images may have a size of 40 × 160 pixels, while the calibration sub-image is e.g. 32 × 24 pixels. 
     The captured further sub-images captured are continuously being written into a respective location of memory as they are being captured. The capturing of the further sub-images is repeated until a sufficient number of sub-images have been captured, such that a fully or partly complete fingerprint image subsequently can be read out from the memory. For instance, 2-4 further sub-images are captured and written into the memory, but this may vary dependent on configuration of the system. 
     After having captured a sufficient number of sub-images these sub-images are read out, and thus combined, by the processor into one single image representing the fingerprint of the user. 
     These further sub-images are advantageously captured during a part of a WTX period when the smartcard is not engaged in WTX request signalling with a card reader in order to avoid performing processing-heavy operations during a period when the smartcard is harvesting energy from signals being received wirelessly from the card reader. 
     In an embodiment, in case the quality criterion is not met for the calibration sub-image, the processor modifies the sensor settings based on data derived from the acquired calibration sub-image for which the quality criterion is not met. Thereafter, the fingerprint sensor is reinitialized with the modified sensor settings, and a new calibration sub-image is acquired using the modified sensor settings. In case the quality criterion is not met for the acquired new calibration sub-image, the sensor settings are modified until a calibration sub-image is captured for which the quality criterion is met. 
     In an embodiment, the processor detects whether or not the finger is stable on the sensing area of the sensor and if so proceeds to initialize the fingerprint sensor with a predetermined sensor setting, and if not detection of a finger of the user contacting a sensing area of the fingerprint sensor is restarted. 
     In an embodiment, the processor detects whether or not the finger is stable on the sensing area, and if not the acquired further sub-images are discarded. 
     In an embodiment, the acquiring of any sub-images — the calibration sub-images as well as the further sub-images — are scheduled to be performed during a part of a WTX period when the smartcard is not engaged in WTX request signalling with the card reader. 
     In an embodiment, one or more of the detection of a finger, detection whether or not the finger is stable on the sensing area, and initializing and reinitializing the fingerprint sensor is performed during a time period when the smartcard is not engaged in WTX request signalling with the card reader. 
     In a third aspect, a computer program is provided comprising computer-executable instructions for causing a fingerprint sensing system to perform the method of the first aspect when the computer-executable instructions are executed on a processing unit included in the fingerprint sensing system. 
     In a fourth aspect, a computer program product is provided comprising a computer readable medium, the computer readable medium having the computer program according to the third aspect embodied thereon. 
     Generally, all terms used in the claims are to be interpreted according to their ordinary meaning in the technical field, unless explicitly defined otherwise herein. All references to “a/an/the element, apparatus, component, means, step, etc.” are to be interpreted openly as referring to at least one instance of the element, apparatus, component, means, step, etc., unless explicitly stated otherwise. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless explicitly stated. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Aspects and embodiments are now described, by way of example, with reference to the accompanying drawings, in which: 
         FIG.  1    schematically illustrates a smartcard comprising a bendable main body and a biometric sensor such as a fingerprint sensor for authorizing transactions carried out using the smart card; 
         FIG.  2    illustrates an enlarged view of the fingerprint sensor onto which a user places her finger; 
         FIG.  3    shows the fingerprint sensor being part of a fingerprint sensing system; 
         FIG.  4    illustrates a general prior art sensor initialization process being performed in order to subsequently enable a fingerprint sensor to capture a fingerprint image; 
         FIG.  5    illustrates in more detail steps performed in the finger stable search of  FIG.  4   ; 
         FIG.  6    illustrates a contactless transaction being performed between a credit card and a card reader; 
         FIG.  7    shows a timing diagram illustrating re-occurring WTX requests and the time periods required for the sensor to capture fingerprint images; 
         FIG.  8    shows a timing diagram illustrating re-occurring WTX requests and fingerprint images being captured according to an embodiment; 
         FIG.  9    illustrates a flowchart of a method of acquiring fingerprint data of a user with a fingerprint sensor in an embodiment; 
         FIG.  10    shows a timing diagram illustrating various actions performed by the method of  FIG.  9   ; 
         FIG.  11    illustrates a flowchart of a method of acquiring fingerprint data of a user with a fingerprint sensor in another embodiment; 
         FIG.  12    shows a timing diagram illustrating various actions performed by the method of  FIG.  11   ; 
         FIG.  13    illustrates a flowchart of a method of acquiring fingerprint data of a user with a fingerprint sensor in a further embodiment; and 
         FIG.  14    shows an alternative finger stability detection approach as compared to that in  FIG.  13   . 
     
    
    
     DETAILED DESCRIPTION 
     The aspects of the present disclosure will now be described more fully hereinafter with reference to the accompanying drawings, in which certain embodiments of the invention are shown. 
     These aspects may, however, be embodied in many different forms and should not be construed as limiting; rather, these embodiments are provided by way of example so that this disclosure will be thorough and complete, and to fully convey the scope of all aspects of invention to those skilled in the art. Like numbers refer to like elements throughout the description. 
       FIGS.  1 - 3    illustrates a fingerprint sensing system in which embodiments may be implemented. 
       FIG.  1    schematically illustrates a smartcard  100  comprising a bendable main body  101  and a biometric sensor  102  such as a fingerprint sensor for authorizing transactions carried out using the smartcard  100 . 
     It is understood that the fingerprint sensor  102  according to embodiments of the invention may be implemented in other types of electronic devices, such as laptops, remote controls, tablets, smart cards, smartwatches, etc., or any other type of present or future similarly configured device utilizing fingerprint sensing. 
       FIG.  2    illustrates a somewhat enlarged view of the fingerprint sensor  102  onto which a user places her finger  201 . The fingerprint sensor  102  is configured to comprise a plurality of sensing elements. A single sensing element (also denoted as a pixel) is in  FIG.  2    indicated by reference numeral  202 . 
       FIG.  3    shows the fingerprint sensor  102  being part of a fingerprint sensing system  110  implemented in e.g. the smartcard  100  of  FIG.  1   . The fingerprint sensing system  110  comprises the fingerprint sensor  102  and a processing unit  103 , such as one or more microprocessors, for controlling the fingerprint sensor  102  and for analysing captured fingerprints. The fingerprint sensing system  110  further comprises a memory  105 . The fingerprint sensing system  110  in turn, typically, forms part of the smartcard  100  as exemplified in  FIG.  1   . The sensor  102  and the processing unit  103  may both perform tasks of an authentication process. It may further be envisaged than in case a sensor with sufficient processing power is utilized, the sensor  102  may take over authentication tasks from the processing unit  103 , and possibly even replace the processing unit  103 . 
     The fingerprint sensor  102  may be implemented using any kind of current or future fingerprint sensing principle, including for example capacitive, optical, ultrasonic or thermal sensing technology. 
     Now, upon an object contacting the fingerprint sensor  102 , the sensor  102  will capture an image of the object in order to have the processing unit  103  determine whether the object is a fingerprint of an authorised user or not by comparing the captured fingerprint to one or more authorised previously enrolled fingerprint templates pre-stored in the memory  105 . 
     In a general authorization process, the user places a finger  201  on a sensing area of the fingerprint sensor  102 . The processing unit  103  evaluates the captured fingerprint and compares it to one or more enrolled authenticated fingerprint templates stored in the memory  105 . If the recorded fingerprint matches the pre-stored template, the user is authenticated and the processing unit  103  will accordingly inform e.g. a point-of-sale (POS) terminal with which it is involved in a transaction process such that the transaction undertaken is authenticated. 
     With reference again to  FIG.  3   , the steps of the method performed by the fingerprint sensing system  110  are in practice performed by the processing unit  103  embodied in the form of one or more microprocessors arranged to execute a computer program  107  downloaded to the storage medium  105  associated with the microprocessor, such as a RAM, a Flash memory or a hard disk drive. Alternatively, the computer program is included in the memory (being for instance a NOR flash) during manufacturing. The processing unit  103  is arranged to cause the fingerprint sensing system  101  to carry out the method according to embodiments when the appropriate computer program  107  comprising computer-executable instructions is downloaded to the storage medium  105  and executed by the processing unit  103 . The storage medium  105  may also be a computer program product comprising the computer program  107 . Alternatively, the computer program  107  may be transferred to the storage medium  105  by means of a suitable computer program product, such as a Digital Versatile Disc (DVD) or a memory stick. As a further alternative, the computer program  107  may be downloaded to the storage medium  105  over a network. The processing unit  103  may alternatively be embodied in the form of a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a complex programmable logic device (CPLD), etc. It should further be understood that all or some parts of the functionality provided by means of the processing unit  103  may be at least partly integrated with the fingerprint sensor  102 . 
       FIG.  4    illustrates a general prior art sensor initialization process  300  being performed in order to subsequently enable the fingerprint sensor  102  to capture a full fingerprint image in step S 304 . 
     In a first step S 301  designated “sleep mode”, the processor  103  controlling the sensor  102 , which performs software and/or hardware based finger stable detection, is in a low-power mode where groups of sensor elements  202  located at group-wise spaced apart positions in an array of sensor elements are monitored. 
     When more than a threshold number of sensor elements  202  indicate a touch of a finger  201 , the finger  201  is indeed detected and a transition to a second state designated “finger stable search” is performed in step S 302 , i.e. the sensor  102  exits the sleep mode of step S 301  and enters an active mode. 
     While in the “finger stable search” state of step S 302 , sub-images are captured and processed to determine whether the finger  201  being pressed against the sensor  102  is stable or not. 
     When capturing a sub-image, a sub-section of the sensing area of sensor  102  is selected to capture an image of the finger  201  touching the sub-section. The sub-section is an area which is confined in size with respect to the total sensing area. The image captured of the part of the finger  201  touching the sub-section is referred to as a sub-image. As an example, while the total sensing area may amount to for instance 160 × 160 or 96 × 96 sensing elements (aka. pixels), the sub-section may constitute 40 × 160 pixels and 24 × 96 pixels, respectively. 
     In case the processing of sub-images in step S 302  does not result in a stable state being determined and a termination criterion is satisfied, the touch is considered “not stable” and a transition back to the sleep mode in step S 301  is performed. 
     A termination criterion may be that a time-out is reached e.g. started from the point in time when a first sub-image is acquired, or when a threshold number of sub-images have been acquired without a stable state being identified or when a statistical indicator exceeds a predefined criterion indicating a non-convergence towards a stable state. 
     If to the contrary a stable state is reached, a transition to a state designated “full fingerprint image acquisition and check” is performed in step S 303 . In this state a full fingerprint image is acquired. Optionally, a check of the quality of the full fingerprint image is performed. 
     In case the quality check is not performed, the full fingerprint image is provided unconditionally in step S 304 . In case the quality check is performed, the full fingerprint image is provided conditioned on a successful outcome (designated “Success”) of the quality check. In a further alternative, the full fingerprint image is provided in any event but is assigned with a value indicating the outcome of the quality check. 
     If the outcome of the quality check is that the quality is not sufficiently high (designated as “Failure”) in step S 303 , a transition back to the sleep mode of step S 301  is performed, optionally comprising a step of prompting a user to repeat the touch. 
       FIG.  5    illustrates in more detail the actions of step S 302  of performing a finger stable search. 
     Now, after a threshold number of sensor elements  202  have been detected to have been touched by a finger  201  in step S 401 , the processor  103  initializes in step S 402  the fingerprint sensor  102  with selected settings. At a first run of the method, default settings may be used to initialize the sensor  102  in step S 402 . 
     Then, in step S 403 , a sub-section of the sensing area of sensor  102  is selected to capture a sub-image of the finger  201  touching the sub-section. 
     From data derived from the captured sub-image, properties are computed indicating stability, i.e. whether or not the finger touching the sensing area of the sensor  102  is stable. 
     For instance, statistical indicators may be computed comprising a mean value of intensity values in the captured sub-image, a minimum and/or maximum value, a lower and/or upper quantile or the so-called Kullback-Leibler divergence measure. Alternatively, the Jensen-Shannon divergence could be used instead of the Kullback-Leibler divergence measure. 
     Based on these computed indicators, a property referred to as slope is computed for the change in intensity change. By evaluating the slope of the values of the statistical indicator over time as the values are computed, it may be concluded that the values of the statistical indicator has reached or is about to reach a stable state when the computed slope is below a predefined slope threshold. 
     The processor  103  thus determines in step S 404 , based on the evaluation of how one or more of the slopes develops, whether a stable state is reached or not. 
     If the finger is stable on the sensing area of the sensor  102 , a full image is captured in step S 303  as previously described (which in practice may occur after multiple iterations), where optionally a check of the quality of the full fingerprint image is performed in order to determine whether or not the full image should be used for authentication. 
     If not, the method proceeds to step S 405  where the processor  103  evaluates the previously computed the statistical indicators, for instance the minimum and maximum of the intensity values, in order evaluate how the dynamic range of the fingerprint sensor  102  is used. In case the values that are being output from the fingerprint sensor  102  appear to assume values in range close to e.g. the minimum values or the maximum values, it is practically difficult — if not impossible —to derive sensible information about the fingerprint, at least for authorization purposes. 
     If the computed statistical indicators are evaluated to be adequate, the processor  103  returns to step S 403  for capturing another sub-image. It should be noted that this sub-image may be captured by selecting the same sub-area of the sensor  102  as for the previously captured sub-image, but it may also be envisaged that another sub-area is selected. Again, it will be determined in step S 404  whether or not finger stability prevails. 
     In contrast, should the computed statistical indicators by evaluated to be inadequate, the settings of the sensor  102  must be modified, and the method proceeds to step S 406 , where the sensor settings are modified with the objective to capture a new sub-image having a quality higher than the previous one. 
     Fingerprint sensor settings which may be changed include one or more of e.g. sensor gain, offset or gain of an analogue-to-digital converter (ADC) of the sensor, pixel sensitivity, exposure time, etc. 
     Now, in for instance a smartcard in which the fingerprint sensing system  110  may be implemented, the time available for performing fingerprint sensor operations is heavily restricted. 
       FIG.  6    illustrates a transaction being performed between a credit card  100  and a card reader  200  in the form of a point-of-sale (POS) terminal. The credit card  100  is equipped with a fingerprint sensing system comprising a fingerprint sensor (located under the thumb of the user in  FIG.  6   ) enabling biometric authentication of a user of the credit card  100 . The transaction may be performed in a contactless manner, i.e. via wireless communication (as shown in  FIG.  6   ) or via direct physical contact being established by inserting the credit card  100  into the POS terminal  200 . 
     The smart card  100  communicates wirelessly with the POS terminal  200  according to established standards such as ISO14443 and EMVCo. When the wireless connection is established between the smart card  100  and the POS terminal  200  and the POS terminal  200  sends a command to the smart card  100 , the standards specify that the POS terminal  200  sets a so-called frame waiting time (FWT) during which the smart card  100  is expected to respond. 
     If the credit card  100  does not respond within the specified FWT period, a time-out may occur and the connection may be discontinued. The credit card  100  may request an extension of the waiting time before expiry if the FWT, which is referred to as a waiting time extension (WTX) request to which the POS terminal  200  responds by extending the waiting time FWT. 
       FIG.  7    shows a timing diagram illustrating re-occurring WTX requests and the time periods required for the sensor  102  to capture fingerprint images. As shown, the duration of a WTX request is approximately 5 ms and the WTX requests occur with a period of approximately every 30 ms, while the time required for capturing a full fingerprint image exceeds that period. 
     For a smart card, near-field communication (NFC) may be performed between the card  100  and the POS terminal  200 , wherein the smart card  100  harvests energy from the wireless signal received from the POS terminal  200  for further distribution to other smart card components such as the fingerprint sensing system and transceiver (not shown) via which the communication with the POS terminal is undertaken. 
     Since the amount of energy being harvested by the card  100  is scarce, priority is to be given to the wireless communication between the smart card  100  and the POS terminal  200  during the WTX request signalling. Thus, no fingerprint images should be captured during the time period of the WTX request signalling. In practice, as illustrated in  FIG.  7   , this is problematic since the total time for capturing an image exceeds the WTX request signalling period. 
     In an embodiment, with reference to  FIG.  8    showing a timing diagram, this problem is solved by capturing a number of sub-images during the part of a WTX period when a WTX request is not sent. That is, at some occasion during the 25-ms time slot of the 30-ms WTX period where a WTX request is not sent, one or more sub-images are captured. The sub-images may be captured over a plurality of WTX periods. In this, example three sub-images are captured, each being captured when a WTX request is not sent. 
     The sub-images are loaded into a memory (e.g. the memory  105 ) as they are captured, and after a sufficient number of sub-images have been captured, the captured sub-images are read out of the memory and thus combined into a partly or fully complete fingerprint image (i.e. a representation of the fingerprint of the user) to be used for authentication of the user in the transaction between the credit card  100  and the POS terminal  200 . 
     Advantageously, with this approach as shown in  FIG.  8   , no fingerprint images are captured when a WTX request is sent from the credit card  100  to the POS terminal. 
     Rather, the processor  103  of the fingerprint sensing system  110  advantageously schedules the acquiring of sub-images to be performed during a WTX period when a WTX request is not sent to the POS terminal  200 . As a result, no images are captured during the time period when the smart card  100  harvests energy from communication signals being sent from the POS terminal  200 . 
       FIG.  9    illustrates a flowchart of a method of acquiring fingerprint data of a user with a fingerprint sensor in an embodiment, which method advantageously complies with the restricted timing discussed with reference to  FIG.  8   . 
     Reference will further be made to  FIG.  10    showing a timing diagram illustrating various actions performed by the method of  FIG.  9   . 
     In a first step S 501 , the fingerprint sensor  102  detects that a finger  201  contacts a sensing area of the sensor. As previously discussed, this may be performed by determining that the number of sensing elements  202  of the sensor  102  indicated to be touched exceeds a predetermined touch threshold value. Step S 501  is referred to as finger detect (FD) in  FIG.  9   . 
     Thereafter (or even before step S 501 ), the fingerprint sensor is initialized in step S 502  with a predetermined sensor setting. This may be a default setting which empirically may have proven to result in captured images of a high quality. 
     In step S 503 , a calibration sub-image is acquired, i.e. captured by the fingerprint sensor  102  being initialized with the settings of step S 502 . It should be noted that this calibration sub-image typically is smaller than the sub-images subsequently being captured in step S 505  for the purpose of performing authentication of the fingerprint of the user; the smaller calibration sub-image captured in step S 503  is used for determining whether or not the sensor settings are adequate or if they need to be adjusted. The size of the calibration sub-image is not necessarily dependent on the size of the sensor, but may be of the same dimension regardless of sensor size, such as for instance 32 × 24 pixels. 
     In order to be able to use a fingerprint image for biometric authentication of the user, the quality of the image must be sufficiently high. If not, it is not feasible to match the captured fingerprint image to previously enrolled fingerprint templates of the fingerprint sensing system  110 . 
     Thus, in step S 504 , the processor  103  determines whether or not the quality of the captured calibration sub-image complies with a predetermined quality criterion. For instance, the perceived quality of the image may be graded from 0 to 100%, where 100% would correspond to a more or less perfect image. 
     The process  103  may conclude that the quality criterion is met for the captured calibration sub-image if the quality is assigned a value of 80% or higher, thereby indicating that the utilized sensor settings of step S 502  are adequate. 
     In this particular exemplifying embodiment, it is assumed that the quality criterion is met with the sensor  102  being initialized with the default sensor settings in step S 502 . Steps S 502 -S 504  represent an initialization process referred to as SEARCH in  FIG.  9   . 
     As can be concluded from  FIG.  10   , the FD and SEARCH procedure is advantageously performed during a part of the WTX period when no WTX request is sent in order to avoid that these procedures are being undertaken during a period when the smartcard  100  is harvesting energy. 
     Since the quality criterion is complied with, the processor  103  proceeds with controlling the fingerprint sensor  102  to capture further sub-images using the default sensor settings in step S 505 . As previously mentioned, these sub-images are typically larger than the calibration sub-image captured during the SEARCH process in step S 503 . The sub-images captured in step S 505  is continuously being written into a respective location of memory as they are being captured. 
     The capturing of sub-images in step S 505  is repeated until a sufficient number of sub-images have been captured, such that a fully or partly complete fingerprint image subsequently can be read out from the memory. For instance, 2-4 sub-images are captured and written into the memory, but this may vary dependent on configuration of the system. 
     After having captured a sufficient number of sub-images in step S 505 , these sub-images are read out, and thus combined, by the processor  103  in step S 506  into one single image representing the fingerprint of the user. This will in the following be referred to as a full fingerprint image, even though it may constitute an image representing only a part of a fingerprint, which may or may not be sufficient in fingerprint feature content to allow authentication. 
     It is noted that the reading out of the single image from the memory is typically not performed when a WTX request is sent. 
     As further can be concluded from  FIG.  10   , the capturing of sub-images is advantageously performed during a part of the WTX period when no WTX request is sent. 
     As mentioned, the calibration sub-image captured in step S 502  during the SEARCH phase is generally smaller in size than the further sub-images captured in step S 505 , which has as an advantage that the FD+SEARCH phase not necessarily is longer than the time required to capture a further sub-image in step S 505 . 
     A number of sub-images captured in step S 505 , e.g. 2-3 sub-images, are combined by the processor  103  to accomplish a more substantial representation of the fingerprint, and the resulting single image is subsequently compared to one or more enrolled fingerprint templates in order to find a match and thus authenticate the user. 
     Advantageously, the user has been authenticated without the fingerprint sensing system  110  interfering with the WTX requests transmitted from the smartcard  100  to the POS terminal  200 . 
       FIG.  11    illustrates a flowchart of a method of acquiring fingerprint data of a user with a fingerprint sensor in another embodiment. 
     Reference will further be made to  FIG.  12    showing a timing diagram illustrating various actions performed by the method of  FIG.  11   . 
     In a first step S 501 , the fingerprint sensor  102  detects that a finger  201  contacts a sensing area of the sensor. As previously discussed, this may be performed by determining that the number of sensing elements  202  of the sensor  102  indicated to be touched exceeds a predetermined touch threshold value. Step S 501  is referred to as finger detect (FD) in  FIG.  11   . 
     Thereafter (or even before step S 501 ), the fingerprint sensor is initialized in step S 502  with a predetermined sensor setting. This may be a default setting which empirically may have proven to result in captured images of a high quality. 
     In step S 503 , a calibration sub-image is acquired, i.e. captured by the fingerprint sensor  102  being initialized with the settings of step S 502 . 
     In order to be able to use a fingerprint image for biometric authentication of the user, the quality of the image must be sufficiently high. If not, it is not feasible to match the captured fingerprint image to previously enrolled fingerprint templates of the fingerprint sensing system  110 . 
     Thus, in step S 504 , the processor  103  determines whether or not the quality of the captured calibration sub-image complies with a predetermined quality criterion. As previously discussed, the perceived quality of the image may be graded from 0 to 100%, where 100% would correspond to a more or less perfect image. 
     The processor  103  may conclude that the quality criterion is met for the captured calibration sub-image if the quality is assigned a value of 80% or higher. 
     In this particular exemplifying embodiment, it is assumed that the quality criterion is not met with the sensor  102  being initialized with the default sensor settings in step S 502 ; the quality is e.g. assigned a value of 70%. Steps S 502 -S 504  are referred to as SEARCH in  FIG.  11   . 
     Therefore, the processor  103  modifies the sensor settings in step S 504   a  based on data derived from the acquired calibration sub-image for which the quality criterion is not met. As previously discussed, the data derived from the image may be related to intensity from which statistical indicators are be computed to be used for modifying the sensor settings. 
     In step S 502 , the fingerprint sensor  102  is re-initialized with the modified sensor setting, whereupon a new SEARCH process is undertaken in that a new calibration sub-image is captured in step S 503 , the quality of which is assessed in step S 504 . 
     As can be concluded from  FIG.  12   , the FD, initial SEARCH and repeated SEARCH procedures are advantageously performed during a part of the WTX period when no WTX request is sent. 
     Since the quality criterion now is complied with in step S 504 , the processor  103  proceeds with controlling the fingerprint sensor  102  to capture further sub-images in step S 505  using the modified sensor settings of step S 504   a , i.e. the most recent sensor settings for which an image is captured, the quality of which complies with the quality criterion. 
     After having captured and written a plurality of further sub-images to memory, these sub-images are read out from the memory by the processor  103  in step S 506  and thus combined into one single image representing the fingerprint of the user as previously discussed. 
     As further can be concluded from  FIG.  12   , the capturing of sub-images is advantageously performed during a part of the WTX period when no WTX request is sent. 
       FIG.  13    illustrates a flowchart of a method of acquiring fingerprint data of a user with a fingerprint sensor in a further embodiment. 
     Only step S 501   a  added with respect to the flowchart of  FIG.  11    will be discussed in detail as the other steps already have been discussed with reference to  FIG.  11   . 
     After a finger is detected in step S 501 , the processor  103  determines in step S 501   a  whether or not the finger is stable, e.g. by evaluating intensity parameters of the sub-image. If so, the method proceeds to step S 502  as previously has been described. 
     However, if the finger is determined to be unstable on the sensing area of the sensor  102  in step S 501   a , the processor  103  re-starts the process to again determine in step S 501  that a finger touches the sensor. 
     Advantageously, a check for finger stability is incorporated into the method with step S 501   a . 
       FIG.  14    shows an alternative finger stability detection approach as compared to that in  FIG.  13   . In this embodiment, after the sub-images have been captured in step S 505 , the process  103  checks that the finger that was detected in step S 501  still remains on the sensing area of the sensor  102 . 
     If so, the processor  103  proceeds with reading out, from the memory, the captured sub-images forming a single image in step S 506  and the process proceeds to fingerprint authentication. If not, the captured images are discarded in step S 505   b , and the process starts over. 
     It is noted that the step of reading out the sub-images forming the single image in step S 506  may be performed before the step of determining whether or not the finger is stable in step S 505   a . Further, step S 501   a  of  FIG.  13    of performing initial finger stable detection may be added to the embodiment of  FIG.  14   . 
     The aspects of the present disclosure have mainly been described above with reference to a few embodiments and examples thereof. However, as is readily appreciated by a person skilled in the art, other embodiments than the ones disclosed above are equally possible within the scope of the invention, as defined by the appended patent claims. 
     Thus, while various aspects and embodiments have been disclosed herein, other aspects and embodiments will be apparent to those skilled in the art. The various aspects and embodiments disclosed herein are for purposes of illustration and are not intended to be limiting, with the true scope and spirit being indicated by the following claims.