Ultrasonic fingerprint imaging method, fingerprint recognition device and electronic equipment

Abstract

The present invention relates to the field of ultrasonic fingerprint recognition technology, and in particular to an ultrasonic fingerprint imaging method, fingerprint recognition device, and electronic device. The method comprises the following steps: distributing ultrasonic transducers in a uniform rectangular array on a sensor, dividing each n×n ultrasonic transducer array into a group, transmitting multiple ultrasonic waves toward an object, and receiving and outputting multiple ultrasonic signals reflected from the object by the ultrasonic transducers; based on the bionic principle of image convolution and the numerical value of each point in the convolution kernel, individually adjusting the amplitude of each pixel in the ultrasonic transducer array; based on the principle of beamforming, individually adjusting the phase of each pixel in the ultrasonic transducer array; focusing the sound wave intensity of surrounding pixels above the central pixel through beamforming technology; and acquiring a fingerprint image of the object at the central pixel.

Description

Technical field

[0001] The present invention relates to the technical field of ultrasonic fingerprint recognition, and in particular to an ultrasonic fingerprint imaging method, a fingerprint recognition device and an electronic device. [Background Technology]

[0002] Ultrasonic fingerprint recognition is an advanced biometric technology widely used in security authentication, identity verification, and payment authorization. Compared to traditional capacitive and optical fingerprint recognition technologies, ultrasonic fingerprint recognition offers greater adaptability and stronger anti-counterfeiting capabilities because ultrasound can penetrate the epidermis and reach the dermis, resulting in more stable and reliable fingerprint images. In recent years, with the rapid development of mobile devices, smart homes, and other fields, ultrasonic fingerprint recognition technology has also gained widespread application.

[0003] Ultrasonic fingerprint recognition modules utilize the propagation and reflection characteristics of ultrasound waves in biological tissue. Ultrasonic sensors transmit and receive ultrasonic signals to capture fingerprint images from the user's finger surface and perform identity verification. The key to ultrasonic fingerprint recognition lies in the quality of the sound waves used for imaging. Its operation primarily involves four stages: emission, propagation, reflection, and reception. Due to the compact design of mobile devices, the size and power of ultrasonic fingerprint recognition modules are limited. The ultrasonic frequency used is capped at above 10MHz, resulting in poor sound penetration, significant loss of sound wave intensity during propagation, and low intensity, making it difficult to obtain a clear fingerprint image for subsequent image processing and recognition.

[0004] Ultrasonic beamforming technology uses phase and amplitude differences between multiple sensor elements to direct and focus ultrasonic signals. It has a wide range of applications in ultrasonic imaging and sensing, including medical ultrasound imaging, ultrasonic measurement, ultrasonic tracking, and fingerprint recognition. Beamforming aims to concentrate ultrasonic energy in a specific area, thereby improving signal strength and resolution. Traditional ultrasonic transmission and reception are omnidirectional, meaning they transmit and receive signals in all directions. In this case, ultrasonic sensors receive signals from various directions, containing a significant amount of scattered information and noise, reducing the clarity and accuracy of imaging or measurement. Beamforming technology controls the phase and amplitude of sensor elements so that the transmitted and received signals interfere with each other, forming a concentrated beam in a specific direction. This allows ultrasonic waves to penetrate biological tissue more precisely, improving the resolution and accuracy of imaging or measurement.

[0005] Existing solutions apply beamforming technology to ultrasonic fingerprint recognition modules to achieve concentrated enhancement of sound wave intensity without increasing power consumption or changing the ultrasonic frequency. However, existing beamforming technology only applies to the ultrasonic transducer array column by column, with five columns forming a group. By varying the phase of the drive signals of four adjacent columns of transducers, the ultrasonic signals interfere within a certain depth range, resulting in limited enhancement of sound wave intensity. [Summary of the invention]

[0006] In order to solve the technical problem that the existing beamforming technology has limited enhancement of the signal-to-noise ratio of ultrasonic fingerprint images without changing the power consumption and ultrasonic frequency, the present invention provides an ultrasonic fingerprint imaging method, a fingerprint recognition device and an electronic device.

[0007] The solution to the technical problem of the present invention is to provide an ultrasonic fingerprint imaging method, comprising the following steps:

[0008] The ultrasonic transducers are arranged on the sensor in a uniform rectangular array, each n×n ultrasonic transducer array is divided into a group, the ultrasonic transducers transmit a plurality of ultrasonic waves toward the object, and receive and output a plurality of ultrasonic signals reflected from the object;

[0009] Based on the bionic principle of image convolution, the amplitude of each pixel in the ultrasonic transducer array is individually adjusted based on the value of each point in the convolution kernel;

[0010] Based on the principle of beamforming, the phase of each pixel in the ultrasonic transducer array is individually adjusted;

[0011] Through beamforming technology, the sound wave intensity of surrounding pixels is focused above the central pixel;

[0012] The fingerprint image of the object is acquired at the central pixel point. Preferably, the ultrasonic transducer comprises a first controller and a second controller, and the first controller and the second controller respectively adjust the amplitude and phase of each ultrasonic transducer.

[0013] Preferably, the ultrasonic transducer further includes a TFT thin film array for controlling the ultrasonic transducer, and after focusing the intensity of the sound wave and before acquiring the fingerprint image at the central pixel point, the following steps are further included:

[0014] Each row and column in the TFT thin film array is connected to a signal line;

[0015] The signal lines of each row and column are connected to a multiplexer, and the multiplexer selects n voltage signals to pass through;

[0016] The row and column voltage signals selected by each pixel are superimposed to calculate the final convolution kernel value.

[0017] Preferably, when determining the amplitude of the convolution kernel of the constrained beamforming, the following steps are also required:

[0018] Use Gaussian convolution kernel to remove high-frequency noise from the image;

[0019] Use Laplacian convolution kernel to enhance the edge features of the image;

[0020] The two convolution kernels are weighted added together to form a new convolution kernel.

[0021] Preferably, the convolution operation comprises the following steps:

[0022] The emission of ultrasonic waves with different phases is achieved through timing design, and the amplitude of the ultrasonic waves is adjusted by designing the voltage.

[0023] Preferably, the depth range of the acoustic wave intensity after focusing the acoustic wave intensity of the surrounding pixel points is 0.8 mm-1.2 mm.

[0024] Preferably, the spacing between the ultrasonic transducers is in the range of 40 μm to 60 μm.

[0025] The present invention also provides a fingerprint recognition device, comprising a fingerprint recognition module and a touch layer, wherein the fingerprint recognition module implements the above-mentioned ultrasonic fingerprint imaging method;

[0026] One surface of the touch layer is a touch surface for user operation, and the fingerprint recognition module is arranged on the other surface opposite to the touch surface.

[0027] Preferably, the fingerprint recognition module includes an ultrasonic transducer, and the fingerprint recognition module is composed of the ultrasonic transducer array.

[0028] The present invention also provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer program is configured to execute the above-mentioned ultrasonic fingerprint imaging method when running;

[0029] The processor is configured to execute the ultrasonic fingerprint imaging method through the computer program.

[0030] Compared with the prior art, the ultrasonic fingerprint imaging method, fingerprint recognition device, and electronic device provided by the present invention have the following advantages:

[0031] 1. The ultrasonic fingerprint imaging method provided in an embodiment of the present invention includes the following steps: setting ultrasonic transducers to be distributed in a uniform rectangular array on the sensor, dividing each n×n ultrasonic transducer array into a group, and having the ultrasonic transducers transmit multiple ultrasonic waves to the object, and receiving and outputting multiple ultrasonic signals reflected from the object; based on the bionic principle of image convolution, the amplitude of each pixel point in the ultrasonic transducer array is individually adjusted based on the value of each point in the convolution kernel; based on the principle of beamforming, the phase of each pixel point in the ultrasonic transducer array is individually adjusted; through beamforming technology, the sound wave intensity of the surrounding pixels is focused above the central pixel point; and the fingerprint image of the object is obtained at the central pixel point.

[0032] It should be noted that the existing beamforming technology only implements beamforming technology for ultrasonic transducer arrays in columns, with five columns as a group. By changing the phase of the driving signal of four adjacent columns of ultrasonic transducers, the ultrasonic signals are interfered within a certain depth range, and the enhancement of the sound wave intensity is limited.

[0033] It can be understood that the present invention uses a beamforming transmitting array to replace the traditional transmitting array, and combines the bionic principle of image convolution to adjust the sound wave intensity of different pixel points. It can realize image convolution operation at the hardware level and enhance the imaging effect without increasing the cost.

[0034] It can be further understood that when achieving the same imaging quality, the ultrasonic fingerprint imaging method involved in the present invention can significantly reduce power consumption. The ultrasonic beamforming array used in the present invention makes the sound wave intensity of the ultrasonic wave more concentrated after focusing, and greatly improves the penetration of the ultrasonic wave. Therefore, the ultrasonic emission energy required to stimulate the same piezoelectric sensing signal will be greatly reduced. At the same time, the service life of the ultrasonic module is also increased.

[0035] 2. In the ultrasonic fingerprint imaging method provided in an embodiment of the present invention, the ultrasonic transducer includes a first controller and a second controller, each of which adjusts the amplitude and phase of the ultrasonic transducer. This method implements image convolution at the hardware level, utilizing the principles of convolutional image processing to improve image quality at the hardware level. This ensures enhanced imaging without increasing costs, resulting in clearer and more accurate images and overcoming the drawbacks of traditional ultrasonic imaging, which often suffer from difficulty and poor image quality.

[0036] 3. In the ultrasonic fingerprint imaging method provided by an embodiment of the present invention, the ultrasonic transducer also includes a TFT thin film array for controlling the ultrasonic transducer. After focusing the sound wave intensity and before acquiring the fingerprint image at the central pixel, the method further includes the following steps: connecting a signal line to each row and column in the TFT thin film array; connecting the signal line of each row and column to a multiplexer, which selects n voltage signals to pass through; and superimposing the row and column voltage signals selected by each pixel to calculate the value of the final convolution kernel.

[0037] It can be understood that the present invention multiplies different convolution kernels with different weights and then adds them together to form a new convolution kernel that can be used for ultrasonic fingerprint image enhancement. The value of this convolution kernel is then used as the coefficient for controlling the amplitude of each pixel to implement hardware-level image convolution, and a clearer fingerprint image can be obtained for subsequent processing.

[0038] 4. In the ultrasonic fingerprint imaging method provided by the embodiment of the present invention, the convolution operation includes the following steps: emitting ultrasonic waves of different phases through timing design, and adjusting the ultrasonic amplitude by designing the voltage.

[0039] It can be understood that the essence of timing design is to meet the requirements of the emission time, holding time, etc. of each different phase ultrasound, so as to achieve the process of timing convergence. It can be further understood that timing design enables data to arrive at the correct time and be processed correctly.

[0040] It should be noted that timing closure is the process of adjusting and modifying the design during the design of integrated circuits such as field programmable gate arrays and application-specific integrated circuits so that the designed circuit meets the timing requirements.

[0041] The amplitude of the ultrasonic wave is adjusted by designing the voltage. The voltage has a greater impact on the ultrasonic wave. The stronger the voltage, the greater the amplitude of the ultrasonic wave.

[0042] 5. The ultrasonic fingerprint imaging method provided by the embodiment of the present invention further requires the following steps when determining the amplitude of the constrained beamforming convolution kernel: using a Gaussian convolution kernel to remove high-frequency noise from the image; using a Laplacian convolution kernel to enhance the edge features of the image; and performing weighted addition of the two convolution kernels to form a new convolution kernel.

[0043] As can be understood, the Gaussian convolution kernel and the Laplacian convolution kernel of the present invention process images separately. The Gaussian convolution kernel performs noise reduction processing on the image, reducing noise introduced by sampling, transmission, and other reasons, shielding noise interference, and thus improving image quality; the Laplacian convolution kernel performs image sharpening processing, highlighting details in the image, making the image appear clearer and more refined.

[0044] In addition, noise reduction processing can also help improve the accuracy and reliability of target detection and image segmentation; sharpening processing can also enhance the edges in the image, making the boundaries of human bodies or objects more obvious, which is helpful for target detection and segmentation.

[0045] 6. In the ultrasonic fingerprint imaging method provided by an embodiment of the present invention, the depth range of the sound wave intensity after focusing the sound wave intensity of the surrounding pixels is 0.8mm-1.2mm. It can be understood that the actual application scenarios of the fingerprint imaging method involved in the present invention are mostly fingerprint recognition under the screen of electronic devices. The depth of focusing the sound wave intensity of the surrounding pixels on the central pixel is set to 0.8mm-1.2mm above the array. This distance is approximately the distance from the fingerprint recognition sensor to the finger, ensuring that the sound wave can be accurately focused on the surface of the finger.

[0046] 7. In the ultrasonic fingerprint imaging method provided by the embodiment of the present invention, the spacing between ultrasonic transducers ranges from 40μm to 60μm. It is understood that the ultrasonic transducers are distributed in a uniform rectangular array on the sensor, and the spacing between adjacent ultrasonic transducers in the horizontal or vertical direction is a fixed value. Each ultrasonic transducer represents a pixel point. The spacing between ultrasonic transducers can be set according to the resolution requirements. Therefore, it can be adjusted and modified according to the specific situation in different application scenarios.

[0047] 8. An embodiment of the present invention further provides a fingerprint recognition device, comprising a fingerprint recognition module and a touch layer, wherein the fingerprint recognition module implements the above-mentioned ultrasonic fingerprint imaging method; one surface of the touch layer is a touch surface for user operation, and a fingerprint recognition module is provided on the other surface opposite to the touch surface.

[0048] Specifically, the fingerprint recognition module includes an ultrasonic transducer, and the fingerprint recognition module is composed of an ultrasonic transducer array.

[0049] The fingerprint recognition device has the same beneficial effects as the above-mentioned ultrasonic fingerprint imaging method, which will not be described in detail here.

[0050] 9. An embodiment of the present invention further provides an electronic device, comprising a memory and a processor, wherein a computer program is stored in the memory, and the computer program is configured to execute the above-mentioned ultrasonic fingerprint imaging method when it is run; and the processor is configured to execute the above-mentioned ultrasonic fingerprint imaging method through the computer program.

[0051] This electronic device has the same beneficial effects as the above-mentioned ultrasonic fingerprint imaging method, which will not be described in detail here.

Brief Description of the Drawings

[0052] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0053] Figure 1 This is a schematic diagram of the bionic principle of visual system cell imaging, which is the technical inspiration source of the present invention.

[0054] Figure 2 This is a schematic diagram of the process of an ultrasonic fingerprint imaging method provided by the first embodiment of the present invention. Figure 1 .

[0055] Figure 3 This is a schematic diagram of a 3×3 convolution kernel and a new pixel obtained by convolution of the original pixel in an ultrasonic fingerprint imaging method provided by the first embodiment of the present invention.

[0056] Figure 4 Schematic diagram of utilizing amplitude and phase to enhance ultrasonic focusing in an ultrasonic fingerprint imaging method provided by the first embodiment of the present invention.

[0057] Figure 5 This is a schematic diagram of the process of an ultrasonic fingerprint imaging method provided by the first embodiment of the present invention. Figure 2 .

[0058] Figure 6 Schematic diagram of square wave phase difference of a beamforming technology in an ultrasonic fingerprint imaging method provided by the first embodiment of the present invention.

[0059] Figure 7 Schematic diagram of the distribution of convolution kernels of a transmitting array in an ultrasonic fingerprint imaging method provided in the first embodiment of the present invention.

[0060] Figure 8 1 is a schematic diagram of a framework of an ultrasonic transducer in an ultrasonic fingerprint imaging method provided by the first embodiment of the present invention.

[0061] Figure 9 Schematic diagram of the connection relationship of voltage signals in an ultrasonic fingerprint imaging method provided by the first embodiment of the present invention.

[0062] Figure 10 This is a schematic diagram of the process of an ultrasonic fingerprint imaging method provided by the first embodiment of the present invention. Figure 3 .

[0063] Figure 11 It is a schematic diagram of the framework of a fingerprint recognition device provided by the second embodiment of the present invention.

[0064] Figure 12 It is a schematic diagram of the framework of an electronic device provided by the third embodiment of the present invention.

[0065] Description of the accompanying drawings:

[0066] 10. Ultrasonic transducer; 100. First controller; 101. Second controller; 102. TFT thin film array; 103. Signal line; 104. Multiplexer;

[0067] 2. Fingerprint recognition device; 20. Fingerprint recognition module; 21. Touch layer;

[0068] 3. Electronic device; 30. Memory; 300. Computer program; 31. Processor. [Specific implementation method]

[0069] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and implementation examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0070] In the embodiments provided herein, it should be understood that "B corresponding to A" means that B is associated with A and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B based solely on A; B can also be determined based on A and / or other information.

[0071] It should be understood that references to "one embodiment" or "an embodiment" throughout this specification mean that specific features, structures, or characteristics associated with the embodiment are included in at least one embodiment of the present invention. Therefore, the appearance of "in one embodiment" or "in an embodiment" throughout this specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. Those skilled in the art should also be aware that the embodiments described in this specification are all optional embodiments, and the actions and modules involved are not necessarily required for the present invention.

[0072] In various embodiments of the present invention, it should be understood that the size of the serial numbers of the above-mentioned processes does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0073] The flow charts and block diagrams in the accompanying drawings of the present invention illustrate the possible implementation architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementation schemes, the functions marked in the box can also occur in a different order than those marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which is determined based on the functions involved. It should be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0074] Existing beamforming technology has different phases but the same intensity, and only implements beamforming technology for ultrasonic transducer arrays in columns, with five columns as a group. By changing the phase of the drive signal of four adjacent columns of ultrasonic transducers, the ultrasonic signals are interfered within a certain depth range, and the enhancement of sound wave intensity is limited.

[0075] The present invention relates to the acquisition and processing of fingerprint images, combining the bionic principles of image convolution technology with those of human and animal vision systems to achieve the enhancement of ultrasonic fingerprint images. It should be noted that the technical implementation of the present invention is based on the fact that the amplitude and phase of each ultrasonic transducer can be individually controlled.

[0076] See also Figure 1 , primary cells in the visual system, such as simple and complex cells in the visual cortex, have specific responses to specific spatial patterns or directions. These cells can be regarded as biological filters because they are activated when they encounter specific image features. When researchers tried to simulate this visual processing, they found that convolution operations were an effective way to imitate this selective neural activation. In the design of convolutional neural networks, this principle is implemented as a series of convolutional layers, in which filters can learn to extract a variety of features from the data.

[0077] It should be noted that image convolution is a mathematical operation widely used in image processing and computer vision, and plays an important role in deep learning and convolutional neural networks.

[0078] Convolution operations can extract specific features of an image, enhance an image, or smooth an image to achieve various purposes, such as edge detection, image sharpening, and noise reduction. Simply put, image convolution uses a small matrix called a "convolution kernel" or "filter" to slide over each pixel of the image; for each local area covered by the filter, it performs a weighted sum operation to generate a new pixel value.

[0079] For details, please refer to Figures 2 to 4 A first embodiment of the present invention provides an ultrasonic fingerprint imaging method, comprising the following steps:

[0080] S1: The ultrasonic transducers are distributed in a uniform rectangular array on the sensor. Each n×n ultrasonic transducer array is divided into a group. The ultrasonic transducers transmit multiple ultrasonic waves to the object and receive and output multiple ultrasonic signals reflected from the object.

[0081] S2: Based on the bionic principle of image convolution, the amplitude of each pixel in the ultrasonic transducer array is adjusted individually according to the value of each point in the convolution kernel;

[0082] S3: Based on the principle of beamforming, the phase of each pixel in the ultrasonic transducer array is individually adjusted;

[0083] S4: Uses beamforming technology to focus the sound wave intensity of surrounding pixels on the center pixel.

[0084] S5: Obtain the fingerprint image of the object at the center pixel point.

[0085] It can be understood that the ultrasonic fingerprint imaging method provided in the first embodiment of the present invention adopts a beamforming transmitting array to replace the traditional transmitting array, and combines the bionic principle of image convolution to adjust the sound wave intensity of different pixel points to realize image convolution operation at the hardware level, which can enhance the imaging effect at a low cost.

[0086] It can be further understood that when achieving the same imaging quality, the ultrasonic fingerprint imaging method involved in the present invention can significantly reduce power consumption. The ultrasonic beamforming array used in the present invention can make the sound wave intensity of the ultrasonic wave more concentrated after focusing, thereby greatly improving the penetration of the ultrasonic wave. As a result, the ultrasonic emission energy required to excite the same piezoelectric sensing signal will be greatly reduced. At the same time, the service life of the ultrasonic module is also increased.

[0087] The existing beamforming technology solutions were mentioned in the background technology. The enhanced beamforming technology involved in the present invention is that the ultrasonic transducers composed of transmitting electrodes and piezoelectric films are distributed on the sensor in a uniform rectangular array. In the first embodiment of the present invention, each 3×3 ultrasonic transducer array is divided into a group (that is, the above n is 3). By controlling the amplitude and phase of each pixel point in the 3×3 ultrasonic transducer array, the sound wave intensity of the eight surrounding pixel points is focused above the central pixel point, thereby improving the sound wave intensity without increasing the power consumption of the module.

[0088] The present invention acquires fingerprint images at the front end and relies on beamforming to implement image convolution technology to obtain fingerprint images with higher signal-to-noise ratio and clearer edge features. It should be noted that image convolution is essentially a process of multiplication followed by summation. Taking a 3×3 convolution kernel as an example, to implement the image convolution operation, it is necessary to first map the pixels of the 3×3 area in the original image to the elements of the convolution kernel one by one and multiply them. The absolute value of the result obtained for each pixel is taken and then added. The final result is placed in the center of the original 3×3 area as the new pixel point of the generated image.

[0089] As an optional implementation, the convolution operation includes the following steps:

[0090] The emission of ultrasonic waves with different phases is achieved through timing design, and the amplitude of the ultrasonic waves is adjusted by designing the voltage.

[0091] It can be understood that the essence of timing design is to meet the requirements of the emission time, holding time, etc. of each different phase ultrasound, so as to achieve the process of timing convergence. It can be further understood that timing design enables data to arrive at the correct time and be processed correctly.

[0092] It should be further explained that timing closure is the process of adjusting and modifying the design during the design of integrated circuits such as field programmable gate arrays and application-specific integrated circuits so that the designed circuit meets the timing requirements; in addition, the amplitude of the ultrasonic wave is adjusted by designing the voltage. The voltage has a greater impact on the ultrasonic wave. The stronger the voltage, the greater the amplitude of the ultrasonic wave.

[0093] For further information, see Figure 5 , when determining the amplitude of the convolution kernel for constrained beamforming, the following steps are required:

[0094] S21: Use Gaussian convolution kernel to remove high-frequency noise from the image;

[0095] S22: Use Laplacian convolution kernel to enhance the edge features of the image;

[0096] S23: Add the two convolution kernels together to form a new convolution kernel.

[0097] It can be understood that the Gaussian convolution kernel and the Laplace convolution kernel of the present invention process the image separately, multiply different convolution kernels with different weights and then add them together to form a new convolution kernel that can be used for ultrasonic fingerprint image enhancement, and then use the value of this convolution kernel as the coefficient for controlling the amplitude of each pixel to realize hardware-level image convolution, so that a clearer fingerprint image can be obtained for subsequent processing.

[0098] Among them, the Gaussian convolution kernel performs noise reduction processing on the image, which can reduce the noise introduced by sampling, transmission, etc. in the image, shield noise interference, and thus improve image quality; the signal-to-noise ratio of the traditional ultrasonic transmitting array is 3, while the signal-to-noise ratio of the beamforming ultrasonic transmitting array involved in the present invention is 3.6. The higher the signal-to-noise ratio, the less clutter, which is more beneficial to the detection of ultrasonic signals.

[0099] The Laplace convolution kernel sharpens the image, making the details in the image more prominent and the image appear clearer and finer. The high-frequency information component of the beamforming ultrasonic transmitting array involved in the present invention is enhanced by 20% compared with the traditional ultrasonic transmitting array.

[0100] In addition, noise reduction processing can also help improve the accuracy and reliability of target detection and image segmentation; sharpening processing can also enhance the edges in the image, making the boundaries of human bodies or objects more obvious, which is helpful for target detection and segmentation.

[0101] See also Figure 6 and Figure 7 In the first embodiment of the present invention, the convolution kernel and its calculation process are as follows: two convolution kernels are selected and weightedly added together. The convolution effect of the resulting convolution kernel is equivalent to the weighted superposition of image information after convolution of the image with the two convolution kernels. Since the convolution kernel in the present invention needs to be implemented on the hardware side, the values ​​of the convolution kernel after addition must be positive and the change in brightness needs to be minimized. After consideration, we use the Gaussian convolution kernel. Convolution with Laplacian kernel 2 and Weighted addition, the convolution effect of the convolution kernel is obtained as follows:

[0102]

[0103] Among them, the values ​​on the four corners of the convolution kernel are Similarly, you can use U1 signal to control the values ​​of the four middle points of the convolution kernel at the same time. Similarly, the U2 signal can be used to control the convolution kernel simultaneously, while the point (1) at the center of the convolution kernel is controlled solely by the U3 signal.

[0104] For details, please refer to Figure 8 The ultrasonic transducer 10 includes a first controller 100 and a second controller 101 , and the first controller 100 and the second controller 101 adjust the amplitude and phase of each ultrasonic transducer 10 respectively.

[0105] It should be noted that each time ultrasonic waves are emitted, with 3×3 pixels as a group, the first controller 100 controls the amplitude of the square wave with the convolution kernel value as the weight, and the second controller 101 controls the phase of the square wave with the pixel type as a reference.

[0106] It can be understood that in order to realize image convolution operation at the hardware level, the principle of convolution image processing is used to improve image quality from the hardware level to ensure that the imaging effect is enhanced without increasing the cost, making the imaging clearer and more accurate, and overcoming the defects of traditional ultrasonic imaging difficulty and poor image quality.

[0107] For further information, see Figures 8 to 10 The ultrasonic transducer 10 further includes a TFT thin film array 102 for controlling the ultrasonic transducer 10. After focusing the intensity of the sound wave and before acquiring the fingerprint image at the central pixel point, the following steps are also included:

[0108] S41: Connecting each row and column of the TFT thin film array 102 to a signal line 103;

[0109] S42: The signal lines 103 of each row and column are connected to the multiplexer 104, and the multiplexer 104 selects n voltage signals to pass through;

[0110] S43: Superimpose the row and column voltage signals selected by each pixel point to calculate the final convolution kernel value.

[0111] It can be understood that the present invention multiplies different convolution kernels with different weights and then adds them together to form a new convolution kernel that can be used for ultrasonic fingerprint image enhancement. The value of this convolution kernel is then used as the coefficient for controlling the amplitude of each pixel to implement hardware-level image convolution, and a clearer fingerprint image can be obtained for subsequent processing.

[0112] It should be noted that the core of the convolution kernel lies in the weight, and the core of the present invention lies in realizing hardware-level image convolution operations by controlling the amplitude of each pixel.

[0113] As another optional implementation, the depth range of the acoustic wave intensity after focusing the acoustic wave intensity of surrounding pixel points is 0.8 mm-1.2 mm.

[0114] It can be understood that the actual application scenarios of the fingerprint imaging method involved in the present invention are mostly fingerprint recognition under the screen of electronic devices. The depth of focusing the sound wave intensity of the surrounding pixels at the central pixel point is set to 0.8mm-1.2mm above the array. This distance is approximately the distance from the fingerprint recognition sensor to the finger, ensuring that the sound waves can be accurately focused on the surface of the finger.

[0115] As a preferred implementation scheme of the first embodiment of the present invention, the focusing depth is 1 mm, that is, the distance from the fingerprint recognition sensor to the dermis of the finger. The ultrasonic wave needs to pass through the OLED screen of the electronic device and the epidermis of the finger. When the focusing depth is 1 mm, the actual measured propagation speed of the ultrasonic wave in the OLED screen is 2.422 mm / μs. It can be understood that the propagation speed of the ultrasonic wave may vary depending on different usage scenarios, which will not be repeated here.

[0116] It should be noted that the first embodiment of the present invention uses the depth of the sound wave intensity after focusing the sound wave intensity of the surrounding pixels as an example of 1mm. The focusing depth can be adjusted according to different application scenarios or usage environments. The present invention only gives one embodiment for illustration, and it can be set according to specific actual conditions. Any modifications, equivalent replacements, and improvements made within the principles of the present invention should be included in the scope of protection of the present invention.

[0117] For further information, please refer to Figures 6 to 8 , the spacing between the ultrasonic transducers 10 ranges from 40 μm to 60 μm.

[0118] It can be understood that the ultrasonic transducers 10 are distributed in a uniform rectangular array on the sensor, and the spacing between adjacent ultrasonic transducers 10 in the transverse or longitudinal direction is a constant value. Each ultrasonic transducer 10 represents a pixel point, and the spacing between the ultrasonic transducers 10 can be set according to the resolution requirements. Therefore, it can be adjusted and modified in different application scenarios according to specific circumstances; as a preferred implementation scheme of the first embodiment of the present invention, the spacing between the ultrasonic transducers 10 is 50μm.

[0119] It should be noted that, according to the beamforming principle, it is necessary to ensure that the three waves U1, U2, and U3 reach the focal point at the same time, that is, the pixels far from the focal point transmit ultrasonic waves first, and the pixels close to the focal point transmit ultrasonic waves later. The three ultrasonic waves are controlled by three square wave drive signals, and the three square wave signals are manifested as different phases in the time domain; the frequency of the ultrasonic wave used in this embodiment is 14 MHz, and according to the formula T = 1 / f, the period of the square wave is approximately 71.4 ns.

[0120] The specific calculation process of the phase difference is as follows, where X is the distance between the surrounding transducers and the central transducer, h is the focal depth, and s is the actual propagation distance of the sound wave. In addition, U1 controls the four corners of the convolution kernel at the same time, U2 controls the middle points of the four sides of the convolution kernel at the same time, and U3 controls the center point of the convolution kernel alone.

[0121] For the center transducer controlled by U3 signal,

[0122] X=0, h=1mm, S=h=1mm;

[0123]

[0124] For the transducer controlled by U2 signal,

[0125] X=50μm, h=1mm, S=h=1mm;

[0126] According to the Pythagorean theorem, we can get

[0127]

[0128]

[0129] For the transducer controlled by U1 signal,

[0130] h=1mm,S=h=1mm

[0131] According to the Pythagorean theorem, we can get

[0132]

[0133]

[0134] Finally, calculations yield

[0135] Δt1=t2-t3=0.52ns;

[0136] Δt2=t1-t3=1.00104ns.

[0137] See also Figure 11 A second embodiment of the present invention provides a fingerprint recognition device 2 for recognizing a user's fingerprint. The fingerprint recognition device 2 includes a fingerprint recognition module 20 and a touch layer 21. The fingerprint recognition module 20 implements the above-mentioned ultrasonic fingerprint imaging method.

[0138] One surface of the touch layer 21 is a touch surface for user operation, and the fingerprint recognition module 20 is disposed on the other surface opposite to the touch surface.

[0139] It should be noted that the fingerprint recognition module 20 provided in the second embodiment of the present invention can be applied to devices including but not limited to: mobile phones, laptops, tablet computers, printers, copiers, scanners, fax devices, global positioning system (GPS) receivers / navigators, cameras, digital media players, personal data assistants (PDAs), portable cameras, game consoles, watches, clocks, calculators, television monitors, flat-panel displays, electronic reading devices (e.g., e-readers), mobile health devices, computer monitors, car displays (including odometer and speedometer displays, etc.), cockpit controls and / or displays, camera view displays (e.g., displays of rearview cameras in vehicles), electronic photographs, electronic bulletin boards or signs, projectors, refrigerators, stereo systems, cassette recorders or players, DVD players, CD players, VCRs, radio devices, portable memory chips, washing machines, dryers, washing machines / dryers, parking meters, etc.

[0140] For details, please refer to Figure 11 The fingerprint recognition module 20 includes an ultrasonic transducer 10 , and the fingerprint recognition module 20 is composed of an array of ultrasonic transducers 10 .

[0141] It should be noted that the working principle of the fingerprint recognition module 20 is based on the propagation and reflection characteristics of ultrasound in biological tissues. The ultrasonic signal emitted and received by the ultrasonic sensor is used to obtain the fingerprint image of the user's finger surface and perform identity authentication.

[0142] See also Figure 12 The third embodiment of the present invention provides an electronic device 3, comprising a memory 30 and a processor 31, wherein the memory 30 stores a computer program 300, and the computer program 300 is configured to execute the ultrasonic fingerprint imaging method described above when running;

[0143] The processor 31 is configured to execute the above-mentioned ultrasonic fingerprint imaging method through the computer program 300 .

[0144] Optionally, in a third embodiment of the present invention, the electronic device may be located in at least one network device among a plurality of network devices of a computer network.

[0145] Specifically, the electronic device may be a fingerprint recognition device used in the field of ultrasonic fingerprint recognition technology, which is used for preprocessing fingerprint images to improve image quality from a hardware level, making the imaging clearer and more accurate.

[0146] Compared with the prior art, the ultrasonic fingerprint imaging method, fingerprint recognition device, and electronic device provided by the present invention have the following advantages:

[0147] 1. The ultrasonic fingerprint imaging method provided in an embodiment of the present invention includes the following steps: setting ultrasonic transducers to be distributed in a uniform rectangular array on the sensor, dividing each n×n ultrasonic transducer array into a group, and having the ultrasonic transducers transmit multiple ultrasonic waves to the object, and receiving and outputting multiple ultrasonic signals reflected from the object; based on the bionic principle of image convolution, the amplitude of each pixel point in the ultrasonic transducer array is individually adjusted based on the value of each point in the convolution kernel; based on the principle of beamforming, the phase of each pixel point in the ultrasonic transducer array is individually adjusted; through beamforming technology, the sound wave intensity of the surrounding pixels is focused above the central pixel point; and the fingerprint image of the object is obtained at the central pixel point.

[0148] It should be noted that the existing beamforming technology only implements beamforming technology for ultrasonic transducer arrays in columns, with five columns as a group. By changing the phase of the driving signal of four adjacent columns of ultrasonic transducers, the ultrasonic signals are interfered within a certain depth range, and the enhancement of the sound wave intensity is limited.

[0149] It can be understood that the present invention uses a beamforming transmitting array to replace the traditional transmitting array, and combines the bionic principle of image convolution to adjust the sound wave intensity of different pixel points. It can realize image convolution operation at the hardware level and enhance the imaging effect without increasing the cost.

[0150] It can be further understood that when achieving the same imaging quality, the ultrasonic fingerprint imaging method involved in the present invention can significantly reduce power consumption. The ultrasonic beamforming array used in the present invention makes the sound wave intensity of the ultrasonic wave more concentrated after focusing, and greatly improves the penetration of the ultrasonic wave. Therefore, the ultrasonic emission energy required to stimulate the same piezoelectric sensing signal will be greatly reduced. At the same time, the service life of the ultrasonic module is also increased.

[0151] 2. In the ultrasonic fingerprint imaging method provided in an embodiment of the present invention, the ultrasonic transducer includes a first controller and a second controller, each of which adjusts the amplitude and phase of the ultrasonic transducer. This method implements image convolution at the hardware level, utilizing the principles of convolutional image processing to improve image quality at the hardware level. This ensures enhanced imaging without increasing costs, resulting in clearer and more accurate images and overcoming the drawbacks of traditional ultrasonic imaging, which often suffer from difficulty and poor image quality.

[0152] 3. In the ultrasonic fingerprint imaging method provided by an embodiment of the present invention, the ultrasonic transducer also includes a TFT thin film array for controlling the ultrasonic transducer. After focusing the sound wave intensity and before acquiring the fingerprint image at the central pixel, the method further includes the following steps: connecting a signal line to each row and column in the TFT thin film array; connecting the signal line of each row and column to a multiplexer, which selects n voltage signals to pass through; and superimposing the row and column voltage signals selected by each pixel to calculate the value of the final convolution kernel.

[0153] It can be understood that the present invention multiplies different convolution kernels with different weights and then adds them together to form a new convolution kernel that can be used for ultrasonic fingerprint image enhancement. The value of this convolution kernel is then used as the coefficient for controlling the amplitude of each pixel to implement hardware-level image convolution, and a clearer fingerprint image can be obtained for subsequent processing.

[0154] 4. In the ultrasonic fingerprint imaging method provided by the embodiment of the present invention, the convolution operation includes the following steps: emitting ultrasonic waves of different phases through timing design, and adjusting the ultrasonic amplitude by designing the voltage.

[0155] It can be understood that the essence of timing design is to meet the requirements of the emission time, holding time, etc. of each different phase ultrasound, so as to achieve the process of timing convergence. It can be further understood that timing design enables data to arrive at the correct time and be processed correctly.

[0156] It should be noted that timing closure is the process of adjusting and modifying the design during the design of integrated circuits such as field programmable gate arrays and application-specific integrated circuits so that the designed circuit meets the timing requirements.

[0157] The amplitude of the ultrasonic wave is adjusted by designing the voltage. The voltage has a greater impact on the ultrasonic wave. The stronger the voltage, the greater the amplitude of the ultrasonic wave.

[0158] 5. The ultrasonic fingerprint imaging method provided by the embodiment of the present invention further requires the following steps when determining the amplitude of the constrained beamforming convolution kernel: using a Gaussian convolution kernel to remove high-frequency noise from the image; using a Laplacian convolution kernel to enhance the edge features of the image; and performing weighted addition of the two convolution kernels to form a new convolution kernel.

[0159] As can be understood, the Gaussian convolution kernel and the Laplacian convolution kernel of the present invention process images separately. The Gaussian convolution kernel performs noise reduction processing on the image, reducing noise introduced by sampling, transmission, and other reasons, shielding noise interference, and thus improving image quality; the Laplacian convolution kernel performs image sharpening processing, highlighting details in the image, making the image appear clearer and more refined.

[0160] In addition, noise reduction processing can also help improve the accuracy and reliability of target detection and image segmentation; sharpening processing can also enhance the edges in the image, making the boundaries of human bodies or objects more obvious, which is helpful for target detection and segmentation.

[0161] 6. In the ultrasonic fingerprint imaging method provided by an embodiment of the present invention, the depth range of the sound wave intensity after focusing the sound wave intensity of the surrounding pixels is 0.8mm-1.2mm. It can be understood that the actual application scenarios of the fingerprint imaging method involved in the present invention are mostly fingerprint recognition under the screen of electronic devices. The depth of focusing the sound wave intensity of the surrounding pixels on the central pixel is set to 0.8mm-1.2mm above the array. This distance is approximately the distance from the fingerprint recognition sensor to the finger, ensuring that the sound wave can be accurately focused on the surface of the finger.

[0162] 7. In the ultrasonic fingerprint imaging method provided by the embodiment of the present invention, the spacing between ultrasonic transducers ranges from 40μm to 60μm. It is understood that the ultrasonic transducers are distributed in a uniform rectangular array on the sensor, and the spacing between adjacent ultrasonic transducers in the horizontal or vertical direction is a fixed value. Each ultrasonic transducer represents a pixel point. The spacing between ultrasonic transducers can be set according to the resolution requirements. Therefore, it can be adjusted and modified according to the specific situation in different application scenarios.

[0163] 8. An embodiment of the present invention further provides a fingerprint recognition device, comprising a fingerprint recognition module and a touch layer, wherein the fingerprint recognition module implements the above-mentioned ultrasonic fingerprint imaging method; one surface of the touch layer is a touch surface for user operation, and a fingerprint recognition module is provided on the other surface opposite to the touch surface.

[0164] Specifically, the fingerprint recognition module includes an ultrasonic transducer, and the fingerprint recognition module is composed of an ultrasonic transducer array.

[0165] The fingerprint recognition device has the same beneficial effects as the above-mentioned ultrasonic fingerprint imaging method, which will not be described in detail here.

[0166] 9. An embodiment of the present invention further provides an electronic device, comprising a memory and a processor, wherein a computer program is stored in the memory, and the computer program is configured to execute the above-mentioned ultrasonic fingerprint imaging method when it is run; and the processor is configured to execute the above-mentioned ultrasonic fingerprint imaging method through the computer program.

[0167] This electronic device has the same beneficial effects as the above-mentioned ultrasonic fingerprint imaging method, which will not be described in detail here.

[0168] The above is a detailed introduction to an ultrasonic fingerprint imaging method, fingerprint recognition device and electronic device disclosed in the embodiments of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the ideas of the present invention, there may be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention. Any modifications, equivalent replacements and improvements made within the principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. An ultrasonic fingerprint imaging method, characterized in that: The following steps are involved: Ultrasonic transducers are arranged on the sensor in a uniform rectangular array, each n×n ultrasonic transducer array is divided into a group, the ultrasonic transducers transmit a plurality of ultrasonic waves toward an object, and receive and output a plurality of ultrasonic signals reflected from the object; Based on the bionic principle of image convolution, the numerical value of each point in the convolution kernel is used as the basis for the timing design to transmit ultrasonic waves of different phases, and the ultrasonic amplitude of each pixel point in the ultrasonic transducer array is individually adjusted by designing the voltage. Based on the principle of beamforming, the phase of each pixel in the ultrasonic transducer array is individually adjusted; Through beamforming technology, the sound wave intensity of surrounding pixels is focused above the central pixel; Acquire a fingerprint image of the object at the central pixel point; Among them, when determining the amplitude of the convolution kernel of the constrained beamforming, the following steps are required: Use Gaussian convolution kernel to remove high-frequency noise from the image; Use Laplacian convolution kernel to enhance the edge features of the image; The two convolution kernels are weighted added together to form a new convolution kernel.

2. The ultrasonic fingerprint imaging method according to claim 1, wherein: The ultrasonic transducer includes a first controller and a second controller, and the first controller and the second controller respectively adjust the amplitude and phase of each ultrasonic transducer.

3. The ultrasonic fingerprint imaging method according to claim 2, wherein the ultrasonic transducer further comprises a TFT thin film array for controlling the ultrasonic transducer, wherein: After focusing the intensity of the acoustic wave and before acquiring the fingerprint image at the central pixel point, the following steps are also included: Each row and column in the TFT thin film array is connected to a signal line; The signal lines of each row and column are connected to a multiplexer, and the multiplexer selects n voltage signals to pass through; The row and column voltage signals selected by each pixel are superimposed to calculate the final convolution kernel value.

4. The ultrasonic fingerprint imaging method according to claim 1, wherein: The depth range of the sound wave intensity after focusing the sound wave intensity of the surrounding pixel points is 0.8mm-1.2mm.

5. The ultrasonic fingerprint imaging method according to claim 4, wherein: The intervals between the ultrasonic transducers range from 40 μm to 60 μm.

6. A fingerprint recognition device comprising a fingerprint recognition module and a touch layer, characterized in that: The fingerprint recognition module implements the ultrasonic fingerprint imaging method according to any one of claims 1 to 5; One surface of the touch layer is a touch surface for user operation, and the fingerprint recognition module is arranged on the other surface opposite to the touch surface.

7. The fingerprint recognition device according to claim 6, wherein: The fingerprint recognition module includes an ultrasonic transducer, and the fingerprint recognition module is composed of the ultrasonic transducer array.

8. An electronic device comprising a memory and a processor, characterized in that: The memory stores a computer program, which is configured to execute the ultrasonic fingerprint imaging method according to any one of claims 1 to 5 when running; The processor is configured to execute the ultrasonic fingerprint imaging method according to any one of claims 1 to 5 through the computer program.

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