A multi-modal biological acquisition terminal for ten-finger synchronous acquisition and identification

Abstract

The application provides a multi-modal biological acquisition terminal for ten-finger synchronous acquisition and identification, comprising: a shell, the upper surface and the two side surfaces of the shell are respectively embedded with capacitive fingerprint acquisition screens, the inside of the capacitive fingerprint acquisition screen is provided with capacitive nodes C arranged in an array, and the shell is a metal conductive shell; the inside of the shell contains a control circuit, the control circuit comprises: an excitation signal generating unit for generating three excitation signals to drive three capacitive fingerprint acquisition screens; a signal processing unit for receiving the charge change amount Delta Q of each capacitive node C and converting it into a fingerprint feature. The multi-modal biological acquisition terminal for ten-finger synchronous acquisition and identification is based on the ergonomics of three screens in one body, realizes ten-finger synchronous acquisition and identification, and improves the efficiency of fingerprint acquisition and identification; the metal conductive shell in contact with the palm can solve the interference of the superimposed phase difference and common-mode signal, and improve the accuracy of ten-finger synchronous acquisition and identification.

Description

Technical Field

[0001] This application belongs to the field of ten-finger synchronous acquisition and recognition technology, and more specifically, it relates to a multimodal biometric acquisition terminal for ten-finger synchronous acquisition and recognition. Background Technology

[0002] A capacitive fingerprint scanner is a device that uses capacitive sensing technology to capture images of human fingerprints. Its working principle involves detecting the capacitance difference between the ridges and valleys of a fingerprint using a tiny array of capacitor nodes, thereby generating a high-precision fingerprint image.

[0003] However, currently widely used capacitive fingerprint scanners require multiple batches of fingerprints for collection and recognition, resulting in low collection efficiency. Furthermore, these devices are susceptible to interference in complex environments, easily affected by external electromagnetic signals or other environmental factors, leading to data inaccuracies. In addition, their ability to process common-mode information is significantly insufficient, failing to effectively distinguish and filter common-mode noise, further impacting the clarity and accuracy of fingerprint images. These issues collectively contribute to the decline in fingerprint collection quality, limiting the effectiveness of these devices in security authentication and high-precision recognition scenarios. Summary of the Invention

[0004] The purpose of this application is to provide a multimodal biometric acquisition terminal that simultaneously acquires and recognizes ten fingers, so as to solve the technical problem of insufficient efficiency and accuracy of existing capacitive fingerprint acquisition and recognition devices when facing the process of acquiring and recognizing ten fingers.

[0005] To achieve the above objectives, the technical solution adopted in this application is: to provide a multimodal biometric acquisition terminal for simultaneous acquisition and recognition of ten fingers, including a shell, wherein capacitive fingerprint acquisition screens are respectively embedded on the upper surface and two sides of the shell, and the capacitive fingerprint acquisition screens are provided with capacitor nodes C arranged in an array inside, and the shell is a metal conductive shell;

[0006] The housing contains a control circuit, which includes: an excitation signal generating unit for generating three excitation signals to drive three capacitive fingerprint acquisition screens respectively; and a signal processing unit for receiving the charge change ΔQ of each capacitor node C and converting it into fingerprint features.

[0007] In a preferred embodiment, a bias voltage application unit is housed inside the housing, the output of which is electrically connected to the metal conductive housing for continuously applying a bias voltage to the metal conductive housing.

[0008] In a preferred embodiment, the signal processing unit extracts the ridge and valley regions based on the charge change ΔQ of the capacitor node C to convert them into a fingerprint image.

[0009] In a preferred embodiment, the bias voltage is less than the voltage at capacitor node C.

[0010] In a preferred embodiment, the fingerprint feature includes a fingerprint image and a ridge depth, wherein the ridge depth is associated with and mapped to ridge pixels in the fingerprint image; the control circuit further includes: an identification and matching unit, used to perform comprehensive matching of the fingerprint feature with the registered fingerprint feature.

[0011] In a preferred embodiment, the control circuit further includes a voltage adjustment unit connected to a bias voltage application unit, used to adjust the magnitude of the bias voltage applied by the bias voltage application unit to the metal conductive casing; the signal processing unit receives the charge change ΔQ of each capacitor node C under different bias voltage conditions and converts it into fingerprint features.

[0012] In a preferred embodiment, if the voltage of capacitor node C is U, then the voltage adjustment unit adjusts the magnitude of the bias voltage applied by the bias voltage application unit to the metal conductive casing in a gradient manner.

[0013] In a preferred embodiment, the bias voltage is 0.3U, 0.5U, 0.7U, or 0.9U.

[0014] In a preferred embodiment, the signal processing unit is used to perform quality scoring on the fingerprint image of all fingerprint features, and the recognition and matching unit is used to perform comprehensive matching between the fingerprint features and the registered fingerprint features in sequence according to the quality scores.

[0015] In a preferred embodiment, the multimodal biometric acquisition terminal for simultaneous fingerprint acquisition and recognition includes a display screen, on which a face recognition device is provided. The face recognition device is used to perform face recognition simultaneously with fingerprint acquisition.

[0016] The beneficial effects of the multimodal biometric acquisition terminal for simultaneous acquisition and recognition of ten fingers provided in this application are as follows: compared with the prior art, it improves the fingerprint acquisition and recognition efficiency by adopting a three-screen integrated design based on ergonomics and achieving simultaneous acquisition and recognition of ten fingers; the metal conductive shell that contacts the palm can solve the interference of superimposed phase difference and common mode signal, thereby improving the accuracy of simultaneous acquisition and recognition of ten fingers. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A first-view stereoscopic structural diagram of the multimodal bio-acquisition terminal for simultaneous acquisition and recognition of ten fingers provided in this application;

[0019] Figure 2 A second-view stereoscopic structural diagram of the multimodal bio-acquisition terminal for simultaneous acquisition and recognition of ten fingers provided in this application;

[0020] Figure 3 A three-dimensional structural diagram of the shell provided in this application;

[0021] Figure 4 A macroscopic schematic diagram illustrating the interaction between the finger and the capacitive fingerprint sensor during the fingerprint acquisition process provided in this application;

[0022] Figure 5 A microscopic schematic diagram illustrating the interaction between a finger and a capacitive fingerprint sensor during the fingerprint acquisition process provided in this application;

[0023] Figure 6 A visual fingerprint comparison diagram of traditional methods and the present application.

[0024] Figure 7 Visual fingerprint comparison images collected under different bias voltages for this application.

[0025] in Figure 6 and Figure 7 The fingerprint images involved are simulated fingerprints that have been desensitized, removing real fingerprint features. Furthermore, the right half of each fingerprint has been pixelated to protect personal privacy and to more intuitively demonstrate the beneficial effects of the corresponding embodiments. Detailed Implementation

[0026] To make the technical problems, technical solutions, and beneficial effects to be solved by this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and are not intended to limit the scope of this application.

[0027] It should be noted that when a component is referred to as being "fixed to" or "set on" another component, it can be directly on or indirectly on that other component. When a component is referred to as being "connected to" another component, it can be directly connected to or indirectly connected to that other component.

[0028] It should be understood that the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0029] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0030] The first embodiment of this application will be described below.

[0031] Please refer to the following: Figures 1 to 3 The multimodal biometric acquisition terminal 100 for simultaneous acquisition and recognition of ten fingers provided in this application embodiment will now be described. The multimodal biometric acquisition terminal 100 for simultaneous acquisition and recognition of ten fingers includes a shell 10, and capacitive fingerprint acquisition screens 20 are respectively embedded on the upper surface and both sides of the shell 10. The capacitive fingerprint acquisition screens 20 have capacitor nodes C arranged in an array inside. The shell 10 is a metal conductive shell.

[0032] The housing 10 contains a control circuit, which includes: an excitation signal generating unit for generating three excitation signals to drive three capacitive fingerprint acquisition screens 20 respectively; and a signal processing unit connected to the three capacitive fingerprint acquisition screens 20 for receiving the charge change ΔQ of each capacitor node C and converting it into fingerprint features.

[0033] Because capacitive fingerprint sensor screens 20 are embedded on the upper surface and both sides of the outer casing 10, fingerprint collection can be achieved simultaneously with all ten fingers based on ergonomics. Specifically, when collecting fingerprints from all ten fingers, with both hands outstretched and palms facing down, the capacitive fingerprint sensor screen 20 embedded on the upper surface of the outer casing 10 collects both thumbs, the capacitive fingerprint sensor screen 20 embedded on the left side of the outer casing 10 collects the four fingers of the left hand, and the capacitive fingerprint sensor screen 20 embedded on the right side of the outer casing 10 collects the four fingers of the right hand. In this way, the palm of the hand will inevitably contact the conductive metal casing during the collection process. The conductive metal casing provides stable support for the palm, improving the stability of the fingerprint collection process and achieving the goal of simultaneous collection of all ten fingers, thus improving collection efficiency.

[0034] It is worth noting that when the three capacitive fingerprint sensor screens 20 are working, each generates an independent excitation signal. Since the human body is a conductor, when a finger touches different capacitive fingerprint sensor screens 20, the human body becomes a shared common node. Even if the same excitation signal generating unit generates excitation signals with the same phase simultaneously, there will still be a certain phase difference between the different capacitive fingerprint sensor screens 20 during execution. When the human body's hands simultaneously contact the capacitive fingerprint sensor screens 20 on three surfaces during simultaneous fingerprint acquisition, the human hands act as a bridge to conduct the interference of this phase difference. After the three phase differences converge and superimpose within the human body, they will be amplified exponentially. The superposition interference of the phase difference further aggravates the chaos of the common-mode signal, causing serious interference to the weak and effective signal of fingerprint acquisition, resulting in a decrease in fingerprint image quality.

[0035] However, when the human body collects fingerprints simultaneously with all ten fingers, the palm of the hand will come into contact with the metal conductive shell. The metal conductive shell enhances the grounding effect. On the one hand, the metal conductive shell can eliminate static electricity from the fingers. On the other hand, since the palm is located at the junction of the thumb and the other four fingers, the metal conductive shell in contact with the palm can absorb the superimposed phase difference interference information, weaken the signal interference between different screens, and thus enable the signal processing unit to obtain the real charge change ΔQ of each capacitor node C.

[0036] Specifically, the conductive metal shell can be made of conductive materials such as aluminum alloy, brass, stainless steel or titanium alloy. Aluminum alloy has both conductivity and lightweight properties, brass has excellent conductivity, stainless steel has strong corrosion resistance, and titanium alloy has high strength and biocompatibility.

[0037] The second embodiment of this application will be described below, which is based on the first embodiment.

[0038] The housing 10 contains a bias voltage application unit, the output of which is electrically connected to the metal conductive housing and is used to continuously apply a bias voltage to the metal conductive housing.

[0039] It is understandable that by applying a bias voltage to the conductive metal casing, the palm of the hand will inevitably come into contact with the conductive metal casing when a fingerprint is collected. This causes the electric potential of the human body to change from a floating state (equivalent to passively enduring common-mode interference in Example 1) to being actively clamped to a fixed potential by the external circuit. At this time, a stable equipotential body is formed on the surface of the human finger, which can then actively resist the superposition of phase difference interference propagated from different screens.

[0040] In addition, please refer to the following: Figure 4Since the charge change ΔQ of each capacitor node C can be decomposed into two parts: effective charge Q1 and common-mode charge Q2. Effective charge Q1 refers to a portion of the charge generated by the emitting electrode of capacitor node C when the fingerprint ridge directly contacts the capacitive fingerprint collection screen 20; common-mode charge Q2 refers to the common-mode interference signal absorbed by the finger from capacitor node C.

[0041] Please refer to the following in this second embodiment: Figure 5 Because the human body's electric potential is clamped, the electric potential of all finger surfaces is consistent. The protective film on the surface of the capacitive fingerprint sensor 20 is in contact with the skin, and the ridges of the finger contact surface can be considered to be located on the same horizontal plane. Therefore, the effective charge Q1 value of the capacitor node C at the ridge covered by the same finger contact surface can be considered equal when the medium is the same, and its common mode charge Q2 value can also be considered equal. Furthermore, because the valley depths of the same finger contact surface are not equal, the common mode charge Q2 value of the capacitor node C at the valley covered by the finger contact surface represents the valley depth. The greater the valley depth, the smaller the common mode charge Q2.

[0042] Therefore, the signal processing unit extracts the ridge and valley regions based on the charge change ΔQ of the capacitor node C to convert them into a fingerprint image.

[0043] The specific implementation is as follows:

[0044] The change in charge ΔQ of a capacitor node C without finger coverage: ΔQ≈0;

[0045] The change in charge ΔQ at the capacitance node C of the ridge contact surface: Since the finger skin is in direct contact, the effective charge Q1 and the common mode charge Q2 are coupled away at the same time, so ΔQ≈Q1+Q2;

[0046] The charge change ΔQ at the capacitance node C of the valley-covered surface: Since the finger skin is close to but not in direct contact with the skin, the common-mode charge Q2 is mainly coupled away, so ΔQ≈Q2.

[0047] By classifying the capacitor nodes C according to the gradient change of charge change ΔQ, fingerprint features with stable and clear ridges and high contrast valleys can be generated.

[0048] It must be emphasized that the bias voltage should be understood as a voltage within the safe voltage range for the human body. Preferably, the bias voltage is less than the voltage of capacitor node C. For example, the voltage of capacitor node C in a capacitive fingerprint sensor 20 is typically 3.3 volts, and the bias voltage range is (0, 3.3). Thus, the human body will not feel the presence of the bias voltage during fingerprint collection, and it will not affect human health.

[0049] Compared with the prior art, Embodiment 2 of the present invention has the following significant beneficial effects:

[0050] (1) By actively clamping the human body potential, a stable equipotential body is formed on the surface of the human finger, which transforms the passive bearing into an active resistance to the phase difference superposition interference and common mode interference propagated from different screens as well as external interference.

[0051] (2) Please refer to the following: Figure 6 Traditional methods often result in uneven distribution of the effective charge Q1, with a higher concentration at the fingerprint center and a lower concentration at the edges. This leads to thicker and more continuous ridge lines in the center, while the edges are thinner and less defined. In this second embodiment, because the potential and height of the ridges on all finger surfaces are consistent, all effective charges Q1 are forced to be unified to a single baseline, improving the uniformity and integrity of the ridge line distribution in the fingerprint image.

[0052] (3) In traditional methods, common-mode signals are considered as interference information and are usually suppressed as much as possible. However, in this second embodiment, the common-mode charge Q2 value of the capacitor node C at the valley covered by the same finger contact surface represents the valley depth, which transforms the common-mode interference into effective information with actual physical meaning. The fingerprint image can be defined by the ridge features and valley features, which improves the quality of fingerprint feature acquisition and recognition accuracy.

[0053] The third embodiment of this application will be described below, which is based on the second embodiment.

[0054] Please refer to the following: Figure 5 The fingerprint features include a fingerprint image and ridge depth, wherein the ridge depth is associated with and mapped to ridge pixels in the fingerprint image. The control circuit further includes a recognition and matching unit, used to comprehensively match the fingerprint features with registered fingerprint features.

[0055] Understandably, traditional fingerprint recognition technology primarily relies on matching fingerprint images for identification. However, this approach often overlooks the crucial feature of fingerprint ridge depth. Ridge depth, as an inherent attribute of fingerprints, possesses high uniqueness and stability, providing richer information for fingerprint recognition. In this embodiment, by associating ridge depth with ridge pixels in the fingerprint image, the fingerprint features not only include the ridge information but also incorporate ridge depth information.

[0056] In its implementation, the recognition and matching unit first preprocesses the acquired fingerprint image, extracting the ridges and valleys of the fingerprint. Then, based on the mapping relationship between valley pixels and valley depth, it converts the valley pixels into corresponding valley depth values. In this way, each fingerprint feature contains two parts of information: the fingerprint image and the valley depth.

[0057] During fingerprint matching, the identification and matching unit comprehensively compares the collected fingerprint features with the registered fingerprint features. This comparison includes not only the similarity of the fingerprint images but also the degree of matching in the depth of the fingerprint ridges. Only when both the fingerprint image and the ridge depth reach a certain matching threshold are the two fingerprint features considered a match.

[0058] This comprehensive matching method greatly improves the accuracy and reliability of fingerprint recognition. On the one hand, the introduction of ridge depth increases the dimensionality of fingerprint features, making the matching process more rigorous and accurate; on the other hand, as an inherent property of fingerprints, ridge depth is not easily affected by external factors, such as the pressure applied by the finger or the dryness of the skin, thereby improving the stability of fingerprint recognition.

[0059] The fourth embodiment of this application will now be described, which is based on the third embodiment.

[0060] Please refer to the following: Figure 7 The control circuit further includes a voltage adjustment unit connected to the bias voltage application unit, used to adjust the magnitude of the bias voltage applied by the bias voltage application unit to the metal conductive casing. The signal processing unit receives the charge change ΔQ of each capacitor node C under different bias voltage conditions and converts it into fingerprint features.

[0061] Understandably, the effective charge Q1 is the charge coupled when the fingerprint ridge directly contacts the capacitor node C, and its value is directly related to the potential difference between the capacitor node C and the finger. When the bias voltage is higher, i.e., close to the voltage of the capacitor node C, the potential difference between the human body and the capacitor node C decreases, weakening the electric field strength driving charge transfer. This reduces the coupling ability of the fingerprint ridge to the effective charge Q1, causing more capacitor nodes C that were originally identified as ridges to be identified as valleys due to the potential change. This results in a smaller ridge area, visually appearing as thinner fingerprint lines and larger gaps, effectively reducing the pressure applied by the finger. Conversely, if the bias voltage decreases, the fingerprint lines appear thicker and the gaps smaller, effectively increasing the pressure applied by the finger.

[0062] Therefore, fingerprint features obtained under different bias voltage conditions are equivalent to collecting multiple sets of fingerprint features under different pressures, which can solve the influence of finger pressure on fingerprint acquisition and recognition, and improve the accuracy of fingerprint recognition.

[0063] In addition, this method can also solve the problem of fingerprint images being too thin or too thick due to regional fingerprint differences.

[0064] Preferably, if the voltage at capacitor node C is U, then the voltage adjustment unit adjusts the bias voltage applied by the bias voltage application unit to the metal conductive casing in a gradient manner. For example, the bias voltage values ​​are 0.3U, 0.5U, 0.7U, and 0.9U.

[0065] Preferably, the signal processing unit is used to perform quality scoring on the fingerprint image of all fingerprint features, and the recognition and matching unit is used to perform comprehensive matching between the fingerprint features and the registered fingerprint features in order of quality score.

[0066] Understandably, by using a signal processing unit to score the quality of each fingerprint image, key indicators such as clarity and integrity of each fingerprint can be objectively evaluated. Subsequently, the identification and matching unit, based on these quality scores, sequentially matches the fingerprint features with the registered fingerprint features in descending order of quality. This approach ensures that the highest quality fingerprint features are prioritized for identification, thereby effectively improving the efficiency and accuracy of fingerprint recognition and avoiding identification errors or duplicate identifications caused by using low-quality fingerprint features.

[0067] The fifth embodiment of this application will now be described, while the fourth embodiment is based on any one of the first to fourth embodiments.

[0068] Please refer to the following: Figure 1 and Figure 2 The multimodal biometric acquisition terminal 100 for simultaneous fingerprint acquisition and recognition includes a display screen 30, on which a face recognition device 40 is provided. The face recognition device 40 is used to perform face recognition simultaneously with fingerprint acquisition.

[0069] Understandably, in traditional identity verification methods, fingerprint recognition and facial recognition are often performed independently, which increases the complexity and time cost of verification to some extent. However, in this embodiment, by setting a facial recognition device 40 on the display screen 30 of the multimodal biometric data acquisition terminal 100 that simultaneously acquires and recognizes ten fingers, facial recognition is achieved simultaneously with fingerprint acquisition, greatly improving the efficiency and convenience of identity verification. Specifically, when a user places both hands on the acquisition terminal for fingerprint acquisition, the facial recognition device 40 on the display screen 30 simultaneously captures the user's facial image and compares it with pre-stored registered facial images in the system. Identity verification is considered successful only when both fingerprint and facial features match successfully. This multimodal biometric method not only improves the accuracy of recognition but also enhances system security, effectively preventing the risk of a single biometric feature being forged or misused.

[0070] The sixth embodiment of this application will now be described, which is based on any one of the first to fifth embodiments.

[0071] The control circuit also includes a CPU, which serves as the core processing unit of the entire acquisition terminal, undertaking the important tasks of data processing, instruction control, and collaborative work with other modules. The CPU is connected to the capacitive fingerprint acquisition screen 20, the excitation signal generation unit, the signal processing unit, the bias voltage application unit, the identification matching unit, and the voltage regulation unit. It can efficiently process data from multiple modules, including the excitation signal generation unit, the signal processing unit, the identification matching unit, and the voltage regulation unit, ensuring the stable operation of the entire acquisition terminal. During fingerprint acquisition, the CPU precisely regulates the excitation signal generated by the excitation signal generation unit to ensure that the three capacitive fingerprint acquisition screens 20 operate normally according to preset requirements. Simultaneously, the CPU receives real-time data on the charge change ΔQ of each capacitor node C from the signal processing unit and uses advanced algorithms to perform in-depth analysis and processing of this data, thereby extracting accurate and clear fingerprint features. In the identification matching stage, the CPU directs the identification matching unit to quickly and accurately compare the acquired fingerprint features with the registered fingerprint features, and determines whether identity verification is successful based on a set matching threshold. Furthermore, the CPU works closely with the voltage regulation unit to dynamically adjust the bias voltage applied by the bias voltage application unit to the metal conductive casing according to actual needs, thereby acquiring fingerprint features under different conditions and further improving the accuracy and adaptability of fingerprint recognition. When the face recognition device 40 on the display screen 30 performs face recognition, the CPU also undertakes the important work of data processing and comparison, meticulously comparing the captured face image with the registered face image to ensure the accuracy of face recognition. Through the powerful processing capabilities and precise control of the CPU, the multimodal biometric acquisition terminal 100, which simultaneously acquires and recognizes ten fingers, can achieve efficient, accurate, and secure identity verification functions.

[0072] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A multimodal biometric data acquisition terminal for simultaneous acquisition and recognition of ten fingers, characterized in that, The device includes an outer shell, on the upper surface and both sides of which are respectively embedded with capacitive fingerprint collection screens. The capacitive fingerprint collection screens are provided with capacitor nodes C arranged in an array inside. The outer shell is a metal conductive shell. The housing contains a control circuit, which includes: an excitation signal generating unit for generating three excitation signals to drive three capacitive fingerprint acquisition screens respectively; and a signal processing unit for receiving the charge change ΔQ of each capacitor node C and converting it into fingerprint features. The housing contains a bias voltage application unit, the output of which is electrically connected to the metal conductive housing and is used to continuously apply a bias voltage to the metal conductive housing. The signal processing unit extracts the ridge and valley regions based on the charge change ΔQ of capacitor node C to convert them into a fingerprint image. The charge change ΔQ of each capacitor node C is divided into two parts: effective charge Q1 and common mode charge Q2. The common mode charge Q2 value of capacitor node C at the valley covered by the finger contact surface represents the valley depth. The fingerprint features include a fingerprint image and a valley depth, wherein the valley depth is associated with and mapped to valley pixels in the fingerprint image.

2. The multimodal biometric acquisition terminal for simultaneous acquisition and recognition of ten fingers as described in claim 1, characterized in that, The bias voltage is less than the voltage at capacitor node C.

3. The multimodal biometric acquisition terminal for simultaneous acquisition and recognition of ten fingers as described in claim 1, characterized in that, The control circuit further includes an identification and matching unit, used to comprehensively match fingerprint features with registered fingerprint features.

4. The multimodal biometric acquisition terminal for simultaneous acquisition and recognition of ten fingers as described in claim 3, characterized in that, The control circuit also includes a voltage adjustment unit connected to the bias voltage application unit, which is used to adjust the magnitude of the bias voltage applied by the bias voltage application unit to the metal conductive shell; the signal processing unit receives the charge change ΔQ of each capacitor node C under different bias voltage conditions and converts it into fingerprint features.

5. The multimodal biometric acquisition terminal for simultaneous acquisition and recognition of ten fingers as described in claim 4, characterized in that, Let the voltage of capacitor node C be U. Then, the voltage adjustment unit adjusts the bias voltage applied by the bias voltage application unit to the metal conductive shell in a gradient manner.

6. The multimodal biometric acquisition terminal for simultaneous acquisition and recognition of ten fingers as described in claim 5, characterized in that, The bias voltages are 0.3U, 0.5U, 0.7U, and 0.9U.

7. The multimodal biometric acquisition terminal for simultaneous acquisition and recognition of ten fingers as described in claim 6, characterized in that, The signal processing unit is used to score the quality of fingerprint images with all fingerprint features, and the recognition and matching unit is used to perform comprehensive matching between fingerprint features and registered fingerprint features in order of quality score.

8. The multimodal biometric acquisition terminal for simultaneous acquisition and recognition of ten fingers as described in any one of claims 1 to 7, characterized in that, The multimodal biometric acquisition terminal that simultaneously acquires and identifies ten fingers includes a display screen, on which a face recognition device is installed. The face recognition device is used to perform face recognition simultaneously with fingerprint acquisition.

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