Image acquisition method and device, electronic equipment and storage medium

Abstract

The invention provides an image acquisition method and device, equipment and a storage medium, and relates to the technical field of biological recognition and artificial intelligence. The image acquisition method comprises the following steps: controlling the reflection intensity of a reflector in a first specific area in a reflector array to light emitted by an optical compensation module; a first feature image of a to-be-recognized body part of the object is obtained through the image collection module, and light emitted by the optical compensation module is reflected by the reflector array and intersects with the to-be-recognized body part of the object; the gray value of the pixel of the second specific area of the first feature image corresponds to the reflection intensity of the first specific area; obtaining object feature information according to the first feature image; wherein the object feature information is used for performing biological feature recognition on the object. According to the embodiment of the invention, the biological information security can be ensured.

Description

Technical Field

[0001] The present application relates to the field of biometric identification technology, and more specifically, to an image acquisition method, device, electronic device, and storage medium. Background Art

[0002] As technology becomes a more integral part of our daily lives, people are increasingly willing to replace traditional security authentication methods with simple biometrics. Biometrics, a method of measuring a person's physical characteristics to verify their identity, can significantly increase the convenience of identity verification. Physical characteristics can include physiological features (such as fingerprints, irises, faces, and palm prints) or behavioral characteristics (such as gait or a unique way of completing a security authentication puzzle).

[0003] Ensuring the security of biometric information has become a key issue. Generally, after a biometric image is captured, the biometric features are masked through an algorithm. By adding transformations to the generated feature code, unauthorized access to the biometric image is difficult. However, algorithmic encryption is often not implemented at the image end, and there is a risk that the image will be leaked before encryption. Leaked image information can make it possible to forge biometric information. Therefore, further ensuring the security of biometric information is an urgent issue. Summary of the invention

[0004] The embodiments of the present application provide a method, apparatus, device, and storage medium for image acquisition. By concealing some biometric features during the acquisition phase of a biometric image, the risk of forging biometric information using feature images is reduced, thereby ensuring the security of biometric information.

[0005] In a first aspect, an embodiment of the present application provides a method for acquiring an image, comprising:

[0006] Controlling the reflection intensity of the reflector in the first specific area of the reflector array to the light emitted by the optical compensation module;

[0007] Acquiring a first characteristic image of the subject's body part to be identified using an image acquisition module, wherein light emitted by the optical compensation module is reflected by the reflector array and intersects the subject's body part to be identified; and the grayscale value of a pixel in a second specific area of the first characteristic image corresponds to the reflection intensity of the first specific area;

[0008] According to the first feature image, object feature information is obtained; wherein the object feature information is used to perform biometric feature recognition on the object.

[0009] In a second aspect, an embodiment of the present application provides an image acquisition device, comprising:

[0010] A control unit for controlling the reflection intensity of the mirrors in a first specific area of the mirror array for the light emitted by the optical compensation module;

[0011] An acquisition unit for using the image acquisition module to acquire a first feature image of the body part to be recognized of the object, wherein the light emitted by the optical compensation module is reflected by the mirror array and intersects with the body part to be recognized of the object; the gray value of the pixels in the second specific area of the first feature image corresponds to the reflection intensity of the first specific area;

[0012] A processing unit for obtaining object feature information according to the first feature image; wherein the object feature information is used for biometric recognition of the object.

[0013] Optionally, the processing unit is specifically configured to:

[0014] Determine a compensation value for the gray value of the pixels in the second specific area according to the reflection intensity corresponding to the mirror in the first specific area;

[0015] Compensate the gray value of the pixels in the second specific area in the first feature image according to the compensation value to obtain the object feature information.

[0016] Optionally, the control unit is further configured to: control the reflection intensity of the mirrors in a third specific area of the mirror array for the light emitted by the optical compensation module; the third specific area is different from the first specific area;

[0017] The acquisition unit is further configured to use the image acquisition module to acquire a second feature image of the body part to be recognized of the object; the gray value of the pixels in the fourth specific area of the second feature image corresponds to the reflection intensity of the third specific area;

[0018] The processing unit is further configured to: obtain the object feature information according to the first feature image and the second feature image.

[0019] Optionally, the processing unit is specifically configured to:

[0020] Determine the gray value of the pixel point corresponding to the second specific area in the first feature image according to the gray value of the pixel point corresponding to the second specific area in the second feature image;

[0021] Obtain the object feature information according to the gray value of the pixel point corresponding to the second specific area in the first feature image and the first feature image.

[0022] Optionally, the processing unit is specifically configured to:

[0023] Determine that the second specific area matches the first specific area;

[0024] Determine the object feature information according to the gray values of the pixels in the first feature image except for the second specific area.

[0025] Optionally, the pixels in the second specific area are overexposed or underexposed.

[0026] Optionally, the control unit is specifically configured to:

[0027] Obtain the position information of the body part to be recognized by using a distance sensor;

[0028] Control the reflection intensity of the light emitted by the optical compensation module by the mirror in the first specific area according to the position information.

[0029] Optionally, the first specific area includes at least one mirror at the pixel level.

[0030] Optionally, the mirror array includes a digital micromirror device.

[0031] Optionally, the body part to be recognized includes at least one of a palm print or a fingerprint.

[0032] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0033] A processor, adapted to implement computer instructions; and,

[0034] A memory, storing computer instructions, the computer instructions being adapted to be loaded and executed by the processor to perform the method in the first aspect above.

[0035] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores computer instructions, and when the computer instructions are read and executed by the processor of a computer device, the computer device is caused to execute the method in the first aspect above.

[0036] In a fifth aspect, an embodiment of the present application provides a computer program product or a computer program, the computer program product or the computer program including computer instructions, the computer instructions being stored in a computer-readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method in the first aspect above.

[0037] Through the above technical solution, the light reflected by the optical compensation module intersects with the body part to be recognized of the object after being reflected by the mirror array. By controlling the reflection intensity of the light emitted by the optical compensation module by the mirrors in the first specific area of the mirror array, the brightness and darkness states of different areas within the illumination area of the mirror array can be controlled, so as to achieve overbrightness or overdarkness of the local area of the body part to be recognized. Furthermore, the biometric features in the second specific area corresponding to the overbright or overdark area in the first feature image acquired by the image acquisition module can be concealed, and then the object feature information can be obtained according to the first feature image for biometric recognition of the object. Therefore, the embodiments of the present application can conceal the biometric features of some areas in the image during the acquisition stage of the biometric image, thereby reducing the risk of forging biometric information using the first feature image and being beneficial to further ensuring biometric information security. Description of the Drawings

[0038] Figure 1 An optional schematic diagram of the application scenario of the embodiments of the present application;

[0039] Figure 2 Another optional schematic diagram of the application scenario of the embodiments of the present application;

[0040] Figure 3 Another optional schematic diagram of the application scenario of the embodiments of the present application;

[0041] Figure 4 A schematic flowchart of a method for obtaining an image provided by the embodiments of the present application;

[0042] Figure 5 A related schematic diagram of the position distribution of pixel points involved in the embodiments of the present application;

[0043] Figure 6 A schematic flowchart of another method for obtaining an image provided by the embodiments of the present application;

[0044] Figure 7 A schematic diagram of a method for image processing involved in the embodiments of the present application;

[0045] Figure 8 A schematic flowchart of another method for obtaining an image provided by the embodiments of the present application;

[0046] Figure 9 A schematic flowchart of another method for obtaining an image provided by the embodiments of the present application;

[0047] Figure 10A A schematic diagram of the relative position of the palm and the mirror array;

[0048] Figure 10BAnother schematic diagram of the relative position between the palm and the mirror array;

[0049] Figure 10C is Figure 10A and Figure 10B a schematic diagram of the corresponding feature image;

[0050] Figure 11 A schematic block diagram of an image acquisition device provided by an embodiment of the present application;

[0051] Figure 12 A schematic block diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0052] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application.

[0053] It should be understood that in the embodiments of the present application, "B corresponding to A" means that B is associated with A. In one implementation, B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0054] In the description of the present application, unless otherwise specified, "at least one" means one or more, and "a plurality" means two or more than two. In addition, "and / or" describes the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone, where A and B can be singular or plural. The character " / " generally represents an "or" relationship between the associated objects before and after. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural item(s). For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0055] It should also be understood that the first, second, etc. descriptions that appear in the embodiments of the present application are only for schematic and distinguishing the described objects, without an order, and do not represent a special limitation on the number of devices in the embodiments of the present application, and cannot constitute any limitation to the embodiments of the present application.

[0056] It should also be understood that the specific features, structures, or characteristics related to the embodiments in the specification are included in at least one embodiment of the present application. In addition, these specific features, structures, or characteristics can be combined in one or more embodiments in any suitable manner.

[0057] In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units need not be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0058] The solution of the embodiment of this application relates to the field of artificial intelligence technology. Artificial Intelligence (AI) is to use a digital computer or a machine controlled by a digital computer to simulate, extend, and expand human intelligence, a theory, method, technology, and application system that perceives the environment, acquires knowledge, and uses knowledge to obtain the best results. In other words, artificial intelligence is a comprehensive technology in computer science that attempts to understand the essence of intelligence and produce a new intelligent machine that can respond in a way similar to human intelligence. Artificial intelligence also studies the design principles and implementation methods of various intelligent machines to enable the machines to have the functions of perception, reasoning, and decision-making.

[0059] Artificial intelligence technology is an interdisciplinary subject that involves a wide range of fields, including both hardware-level and software-level technologies. Artificial intelligence basic technologies generally include, for example, sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, pre-trained model technology, operation / interaction systems, mechatronics, etc. Among them, the pre-trained model, also known as the large model or the base model, can be widely applied to downstream tasks in major directions of artificial intelligence after fine-tuning. Artificial intelligence software technologies mainly include several major directions such as computer vision technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0060] The solution of the embodiment of the present application may also relate to the field of computer vision technology. Computer vision (CV) is a science that studies how to enable machines to "see". Further, it refers to using cameras and computers to replace human eyes for tasks such as object recognition and measurement in machine vision, and further performing graphic processing to make the computer-processed images more suitable for human eyes to observe or be transmitted to instruments for detection. As a scientific discipline, computer vision studies related theories and technologies, and attempts to establish artificial intelligence systems that can obtain information from images or multi-dimensional data. The large model technology has brought important changes to the development of computer vision technology. Pre-trained models in the vision field such as swin-transformer, ViT, V-MOE, and MAE can be quickly and widely applied to specific downstream tasks after fine-tuning. Computer vision technology usually includes technologies such as image processing, image recognition, image semantic understanding, image retrieval, OCR, video processing, video semantic understanding, video content / behavior recognition, three-dimensional object reconstruction, 3D technology, virtual reality, augmented reality, simultaneous localization and mapping, and also includes common biometric recognition technologies such as face recognition and fingerprint recognition.

[0061] With the research and progress of artificial intelligence technology, artificial intelligence technology has been studied and applied in multiple fields, such as common smart homes, smart wearable devices, virtual assistants, smart speakers, smart marketing, driverless, autonomous driving, drones, digital twins, virtual humans, robots, artificial intelligence-generated content (AIGC), conversational interactions, intelligent healthcare, intelligent customer service, game AI, etc. It is believed that with the development of technology, artificial intelligence technology will be applied in more fields and play an increasingly important role.

[0062] Figure 1 An optional schematic diagram of the application scenario of the embodiment of the present application is shown.

[0063] As Figure 1 shown, this application scenario involves a terminal 102 and a server 104. The terminal 102 can communicate with the server 104 through a communication network. The server 104 can be the background server of the terminal 102.

[0064] Exemplarily, the terminal 102 may refer to a type of device that has rich human-computer interaction methods, the ability to access the Internet, usually runs various operating systems, and has strong processing capabilities. The terminal 102 may be a smart phone, a tablet computer, a portable laptop, a desktop computer, a wearable device, a smart home appliance, a vehicle-mounted device, etc., but is not limited thereto. The server 104 may be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. It may also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. The server may also become a node of the blockchain.

[0065] The server may be one or more. When there are multiple servers, at least two servers are used to provide different services, and / or at least two servers are used to provide the same service. For example, the same service is provided in a load balancing manner. The embodiments of the present application do not limit this.

[0066] The terminal and the server may be directly or indirectly connected through wired or wireless communication. The present application does not limit this. The present application does not limit the number of servers or terminals. The solution provided by the present application may be completed independently by the terminal, may also be completed independently by the server, or may be completed by the cooperation of the terminal and the server. The present application does not limit this.

[0067] Optionally, the terminal or the server may obtain a feature image of the body part to be recognized of the object, and perform biometric recognition on the object according to the feature image to verify the identity information of the object. Optionally, the terminal may obtain a feature image of the body part to be recognized of the object, and send the feature image to the server, and the server performs biometric recognition on the object according to the feature image to verify the identity information of the object. Optionally, the server may send the identity verification result to the terminal.

[0068] Optionally, the application scenario may further include a data storage system. The data storage system may store the data required by the server 104. The data storage system may be set separately, integrated on the server 104, or deployed on the cloud or other servers, and is not limited.

[0069] It should be understood that Figure 1 is only an exemplary illustration and does not specifically limit the application scenario of the embodiments of the present application. For example, Figure 1 Exemplarily shows one terminal and one server. In fact, it may include other numbers of terminals and servers. The present application does not limit this.

[0070] Figure 2 Another schematic diagram showing an application scenario of an embodiment of the present application.

[0071] like Figure 2 As shown, this application scenario includes an image acquisition module 202 and a data processing module 203. The image acquisition module 202 can be, for example, a camera that can be used to capture a feature image of the subject's body part to be identified. The data processing module 203 can perform data processing, such as image processing, feature extraction, and feature matching, on the feature image captured by the image acquisition module 202, thereby enabling identification of the subject's identity.

[0072] For example, the body part to be identified may be a palm, a finger, a face, or an eye, etc., without limitation.

[0073] Optional, in Figure 2 The illustrated application scenario may also include an optical compensation module 201, which may be, for example, a light source. Exemplarily, the light source may emit infrared light or visible light, without limitation. The light emitted by the optical compensation module 201 intersects with the subject's body part to be identified (e.g., palm, finger, face, eye, etc.), thereby compensating the light for the body part to be identified, allowing the image acquisition module 202 to capture a clearer and richer feature image. Exemplarily, the acquisition of images such as fingerprints and palm prints requires the joint configuration of the image acquisition module 202 and the optical compensation module 201.

[0074] Ensuring the security of biometric information has become a key issue. Generally, after a biometric image is captured, the biometric features are masked through algorithms. By adding transformations to the generated feature code, unauthorized access to the biometric image is difficult. However, algorithmic encryption often isn't implemented at the image end, and there's a chance that the image will be leaked before encryption. Leaked image information can make it possible to forge biometric information.

[0075] For example, there are generally two existing intrusion methods: (1) stealing the original biometric image and making it into a biometric model to break into the biometric recognition system; (2) using previously used biometric information to conduct a secondary attack on the recognition device, thereby stealing the user's permissions.

[0076] In the above method (1), a biometric image of a user containing complete biometric information is required, such as a clear and complete image of the user's palm. Using this image, it can be printed out or applied to a three-dimensional (3D) model template to restore it to the user's palm model, and the palm model is presented in the acquisition link of the biometric recognition system, so that the system can collect the biometric image of the stolen user again, thus realizing the theft of the user's identity information. In the above method (2), similarly, a biometric image of the user containing complete information is required. The image that has been used and stolen can skip the feature acquisition link through technical means and be directly input into the feature extraction link, thus realizing the theft of user permissions.

[0077] Therefore, how to further ensure biometric information security urgently needs to be solved.

[0078] In view of this, the embodiments of the present application provide a method, device, electronic device, and storage medium for image acquisition, which can help to further ensure biometric information security.

[0079] Specifically, the reflection intensity of the light emitted by the optical compensation module by the mirrors in the first specific area of the mirror array can be controlled; the image acquisition module is used to acquire a first feature image of the body part to be recognized of the object, wherein the light emitted by the optical compensation module intersects with the body part to be recognized of the object after being reflected by the mirror array; the gray value of the pixels in the second specific area of the first feature image corresponds to the reflection intensity of the first specific area; and object feature information is obtained according to the first feature image; wherein the object feature information is used for biometric recognition of the object.

[0080] In the embodiments of the present application, the light reflected by the optical compensation module intersects with the body part to be recognized of the object after being reflected by the mirror array. By controlling the reflection intensity of the light emitted by the optical compensation module by the mirrors in the first specific area of the mirror array, the bright and dark states of different areas in the illumination area of the mirror array can be controlled, so as to realize over-brightness or over-darkness of the local area of the body part to be recognized, and then the biometric features in the corresponding second specific area in the over-bright or over-dark area in the first feature image acquired by the image acquisition module can be concealed. Furthermore, object feature information is obtained according to the first feature image and is used for biometric recognition of the object. Therefore, the embodiments of the present application can conceal the biometric features in some areas of the image at the acquisition stage of the biometric image, thereby reducing the risk of forging biometric information using the first feature image, which is beneficial to further ensuring biometric information security.

[0081] In some embodiments, the reflection intensity of the mirrors in the first specific area of the mirror array for the light emitted by the optical compensation module can be controlled according to an encryption algorithm, so as to conceal the biometric features in the second specific area corresponding to the over-bright or over-dark area in the first feature image, that is, to encrypt the biometric features in the second specific area. Subsequently, object feature information can be obtained according to the encryption algorithm and the first feature image. Therefore, the embodiments of the present application encrypt the image at the image acquisition stage of biometric information, that is, in the process of image acquisition, the brightness of the local position of the body part to be recognized is associated with the encryption algorithm, and the biometric information corresponding to the over-bright or over-dark part is concealed. Thus, an original feature image does not completely display the complete personal biometric information, and the concealed part or special gray-scale area needs to match the encrypted data corresponding to the corresponding encryption algorithm in the subsequent identity recognition link to accurately obtain the identity feature information of the object, thereby playing a role in protecting the biometric information of the object. Therefore, the embodiments of the present application can pre-place encryption at the image acquisition end at the algorithm level, thereby reducing the risk of forging biometric information using the feature image.

[0082] Figure 3 Another schematic diagram of the application scenario of the embodiments of the present application is shown.

[0083] As Figure 3 shown, the application scenario includes an optical compensation module 301, a mirror array 302, an image acquisition module 303, a control module 304, and a data processing module 305.

[0084] Exemplarily, the optical compensation module 301, the mirror array 302, the image acquisition module 303, and the control module 304 can be deployed on the terminal. Exemplarily, the data processing module 305 can be deployed on the terminal or the server. The data processing module 305 can be referred to as the backend.

[0085] Among them, the optical compensation module 30 emits light of a specific wavelength band at a certain angle. The mirror array 302 reflects the light emitted by the optical compensation module 301, so that the light is reflected to the body part to be recognized of the object, and part of the light emitted by the optical compensation module 301 intersects with the body part to be recognized of the object after being reflected by the mirror array 302. The image acquisition module 303 acquires the feature image of the body part to be recognized of the object. Among them, the light emitted by the optical compensation module 301 intersects with the body part to be recognized of the object (such as palm, finger, face, human eye, etc.) after being reflected by the mirror array 302 to compensate the light of the body part to be recognized, so that the image acquisition module 302 can acquire a clearer and richer feature image.

[0086] Optionally, the mirror array 302 can have pixel-level resolution, so as to be able to control the reflection intensity of light by the mirrors in the area at the pixel level.

[0087] The control module 304 can be respectively connected to the optical compensation module 301, the mirror array 302, the image acquisition module 303, and the data processing module 305. The control module 304 is used for:

[0088] Controlling the optical compensation module 301 to emit light;

[0089] Controlling the reflection intensity of the light emitted by the optical compensation module 301 by the mirrors in the first specific area of the mirror array 302;

[0090] Controlling the image acquisition module 303 to acquire a first feature image of the body part to be recognized of the object, wherein the gray value of the pixels in the second specific area of the first feature image corresponds to the reflection intensity of the first specific area;

[0091] Controlling the data processing module 305 to obtain object feature information according to the first feature image; wherein the object feature information is used for biometric recognition of the object.

[0092] Optionally, the data processing module 305 can also perform data processing on the object feature information, such as feature extraction and feature matching, so as to realize the identification of the identity of the object.

[0093] Optionally, the control module 304 can, according to the need of the image acquisition module 303 to acquire images, realize the brightness change of the optical compensation module 301 under the drive of different currents and duty cycles.

[0094] Optionally, the control module 304 can also include an encryption module. Exemplarily, the encryption module can generate a random code according to the need, which is used to control the rotation angle of the mirrors of each pixel point, and further realize the control of the gray value of each pixel point in the first feature image acquired by the image acquisition module.

[0095] Optionally, the control module 304 can also send the random code to the data processing module 305, so that the data processing module 305 can match the random code with the feature code string corresponding to the first feature image, and then perform biometric recognition according to the matching result.

[0096] Optionally, this application scenario can also include a protection cover 306. Exemplarily, the protection cover 306 can be deployed on the terminal.

[0097] Optionally, the application scenario may further include a distance sensor 307. Exemplarily, the distance sensor 307 may be configured to obtain the position information of the body part to be recognized, and further the control module 304 controls the reflection intensity of the mirrors in the first specific area of the mirror array 302 according to the position information. Optionally, the control module 304 may further control the light brightness and / or the incident angle of the optical compensation module 301 according to the position information.

[0098] As an example, the optical compensation module 301 may include, but is not limited to, a light emitting diode (LED). The optical compensation module 301 may emit infrared light or visible light, which is not limited in this application.

[0099] As an example, the mirror array 302 may include, but is not limited to, a digital micro-mirror device (DMD). The DMD is a micro-electro-mechanical system (MEMS) with electronic input and optical output, which consists of many small aluminum mirror surfaces, and each mirror surface can be called a pixel. Based on semiconductor manufacturing technology, the DMD consists of a high-speed digital optical reflection switch array, and determines the imaging pattern and its characteristics by controlling the rotation of the micro-mirrors around a fixed (yoke) and the time-domain response (determining the reflection angle and dwell time of the light). Exemplarily, each pixel point in the DMD can be flipped at a specific angle under the drive of different voltages, so as to realize pixel-level control of the reflection intensity of the mirrors in the area.

[0100] As an example, the distance sensor 307 includes, but is not limited to, an infrared modulation spectroscopy reflection intensity detection type device or an infrared time-of-flight detection type device.

[0101] Therefore, in the embodiment of this application, the light reflected by the optical compensation module intersects the body part to be recognized of the object after being reflected by the mirror array. By controlling the reflection intensity of the mirrors in the first specific area of the mirror array for the light emitted by the optical compensation module, the brightness and darkness states of different areas in the illumination area of the mirror array can be controlled, so as to realize over-brightness or over-darkness of the local area of the body part to be recognized. Furthermore, in the first feature image acquired by the image acquisition module, the biological features in the second specific area corresponding to the over-bright or over-dark area can be concealed. Then, object feature information is obtained according to the first feature image, and biometric recognition of the object is realized. Therefore, the embodiment of this application can conceal the biological features of some areas in the image at the stage of collecting the biometric image, thereby reducing the risk of forging biometric information using the first feature image, which is beneficial to further ensuring biometric security.

[0102] The technical solutions of the embodiments of the present application will be described in detail below through some embodiments. These several embodiments below can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0103] Figure 4 It is a schematic flowchart of a method 400 for image acquisition provided by an embodiment of the present application. The method 400 for image acquisition can be executed by any electronic device with data processing capabilities, such as Figure 1 the terminal 402 or the server 404 in, and the present application does not make any limitations in this regard. Exemplarily, the method 400 can be applied to Figure 3 the application scenarios in.

[0104] As Figure 4 shown, the method 400 for image acquisition may include steps 410 to 430.

[0105] 410, control the reflection intensity of the light emitted by the optical compensation module by the mirrors in the first specific area of the mirror array.

[0106] Exemplarily, referring to Figure 3 , the light emitted by the optical compensation module 301 is reflected by the mirror array 302 to the body part to be recognized (the palm shown in the figure) and intersects with the body part to be recognized. Among them, the mirror array 302 may include a plurality of mirror surfaces, and the control module 304 can control the mirror surfaces in the mirror array 302 to reflect the light emitted by the optical compensation module 301 to the body part to be recognized, so as to compensate the light for the body part to be recognized, so that the image acquisition module 303 can collect a clearer and richer feature image.

[0107] Further, in the embodiments of the present application, by controlling the reflection intensity of the light emitted by the optical compensation module 301 by the mirrors in the first specific area of the mirror array 302, it is possible to control the bright and dark states of different areas within the illumination area of the mirror array 302, thereby realizing over-brightness or over-darkness of the local area of the part to be recognized. For example, the mirrors in the first specific area can reflect too much light, thereby realizing an over-bright state of the corresponding area, or reflect too little light, thereby realizing an over-dark state of the corresponding area.

[0108] In some embodiments, the body part to be recognized includes at least one of palmprint or fingerprint. Or it can also be other parts of the body, such as the human face, eyes, etc., and the present application does not make any limitations in this regard.

[0109] In some embodiments, the first specific region includes at least one mirror at the pixel level. That is, the first specific region is a region at the pixel level in the mirror array 302. In this way, it is possible to control the reflection intensity of the mirrors of each pixel point in the mirror array 302 at the pixel level.

[0110] Specifically, each mirror surface in the mirror array 302 can correspond to a pixel. By controlling the reflection angle and / or the dwell time of the mirrors of each pixel point in the mirror array 302 with respect to light, it is possible to control the reflection intensity of the mirrors of each pixel point in the region of the mirror array 302 at the pixel level. For example, the mirrors of at least one pixel in the first specific region can reflect too much light, thus achieving an over-bright state in the corresponding region; or the mirrors of at least one pixel in the first specific region can reflect too little light, thus achieving an over-dark state in the corresponding region; or the mirrors of a part of the pixels in the first specific region reflect too much light to achieve an over-bright state in the corresponding region, and the mirrors of another part of the pixels reflect too little light to achieve an over-dark state in the corresponding region.

[0111] Exemplarily, the mirror array 302 can include a DMD. Specifically, the mirror surfaces of each pixel point in the DMD can be flipped at a specific angle under the drive of different voltages, so as to achieve the reflection intensity of the mirror surfaces of each pixel point with respect to light.

[0112] In some embodiments, the first specific region can include at least one specific pixel point in the mirror array 302. Optionally, the at least one specific pixel point can be randomly distributed in the mirror array 302.

[0113] See Figure 5 , FIG. (a) shows a schematic diagram of the position distribution and reflection intensity of at least one specific pixel point. Exemplarily, in FIG. (a), a square can correspond to a pixel point in a mirror array, and different colors of the squares can correspond to different reflection intensities of the mirrors. For example, lighter colors can correspond to larger reflection intensities, and darker colors can correspond to smaller reflection intensities.

[0114] In some embodiments, the schematic diagram of the position distribution and reflection intensity of at least one specific pixel point in the first specific region, as shown in FIG. (a), can be referred to as a grayscale mask, and the embodiments of the present application do not limit this.

[0115] As an implementable manner, the control module 304 can generate a random code as needed to control the rotation angles of the mirrors at each specific pixel point in the mirror array 302, thereby controlling the reflection intensity of the light by the mirrors in the first specific area in the area of the mirror array 302, that is, controlling the generation of a grayscale mask corresponding to the random code. It should be understood that one random code can correspond to a specific grayscale mask. Optionally, the control module 304 can save each random code and the corresponding grayscale mask.

[0116] 420, use the image acquisition module to obtain a first feature image of the body part to be recognized of the object; the gray value of the pixels in the second specific area of the first feature image corresponds to the reflection intensity of the first specific area.

[0117] Exemplarily, referring to Figure 3 , the control module 304 can control the image acquisition module 303 to obtain a first feature image of the body part to be recognized of the object, such as taking a picture of the body part to be recognized to obtain a picture or photo containing the body part to be recognized. Since the local area of the part to be recognized is too bright or too dark, there are overexposed or underexposed pixels in the second specific area in the first feature image, and the gray value will also change accordingly.

[0118] For example, when the reflection intensity of the first specific area is large and too much light is reflected, causing the corresponding area of the body part to be recognized to be too bright, the gray value of the pixels in the second specific area is large, making the brightness of the corresponding pixels higher. Optionally, when the pixels in the second specific area are overexposed, the gray value will reach the maximum value of 255, causing the loss of the gray information that may originally exist. Therefore, the embodiment of the present application can conceal the biological information in the corresponding second specific area in the first feature image.

[0119] For another example, when the reflection intensity of the first specific area is small and too little light is reflected, causing the corresponding area of the body part to be recognized to be too dark, the gray value of the pixels in the second specific area is small, making the brightness of the corresponding pixels lower. Optionally, when the pixels in the second specific area are underexposed, the gray value will be small or even close to 0, which may also cause the loss of gray information. Therefore, the embodiment of the present application can conceal the biological information in the corresponding second specific area in the first feature image.

[0120] Continue to refer to Figure 5, (b) shows an example of a characteristic image of a normally photographed palm. When the mirrors in the first specific area of the mirror array generate a grayscale mask for the light emitted by the optical compensation module as shown in (a), the image acquisition module can obtain a characteristic image as shown in (c) (an example of the first characteristic image). As shown in (c), a hidden area corresponding to the grayscale mask in (a) is generated on the palm image. Among them, the lighter color area is overexposed, corresponding to a larger grayscale value, such as reaching 255; the darker color area has insufficient pixel exposure, corresponding to a smaller grayscale value, such as reaching 0. Among them, the hidden area is manifested as black or bright blocks on the palm picture, and the biometric information of the occluded part cannot be directly observed.

[0121] Therefore, by hiding the biometric information in the corresponding second specific area of the first characteristic image, it is possible to avoid a complete characteristic information for biometric recognition of the body part to be recognized of the object on a single picture obtained in the image acquisition stage.

[0122] 430. Obtain object characteristic information according to the first characteristic image; wherein, the object characteristic information is used for biometric recognition of the object.

[0123] Exemplarily, refer to Figure 3 , the data processing module 305 can perform data processing according to the first characteristic image to obtain object characteristic information. Among them, the object characteristic information can include the complete object characteristic information of the body part to be detected, or the object characteristic information in the first characteristic image except for the hidden part characteristic information. This application does not make a limitation on this. Here, the complete object characteristic information can refer to the complete characteristic information required for biometric recognition.

[0124] Therefore, the embodiment of the present application can hide the biometric characteristics of some areas in the image during the acquisition stage of the biometric image, obtain the first characteristic image with some biometric characteristics hidden, and then obtain the object characteristic information for biometric recognition of the object according to the first characteristic image. Since some biometric characteristics in the first characteristic image are hidden, the embodiment of the present application can reduce the risk of forging biometric information using the first characteristic image, thereby being beneficial to further ensuring biometric information security.

[0125] However, since some biometric characteristics are controlled to be occluded, it will inevitably affect the accuracy of biometric recognition. Since the mirrors in the first specific area of the mirror array are controlled to change their reflection intensity, based on this, the backend data processing module can further combine the relevant information of the first specific area in the mirror array to obtain the object characteristic information for biometric recognition, thereby improving the accuracy of biometric recognition.

[0126] In some embodiments, the compensation value for the gray value of the pixels in the second specific area of the first feature image can be determined according to the reflection intensity of the light rays emitted by the optical compensation module by the mirrors in the first specific area of the mirror array. Then, the first feature image can be processed according to the compensation value to obtain complete object feature information, thereby improving the accuracy of biometric recognition.

[0127] Exemplarily, referring to Figure 6 , the object feature information can be obtained according to the following steps 431 and 432.

[0128] 431. Determine the compensation value for the gray value of the pixels in the second specific area according to the reflection intensity corresponding to the mirrors in the first specific area.

[0129] Exemplarily, the compensation value for the gray value of the pixels in the second specific area can be determined according to the reflection intensity of the mirrors in the first specific area or a parameter related to the reflection intensity (such as the flipping angle of the mirrors).

[0130] As a possible implementation, the control module 304 can send the reflection intensity of the mirrors in the first specific area or the related parameter to the data processing module 305, and the data processing module 305 determines the compensation value for the gray value of the pixels in the second specific area according to the reflection intensity or the related parameter.

[0131] As another possible implementation, the control module 304 can send the calculated compensation value for the gray value of the pixels in the second specific area to the data processing module.

[0132] As a specific embodiment, the control module 304 can generate a random code, control the reflection intensity of the light rays by the first specific area in the mirror array 302 according to the random code, and send the random code to the data processing module 305. The data processing module 305 determines the gray mask according to the random code, and then determines the compensation value for the gray value of the pixels in the second specific area according to the gray mask.

[0133] Specifically, the reflection intensity corresponding to the mirrors in the first specific area of the mirror array is related to the gray value of the pixels in the second specific area. For example, the greater the reflection intensity corresponding to the mirrors in the first specific area, the brighter the corresponding illumination area, and the greater the gray value of the corresponding pixels in the second specific area. At this time, the compensation value for the gray value of the pixels can be determined according to the illumination intensity, and the gray value of the pixels in the second specific area can be appropriately reduced. Also, for example, the smaller the reflection intensity corresponding to the mirrors in the first specific area, the darker the corresponding illumination area, and the smaller the gray value of the corresponding pixels in the second specific area. At this time, the compensation value for the gray value of the pixels can be determined according to the illumination intensity, and the gray value of the pixels in the second specific area can be appropriately increased.

[0134] 432. Compensate the grayscale values of the pixels in the second specific area of the first feature image according to the compensation value to obtain object feature information.

[0135] Exemplarily, the grayscale values of the pixels in the second specific area can be superimposed with the compensation value to obtain object feature information. For example, when the grayscale values of the pixels in the second specific area are too high due to the large reflection intensity of the mirror in the first specific area, the corresponding compensation value can be used to appropriately reduce the grayscale values. Another example is that when the grayscale values of the pixels in the second specific area are too low due to the small reflection intensity of the mirror in the first specific area, the corresponding compensation value can be used to appropriately increase the grayscale values. Therefore, the compensated grayscale values of the pixels in the second specific area in the embodiments of the present application can reflect the true grayscale values of the corresponding areas as much as possible.

[0136] As a possible implementation manner, refer to Figure 7 , the first feature image 501 can be converted into a feature code 502, and the feature code can be obtained by integrating the grayscale values in a specific area of the first feature image. After controlling the reflection intensity of the mirrors in the first specific area of the mirror array to achieve the light intensity difference in the illumination area, a specific deviation value is generated in the grayscale values of the corresponding areas in the first feature image 501. That is to say, by controlling the illumination intensity of the body part to be recognized, the grayscale values of the feature image of the body part to be recognized can be controlled, bringing a specific grayscale value deviation. Therefore, by controllably changing the local light information of the body part to be recognized, the grayscale integration data of the image can be affected, so as to ensure that even if the image is stolen, it cannot be directly used to forge biometric information, improving the security level of the system.

[0137] Then, the increased illumination difference can be compensated according to the compensation value 503 of the corresponding area, so that the gray level of the corresponding area of the first feature image 501 returns to the normal value. Specifically, the size of the compensation value 503 of the gray level value of the second specific area in the first feature image 501 can be determined according to the control signal for controlling the reflection intensity of the mirrors in the first specific area of the mirror array, such as the generated random code. This compensation value can compensate for the gray level value deviation according to the reflection intensity of the mirrors in the first specific area, so that it is restored to the accurate gray level value. For example, when the reflection intensity is large and overexposure occurs in the body part to be recognized, the gray level value can be appropriately reduced and corrected; when the reflection intensity is small and underexposure occurs in the body part to be recognized, the corresponding value can be appropriately increased and corrected. Therefore, by compensating the original feature code 502 of the first feature image 501 with the compensation value 503, a more accurate feature code can be obtained, which contains complete object feature information. Further, based on the compensated feature code, biometric identification of the object can be performed to obtain an identity matching result 504.

[0138] In some embodiments, by obtaining feature images in which biometric features of two or more mutually complementary different specific areas are hidden, complete object feature information can be obtained, thereby improving the accuracy of biometric identification.

[0139] Exemplarily, referring to Figure 8 , object feature information can be obtained according to the following steps 433 and 435.

[0140] 433, control the reflection intensity of the light emitted by the optical compensation module by the mirrors in the third specific area of the mirror assembly; the third specific area is different from the first specific area.

[0141] 434, use the image acquisition module to obtain the second feature image of the body part to be recognized; the gray level value of the pixels in the fourth specific area of the second feature image corresponds to the reflection intensity of the third specific area.

[0142] Specifically, steps 433 and 434 are similar to steps 410 and 420, and the relevant descriptions in Figure 4 can be referred to.

[0143] By performing steps 433 and 434, it is possible to obtain two or more feature images in which biometric features of different specific areas are hidden by controlling the reflection intensity of the light emitted by the light compensation module by the mirrors in different specific areas of the mirror assembly. Since the third specific area is different from the first specific area, the fourth feature area is also different from the second feature area, so that the hidden biometric features of different specific areas can be mutually complementary.

[0144] As an implementable manner, the first feature image and the second feature image may be acquired at time intervals shorter than a preset duration, so that the number of pixel points corresponding to the body part to be recognized in the first feature image and the second feature image is relatively close, so that each pixel point in the first feature image can correspond to a pixel point in the second feature image.

[0145] Exemplarily, the first feature image and the second feature image may be continuously acquired during a period when the body part to be recognized of the object remains stationary in the illumination area. In this way, the body parts to be recognized in the first feature image and the second feature image may correspond to the same or a relatively close number of pixel points, which is conducive to quickly and accurately fusing the first feature image and the second feature image.

[0146] 435. Obtain object feature information according to the first feature image and the second feature image.

[0147] Specifically, two or more feature images in which biometric features in different specific regions are hidden can complement each other, and complete object feature information can be obtained according to the two or more different feature images.

[0148] Optionally, the gray value of the pixel point corresponding to the second specific region in the second feature image may be used to determine the gray value of the pixel point corresponding to the second specific region in the first feature image; and object feature information may be obtained according to the gray value of the pixel point corresponding to the second specific region in the first feature image and the first feature image.

[0149] Specifically, the gray value of the pixel point corresponding to the second specific region in the second feature image may be acquired, and the gray value of the pixel point corresponding to the second specific region in the second feature image may be determined as the gray value of the pixel point corresponding to the second specific region in the first feature image. Exemplarily, the gray value of the pixel point corresponding to the original second specific region in the first feature image may be replaced with the gray value of the pixel point corresponding to the second specific region acquired from the second feature image. In this way, the biometric feature information hidden in the first feature image can be obtained from the second feature image, so as to obtain complete object feature information.

[0150] For example, in the first feature image, specific pixel point 1 is darker or brighter, and specific pixel point 2 is normal; while in the second feature image, specific pixel point 1 is normal, and specific pixel point 2 is brighter or normal. Thus, the first feature image and the second feature image can complement each other to obtain object feature information in which both specific pixel point 1 and pixel point 2 are normal.

[0151] It should be noted that the above steps 433 to 435 describe an embodiment of fusing the first feature image and the second feature image. Based on the same principle, it is also possible to fuse multiple (such as three or more) feature images with different regions being occluded and complementary to each other to obtain complete object feature information.

[0152] Therefore, by using multiple feature images with different regions being occluded and complementary to each other to collect multiple pieces of biometric information, since the gray values of each pixel point are complementary, it is possible to ensure that each feature image does not display the complete biometric information. Only when a complete set of several matching feature images is collected can an image with all feature information clearly displayed be obtained for biometric recognition, thereby increasing the security of the image acquisition device and making it more difficult for biometric information to be stolen.

[0153] In some embodiments, when the first specific region in the mirror array matches the second specific region in the first feature image, object feature information can be obtained based on the biometric information not hidden in the first feature image, thereby improving the accuracy of biometric recognition.

[0154] Exemplarily, referring to Figure 9 , object feature information can be obtained according to the following steps 436 and 437.

[0155] 436, determine that the second specific region matches the first specific region.

[0156] Exemplarily, the data processing module 305 can determine whether the position distribution of the pixel points in the second specific region in the first feature image is consistent with the position distribution of the pixel points in the first specific region in the mirror array. If the two are consistent, the second specific region matches the first specific region. Otherwise, the second specific region does not match the first specific region.

[0157] Exemplarily, continuing to refer to Figure 5 , the position distribution of the pixel points in figure (a) is consistent with the position distribution of the occluded pixel points in figure (c). Therefore, the first specific region corresponding to figure (a) matches the second specific region corresponding to figure (c).

[0158] 437, determine object feature information according to the gray values of the pixels in the first feature image except for the second specific region.

[0159] That is, object feature information can be obtained based on the biometric information not hidden in the first feature image. Since it has been verified in step 436 whether the second feature region matches the first feature region, in the case of a match, it indicates that the obtained first feature image is based on the image acquired using the security system rather than a stolen image. Therefore, object feature information can be obtained based on the biometric information not hidden in the first feature image for the backend to verify the identity of the object.

[0160] Therefore, the embodiments of the present application can obtain complete object feature information by compensating the gray values of the hidden biometric features in the first feature image, or by the feature images with hidden features in at least two mutually complementary specific regions, or when the second specific region in the first feature image matches the first specific region in the mirror array, obtain object feature information based on the first feature image, and then perform biometric recognition on the object based on the object feature information. The complete object feature information, as well as the unhidden feature information in the first feature image when the first feature region matches the second feature region, can help increase the security of the identity authentication service.

[0161] As a specific example, an encryption system can be used to generate a random code (i.e., password) and a corresponding gray mask, and use the random code to drive the DMD device. Thus, when illuminating the palm, the brightness of different regions in the palm is inconsistent, and bright and dark patches appear on the corresponding palm photo. Since the image is the gray information of each pixel point, combined with the bright and dark states of the illumination regions corresponding to the DMD device, overexposure or underexposure can be achieved at specific positions on the palm photo to conceal palm features, or special gray processing of specific regions can be realized. That is, by controlling the DMD device, gray control can be performed on each block of the acquired image. Exemplarily, the palm photo appears with black or bright blocks on the image, and local biometric information cannot be directly observed. Therefore, it is possible to conceal some biometric information during the image acquisition process in combination with the encryption algorithm management, so that an original picture does not completely display complete personal biometric information, and these blocked parts or regions with special gray processing can obtain accurate identity feature information by matching the corresponding encrypted data of the random code or gray mask in the identity recognition link, thus playing a role in information protection.

[0162] Therefore, the embodiments of the present application can achieve the protection of biometric information at the front end of image acquisition, that is, by controllably shielding the corresponding biometric blocks during the process of image acquisition, so as to avoid a picture completely containing the complete biometric information of the object, thus reducing the possibility of using the picture to make prosthetics or using the same picture multiple times after it is stolen. Since some biometric features are controllably shielded, it will inevitably affect the accuracy of biometric recognition. Based on this, three strategies can be adopted to balance this loss: First, since the DMD device itself changes the local brightness of the picture, that is, the gray value, therefore, the backend can also obtain the picture for biometric recognition through local gray compensation and repair. However, for a single captured picture, there are obvious local brightness differences, which is beneficial to reducing the risk of the user's biometric features being stolen and directly used; Second, use the method of fusing multiple pictures to encrypt a single picture, and after fusing multiple pictures, high-precision biometric recognition can be completely achieved in the form of complementary feature codes; Third, match the shielded part in the captured image with the gray mask used at the front end of the image acquisition. If the match is successful, the unshielded part in the image can be used for the user's biometric recognition.

[0163] In some embodiments, a distance sensor may also be used to obtain the position information of the body part to be recognized; and according to the position information, control the reflection intensity of the light reflected by the mirror of the first specific area on the light emitted by the optical compensation module.

[0164] Continue to refer to Figure 3 , the distance sensor 307 can obtain the position information of the body part to be recognized, and the further control module 304 controls the reflection strength of the light reflected by the mirrors of each pixel point of the mirror array 302 according to the position information. Exemplarily, the position information may include the distance D between the body part to be recognized and the distance sensor 307, or the distance between the body part to be recognized and the mirror array 302, or the distance from the protection cover 306, etc., which is not limited. Optionally, according to the distance D between the body part to be recognized and the distance sensor 307, the distance between the body part to be recognized and the mirror array 302, or the distance from the protection cover 306, etc. can be further determined.

[0165] Optionally, the number of distance sensors may be one or more, which is not limited. The position information includes, but is not limited to, the direction and / or distance of the body part to be recognized relative to the product (such as the distance sensor, mirror array or protection cover, etc. in the product). Exemplarily, multiple distance sensors can be combined to comprehensively judge the position of the body part to be recognized in the acquisition area of the image acquisition module (such as a camera), such as the middle, upper left, lower left, upper right, lower right, etc.

[0166] Exemplarily, taking the palm as the body part to be recognized, the palm can be located at a certain distance above the product (such as a distance sensor, a mirror array, or a protective cover plate, etc.). Refer to Figure 10A , when the distance D1 between the palm and the mirror array 302 is relatively large, the image of the palm captured by the image acquisition module 303 is relatively small (containing fewer pixels); refer to Figure 10B , while when the distance D2 between the palm and the mirror array 302 is relatively small, the image of the palm captured by the image acquisition module 303 is relatively large (containing more pixels). In Figure 10A , since the image of the palm captured is relatively small, the reflection intensity of a relatively small number of pixel points (such as 1) of the mirrors in the first specific area 701a of the mirror array 302 can be configured to control the over-brightness or over-darkness of a specific-sized area 702a of the palm part in the palm image. In Figure 10B , since the image of the palm captured is relatively large, the reflection intensity of a relatively large number of pixel points (such as 4) of the mirrors in the first specific area 701b of the mirror array 302 can be configured to control the over-brightness or over-darkness of a specific-sized area 702b of the palm part in the palm image. In this way, in the image captured by the image acquisition module 303, both the area 702a and the area 702b can correspond to the same-sized area in the palm, that is, the occlusion of the same biometric feature in the palm is achieved. Exemplarily, refer to Figure 10C , Figure 10A the area 702a in Figure 10B and the area 702b in Figure 10C can both correspond to the area 703 in

[0167] , so as to control the reflection intensity of the mirrors in the corresponding first specific area on the light emitted by the optical compensation module for the body part to be recognized at different distances, so that the pixel points in the feature images captured at different distances can correspond.

[0168] The specific embodiments of the present application have been described in detail above in conjunction with the accompanying drawings. However, the present application is not limited to the specific details in the above embodiments. Within the scope of the technical concept of the present application, various simple modifications can be made to the technical solutions of the present application, and these simple modifications all belong to the protection scope of the present application. For example, in the various specific technical features described in the above specific embodiments, they can be combined in any appropriate manner without contradiction. To avoid unnecessary repetition, the present application will not separately describe various possible combination methods. For another example, any combination can be made between various different embodiments of the present application, as long as it does not violate the idea of the present application, it should also be regarded as the content disclosed in the present application.

[0169] It should also be understood that in various method embodiments of the present application, the magnitudes of the serial numbers of the above processes do not mean the order of execution is prior or subsequent. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application. It should be understood that these serial numbers can be interchanged under appropriate circumstances so that the embodiments of the present application described can be implemented in an order other than those illustrated or described.

[0170] The following will describe in detail the device embodiments of the present application in conjunction with Figures 11 to 12 ,

[0171] Figure 11 FIG. is a schematic block diagram of an image acquisition device 10 according to an embodiment of the present application. The device 10 may include a control unit 11, an acquisition unit 12, and a processing unit 13.

[0172] The control unit 11 is configured to control the reflection intensity of the light emitted by the optical compensation module by the mirrors in the first specific area of the mirror array;

[0173] The acquisition unit 12 is configured to acquire a first feature image of the body part to be recognized of the object by using the image acquisition module, wherein the light emitted by the optical compensation module intersects with the body part to be recognized of the object after being reflected by the mirror array; the gray value of the pixels in the second specific area of the first feature image corresponds to the reflection intensity of the first specific area;

[0174] The processing unit 13 is configured to obtain object feature information according to the first feature image; wherein the object feature information is used for biometric recognition of the object.

[0175] In some embodiments, the processing unit 13 is specifically configured to:

[0176] Determine a compensation value for the gray value of the pixels in the second specific area according to the reflection intensity corresponding to the mirrors in the first specific area;

[0177] Compensate the gray values of the pixels in the second specific area of the first feature image according to the compensation value to obtain the object feature information.

[0178] In some embodiments, the control unit 11 is further configured to: control the reflection intensity of the light emitted by the optical compensation module by the mirrors in the third specific area of the mirror array; the third specific area is different from the first specific area;

[0179] The acquisition unit 12 is further configured to use the image acquisition module to acquire a second feature image of the to-be-identified body part of the object; the gray values of the pixels in the fourth specific area of the second feature image correspond to the reflection intensity of the third specific area;

[0180] The processing unit 13 is further configured to: obtain the object feature information according to the first feature image and the second feature image.

[0181] In some embodiments, the processing unit 13 is specifically configured to:

[0182] Determine the gray value of the pixel point corresponding to the second specific area in the first feature image according to the gray value of the pixel point corresponding to the second specific area in the second feature image;

[0183] Obtain the object feature information according to the gray value of the pixel point corresponding to the second specific area in the first feature image and the first feature image.

[0184] In some embodiments, the processing unit 13 is specifically configured to:

[0185] Determine that the second specific area matches the first specific area;

[0186] Determine the object feature information according to the gray values of the pixels in the first feature image except the second specific area.

[0187] In some embodiments, the pixels in the second specific area are overexposed or underexposed.

[0188] In some embodiments, the control unit 11 is specifically configured to:

[0189] Use a distance sensor to obtain the position information of the to-be-identified body part;

[0190] Control the reflection intensity of the light emitted by the optical compensation module by the mirrors in the first specific area according to the position information.

[0191] In some embodiments, the first specific area includes at least one mirror at the pixel level.

[0192] In some embodiments, the mirror array includes a digital micromirror device.

[0193] In some embodiments, the body part to be recognized includes at least one of a palm print or a fingerprint.

[0194] It should be understood that the device embodiments and the method embodiments can correspond to each other, and similar descriptions can refer to the method embodiments. To avoid repetition, they will not be elaborated here. Specifically, when the image acquisition device 10 in this embodiment can correspond to the image acquisition method 400 of the embodiments of the present application, the foregoing and other operations and / or functions of each module in the device 10 are respectively for implementing Figure 4 the corresponding processes in each method in, and for the sake of brevity, they will not be elaborated here.

[0195] The device and system of the embodiments of the present application have been described above from the perspective of functional modules in combination with the drawings. It should be understood that the functional modules can be implemented in the form of hardware, or in the form of software instructions, or in a combination of hardware and software modules. Specifically, the steps of the method embodiments in the present application can be completed by the integrated logic circuit in the hardware of the processor and / or software instructions. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as being executed and completed by the hardware decoding processor, or executed and completed by the combination of the hardware and software modules in the decoding processor. Optionally, the software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps in the above method embodiments.

[0196] As Figure 12 is a schematic block diagram of the electronic device 30 provided by the embodiments of the present application.

[0197] As Figure 12 shown, the electronic device 30 may include:

[0198] A memory 31 and a processor 32. The memory 31 is used to store a computer program and transmit the program code to the processor 32. In other words, the processor 32 can call and run the computer program from the memory 31 to implement the method in the embodiments of the present application.

[0199] For example, the processor 32 can be used to execute the steps in the image acquisition method according to the instructions in the computer program, including:

[0200] Controlling the reflection intensity of the light emitted by the optical compensation module by the mirrors in the first specific area of the mirror array;

[0201] The first feature image of the body part to be recognized of the object is obtained by using the image acquisition module, wherein the light emitted by the optical compensation module intersects with the body part to be recognized of the object after being reflected by the mirror array; the gray value of the pixel in the second specific area of the first feature image corresponds to the reflection intensity of the first specific area;

[0202] Object feature information is obtained according to the first feature image; wherein, the object feature information is used for biometric recognition of the object.

[0203] In some embodiments of the present application, the processor 32 may include but is not limited to:

[0204] General purpose processor, digital signal processor (DSP), application specific integrated circuit (ASIC), field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and so on.

[0205] In some embodiments of the present application, the memory 31 includes but is not limited to:

[0206] Volatile memory and / or non-volatile memory. Among them, the non-volatile memory can be Read-Only Memory (ROM), Programmable ROM (PROM), Erasable PROM (EPROM), Electrically Erasable PROM (EEPROM), or flash memory. The volatile memory can be Random Access Memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double DataRate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), synch link DRAM (SLDRAM), and Direct Rambus RAM (DR RAM).

[0207] In some embodiments of the present application, the computer program can be divided into one or more modules, and the one or more modules are stored in the memory 31 and executed by the processor 32 to complete the method provided by the present application. The one or more modules can be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device 30.

[0208] Optionally, as Figure 12 shown, the electronic device 30 may further include:

[0209] A communication interface 33, and the communication interface 33 can be connected to the processor 32 or the memory 31.

[0210] Among them, the processor 32 can control the communication interface 33 to communicate with other devices. Specifically, it can send information or data to other devices, or receive information or data sent by other devices. Exemplarily, the communication interface 33 can include a transmitter and a receiver. The communication interface 33 can further include an antenna, and the number of antennas can be one or more.

[0211] It should be understood that each component in the electronic device 30 is connected through a bus system. Among them, the bus system includes not only a data bus, but also a power bus, a control bus, and a status signal bus.

[0212] According to one aspect of the present application, there is provided a computer storage medium, on which a computer program is stored. When the computer program is executed by a computer, the computer is enabled to execute the method of the above method embodiment. Or rather, the embodiment of the present application further provides a computer program product containing instructions. When the instructions are executed by a computer, the computer is enabled to execute the method of the above method embodiment.

[0213] According to another aspect of the present application, there is provided a computer program product or a computer program. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, enabling the computer device to execute the method of the above method embodiment.

[0214] In other words, when implemented using software, it can be implemented in the form of a computer program product in whole or in part. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions according to the embodiments of the present application are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website, a computer, a server, or a data center to another website, a computer, a server, or a data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium may be any available medium that the computer can access or a data storage device such as a server or a data center that includes one or more integrated available media. The available medium may be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a digital video disc (DVD)), or a semiconductor medium (such as a solid state disk (SSD)), etc.

[0215] It can be understood that in the specific implementation of the present application, when the above embodiments of the present application are applied to specific products or technologies and involve relevant data such as user information, user permission or consent needs to be obtained, and the collection, use, and processing of relevant data need to comply with relevant laws, regulations, and standards.

[0216] Those of ordinary skill in the art can realize that the modules and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0217] In several embodiments provided by this application, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of the modules is only a logical function division. In actual implementation, there can be other division methods. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the devices or modules can be in an electrical, mechanical, or other form.

[0218] The modules described as separate components may or may not be physically separated. The components shown as modules may or may not be physical modules, that is, they can be located in one place, or can be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. For example, in each embodiment of this application, the functional modules can be integrated into one processing module, or each module can exist physically alone, or two or more modules can be integrated into one module.

[0219] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed by this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

Claims

1. A method for image acquisition, characterized in that, Including: Controlling the reflection intensity of the mirrors in the first specific area of the mirror array for the light emitted by the optical compensation module; Using the image acquisition module to obtain a first feature image of the body part to be recognized of the object, wherein the light emitted by the optical compensation module is reflected by the mirror array and intersects with the body part to be recognized of the object; the gray value of the pixel in the second specific area of the first feature image corresponds to the reflection intensity of the first specific area; Obtaining object feature information according to the first feature image; wherein, the object feature information is used for biometric recognition of the object.

2. The method according to claim 1, characterized in that The obtaining object feature information according to the first feature image includes: Determining a compensation value for the gray value of the pixel in the second specific area according to the reflection intensity corresponding to the mirror in the first specific area; Compensating the gray value of the pixel in the second specific area in the first feature image according to the compensation value to obtain the object feature information.

3. The method according to claim 1, wherein Further including: Controlling the reflection intensity of the mirrors in the third specific area of the mirror array for the light emitted by the optical compensation module; the third specific area is different from the first specific area; Using the image acquisition module to obtain a second feature image of the body part to be recognized of the object; the gray value of the pixel in the fourth specific area of the second feature image corresponds to the reflection intensity of the third specific area; Wherein, the obtaining object feature information according to the first feature image includes: Obtaining the object feature information according to the first feature image and the second feature image.

4. The method according to claim 3, wherein The obtaining the object feature information according to the first feature image and the second feature image includes: Determining the gray value of the pixel point corresponding to the second specific area in the first feature image according to the gray value of the pixel point corresponding to the second specific area in the second feature image; Obtaining the object feature information according to the gray value of the pixel point corresponding to the second specific area in the first feature image and the first feature image.

5. The method according to claim 1, characterized in that, The obtaining object feature information according to the first feature image includes: Determining that the second specific area matches the first specific area; Determining the object feature information according to the gray value of the pixel other than the second specific area in the first feature image.

6. The method according to claim 1, characterized in that, The controlling the reflection intensity of the mirrors in the first specific area of the mirror array for the light emitted by the optical compensation module includes: Using a distance sensor to obtain the position information of the body part to be recognized; Controlling the reflection intensity of the mirrors in the first specific area for the light emitted by the optical compensation module according to the position information.

7. The method according to any one of claims 1 to 6, characterized in that, The pixels in the second specific area are overexposed or underexposed.

8. The method according to any one of claims 1 to 6, characterized in that, The first specific area includes at least one mirror at the pixel level.

9. The method according to any one of claims 1-6, characterized in that, The mirror array includes a digital micromirror device.

10. The method according to any one of claims 1-6, characterized in that, The body part to be recognized includes at least one of a palm print or a fingerprint.

11. An image acquisition device, characterized in that, Including: A control unit for controlling the reflection intensity of the mirrors in the first specific area of the mirror array for the light emitted by the optical compensation module; An acquisition unit, configured to acquire a first feature image of a body part to be recognized of an object by using an image acquisition module, wherein the light emitted by the optical compensation module intersects with the body part to be recognized of the object after being reflected by the mirror array; the gray value of the pixel in the second specific area of the first feature image corresponds to the reflection intensity of the first specific area; A processing unit, configured to obtain object feature information according to the first feature image; wherein the object feature information is used for performing biometric recognition on the object.

12. An electronic device, characterized in that, Comprising a processor and a memory, wherein instructions are stored in the memory, and when the processor runs the instructions, the processor executes the method according to any one of claims 1-10.

13. A computer storage medium, characterized in that, Comprising instructions, when running on a computer, enabling the computer to execute the method according to any one of claims 1-10.

14. A computer program product, characterized in that, Comprising computer program code, when the computer program code is run on an electronic device, enabling the electronic device to execute the method according to any one of claims 1-10.

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