Digital twin data acquisition method based on multi-modal biological characteristics

Abstract

The invention discloses a digital twinborn data acquisition method based on multi-modal biological characteristics, which comprises the following steps: loading user information, collecting user biological characteristics, and establishing an initial digital twinborn model; and inserting face data, iris data and fingerprint data of the user into the initial digital twinborn model. Face data, iris data and fingerprint data of a user are obtained and preprocessed, the face data, the iris data and the fingerprint data are inserted into an initial digital twinborn model, a complete digital twinborn model is constructed, face recognition, iris recognition and fingerprint recognition are conducted in sequence in a query unit, three sets of digital twinborn models are queried, and the three sets of digital twinborn models are queried. Under the condition that the three sets of digital twinborn models are different, the face data, the iris data and the fingerprint data are obtained again and inserted, the authenticity of the digital twinborn models is guaranteed, and the corresponding digital twinborn model can be inquired subsequently according to any one of face recognition, iris recognition and fingerprint recognition.

Description

Technical Field

[0001] The present invention relates to the technical field of biometric digital twin models, and specifically to a method for collecting data based on multimodal biometric digital twins. Background Art

[0002] Biometrics are physiological or behavioral characteristics inherent in a person, such as fingerprints, irises, faces, finger veins, and palm prints. Biometrics have certain uniqueness and stability, that is, the difference between a certain biometric of any two people is relatively large, and the biometric of each person generally does not change greatly over time. This makes biometrics very suitable as authentication information in identity authentication and recognition systems. Compared with authentication information such as passwords and tokens in traditional authentication and recognition systems, biometrics have the advantages of not being forgotten, not being lost, not being easily stolen, and not being shared. Authentication and recognition systems based on biometrics can provide better user usability and higher security, and therefore have begun to be used more and more widely. For example, fingerprints have been widely used in access control, attendance and other systems.

[0003] Existing biometric recognition has the following problems: poor applicability and a single recognition method, most of which are facial recognition, iris recognition, and fingerprint recognition. When extracting digital twin data, it is necessary to determine user information through facial recognition, iris recognition, fingerprint recognition, etc., and different devices have different recognition methods. When the user cannot provide the corresponding recognition method, digital twin data cannot be extracted. Summary of the invention

[0004] The purpose of the present invention is to provide a digital twin data acquisition method based on multimodal biometrics to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for collecting digital twin data based on multimodal biometric features, comprising the following steps:

[0006] Load user information, collect user biometrics, and build an initial digital twin model;

[0007] Among them, the initial digital twin model includes: biometrics of the user’s limbs and torso;

[0008] Insert the user’s facial data, iris data, and fingerprint data into the initial digital twin model;

[0009] Further improve the digital twin model and put the user's biometric digital twin model into the database;

[0010] Among them, limbs, torso, face, iris, and fingerprints can form a complete biometric feature, which can be converted into a digital twin model for easy storage and query;

[0011] Input the user's facial data, iris data, and fingerprint data in the query unit in sequence to obtain three sets of digital twin models;

[0012] After checking the consistency of the three sets of digital twin models, the user's digital twin model can be obtained by inputting any data;

[0013] Among them, users can query digital twin data through facial recognition, iris recognition, and fingerprint recognition; when the three sets of digital twin models are verified to be inconsistent, it is necessary to re-collect the user's facial data, iris data, and fingerprint data, pre-process the facial data, iris data, and fingerprint data, and then re-insert the facial data, iris data, and fingerprint data into the initial digital twin model after accurate recognition.

[0014] Preferably, the user information includes: name, gender, age, ID number, name, gender, age, ID number, and digital twin model, all in one query unit.

[0015] Preferably, the facial data, iris data, and fingerprint data are obtained by facial recognition, iris recognition, and fingerprint recognition, respectively. After the facial data, iris data, and fingerprint data are obtained, they are pre-processed to obtain accurate biometric features.

[0016] Preferably, the digital twin models of multiple users can be stored in the database, and the database is associated with facial recognition, iris recognition, and fingerprint recognition.

[0017] Preferably, the digital twin model in the database can be extracted by facial recognition, iris recognition, or fingerprint recognition.

[0018] Preferably, after the digital twin model is verified, the digital twin model can be extracted through any of facial recognition, iris recognition, and fingerprint recognition.

[0019] The present invention also provides a multimodal biometric digital twin data acquisition device, comprising:

[0020] The information entry module is used to obtain the user's name, gender, age, and ID number information.

[0021] The biometric information acquisition module is used to obtain the user's limbs, torso, face, iris, and fingerprint biometric features.

[0022] The digital twin model establishment module is used to establish a digital twin model based on the user's limbs, torso, face, iris, and fingerprint biometrics.

[0023] The data query module is used to query digital twin data based on facial recognition, iris recognition, and fingerprint recognition.

[0024] The data output module is used to output the user's unique digital twin model.

[0025] The present invention further provides an electronic device, comprising:

[0026] A processor and a memory, wherein the memory is communicatively connected to the processor;

[0027] The memory is used to store at least one executable instruction executed by the processor, and the processor is used to execute the executable instruction to implement the multimodal biometric digital twin data acquisition method as described above.

[0028] The present invention also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, it implements the multimodal biometric digital twin data acquisition method as described above.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] Obtain the user's name, gender, age, and ID number information, build an initial digital twin model based on the biometrics of the limbs and torso, continue to obtain the user's facial data, iris data, and fingerprint data, and preprocess them, insert the facial data, iris data, and fingerprint data into the initial digital twin model to build a complete digital twin model, associate facial recognition, iris recognition, and fingerprint recognition with the facial data, iris data, and fingerprint data respectively, perform facial recognition, iris recognition, and fingerprint recognition in the query unit in sequence, and query three groups of digital twin models. When the three groups of digital twin models are the same, save the digital twin models in the database. When the three groups of digital twin models are different, re-obtain the facial data, iris data, and fingerprint data and insert them to ensure the authenticity of the digital twin model. Subsequently, the corresponding digital twin model can be queried according to any of the facial recognition, iris recognition, and fingerprint recognition methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 The main flow chart of the multimodal biometric digital twin data acquisition method provided in the embodiment of the present invention;

[0032] Figure 2 A structural block diagram of a multimodal biometric digital twin data acquisition device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0034] The execution subject of the method of this embodiment is a terminal, which can be a mobile phone, tablet computer, PDA, notebook or desktop computer, etc. Of course, it can also be other devices with similar functions, which is not limited in this embodiment.

[0035] See also Figure 1 The present invention provides a method for collecting digital twin data based on multimodal biometric features, which is applied to collecting digital twin data based on multimodal biometric features, and includes:

[0036] Step 101: load user information, collect user biometrics, and establish an initial digital twin model.

[0037] Among them, the initial digital twin model is the biological characteristics of the user's limbs and torso, and the user information is name, gender, age, and ID number. The user's name, gender, age, and ID number are obtained in the information entry module, and the biological characteristics of the limbs and torso are constructed into the initial digital twin model.

[0038] Step 102, insert the user's facial data, iris data, and fingerprint data into the initial digital twin model.

[0039] Among them, the biometric features of face, iris and fingerprint are obtained in the biometric information acquisition module, and the biometric features of face, iris and fingerprint are preprocessed to highlight the biological characteristics.

[0040] Step 103, further improve the digital twin model and put the user biometric digital twin model into the database.

[0041] Specifically, a complete digital twin model is constructed through the biometric features of limbs, torso, face, iris, and fingerprints.

[0042] Step 104, input the user's facial data, iris data, and fingerprint data in the query unit in sequence to obtain three sets of digital twin models.

[0043] Among them, facial data, iris data, and fingerprint data are all associated with the digital twin model.

[0044] Step 105, after checking the consistency of the three sets of digital twin models, the user's digital twin model can be obtained by inputting any data.

[0045] Specifically, the associated digital twin model can be queried through any of facial recognition, iris recognition, and fingerprint recognition.

[0046] In this embodiment, the user's name, gender, age, and ID number information are obtained, and an initial digital twin model is constructed based on the biometric features of the limbs and torso. The user's facial data, iris data, and fingerprint data are further obtained and preprocessed. The facial data, iris data, and fingerprint data are inserted into the initial digital twin model to construct a complete digital twin model. Facial recognition, iris recognition, and fingerprint recognition are respectively associated with the facial data, iris data, and fingerprint data. Facial recognition, iris recognition, and fingerprint recognition are performed in the query unit in sequence to query three groups of digital twin models. When the three groups of digital twin models are the same, the digital twin models are saved in a database. When the three groups of digital twin models are different, the facial data, iris data, and fingerprint data are re-obtained and inserted to ensure the authenticity of the digital twin model. Subsequently, the corresponding digital twin model can be queried according to any of the facial recognition, iris recognition, and fingerprint recognition methods.

[0047] In order to better understand the above embodiments, Figure 2 As shown, the present invention also provides a digital twin data acquisition device based on multimodal biometrics, comprising:

[0048] The information entry module is used to obtain the user's name, gender, age, and ID number information.

[0049] The biometric information acquisition module is used to obtain the user's limbs, torso, face, iris, and fingerprint biometric features.

[0050] The digital twin model establishment module is used to establish a digital twin model based on the user's limbs, torso, face, iris, and fingerprint biometrics.

[0051] The data query module is used to query digital twin data based on facial recognition, iris recognition, and fingerprint recognition.

[0052] The data output module is used to output the user's unique digital twin model.

[0053] In this embodiment, before building a digital twin model, the user's name, gender, age, and ID number are obtained, and the user's limbs, torso, face, iris, and fingerprint biometrics are obtained through the biometric information acquisition module. The limbs and torso are constructed into an initial digital twin model through the digital twin model establishment module, and then the facial, iris, and fingerprint biometrics are inserted into the initial digital twin model through the digital twin model establishment module. The facial data, iris data, and fingerprint data are associated with the digital twin model through the data query module. The corresponding digital twin model can be queried according to the methods of facial recognition, iris recognition, and fingerprint recognition. The digital twin model is verified according to the three methods of facial recognition, iris recognition, and fingerprint recognition. A new digital twin model can be constructed by re-acquiring the facial, iris, and fingerprint biometrics.

[0054] Based on the above embodiments, the present invention also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, it implements the multimodal biometric digital twin data acquisition method as described above.

[0055] Based on the above embodiment, the present invention further provides an electronic device, comprising:

[0056] A processor and a memory, wherein the processor is communicatively connected with the memory;

[0057] In this embodiment, the memory may be implemented in any appropriate manner, for example, the memory may be a read-only memory, a mechanical hard disk, a solid-state hard disk, or a USB flash drive, etc.; the memory is used to store at least one executable instruction executed by the processor;

[0058] In this embodiment, the processor can be implemented in any appropriate manner. For example, the processor can take the form of a microprocessor or a processor and a computer-readable medium storing computer-readable program code (such as software or firmware) executable by the (micro)processor, logic gates, switches, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, etc.; the processor is used to execute the executable instructions to implement the multimodal biometric digital twin data acquisition method based on the above-mentioned multimodal biometrics.

[0059] Based on the above embodiments, the present invention also provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, it implements the multimodal biometric digital twin data acquisition method as described above.

[0060] Those of ordinary skill in the art will appreciate that the modules and method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0061] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices, equipment and modules can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0062] In the several embodiments provided in the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or units can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or equipment, which can be electrical, mechanical or other forms.

[0063] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0064] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0065] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program instructions, such as a USB flash drive, a mobile hard disk, a read-only storage server, a random access storage server, a magnetic disk or an optical disk.

[0066] In addition, it should be noted that the combination of the various technical features in this case is not limited to the combination described in the claims of this case or the combination described in the specific embodiments. All technical features described in this case can be freely combined or combined in any way unless there is a contradiction between them.

[0067] It should be noted that the above examples are only specific embodiments of the present invention, and the present invention is obviously not limited to the above examples, and there are many similar variations. All variations directly derived or associated from the contents disclosed by the technicians in this field should fall within the protection scope of the present invention.

[0068] The above are only preferred embodiments of the present invention and are not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for collecting digital twin data based on multimodal biometrics, characterized in that: The following steps are involved: Load user information, collect user biometrics, and build an initial digital twin model; Among them, the initial digital twin model includes: biometrics of the user’s limbs and torso; Insert the user’s facial data, iris data, and fingerprint data into the initial digital twin model; Wherein, the biometric features of face, iris and fingerprint are obtained in the biometric information acquisition module, and the biometric features of face, iris and fingerprint are preprocessed; Further improve the digital twin model and put the user's biometric digital twin model into the database; Among them, limbs, torso, face, iris, and fingerprints can form a complete biometric feature, which can be converted into a digital twin model for easy storage and query; Input the user's facial data, iris data, and fingerprint data in the query unit in sequence to obtain three sets of digital twin models; Specifically, facial data, iris data, and fingerprint data are all associated with the digital twin model; After checking the consistency of the three sets of digital twin models, the user's digital twin model can be obtained by inputting any data; Among them, users can query digital twin data through facial recognition, iris recognition, and fingerprint recognition; when the three sets of digital twin models are verified to be inconsistent, it is necessary to re-collect the user's facial data, iris data, and fingerprint data, pre-process the facial data, iris data, and fingerprint data, and then re-insert the facial data, iris data, and fingerprint data into the initial digital twin model after accurate recognition.

2. The method for collecting digital twin data based on multimodal biometrics according to claim 1 is characterized in that: The user information includes: name, gender, age, ID number, name, gender, age, ID number, and digital twin model, all in one query unit.

3. The method for collecting digital twin data based on multimodal biometric features according to claim 1 is characterized in that: The facial data, iris data, and fingerprint data are obtained by facial recognition, iris recognition, and fingerprint recognition, respectively. After the facial data, iris data, and fingerprint data are obtained, they are pre-processed to obtain accurate biometric features.

4. The method for collecting digital twin data based on multimodal biometric features according to claim 1 is characterized in that: The database can store digital twin models of multiple users. The database is associated with facial recognition, iris recognition, and fingerprint recognition. The digital twin models in the database can be extracted by facial recognition, iris recognition, and fingerprint recognition.

5. The method for collecting digital twin data based on multimodal biometrics according to claim 1 is characterized in that: After the digital twin model is verified, the digital twin model can be extracted through any of facial recognition, iris recognition, and fingerprint recognition.

6. A digital twin data acquisition device based on multimodal biometrics, characterized in that: include: The information entry module is used to obtain the user's name, gender, age, and ID number information. The biometric information acquisition module is used to obtain the user's limbs, torso, face, iris, and fingerprint biometrics. The digital twin model establishment module is used to establish a digital twin model based on the user's limbs, torso, face, iris, and fingerprint biometrics. The data query module is used to query digital twin data based on facial recognition, iris recognition, and fingerprint recognition. The data output module is used to output the user's unique digital twin model.

7. An electronic device, characterized in that: The electronic device comprises: A processor and a memory, wherein the memory is communicatively connected to the processor; The memory is used to store at least one executable instruction executed by the processor, and the processor is used to execute the executable instruction to implement the multimodal biometric digital twin data acquisition method as described in any one of claims 1 to 6.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the multimodal biometric digital twin data acquisition method according to any one of claims 1 to 6.

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