Biometric identification device with ultrasonic transducer and stress condition detection

Abstract

The invention relates to a biometric identification and stress condition detection device (100) comprising at least one ultrasonic transducer circuit (104), a control circuit (106) and a data processing circuit (108), which are configured to perform biometric identification (204 – 216) comprising at least the capture of one or more fingerprints of at least one finger (101) of a user, wherein the finger (101) is intended to be arranged against a capture surface (102) of the device (100), and to detect (218 – 222) a stress condition of the user by carrying out multiple successive measurements representative of the pressure intended to be applied by the finger (101) to the capture surface (102).

Description

DESCRIPTION Biometric identification device with ultrasonic transducer and duress detection The present application claims the benefit of priority from French patent application number 23 / 15158, filed on December 22, 2023, entitled "Biometric identification device with ultrasonic transducer and detection of duress situation", which is incorporated by reference to the fullest extent permitted by law. Technical field

[0001] This description relates to the field of biometric identification devices based on capture and detection by ultrasonic transduction. Prior art

[0002] A biometric identification device makes it possible to verify or determine the identity of a user of the device based on a measurement of one or more biometric characteristics of the user such as a fingerprint, the shape of the face, the pattern of the iris, the pattern of the retina, etc. The different techniques for measuring one or other of these characteristics each have advantages and disadvantages depending on different criteria, including in particular: more or less significant error rate, ease or not of stealing the template with which the measurements are compared, possibility of detecting an imitation or not, proof or not of life, ease and comfort of use, size of the sensor required, energy consumption required, etc.

[0003] It is known to realize a biometric identification device using a sensor fingerprint scanner performing optical or capacitive measurements to verify whether the captured fingerprint matches the expected one (identity verification phase).

[0004] However, when the user is in a situation of constraint, for example under threat from a malicious individual and identification is not desired by the user, such a device does not make it possible to prevent the consequences linked to the identification of the user. Summary of the invention

[0005] There is a need to propose a biometric identification device that does not have at least some of the disadvantages of existing solutions.

[0006] An embodiment overcomes all or part of the drawbacks of the known solutions and proposes a biometric identification and constraint situation detection device comprising at least one ultrasonic transducer circuit, a control circuit and a data processing circuit, configured to perform a biometric identification comprising at least one capture of at least one fingerprint of at least one finger of a user, the finger being intended to be placed against a capture surface of the device, and to detect a constraint situation of the user by performing several successive measurements representative of pressures intended to be applied by the finger on the capture surface.

[0007] According to a particular embodiment, the data processing circuit is configured to carry out a comparison of the successive measurements representative of the pressures intended to be applied by the finger on the capture surface with at least one sequence of pressures expected, and to detect a constraint situation based on a result of the comparison.

[0008] According to a particular embodiment, the ultrasonic transducer circuit, the control circuit and the data processing circuit are configured to carry out, prior to capturing the fingerprint, an enrollment of the user during which a sequence of pressures is intended to be applied at least once by the user's finger on the capture surface and memorized to form the expected sequence of pressures.

[0009] According to a particular embodiment, each of the pressures in the expected pressure sequence corresponds either to a strong press when the applied pressure is greater than or equal to a pressure threshold value, or to a weak press when the applied pressure is less than the pressure threshold value.

[0010] According to a particular embodiment, the expected sequence of pressures comprises several strong presses such that two strong presses are spaced apart by a weak press.

[0011] According to a particular embodiment, each of the strong presses corresponds either to a long press when a duration during which the strong press is carried out is greater than or equal to a duration threshold value, or to a short press when a duration during which the strong press is carried out is less than the duration threshold value.

[0012] In a particular embodiment, according to a first configuration, a constraint situation is detected when the successive measurements representative of the pressures intended to be applied by the finger on the capture surface correspond to the expected sequence of pressures, or according to a second configuration, a constraint situation is detected when the successive measurements representative of the pressures intended to be applied by the finger on the capture surface do not correspond to the expected sequence of pressures, or according to a third configuration, a constraint situation is detected when any sequence of several successive presses is detected.

[0013] According to a particular embodiment, the data processing circuit is configured to carry out the comparison of successive measurements with the expected sequence of pressures and the detection of a stress situation by implementing the steps of:

[0014] - detection of maximum and minimum values ​​of the support durations on the capture surface during successive measurements, determination of a duration threshold value from the maximum and minimum values ​​of the support durations, and classification of each of the measurements as corresponding to a long support or a short support by comparison of each of them with respect to the duration threshold value, or

[0015] - comparison by correlation of the signal of successive measurements with a signal corresponding to the sequence of expected pressures, then comparison of the result with a threshold value, or

[0016] - several comparisons, considering several speeds of execution of successive measurements, by correlation of the signal of successive measurements with a signal corresponding to the sequence of expected pressures, then comparison of each result with a threshold value, or

[0017] - classification of successive measurements by deep learning thanks to prior training of a neural network.

[0018] According to a particular embodiment, the successive measurements representative of pressures intended to be applied by the user's finger on the capture surface correspond to measurements of a position of an interface between the user's finger and the capture surface along a direction perpendicular to the detection surface.

[0019] According to a particular embodiment, the position of the interface between the user's finger and the capture surface is determined:

[0020] - by detecting at least one maximum value of response signals from a central part of the ultrasonic transducer circuit, or

[0021] - by detecting several maximum values ​​of response signals from several parts of the ultrasonic transducer circuit and calculating an average or median value of said maximum values, or

[0022] - by applying, to the response signals of the ultrasonic transducer circuit, at least one beam forming type treatment then a surface determination algorithm.

[0023] According to a particular embodiment, the successive measurements representative of pressures intended to be applied by the user's finger on the capture surface correspond to measurements of a coupling energy between the user's finger and the ultrasonic transducer circuit.

[0024] According to a particular embodiment, the successive measurements representative of pressures intended to be applied by the user's finger on the capture surface correspond to measurements of movements detected in successive volume images of the finger.

[0025] According to a particular embodiment, the successive measurements representative of pressures intended to be applied by the user's finger to the capture surface include calculations of absolute differences between successive response signals delivered by the ultrasonic transducer circuit.

[0026] According to a particular embodiment, the biometric identification and constraint situation detection device further comprises an element for indicating the pressure of the finger against the capture surface. Brief description of the drawings

[0027] These and other features and advantages will be set forth in detail in the following description of particular embodiments given without limitation in relation to the attached figures, among which:

[0028] - figure 1 and figure 2 schematically represent a biometric identification and constraint situation detection device according to a particular embodiment;

[0029] - figure 3 represents, in the form of a schematic diagram, steps implemented by a biometric identification and constraint situation detection device according to a particular embodiment;

[0030] - Figure 4 schematically illustrates minutiae identified in a surface image captured by a biometric identification and stress situation detection device according to a particular embodiment. Description of the embodiments

[0031] The same elements have been designated by the same references in the different figures. In particular, the structural and / or functional elements common to the different embodiments may have the same references and may have identical structural, dimensional and material properties.

[0032] For the sake of clarity, only the steps and elements useful for understanding the embodiments described have been shown and are detailed. In particular, different elements (ultrasonic transducer circuit, control circuit, data processing circuit, etc.) and different steps implemented (image acquisition, processing of acquired images, determination of minutiae, details of calculations performed, etc.) are not detailed. Those skilled in the art will be able to implement these elements in detail from the functional description given here.

[0033] Unless otherwise specified, when two elements are connected together, this means directly connected without intermediate elements other than conductors, and when two elements are connected (in English "coupled") together, this means that these two elements can be connected or be connected by means of one or more other elements.

[0034] In the following description, when reference is made to absolute position qualifiers, such as the terms "front", "back", "top", "bottom", "left", "right", etc., or relative position qualifiers, such as the terms "above", "below", "upper", "lower", etc., or to orientation qualifiers, such as the terms "horizontal", "vertical", etc., reference is made unless otherwise specified to the orientation of the figures in a normal position of use.

[0035] Unless otherwise specified, the expressions "about", "approximately", "substantially", and "of the order of" mean to within 10%, preferably to within 5%.

[0036] A biometric identification and constraint situation detection device 100 according to a particular embodiment is described below in connection with Figures 1 and 2.

[0037] In the example visible in Figure 1, the device 100 is configured to implement biometric identification from one or more fingers 101 of the user of the device 100. In the remainder of the description, it is considered that the device 100 is configured to carry out biometric identification from a single finger 101 of the user. The device 100 comprises a capture surface 102 on which the finger 101 of the user of the device 100 is intended to be arranged during biometric identification and detection of a constraint situation.

[0038] The device 100 comprises at least one ultrasonic transducer circuit 104, a control circuit 106, and a data processing circuit 108. In the schematic example shown in FIG. 2, the control circuit 106 may be electrically coupled to the ultrasonic transducer circuit 104 and thus be able to transmit to the ultrasonic transducer circuit 104 signals controlling the emission of ultrasound for the measurements to be carried out, and also able to receive electrical measurement signals transmitted by the ultrasonic transducer circuit 104 following the reception of echoes of the emitted ultrasound. The control circuit 106 may also be coupled to the data processing circuit 108 in order to transmit to the data processing circuit 108 the measurement results obtained from the ultrasonic transducer circuit 104.

[0039] In the exemplary embodiment described, the different circuits of the device 100 are configured to carry out a biometric identification comprising at least one capture of at least one fingerprint of at least one finger of the user of the device 100. This fingerprint capture may comprise an acquisition of at least one surface image of the finger 101 of the user placed on the capture surface 102 of the device 100 and in contact therewith, that is to say an acquisition of at least one fingerprint image formed of ridges and valleys present on the surface of the skin of the finger 101 placed on the capture surface 102. In the device 100, the acquisition of a surface image of the finger 101 of the user placed on the capture surface 102 and in contact therewith is based on the fact that the ultrasounds emitted by the transducer circuit 104 are reflected more significantly against the air present in the valleys of the fingerprint of the finger than against the ridges of the print.

[0040] In addition to the biometric identification function, the device 100 is also configured to detect a situation of constraint of the user, that is to say a situation in which the user is forced to carry out a biometric identification against his will. For this, the device 100 is configured to carry out several successive measurements representative of pressures intended to be applied by the finger 101 of the user on the capture surface 102 and representative of durations of pressure by the finger 101 of the user on the capture surface 102.

[0041] The ultrasonic transducer circuit 104 may comprise a plurality of ultrasonic transducers allowing the acquisition of images required for biometric identification, as well as for carrying out the successive measurements representative of the pressures intended to be applied by the finger 101 on the capture surface 102. The ultrasonic transducers are for example arranged in a matrix manner. opposite at least a portion of the capture surface 102 or in another manner suitable for the captures and measurements to be carried out. The number of ultrasonic transducers of the transducer circuit 104 may depend on the dimensions of the capture surface 102.

[0042] The ultrasonic transducer circuit 104 may for example comprise CMUT type transducers. ("Capacitive Micromachined Ultrasonic Transducer" in English, or capacitive micromachined ultrasonic transducer) or PMUT type ("Piezoelectric Micromachined Ultrasonic Transducer" in English, or piezoelectric micromachined ultrasonic transducer) or another type.

[0043] In the exemplary embodiment described herein, the control circuit 106 may be configured to provide the ultrasonic transducer circuit 104 with excitation electrical signals causing the ultrasonic transducer circuit 104 to emit ultrasonic waves, and to receive response electrical signals generated by the ultrasonic transducer circuit 104 as a result of receiving ultrasonic waves reflected by the finger 101 or other elements present on the capture surface 102.

[0044] In the exemplary embodiment described, the data processing circuit 108 can be configured to analyze and process the electrical response signals received by the control circuit 106 and sent by the ultrasonic transducer circuit 104. The processing circuit 108 can comprise, for example, a microprocessor coupled to a memory in order in particular to carry out the processing of the received data.

[0045] The ultrasonic transducer circuit 104, the control circuit 106 and the data processing circuit 108 may be configured to perform biometric identification and detection of a duress situation in implementing the steps described below and represented in diagram form in Figure 3.

[0046] During a first step 202, the device 100 can perform a detection of a finger present on the capture surface 102. If a finger is actually detected on the capture surface 102, a second step 204 can be implemented. In the absence of a detected finger, this detection step 202 can be repeated until a finger is detected on the capture surface 102. The detection step 202 can be repeated continuously or at time intervals which may or may not be regular.

[0047] The device 100 can then be configured such that it is capable of acquiring at least one surface image of the finger 101 present on the capture surface 102 (step 204). For example, this configuration of the device 100 can comprise sending an acquisition order, or a sequence of instructions, to the control circuit 106 for acquiring the surface image of the finger 101.

[0048] During a following step 206, an acquisition of at least one surface image of the finger 101 present on the capture surface 102 can then be implemented. This acquisition can comprise the emission of a series of ultrasonic signals in the form of pulses by the transducer circuit 104, then the reception of the echoes by the transducer circuit 104 and the processing of the responses obtained to obtain the surface image of the finger 101, that is to say the image of the user's fingerprint.

[0049] The processing of the responses obtained to obtain the surface image of the finger 101 corresponds for example to a signal processing of the “beamforming” or “micro-beamforming” type, also called beamforming or spatial filtering. Examples of signal processing of beamforming type are described in the document by MF Rasmussen et al., "3-D imaging using row-column-addressed arrays with integrated apodization - part i: apodization design and line element beamforming", IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 62, no. 5, pp. 947-958, May 2015, as well as in the document by Perrot Vincent et al., "So You Think You Can DAS? A Viewpoint on Delay-and-Sum Beamforming." Ultrasonics, vol. Ill, March 2021, 106309. Alternatively, it is possible to carry out the transmission and reception of signals from the transducer circuit 104 by multiplexing, to carry out a B-mode image acquisition focused at the surface of the finger 101.According to another variant, it is possible to perform orthogonal addressing of the transducer matrix of the circuit 104 to emit a series of ultrasonic pulses in the form of focused waves, or plane waves, or to perform a complete matrix capture of the RCA-OPW type (Row column addressing orthogonal plane wave imaging). As an example, the document by V. Perrot et al., “So you think you can DAS? A viewpoint on delay-and-sum beamforming”, Ultrasonics 111 (2021), 106309, arXiv: 2007.11960, describes an example of a DAS (Delay-and-sum) beamforming method that can be used to obtain the surface image of the finger 101.

[0050] The acquisition of the surface image of the finger 101 may also include the implementation of other steps not detailed here: filtering of the response signals obtained, envelope detection, logarithmic compression, etc.

[0051] The data relating to the acquired surface image are for example stored in a memory of the device 100 or in an external memory of the device 100 for example connected to the device 100 by a communication link.

[0052] After obtaining the surface image of the finger 101, the data processing circuit 108 can be configured to determine fingerprint characteristics from the obtained surface image.

[0053] According to a particular exemplary embodiment, to carry out this determination of the characteristics of the fingerprint from the previously acquired surface image, the data processing circuit 108 can determine or extract minutiae from the fingerprint 101 obtained on this image (step 208). This determination of minutiae can be carried out by one or more image processing algorithms not described in detail here and known to those skilled in the art. Different methods of extracting minutiae from a fingerprint image that can be used here are described for example in the document by R. Bansal et al., “Minutiae Extraction from Fingerprint Images - a Review”, IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 5, No. 3, September 2011.

[0054] In Figure 4, an example of a surface image acquired by the device 100 is represented and designated by the reference 110. This surface image 110 corresponds here to the imprint of a finger 101 present on the capture surface 102 of the device 100. The minutiae determined in this surface image 110 are represented by points and designated by the reference 112.

[0055] Following the determination of the minutiae of the fingerprint, during a following step 210, the data processing circuit 108 can then perform the calculation of the position of at least one minutiae in the surface image and the calculation of geometric relationships between said at least one minutiae and at least a portion of the other minutiae present in the surface image. In the example described, these geometric relationships can comprise:

[0056] - the distance between said at least one minutiae and each of the other minutiae, and

[0057] - an orientation of said at least one minutiae relative to the other minutiae, and

[0058] - an orientation of the other minutiae relative to said at least one minutiae.

[0059] In a particular exemplary embodiment, the data processing circuit 108 may be configured such that the calculation step described above is repeated for at least a portion of the other minutiae 112 previously determined, and for example for each of the other minutiae 112 previously determined.

[0060] For the calculations described above, the positions of the minutiae 112 as well as the geometric relationships between them can be calculated in Cartesian or spherical coordinates.

[0061] The position(s) of the minutiae 112 and the previously calculated geometric relationships may then be compared with one or more expected positions and geometric relationships obtained, for example, during a preliminary enrollment of the user, to confirm or not the identity of the user of the device 100 (step 212). This comparison may be carried out for the positions and geometric relationships calculated for each minutia 112. The preliminary enrollment of the user may comprise the same steps as those described above in order to obtain a surface image of the fingerprint from which expected minutiae positions and geometric relationships are intended to serve as references for the comparison carried out during an identification of the user of the device 100.

[0062] In a particular embodiment, in order to compare the elements (positions and geometric relationships of the minutiae) previously calculated with the results expected to confirm or not the identity of the user of the device 100, the comparison step may comprise a score calculation (step 214 in the diagram of FIG. 3) whose value depends on the correlations between on the one hand the calculated positions and geometric relationships and on the other hand the positions and geometric relationships expected to confirm or not the identity of the user. For example, the chosen score calculation method may allow obtaining a score close to or equal to 1 when the captured fingerprint corresponds to that expected to confirm the identity of the user of the device 100, and a score close to 0 when the captured fingerprint does not correspond to that expected to confirm the identity of the user of the device 100.

[0063] According to one example, such a score can be calculated for each previously determined minutia. Then, it is possible to select some or all of the scores obtained and to calculate an overall score representative of the previously calculated scores (sum, average, linear combination, etc.). The score calculation method is not described in detail here and may correspond to an adaptation of one of the methods known to those skilled in the art and for example applied for identification by comparison of fingerprints.

[0064] The score value can then be compared with a score threshold value in order to assess the correspondence between the biometric measurement carried out and the expected biometric data, and thus confirm or not the identity of the user (step 216).

[0065] In the exemplary embodiment described above, the characteristics of the fingerprint determined from the surface image 110 correspond to the minutiae 112 of this fingerprint. According to another exemplary embodiment, it is possible that the determination of the characteristics of the fingerprint 101 comprises the extraction of at least one vector of characteristics from the surface image by the implementation of a deep learning algorithm. In this case, the comparison of the previously determined characteristics with expected characteristics for identifying or not identifying the user may comprise a comparison, by the deep learning algorithm, of the previously determined vector of characteristics with at least one expected vector of characteristics.In this other example, it is also possible to perform a score calculation whose value depends on the correlations between the determined feature vector and the one expected to identify the user. The paper by Y. Tang et al., "FingerNet: An Unified Deep Network for Fingerprint Minutiae Extraction," arXiv: 1709.02228, and the paper by Engelsma, Joshua J. et al. "Learning a Fixed-Length Fingerprint Representation." IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (2019): 1981-1997, describe examples of deep learning algorithms that can be implemented for this other example implementation.

[0066] In parallel with the implementation of steps 204 to 216 previously described, i.e. the steps implemented to carry out a biometric identification of the user of the device 100, the device 100 also implements other steps to detect whether the user whose identity is verified is in a situation of constraint or not.

[0067] To do this, during a step 218, the device 100 can carry out several successive measurements representative of pressures applied by the finger 101 on the capture surface 102.

[0068] According to a particular exemplary embodiment, the successive measurements representative of the pressures applied by the user's finger 101 to the capture surface 102 may correspond, when the ultrasound transducer circuit 104 forms one or more flexible membranes flexing under the pressure of the finger 101, to measurements of the position of the interface between the user's finger 101 and the capture surface 102 along a direction substantially perpendicular to the capture surface 102 relative to the circuit 104. This position of the interface between the finger 101 and the capture surface 102 may be measured in different ways.

[0069] According to a first example, this position of the finger 101 / capture surface 102 interface along the direction substantially perpendicular to the capture surface 102 can be obtained by detecting at least one maximum value of response signals from a central part of the ultrasonic transducer circuit 104. Indeed, a more or less strong pressure applied by the finger 101 on the capture surface 102 will result in a more or less significant bending of the finger 101 / capture surface 102 interface, in particular at the level of a central part of the transducer circuit 104. The detection of the position of this interface along the axis perpendicular to the capture surface 102 can therefore allow the device 100 to evaluate whether the pressure applied by the finger 101 on the capture surface 102 is significant or not.

[0070] According to a second example, the position of the finger 101 / capture surface 102 interface along the direction perpendicular to the capture surface 102 can be determined by detecting several maximum values ​​of response signals from several parts of the ultrasonic transducer circuit 104, these parts being distinct and for example arranged substantially in a central region of the ultrasonic transducer circuit 104. As for the first example, the detection of the position of the interface along the axis perpendicular to the capture surface 102, at these different parts of the circuit 104, can allow the device 100 to evaluate whether the pressure applied by the finger 101 on the capture surface 102 is significant or not. This position of the interface can be determined by calculating an average or median value of the maximum values ​​of the detected response signals.

[0071] According to a third example, the position of the finger 101 / capture surface 102 interface along the direction perpendicular to the capture surface 102 can be measured by applying, to the response signals of the ultrasonic transducer circuit 104, at least one beamforming type processing, then a surface determination algorithm.

[0072] According to another particular embodiment, the successive measurements representative of the pressures applied by the user's finger 101 to the capture surface 102 may correspond to measurements of a coupling energy between the finger 101 and the transducer circuit 104. Indeed, during the ultrasonic measurements carried out by the transducer circuit 104, the more the finger 101 presses on the capture surface 102, the greater the sum of the energies of the response signals to these measurements. By determining this sum of the energies of the response signals delivered by the transducer circuit 104 and comparing it to a certain energy threshold value (the value of which is a function in particular characteristics of the transducer circuit 104), it is therefore possible to determine whether the pressure of the finger 101 on the capture surface 102 corresponds to a pressure with strong pressure or to a pressure with weak pressure.

[0073] According to another example, the successive measurements representative of the pressures applied by the user's finger 101 on the capture surface 102 may correspond to calculations of absolute differences between successive response signals. By then calculating the sum of these absolute differences, it is possible to determine that a movement of the capture surface 102 has occurred when this sum is large because this means that a press of the finger 101 on the capture surface 102 occurred with strong pressure. On the other hand, if the result of this sum is low or zero, this means that the capture surface 102 has moved little, or not at all, and therefore that a press of the finger 101 on the capture surface 102 occurred with low pressure or did not occur.

[0074] In the examples described above, the processing steps implemented directly from the radiofrequency signals received by the transducer circuit 104 have the advantage of avoiding the implementation of heavy calculation steps.

[0075] According to another exemplary embodiment, the successive measurements representative of the pressures applied by the user's finger 101 on the capture surface 102 may correspond to measurements of variations or movements detected in successive volume images of the finger, i.e. 3D images representative of the tissues and micro-vessels of the finger 101 present under the skin. To carry out such measurements, the device 100 may be configured to carry out acquisitions of volume images of the finger 101 placed on the capture surface 102 and in contact with it, and from which it is possible to determine, by processing these volume images, a global volume image of the finger 101. The global volume image obtained can thus be deduced from several volume images captured successively over time at non-zero depths (dimension along the Z axis visible in FIG. 1 and which is for example substantially perpendicular to the capture surface 102) of the finger present on the capture surface 102.

[0076] In this case, the ultrasound transducer circuit 104 may for example be configured to acquire the volume images of the finger 101 by pulsed wave Doppler imaging. In such a configuration, the transducer circuit 104 may be configured to emit a series of ultrasonic pulses. The responses obtained in such a configuration do not correspond to a change in the frequency of the received wave, but correspond to a pseudo-Doppler effect, i.e. a change in the time interval between the received echoes relative to the time interval between the emitted waves. In the device 100, the pulsed wave Doppler imaging may therefore be used to determine the spatial location of movements in the acquired volume images and also in the overall volume image.

[0077] For example, the acquisition of the volume images can be carried out by means of plane ultrasonic waves emitted by the transducer circuit 104 with a certain number of angles, then the processing of the response signals can include a phase of “beamforming” then of coherent addition of the images corresponding to each angle to obtain a volume image in B mode. This process can be repeated over time to obtain several volume images allowing monitoring of the pressing pressure that the user exerts with the finger 101. As an example, the paper by G. Montaldo et al., "Coherent plane-wave compounding for very high frame rate ultrasonography and transient elastography," in IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, vol. 56, no. 3, pp. 489-506, March 2009, describes an example of a DAS beamforming method with coherent plane-wave summation that can be implemented to obtain the global volume image of the finger 101.

[0078] Thus, using the series of acquired volume images, the movements of the tissues in the finger 101 can be identified. The greater or lesser pressure applied by the finger 101 on the capture surface 102 can then be determined by following the identified movements along the axis perpendicular to the capture surface 102.

[0079] In the various examples above, in addition to the distinction between strong pressure or weak pressure made during successive measurements representative of the pressures applied by the finger 101 on the capture surface 102, these measurements can also be implemented so as to determine the duration of a press made on the capture surface 102.

[0080] The data relating to the overall volume image obtained can be stored in a memory of the device 100 or in an external memory of the device 100, for example connected to the device 100 by a communication link.

[0081] According to a particular embodiment, the data processing circuit 108 can then be configured to carry out a comparison of the successive measurements representative of the pressures applied by the finger 101 on the capture surface 102 with at least one expected sequence of pressures (step 220). According to one example, this comparison can in particular comprise a comparison of the duration of the presses made with strong pressure, the presses with low pressure that can be used to mark the separation between two presses made with strong pressure. For example, the expected sequence of pressures can be obtained prior to capturing the fingerprint, by implementing a user enrollment step during which a sequence of pressures is intended to be applied at least once, and for example several consecutive times, by the user's finger 101 on the capture surface 102, and memorized to form the expected sequence of pressures. This enrollment step can be implemented at the same time as the preliminary enrollment previously described and implemented to obtain the position(s) and geometric relationships of the expected minutiae of the fingerprint to identify the user.

[0082] According to an exemplary embodiment, the expected pressure sequence may comprise several pressures made with a strong pressure of the finger 101 on the capture surface 102 with, between two strong presses, a press made with a weak pressure of the finger 101 on the capture surface 102. In addition, each of the presses of the expected pressure sequence may correspond either to a strong press when the pressure applied is greater than a pressure threshold value, or to a weak press when the pressure applied is less than the pressure threshold value, and each strong press may be made for a long or short duration. This pressure threshold value may be a function of the characteristics of the transducer circuit 104 used and / or of the layer(s) of materials forming the capture surface 102.Additionally, for example, a threshold value of duration above which a press is considered long and below which a press is considered short can be used to distinguish between a long press and a short press.

[0083] Alternatively, the expected sequence of pressures may correspond to a succession of pressures, each strong or weak.

[0084] According to a particular embodiment, the data processing circuit 108 can then be configured to detect a constraint situation based on a result of the previous comparison (step 222).

[0085] According to a first configuration, a constraint situation can be detected when the successive measurements representative of the pressures applied by the finger 101 on the capture surface 102 correspond to the expected sequence of pressures. In this first configuration, the user therefore signals that he is in a constraint situation by reproducing the expected sequence of pressures.

[0086] Alternatively, according to a second configuration, a constraint situation can be detected when the successive measurements representative of the pressures intended to be applied by the finger on the capture surface do not correspond to the expected sequence of pressures. In this second configuration, the user therefore signals that he is in a constraint situation by not reproducing the expected sequence of pressures, this sequence serving on the contrary to the user to indicate that he is not in a constraint situation.

[0087] The comparison of the successive measurements representative of the pressures applied by the finger 101 on the capture surface 102 with at least one expected sequence of pressures, and the correspondence or not between these successive measurements and the expected sequence of pressures can be carried out in different ways, for example:

[0088] - detection of maximum and minimum values ​​of the support durations on the capture surface 102 during the measurements successive, determination of the duration threshold value from these maximum and minimum values ​​(for example the average value), and classification of each of the measurements as corresponding to a long press or a short press by comparison of each of them with respect to the duration threshold value, or

[0089] - comparison by correlation of the signal of successive measurements with that corresponding to the expected sequence of pressures, then comparison of the result with a threshold value, or

[0090] - several comparisons, considering several speeds of execution of successive measurements (to compensate for possible accelerations or slowdowns in the execution of presses by the user), by correlation of the signal of successive measurements with that corresponding to the expected sequence of pressures, then comparison of each result with a threshold value, or

[0091] - classification of successive measurements by deep learning thanks to prior training of a neural network.

[0092] Alternatively, according to a third configuration, a constraint situation can be considered as detected when a sequence of successive presses is carried out by the user and this sequence is not due to the natural or involuntary movements of the finger 101 on the capture surface 102. In the absence of such a press sequence, the device can consider that the user is not in a constraint situation.

[0093] In a particular configuration, when the biometric identification implemented results in an identification of the user of the device 100 (captured fingerprint corresponding to that expected) and whatever is the result of the detection of the constraint situation, it is possible that the device 100 indicates, for example visually, that the biometric identification is successful. When no constraint situation is detected, the device 100 can unlock one or more usage functions of the device 100. On the other hand, if a constraint situation is detected, the device 100 may not unlock this or these usage functions. Other measures can also be envisaged in the event of detection of a constraint situation or absence of detection of a constraint situation.

[0094] The device 100 can thus form a biometric system integrating at least functionalities for identification and detection of situations of constraint. The device 100 can notably offer a better level of security compared to an identification device based solely on a fingerprint capture. The device 100 also offers a means of detecting, transparently for an attacker, that the user is under constraint and taking appropriate measures in such a scenario.

[0095] In the example described above, the device 100 performs biometric identification by comparing the measured data included in the surface image with expected data corresponding to those of a person for whom the identity is verified. Alternatively, it is possible for the device 100 to perform a comparison of the measured data with expected data corresponding to those of several people, the device 100 being able in this case to verify whether the user corresponds to one of these people.

[0096] In the above description, the device 100 may compare the measurements made with expected data stored in a memory of the device 100. Alternatively, it is possible that the device 100 can connect to a remote database in which the expected data corresponding to those of one or more persons are stored to check whether the user of the device 100 corresponds to this person or one of these persons, and whether this user is in a situation of constraint. It is also possible, in another variant, to connect the device 100 to a smart card containing the data recorded during a prior enrollment. The step of comparing the data can then be carried out in the smart card and not in the device 100.

[0097] In the previously described example device 100, the biometric identification performed is based on capturing surface image(s) of the user's finger(s), and comparing characteristics of the captured fingerprint(s) with expected characteristics to confirm the user's identity. Alternatively, it is possible that other information is measured and used for user identification, in addition to or instead of identification by fingerprint measurement. Furthermore, the device 100 may also implement additional functionalities to those previously described.

[0098] For the various examples previously described, the device 100 may comprise an element for indicating, or “feedback”, to the user the pressure he is currently exerting on the capture surface 102 and / or the required pressure duration and / or the required pressure position. This element may for example provide a visual indication, for example in the form of one or more LEDs displaying a color and / or an intensity representative of the pressure and / or the pressure duration and / or the pressure position. Other types of indication are possible, for example sound, haptic, etc.

[0099] Various embodiments and variations have been described. Those skilled in the art will understand that certain features of these various embodiments and variations could be combined, and other variations will occur to those skilled in the art.

[0100] Finally, the practical implementation of the embodiments and variants described is within the reach of the person skilled in the art from the functional indications given above.

Claims

CLAIMS 1. Biometric identification and constraint situation detection device (100) comprising at least one ultrasonic transducer circuit (104), a control circuit (106) and a data processing circuit (108), configured to perform a biometric identification (204 - 216) comprising at least one capture of at least one fingerprint of at least one finger (101) of a user, the finger (101) being intended to be placed against a capture surface (102) of the device (100), and to detect (218 - 222) a constraint situation of the user by performing several successive measurements representative of pressures intended to be applied by the finger (101) on the capture surface (102),and in which the successive measurements representative of pressures intended to be applied by the user's finger (101) on the capture surface (102): correspond to measurements of a position of an interface between the user's finger (101) and the capture surface (102) along a direction perpendicular to the detection surface (102), or, - correspond to measurements of a coupling energy between the user's finger (101) and the ultrasonic transducer circuit (104), or - correspond to measurements of movements detected in successive volume images of the finger (101), or - include calculations of absolute differences between successive response signals delivered by the ultrasonic transducer circuit (104).

2. Biometric identification and constraint situation detection device (100) according to claim 1, wherein the data processing circuit (108) is configured to carry out a comparison (220) of the successive measurements representative of the pressures intended to be applied by the finger (101) on the capture surface (102) with at least one expected sequence of pressures, and to detect (222) a constraint situation as a function of a result of the comparison.

3. Biometric identification and constraint situation detection device (100) according to claim 2, wherein the ultrasonic transducer circuit (104), the control circuit (106) and the data processing circuit (108) are configured to carry out, prior to the capture (206) of the fingerprint, an enrollment of the user during which a sequence of pressures is intended to be applied at least once by the finger (101) of the user on the capture surface (102) and memorized to form the expected sequence of pressures.

4. Biometric identification and constraint situation detection device (100) according to one of claims 2 or 3, in which each of the pressures of the expected pressure sequence corresponds either to a strong press when the applied pressure is greater than or equal to a pressure threshold value, or to a weak press when the applied pressure is less than the pressure threshold value.

5. Biometric identification and constraint situation detection device (100) according to claim 4, in which the expected pressure sequence includes several strong presses such that two strong presses are spaced by a weak press.

6. Biometric identification and constraint situation detection device (100) according to claim 5, wherein each of the strong presses corresponds either to a long press when a duration during which the strong press is made is greater than or equal to a duration threshold value, or to a short press when a duration during which the strong press is made is less than the duration threshold value.

7. Biometric identification and constraint situation detection device (100) according to one of claims 2 to 6, wherein, according to a first configuration, a constraint situation is detected when the successive measurements representative of the pressures intended to be applied by the finger (101) on the capture surface (102) correspond to the expected sequence of pressures, or according to a second configuration, a constraint situation is detected when the successive measurements representative of the pressures intended to be applied by the finger (101) on the capture surface (102) do not correspond to the expected sequence of pressures, or according to a third configuration, a constraint situation is detected when any sequence of several successive presses is detected.

8. Biometric identification and constraint situation detection device (100) according to one of the Claims 2 to 7, wherein the data processing circuit (108) is configured to carry out the comparison (220) of the successive measurements with the expected sequence of pressures and the detection (222) of a stress situation by implementing the steps of: detecting maximum and minimum values ​​of the support durations on the capture surface (102) during the successive measurements, determining a duration threshold value from the maximum and minimum values ​​of the support durations, and classifying each of the measurements as corresponding to a long press or a short press by comparing each of them with respect to the duration threshold value, or - comparison by correlation of the signal of successive measurements with a signal corresponding to the sequence of expected pressures, then comparison of the result with a threshold value, or - several comparisons, considering several speeds of execution of successive measurements, by correlation of the signal of successive measurements with a signal corresponding to the sequence of expected pressures, then comparison of each result with a threshold value, or - classification of successive measurements by deep learning thanks to prior training of a neural network.

9. Biometric identification and constraint situation detection device (100) according to any one of the preceding claims, in which the position of the interface between the user's finger (101) and the capture surface (102) is determined: - by detecting at least a maximum value of response signals from a central part of the ultrasonic transducer circuit (104), or - by detecting several maximum values ​​of response signals from several parts of the ultrasonic transducer circuit (104) and calculating an average or median value of said maximum values, or - by applying, to the response signals of the ultrasonic transducer circuit (104), at least one beam-forming type processing then a surface determination algorithm.

10. Biometric identification and constraint situation detection device (100) according to one of the preceding claims, further comprising an element for indicating the pressure of the finger (101) against the capture surface (102).

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