Method and system for detecting transaminase content information

Abstract

The embodiment of the invention discloses a method and system for detecting transaminase content information, and the method comprises the steps: obtaining collected face video information from a near-infrared camera device, and processing the face video information according to a specified processing mode to obtain an infrared spectrogram; processing the infrared spectrogram by using a calibration model to obtain transaminase content information, and determining a reference infrared spectrogram corresponding to the infrared spectrogram from a pre-established infrared spectrogram library; and comparing the infrared spectrogram with the reference infrared spectrogram by using a calibration model to obtain a comparison result, and determining transaminase content information based on the comparison result. The purpose of determining the content of transaminase in a non-contact mode is achieved, the time needed for detecting the content of transaminase is greatly shortened, operation is convenient, and the recognition efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of near-infrared technology, and particularly to a method and system for detecting transaminase content information. Background Art

[0002] Traditional methods for transaminase examination are all contact-based, with a relatively complicated process and certain requirements for users, such as maintaining a certain state before contact detection, dietary requirements, and so on. How to greatly reduce the time required for transaminase content detection, with convenient operation and improved recognition efficiency, is the problem to be solved by the present invention. Summary of the Invention

[0003] The main purpose of the present invention is to provide a method and device for detecting transaminase content information to solve the deficiencies in the related art.

[0004] To achieve the above object, according to the first aspect of the present invention, a method for detecting transaminase content information is provided, including obtaining the collected face video information from a near-infrared imaging device, and processing the face video information according to a specified processing method to obtain an infrared spectrogram; processing the infrared spectrogram using a calibration model to obtain transaminase content information, wherein the reference infrared spectrogram corresponding to the infrared spectrogram is determined from a pre-established infrared spectrogram library; comparing the infrared spectrogram with the reference infrared spectrogram using the calibration model to obtain a comparison result, and determining the transaminase content information based on the comparison result.

[0005] Optionally, comparing the infrared spectrogram with the reference infrared spectrogram to obtain a comparison result, and determining the transaminase content information based on the comparison result includes: calculating the similarity between the infrared spectrogram and the reference infrared spectrogram; calculating the local similarity between the infrared spectrogram and the reference infrared spectrogram in a specified interval; and determining the transaminase content information based on the similarity and the local similarity.

[0006] Optionally, obtaining the collected face video information from a near-infrared imaging device, and processing the face video information according to a specified processing method to obtain an infrared spectrogram includes: extracting the face region video in the RGB three-channel signal mode to obtain the RGB three-channel signal; performing chromatic aberration method processing on the RGB three-channel signal to obtain a spectral signal, and performing secondary processing on the spectral signal to obtain a dynamic infrared spectrogram of transaminase content.

[0007] Optionally, when establishing the infrared spectral library, the method includes: obtaining a face video sample, processing the face video sample according to a specified processing method to obtain a dynamic infrared spectral map sample; corresponding each infrared spectral map sample to a pre-determined transaminase content; and performing spectral averaging and sample analysis on the infrared spectral map sample to obtain infrared spectral map information.

[0008] Optionally, a calibration model is established based on the MPLS method. The spectral range for modeling is selected as 300nm - 1000nm, and the spectral processing methods include inverse multivariate discrete correction, second derivative processing, and smoothing processing.

[0009] According to the second aspect of the present invention, a detection system for transaminase content information is provided, including: a near-infrared detection subsystem for emitting near-infrared to detect a face; a processing subsystem for obtaining the collected face video information from the near-infrared detection subsystem, processing the face video information according to a specified processing method to obtain an infrared spectral map; using a calibration model to process the infrared spectral map to obtain transaminase content information, where the reference infrared spectral map corresponding to the infrared spectral map is determined from a pre-established infrared spectral library; using the calibration model to compare the infrared spectral map with the reference infrared spectral map to obtain a comparison result, and determining the transaminase content information based on the comparison result.

[0010] As an optional implementation manner of this embodiment, comparing the infrared spectral map with the reference infrared spectral map to obtain a comparison result and determining the transaminase content information based on the comparison result includes: calculating the similarity between the infrared spectral map and the reference infrared spectral map; calculating the local similarity between the infrared spectral map and the reference infrared spectral map in a specified interval; and determining the transaminase content information based on the similarity and the local similarity.

[0011] As an optional implementation manner of this embodiment, obtaining the collected face video information from a near-infrared imaging device and processing the face video information according to a specified processing method to obtain an infrared spectral map includes: extracting the face area video in the RGB three-channel signal mode to obtain the RGB three-channel signal; performing chromatic aberration method processing on the RGB three-channel signal to obtain a spectral signal, and performing secondary processing on the spectral signal to obtain a dynamic infrared spectral map of the transaminase content.

[0012] According to the third aspect of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium stores computer instructions for causing the computer to execute the method according to any one of the first aspect.

[0013] According to a fourth aspect of the present invention, there is provided an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is caused to execute the method according to any one of the implementation manners of the first aspect.

[0014] The method and system for detecting the content information of transaminase in this embodiment, wherein the method includes obtaining the collected face video information from a near-infrared camera device, and processing the face video information according to a specified processing manner to obtain an infrared spectrogram; processing the infrared spectrogram by using a calibration model to obtain the content information of transaminase, wherein the reference infrared spectrogram corresponding to the infrared spectrogram is determined from a pre-established infrared spectrogram library; comparing the infrared spectrogram with the reference infrared spectrogram by using the calibration model to obtain a comparison result, and determining the content information of transaminase based on the comparison result. The purpose of non-contact determination of the content of transaminase is achieved, greatly reducing the time required for detecting the content of transaminase, with convenient operation and improved recognition efficiency. Brief Description of the Drawings

[0015] In order to more clearly illustrate the specific implementation manners of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for use in the description of the specific implementation manners or the prior art. Obviously, the drawings in the following description are some implementation manners of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0016] Figure 1 It is a flowchart of the method for detecting the content information of transaminase according to an embodiment of the present invention;

[0017] Figure 2 It is a schematic diagram of an electronic device according to an embodiment of the present invention. Detailed Embodiments

[0018] In order to enable those skilled in the art to better understand the solution of the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0019] It should be noted that the terms "first", "second", etc. in the description, claims and above-mentioned drawings of the present invention are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so as to implement the embodiments of the present invention described herein. 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 device that includes a series of steps or units does not necessarily have to 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.

[0020] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the drawings and in conjunction with the embodiments.

[0021] According to an embodiment of the present invention, a method for detecting the content information of transaminase is provided, as Figure 1 shown, including the following steps 101 to 103:

[0022] Step 101: Obtain the collected face video information from the near-infrared imaging device, and process the face video information according to a specified processing method to obtain an infrared spectrogram.

[0023] As an optional implementation manner of this embodiment, obtaining the collected face video information from the near-infrared imaging device and processing the face video information according to a specified processing method to obtain an infrared spectrogram includes: extracting the face area video in the RGB three-channel signal mode to obtain the RGB three-channel signal; performing chromatic aberration method processing on the RGB three-channel signal to obtain a spectral signal, and performing secondary processing on the spectral signal to obtain a dynamic infrared spectrogram of the transaminase content.

[0024] In the above manner, by using the near-infrared imaging device, by collecting the face video sample of the user, the spectral sample of the user's transaminase (including alanine aminotransferase and aspartate aminotransferase) is obtained.

[0025] Generally speaking, the periodic contraction and relaxation of the heart cause the periodic flow of blood in the blood vessels. During the acquisition process, it will be interfered by other signals, but it can still be approximately regarded as a periodic signal. Since any periodic signal can be represented by its DC component, fundamental wave component and each harmonic component, that is, it is composed of these frequency components, and there is a one-to-one correspondence between the periodic signal and its respective frequency components. Therefore, the time-domain analysis of the periodic signal is transformed into the frequency-domain analysis. The heart rate signal obtained by filtering the PPG signal through the method of spectrum analysis is subjected to periodic analysis. Since the periodic motion corresponds to a spike in the spectrum, it is necessary to find the frequency value corresponding to the spectral spike from the spectrogram.

[0026] Here, it is mainly divided into the following two parts of work: 1) Extraction based on video information: For the video collected by the color video acquisition device, a video color enhancement method is introduced to enhance the color information of the video image. The region of interest is detected and tracked using face detection to extract the skin color change information of the region of interest, and it is extracted in the form of RGB three-channel signals in the video image. 2) Extraction of transaminase spectrum based on video: According to the RGB three-channel signals extracted in the previous work, chromatic aberration method processing is performed to obtain the most original spectral signal containing noise. It is filtered and denoised, and time-frequency domain processing is performed to extract the final signal. The peaks and valleys of the time-domain signal are obtained to get the dynamic spectrogram of the content of transaminase (including alanine aminotransferase and aspartate aminotransferase) in the blood.

[0027] Step 102: Process the infrared spectrogram using the calibration model to obtain the transaminase content information. Among them, the reference infrared spectrogram corresponding to the infrared spectrogram is determined from the pre-established infrared spectrogram library; the calibration model is used to compare the infrared spectrogram with the reference infrared spectrogram to obtain a comparison result, and the transaminase content information is determined based on the comparison result.

[0028] As an optional implementation manner of this embodiment, when establishing the infrared spectrogram library, the method includes: obtaining a face video sample, processing the face video sample according to a specified processing method to obtain a dynamic infrared spectrogram sample; corresponding each infrared spectrogram sample to the pre-determined transaminase content one by one; and performing spectral averaging and sample analysis on the infrared spectrogram sample to obtain infrared spectrogram information.

[0029] In the above method, the samples are randomly divided into a modeling set and a prediction set. The near-infrared spectra of the samples in the modeling set are corresponded one by one with the detected transaminase content. Using the WINISI III chemometric software of FOSS company, first, the spectra are averaged, and the PCA (Principal Component Analysis) method is used for sample analysis. The processing methods of the spectra are: scatter correction and detrending, first-order derivative processing, and smoothing processing; independent component analysis. Independent Component Analysis (ICA: Independent Component Analysis), also known as independent component analysis method. ICA is a brand-new signal processing and data analysis method developed in the field of signal processing. In the theory of blind source separation, ICA removes the correlation of high-order statistics and adds a priori conditions, that is, there is at most one Gaussian signal in the source signals and the signals are statistically independent of each other. In the signal processing process, this priori condition is basically applicable to any different source signals. Therefore, ICA, as a new signal processing method, makes a single vector in space more localized, thus increasing the accuracy of recognition. ICA assumes that there are n mutually independent s(t) statistical source signals, and the observed signal x(t) is a linear combination of the components of the source signals. Here, t is time or can also be the sample label. Among them, A is an unknown non-singular mixing matrix.

[0030] The mathematical description of ICA is: x(t) = As(t)

[0031] Among them, column vector x(t) = [x1(t), x2(t), x3(t)]T, s(t) = [s1(t), s2(t), s3(t)]T. Another expression form of ICA is: y(t) = Wx(t)

[0032] Among them, column vector x(t) = [x1(t), x2(t), x3(t)]T, s(t) = [s1(t), s2(t), s3(t)]T

[0033] Through this matrix W, mutually independent signals y(t) are obtained, thereby obtaining the pulse wave source signal. The matrix W is also called the demixing matrix.

[0034] It can be known from the formula that if each row and each column in the matrix G has only one element closest to 1, and the other elements are all close to or equal to 0, the estimated signal at this time is also a relatively accurate estimate of the source signal s(t). In this way, it can be said that ICA has successfully separated the source signal. In practice, the separation matrix W can be adjusted to ensure the statistical independence of the source signals, further ensuring that the estimation of the source signals can be realized.

[0035] As an alternative implementation of this embodiment, a calibration model is established based on the MPLS method. The spectral range for modeling is selected as 300nm - 1000nm, and the spectral processing methods include inverse multi - variable discrete correction, second - derivative processing, and smoothing processing.

[0036] In this alternative implementation, the MPLS (Multi - Protocol Label Switching) method is used for modeling. The spectral range for modeling is selected as 300 - 1000nm, and the spectral processing methods include inverse multi - variable discrete correction, second - derivative processing, and smoothing processing to obtain the optimal near - infrared calibration model.

[0037] MPLS, namely Multi - Protocol Label Switching, is a new technology that uses labels to guide high - speed and efficient data transmission on an open communication network. The meaning of multi - protocol is that MPLS can not only support multiple network - layer protocols but also be compatible with various link - layer technologies at the second layer.

[0038] Here, FEC (Forwarding Equivalence Class) is an important concept in MPLS. MPLS is a classification - based forwarding technology that classifies packets with the same characteristics (such as the same destination or the same service level, etc.) into one category, called FEC. Packets belonging to the same FEC will receive exactly the same treatment in the MPLS network. Advantages of MPLS: 1) Cost. Network resources can be easily shared in MPLS because it is a layer - 3 technology. In addition, all customer data can be privately routed using MPLS; 2) Scalability. Scalability is an option that can be easily obtained in MPLS. It is much easier compared to other methods. MPLS can be expanded or contracted as needed. Even if thousands of sites are required; 3) Efficiency. MPLS provides a higher - quality connection without packet loss and jitter. Using it together with VoIP may improve efficiency. This means consistent performance can be achieved; 4) Reliability. There are various features that make MPLS reliable. Since MPLS uses labels to forward data packets, it can ensure that the data packets will be delivered to the correct destination. In addition, network traffic can be allocated according to priorities; 5) Bandwidth. MPLS allows multiple traffic flows to pass through the network. Moreover, different parts of the bandwidth can be allocated to various data types. This means that the bandwidth is optimally utilized. Through all these means, the bandwidth may increase.

[0039] Verify the near - infrared calibration model. Use the near - infrared camera that imports the samples of the prediction set to perform face video scanning on the calibration model to obtain the prediction results of the calibration model, and compare them with the detection values obtained in step A to verify the accuracy of the near - infrared calibration model.

[0040] As an optional implementation manner of this embodiment, comparing the infrared spectrogram with the reference infrared spectrogram to obtain a comparison result, and determining the transaminase content information based on the comparison result includes: calculating the similarity between the infrared spectrogram and the reference infrared spectrogram; calculating the local similarity between the infrared spectrogram and the reference infrared spectrogram in a specified interval; and determining the transaminase content information based on the similarity and the local similarity.

[0041] In this embodiment, a non-contact measurement method based on a face video is adopted to implement transaminase measurement, and the face video is used for image acquisition. It has non-invasiveness, is simpler than traditional methods, has a wider application range, and provides a new solution and scheme for non-contact physiological signal measurement. The accuracy of measuring transaminase by this method is relatively high, but there is a situation where the measurement accuracy in individual time windows is not high, which may be caused by factors such as face movement or environmental and light intensity changes, resulting in errors in the measurement results. The errors can be reduced by methods such as reducing face movement and selecting an environment with more uniform ambient light intensity. How to select or design a suitable filtering algorithm to maximize the removal of signal noise to improve the accuracy of non-contact transaminase measurement will become the next research goal.

[0042] It should be noted that the steps shown in the flowchart of the drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0043] According to an embodiment of the present invention, there is also provided a detection system for transaminase content information, including a near-infrared detection subsystem for emitting near-infrared to detect a human face; a processing subsystem for obtaining the collected face video information from the near-infrared detection subsystem and processing the face video information in a specified processing manner to obtain an infrared spectrogram; and using a calibration model to process the infrared spectrogram to obtain transaminase content information, wherein the reference infrared spectrogram corresponding to the infrared spectrogram is determined from a pre-established infrared spectrogram library; using the calibration model to compare the infrared spectrogram with the reference infrared spectrogram to obtain a comparison result, and determining the transaminase content information based on the comparison result.

[0044] As an optional implementation manner of this embodiment, comparing the infrared spectrogram with the reference infrared spectrogram to obtain a comparison result, and determining the transaminase content information based on the comparison result includes: calculating the similarity between the infrared spectrogram and the reference infrared spectrogram; calculating the local similarity between the infrared spectrogram and the reference infrared spectrogram in a specified interval; and determining the transaminase content information based on the similarity and the local similarity.

[0045] As an optional implementation manner of this embodiment, acquiring the collected face video information from the near-infrared imaging device and processing the face video information in a specified processing manner to obtain an infrared spectrogram includes: extracting the face area video in the form of RGB three-channel signals to obtain RGB three-channel signals; performing chromatic aberration method processing on the RGB three-channel signals to obtain spectral signals, and performing secondary processing on the spectral signals to obtain a dynamic infrared spectrogram of the transaminase content.

[0046] According to an embodiment of the present invention, the present invention also provides an electronic device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor can implement the method described in any of the above embodiments.

[0047] According to an embodiment of the present invention, the present invention also provides a readable storage medium, which stores computer instructions for enabling a computer to implement the method described in any of the above embodiments when executed.

[0048] According to an embodiment of the present invention, the present invention also provides a computer program product, which can implement the method described in any of the above embodiments when executed by a processor.

[0049] Figure 2 FIG. shows a schematic block diagram of an exemplary electronic device 300 that can be used to implement embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices.

[0050] As Figure 2 shown, the electronic device 300 includes a computing unit 301, which can execute various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 302 or a computer program loaded from a storage unit 308 into a random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0051] Multiple components in the electronic device 300 are connected to the I / O interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a magnetic disk, an optical disc, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the electronic device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0052] The computing unit 301 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 301 executes the various methods and processes described above, such as the object matching method. For example, in some embodiments, the object matching method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 308. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 300 via the ROM 302 and / or the communication unit 309. When the computer program is loaded into the RAM 303 and executed by the computing unit 301, one or more steps of the methods described above can be executed.

[0053] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs, which can be executed and / or interpreted on a programmable system including at least one programmable processor, the programmable processor can be a special or general-purpose programmable processor, can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0054] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowchart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, executed partially on the machine and partially on a remote machine as an independent software package, or executed entirely on a remote machine or server.

[0055] In the context of the present invention, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

Claims

1. A method for detecting transaminase content information, characterized in that: include: Acquire collected face video information from a near-infrared camera device, and process the face video information according to a specified processing method to obtain an infrared spectrum graph; The infrared spectrum is processed by using a calibration model to obtain transaminase content information, wherein a reference infrared spectrum corresponding to the infrared spectrum is determined from a pre-established infrared spectrum library; the infrared spectrum is compared with the reference infrared spectrum by using a calibration model to obtain a comparison result, and the transaminase content information is determined based on the comparison result.

2. The method for detecting transaminase content information according to claim 1, characterized in that: Comparing the infrared spectrum with the reference infrared spectrum to obtain a comparison result, and determining the transaminase content information based on the comparison result includes: Calculating the similarity between the infrared spectrum and the reference infrared spectrum; Calculating the local similarity between the infrared spectrum and the reference infrared spectrum in a specified interval; The transaminase content information is determined based on the similarity and the local similarity.

3. The method for detecting transaminase content information according to claim 1, characterized in that: Acquiring collected face video information from a near-infrared camera device, and processing the face video information in a specified processing manner to obtain an infrared spectrum diagram includes: Extract the face area video in RGB three-channel signal mode to obtain RGB three-channel signal; The RGB three-channel signal is processed by color difference method to obtain a spectral signal, and the spectral signal is processed twice to obtain a dynamic infrared spectrum of the transaminase content.

4. The method for detecting transaminase content information according to claim 1, characterized in that: When establishing the infrared spectrum library, the method comprises: Acquire a face video sample, and process the face video sample according to a specified processing method to obtain a dynamic infrared spectrum sample; Each infrared spectrum sample is matched to the pre-determined transaminase content one by one; and the infrared spectrum samples are subjected to spectral averaging and sample analysis to obtain infrared spectrum information.

5. The method for detecting transaminase content information according to claim 1, characterized in that: The calibration model was established based on the MPLS method. The spectral range of the model was selected as 300nm-1000nm. The spectral processing methods were inverse multivariate discrete correction, second-order derivative processing, and smoothing processing.

6. A system for detecting transaminase content information, characterized in that: include: A near infrared detection subsystem, used to emit near infrared to detect human faces; The processing subsystem is used to obtain the collected face video information from the near-infrared detection subsystem, and process the face video information according to a specified processing method to obtain an infrared spectrum; use a calibration model to process the infrared spectrum to obtain transaminase content information, wherein a reference infrared spectrum corresponding to the infrared spectrum is determined from a pre-established infrared spectrum library; use a calibration model to compare the infrared spectrum with the reference infrared spectrum to obtain a comparison result, and determine the transaminase content information based on the comparison result.

7. The detection system for transaminase content information according to claim 6, characterized in that: Comparing the infrared spectrum with the reference infrared spectrum to obtain a comparison result, and determining the transaminase content information based on the comparison result includes: Calculating the similarity between the infrared spectrum and the reference infrared spectrum; Calculating the local similarity between the infrared spectrum and the reference infrared spectrum in a specified interval; The transaminase content information is determined based on the similarity and the local similarity.

8. The detection system of transaminase content information according to claim 6, characterized in that: Acquiring collected face video information from a near-infrared camera device, and processing the face video information in a specified processing manner to obtain an infrared spectrum diagram includes: Extract the face area video in RGB three-channel signal mode to obtain RGB three-channel signal; The RGB three-channel signal is processed by color difference method to obtain a spectral signal, and the spectral signal is processed twice to obtain a dynamic infrared spectrum of the transaminase content.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method according to any one of claims 1 to 5.

10. An electronic device, characterized in that: include: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor executes the method described in any one of claims 1-5.

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