CN115824982A - An optical POCT color interpretation method, system and device - Google Patents

Abstract

The application provides an optical POCT color interpretation method, a system and a device, comprising the following steps: pre-establishing a standard curve between the pH value and the chromatic value; collecting the colorimetric value of the solution to be detected; and substituting the chromatic value of the solution to be detected into the standard curve to obtain the pH value of the solution to be detected. The optical POCT color interpretation method, the system and the device realize high-sensitivity and high-precision quantitative detection, and meet the application requirements of instant fixed-point detection of users; the anti-interference capability is strong, and the interference of factors such as ambient light on the detection process is effectively reduced; easy to integrate and calibrate, the requirements for the professional skills of the operator and the auxiliary equipment are greatly reduced.

Description

An optical POCT color interpretation method, system and device

technical field

The present application belongs to the technical field of optical detection, and in particular relates to an optical POCT color interpretation method, system and device.

Background technique

Point-of-care testing (POCT) is a type of testing method that can be analyzed immediately at the sampling site, eliminating the need for complex processing procedures during laboratory testing of specimens, and quickly obtaining test results. Since POCT can be performed on-site and greatly reduces test time and cost, it has received more and more attention in many aspects such as clinical diagnosis, food safety, and environmental testing.

The most common method of POCT is visual colorimetry. This method uses the eyes to compare the color depth of the test sample. It has the advantages of simple equipment and convenient operation. And low sensitivity, especially when colored interferences are present in the sample, it is difficult to distinguish analytes from interferences by visual colorimetry. Traditional optical detection equipment, such as spectrometers, are easily affected by external optical parameters, which have a great impact on the accuracy of detection results; at the same time, detection instruments are expensive, bulky, difficult to integrate and maintain, and difficult to apply to on-site real-time fixed-point detection .

At present, some optical detection methods have achieved semi-quantitative detection of samples through image acquisition tools and image processing software, such as digital image colorimetry (DIC). However, this type of method is easily affected by ambient light and reflections when collecting sample images, and there are color differences on different devices. On the one hand, it reduces the accuracy and sensitivity of sample detection, and on the other hand, it is only suitable for semi-quantitative detection of samples. , which cannot meet the needs of practical applications.

Contents of the invention

The purpose of this application is to provide an optical POCT color interpretation method, system and device, which are used to solve the technical problems of slow detection speed, low detection sensitivity and low accuracy of existing optical detection equipment.

In the first aspect, the present application provides an optical POCT color interpretation method, comprising the following steps:

A standard curve between the pH value and the chromaticity value is established in advance; the chromaticity value of the solution to be tested is collected; and the chromaticity value of the solution to be tested is substituted into the standard curve to obtain the pH value of the solution to be tested.

In this application, high-sensitivity and high-precision quantitative detection is realized, which meets the application requirements of users for real-time fixed-point.

In an implementation manner of the first aspect, pre-establishing a standard curve between the pH value and the chromaticity value includes the following steps:

Drop the standard solution on the test paper;

The standard solution has a definite pH value;

collecting images of the test paper;

obtaining channel components of the image;

calculating the combined value of the channel components to generate the chromaticity value of the standard solution;

The pH value and the colorimetric value were fitted to generate the standard curve.

In an implementation manner of the first aspect, pre-establishing a standard curve between the pH value and the chromaticity value includes calibrating the generated standard curve, and the calibration includes the following steps:

Extract the chromaticity value of the reference point of the color chart;

Substituting the chromaticity value of the reference point of the color comparison card into the standard curve to obtain the measured pH value of the reference point of the color comparison card;

calculating the offset of the measured pH value relative to the true pH value;

The standard curve is calibrated based on the offset.

In this implementation mode, it is easy to integrate and calibrate, and the requirements for professional skills of operators and auxiliary equipment are greatly reduced.

In an implementation manner of the first aspect, collecting the chromaticity value of the solution to be tested includes the following steps:

Drop the solution to be tested on the test paper;

collecting images of the test paper;

obtaining channel components of the image;

A combined value of the channel components is calculated to generate a chromaticity value of the solution to be tested.

In an implementation manner of the first aspect, collecting the image of the test paper includes preprocessing the image of the test paper, and the preprocessing includes the following steps:

Denoising the image of the test paper;

performing image enhancement on the image after denoising;

Image segmentation is performed on the enhanced image.

In this implementation manner, the anti-interference ability is strong, and the interference of factors such as ambient light on the detection process is effectively reduced.

In an implementation manner of the first aspect, acquiring the channel components of the image includes the following steps:

Determine the sample area of the test paper;

The channel components of the image are extracted in the sample area of the test paper.

In an implementation of the first aspect, the combined value of the channel components is calculated using the formula N=r+g-b; wherein r represents the red channel component of the image; g represents the green channel component of the image; b represents the blue color of the image channel component; N represents the combined calculation value of the channel component.

In the second aspect, the present application provides an optical POCT color interpretation system, including:

Fitting module, used to pre-establish the standard curve between pH value and chromaticity value;

The collection module is used to collect the chromaticity value of the solution to be tested;

The detection module is used for substituting the chromaticity value of the solution to be tested into the standard curve to obtain the pH value of the solution to be tested.

In an implementation manner of the second aspect, an interaction module is also included, configured to implement any one or more of the following functions:

Control the start and close of test strip image acquisition;

Display the collected test strip image;

Displays the pH value of the solution to be tested.

In a third aspect, the present application provides an optical POCT color interpretation device, which is characterized in that it includes: a processor and a memory;

The memory is used to store computer programs;

The processor is configured to execute the computer program stored in the memory, so that the optical POCT color interpretation device executes the optical POCT color interpretation method described in any one of the above.

As mentioned above, the optical POCT color interpretation method, system and device described in this application have the following beneficial effects:

(1) It realizes high sensitivity and high precision quantitative detection, which meets the application requirements of users for real-time fixed-point detection;

(2) Strong anti-interference ability, effectively reducing the interference of environmental light and other factors on the detection process;

(3) It is easy to integrate and calibrate, and the requirements for the professional skills of operators and auxiliary equipment are greatly reduced.

Description of drawings

Fig. 1 is a flow chart of the optical POCT color interpretation method described in the embodiment of the present application.

Fig. 2 is a flow chart of the pre-established standard curve between pH value and chromaticity value in the optical POCT color interpretation method described in the embodiment of the present application.

FIG. 3 is a schematic diagram of a standard curve fitted by the optical POCT color interpretation method described in the examples of the present application.

Fig. 4 is a schematic structural diagram of the optical POCT color interpretation system described in the embodiment of the present application.

Fig. 5 is a schematic diagram showing the structure of the optical POCT color interpretation device described in the embodiment of the present application.

Component designation description

4 Optical POCT color interpretation system

41 Fitting Module

42 acquisition module

43 detection module

44 interactive modules

5 Optical POCT color interpretation device

51 processors

52 memory

53 Multimedia components

54 I/O interface

55 Communication components

S1～S3 method steps

S11～S15 method steps

Detailed ways

Embodiments of the present application are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the content disclosed in this specification. The present application can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, in the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.

It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic idea of the application, and only the components related to the application are shown in the diagrams rather than the number, shape and Dimensional drawing, the type, quantity and proportion of each component can be changed arbitrarily during actual implementation, and the component layout type may also be more complicated.

In addition, descriptions such as "first", "second" and so on in this application are only for description purposes, and should not be understood as indicating or implying their relative importance or implicitly indicating the number of indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include at least one of these features. In addition, the technical solutions of the various embodiments can be combined with each other, but it must be based on the realization of those skilled in the art. When the combination of technical solutions is contradictory or cannot be realized, it should be considered that the combination of technical solutions does not exist , nor within the scope of protection required by the present application.

The following embodiments of the present application provide an optical POCT color interpretation method, system and device, which can be applied to optical detection equipment, including but not limited to automatic pH detectors. When the user needs to obtain the pH value of the solution to be tested, just put the test paper titrated with the solution to be tested into the pH automatic detector, press the corresponding button option in the GUI interface, and the test result will be automatically displayed on the screen.

As shown in Figure 1, this embodiment provides an optical POCT color interpretation method, including the following steps:

S1. Establish a standard curve between the pH value and the chromaticity value in advance.

As shown in Figure 2, in one embodiment, the pre-established standard curve between the pH value and the chromaticity value comprises the following steps:

S11. Drop the standard solution on the test paper; the standard solution has a definite pH value.

Specifically, after fixing the test paper, first use a glass rod to stir the standard solution evenly, then use a burette to dip an appropriate amount of standard solution, and titrate it onto the pH test paper, and wait until the color of the pH test paper no longer changes.

In order to establish an accurate standard curve, eight groups of standard solutions are used in this embodiment, and the eight groups of standard solutions correspond to eight pH values such as 5.5, 6.0, 6.5, 7.0, 7.5, 8.0, 8.5 and 9.0, respectively. Different pH values The standard solution can be measured and configured with the help of a high-precision pH meter.

S12. Collect images of the test paper.

Specifically, considering the influence of factors such as ambient light, shooting angle, and shooting height on the image acquisition process, this application set up the camera on the top of the darkroom, fixed the test paper in the slot on the bottom platform of the darkroom, and the vertical distance between the camera and the test paper In order to fix 3cm, there are 45-degree inclined LED lights on both sides of the camera, which are used to provide evenly distributed light sources for the camera. The camera shoots directly at the test strip from top to bottom to ensure that the image of the test paper has a good image quality. Imaging area and focus effect.

In one embodiment, collecting the image of the test paper includes preprocessing the image of the test paper, and the preprocessing includes the following steps:

(1) Denoising the image of the test paper.

Specifically, a fast median filtering algorithm is used to perform denoising processing on the image of the test paper. For example, assuming that the test paper image X with pixels m×n is collected, it is used as the input of the fast median filtering algorithm, and the kernel radius is set to r, and the pseudo code of the fast median filtering algorithm is run as follows to obtain the same A denoised image Y of the same size as the test paper image X.

Where H is the kernel histogram of the image, and the time consumption of the entire filtering process depends on the calculation of the image bit depth, and has nothing to do with the kernel radius r. Image filtering is an essential process in image preprocessing, which will have a direct impact on the reliability and effectiveness of subsequent image processing and analysis. The fast median filtering algorithm can effectively suppress image noise while trying to preserve the original feature information of the image, making the image look closer to the image before being polluted.

(2) Perform image enhancement on the denoised image.

The image after filtering or denoising is affected by environmental light intensity and other factors during acquisition, which may cause the overall range of the test paper to appear dark in the area where the color reaction occurs after being immersed in the solution to be tested. The image is subjected to image enhancement processing. Specifically, a linear transformation is used to enhance the contrast of the image.

(3) Perform image segmentation on the enhanced image.

Specifically, the K-means edge detection algorithm is used to segment the image. The K-means edge detection algorithm first classifies according to the central point, and calculates the Euclidean distance from each point to the central point through the coordinate μ _k of the central point, and classifies this point into the class c ^(k) to which the shortest distance from the central point belongs, so that All points are divided into K classes. Then move the center point according to the classification, calculate the mean value of the one-dimensional coordinates of all points of this type as the new center point μ _k , and enter the next cycle, so as to automatically detect the sample area of interest.

Using the K-means clustering algorithm to repeatedly initialize the cluster center point coordinates μ ₁ , μ ₂ , μ ₃ … μ _k ∈ R ⁿ , the specific execution pseudo code is as follows:

S13. Acquire channel components of the image.

Specifically, the channel components of the image include red channel components, green channel components and blue channel components of the image in RGB mode. The colors in the image are made by mixing red, green and blue colors in different proportions. The RGB value represents the brightness of the three colors, and the value is [0,255]. Extracting the channel components of the eight groups of standard solution test paper images includes automatically traversing each pixel on each of the test paper images, obtaining the r, g, and b values of each pixel, and then calculating the average r value of all pixels value, the average value of g value and the average value of b value, if any one of r, g, and b of a certain pixel point is greater than 245, the pixel point will be considered as a reflective point and deleted, and will not participate in the calculation of the average value.

The components of each channel are shown in Table 1.

Table 1. Channel components of different pH standard solution test paper images

In one embodiment, obtaining the channel components of the image includes the following steps:

Determine the sample area of the test paper; extract the channel components of the image in the sample area of the test paper.

Due to some reasons, not all of the pH test paper may change color, but only a small part of it, so it is necessary to mark the area of the color reaction. Specifically, on the collected test paper image, select an appropriate point, obtain the abscissa x ₁ and ordinate y ₁ of the point, and then select another point, and you can also know its abscissa and ordinate values x ₂ and y ₂ . With (x ₁ , y ₁ ) and (x ₂ , y ₂ ) as the diagonal vertices, cut out a rectangular area graph with a length of x ₁ -x ₂ and a width of y ₁ -y ₂ , which is used as the test paper the sample area.

In addition, the sample area of the test paper can also be a designated area delineated on the test paper. When the standard solution is dropped on the test paper, the standard solution will be dropped on the designated area delineated on the test paper, and then the designated area will be extracted. The channel components of the image within the region.

S14. Calculate the combined value of the channel components to generate the chromaticity value of the standard solution.

As shown in Table 2, in one embodiment, the combined value of the channel components is calculated using the formula N=r+g-b; wherein r represents the red channel component of the image; g represents the green channel component of the image; b represents the blue color of the image Color channel components; N represents the combined calculation value of the channel components.

Table 2. Channel components and combined values of different pH standard solution test paper images

S15. Fitting the pH value and the chromaticity value to generate the standard curve.

Through the above steps S11-S14, the set of sample points (N _i ,pH _i ) can be obtained, where N _i represents the channel component combination value (or chromaticity value) corresponding to the i-th standard solution, and pH _i represents the i-th standard solution The actual pH value of , i∈[1,8]. For example, the channel component combination value corresponding to the fourth standard solution is 115.7, and the actual pH value of the fourth standard solution is 7.0.

As shown in Figure 3, a ternary polynomial is used to fit the sample point set (N _i ,pH _i ) to establish the standard curve: pH=9.91-0.08N+9.86×10 ⁻⁴ N ² −5.58×10 ^-6 N ³ , where the correlation coefficient R ² =0.99.

It should be noted that the fitting of the pH value and the chromaticity value can use linear fitting or nonlinear fitting, which can be determined according to the type of reactant and the required detection range; When appropriate, the order setting of polynomial fitting can be adjusted according to the number of sample points, which is not limited here.

In one embodiment, pre-establishing a standard curve between the pH value and the chromaticity value includes calibrating the generated standard curve, and the calibration includes the following steps:

Extract the chromaticity value of the reference point of the color comparison card; Substitute the chromaticity value of the reference point of the color comparison card into the standard curve to obtain the measured pH value of the reference point of the color comparison card; Calculate the relative pH value of the measured pH value The offset from the real pH value; the standard curve is calibrated based on the offset to prevent errors in the final result caused by errors in color testing.

In this implementation mode, it is easy to integrate and calibrate, realizes high-sensitivity and high-precision quantitative detection, and meets the application requirements of users for real-time fixed-point detection.

S2. Collect the chromaticity value of the solution to be tested.

In one embodiment, collecting the chromaticity value of the solution to be tested comprises the following steps:

S21. Drop the solution to be tested on the test paper.

Specifically, after fixing the test paper, first use a glass rod to stir the solution to be tested evenly, then use a burette to dip an appropriate amount of the solution to be tested, and titrate it onto the pH test paper, and wait until the color of the pH test paper no longer changes.

S22. Collecting images of the test paper.

Similarly, considering the impact of factors such as ambient light, shooting angle, and shooting height on the image acquisition process, this application sets up the camera on the top of the darkroom, fixes the test paper in the slot on the bottom platform of the darkroom, and the vertical distance between the camera and the test paper In order to fix 3cm, there are 45-degree inclined LED lights on both sides of the camera, which are used to provide evenly distributed light sources for the camera. The camera shoots directly at the test strip from top to bottom to ensure that the image of the test paper has a good image quality. Imaging area and focus effect.

In one embodiment, collecting the image of the test paper includes preprocessing the image of the test paper, and the preprocessing includes the following steps:

(1) Denoising the image of the test paper.

Specifically, a fast median filtering algorithm is used to perform denoising processing on the image of the test paper. For example, assuming that the test paper image X with pixels m×n is collected, it is used as the input of the fast median filtering algorithm, and the kernel radius is set to r, and the pseudo code of the fast median filtering algorithm is run as follows to obtain the same A denoised image Y of the same size as the test paper image X.

Where H is the kernel histogram of the image, and the time consumption of the entire filtering process depends on the calculation of the image bit depth, and has nothing to do with the kernel radius r. Image filtering is an essential process in image preprocessing, which will have a direct impact on the reliability and effectiveness of subsequent image processing and analysis. The fast median filtering algorithm can effectively suppress image noise while trying to preserve the original feature information of the image, making the image look closer to the image before being polluted.

(2) Perform image enhancement on the denoised image.

The image after filtering or denoising is affected by environmental light intensity and other factors during acquisition, which may cause the overall range of the test paper to appear dark in the area where the color reaction occurs after being immersed in the solution to be tested. The image is subjected to image enhancement processing. Specifically, a linear transformation is used to enhance the contrast of the image.

(3) Perform image segmentation on the enhanced image.

Specifically, the K-means edge detection algorithm is used to segment the image. The K-means edge detection algorithm first classifies according to the central point, and calculates the Euclidean distance from each point to the central point through the coordinate μ _k of the central point, and classifies this point into the class c ^(k) to which the shortest distance from the central point belongs, so that All points are divided into K classes. Then move the center point according to the classification, calculate the mean value of the one-dimensional coordinates of all points of this type as the new center point μ _k , and enter the next cycle, so as to automatically detect the sample area of interest.

Using the K-means clustering algorithm to repeatedly initialize the cluster center point coordinates μ ₁ , μ ₂ , μ ₃ … μ _k ∈ R ⁿ , the specific execution pseudo code is as follows:

In this implementation manner, the anti-interference ability is strong, and the interference of factors such as ambient light on the detection process is effectively reduced.

S23. Acquire channel components of the image.

Specifically, the channel components of the image include red channel components, green channel components and blue channel components of the image in RGB mode. The colors in the image are made by mixing red, green and blue colors in different proportions. The RGB value represents the brightness of the three colors, and the value is [0,255]. Extracting the channel components of the test paper image of the solution to be tested includes automatically traversing each pixel on the test paper image of the solution to be tested, obtaining the r, g, and b values of each pixel, and then calculating the average value of r and g of all pixels The average value and the average value of b. If any one of r, g, and b of a certain pixel point is greater than 245, the pixel point will be considered as a reflective point and deleted, and will not participate in the calculation of the average value.

In one embodiment, obtaining the channel components of the image includes the following steps:

Determine the sample area of the test paper; extract the channel components of the image in the sample area of the test paper.

Due to some reasons, not all of the pH test paper may change color, but only a small part of it, so it is necessary to mark the area of the color reaction. Specifically, on the collected test paper image, select an appropriate point, obtain the abscissa x ₁ and ordinate y ₁ of the point, and then select another point, and you can also know its abscissa and ordinate values x ₂ and y ₂ . With (x ₁ , y ₁ ) and (x ₂ , y ₂ ) as the diagonal vertices, cut out a rectangular area graph with a length of x ₁ -x ₂ and a width of y ₁ -y ₂ , which is used as the test paper the sample area.

In addition, the sample area of the test paper can also be a designated area delineated on the test paper, when the solution to be tested is dropped on the test paper, the solution to be tested will be dropped on the designated area delimited on the test paper, and then the The channel components of the image in the specified area.

S24. Calculate the combined value of the channel components to generate the chromaticity value of the solution to be tested.

In one embodiment, the combined value of the channel components is calculated using the formula N=r+g-b; wherein r represents the red channel component of the image; g represents the green channel component of the image; b represents the blue channel component of the image; N represents The combined computed value of the channel components.

S3. Substituting the chromaticity value of the solution to be tested into the standard curve to obtain the pH value of the solution to be tested.

Specifically, the chromaticity value N of the solution to be tested obtained in step S24 is substituted into the standard curve pH=9.91-0.08N+9.86×10 ^-4 N ² -5.58×10 ^-6 N ³ to obtain the The pH of the solution. The scope of protection of the optical POCT color interpretation method described in the embodiment of this application is not limited to the execution order of the steps listed in this embodiment. Included in the scope of protection of this application.

As shown in Figure 4, this embodiment provides an optical POCT color interpretation system 4, including:

Fitting module 41, is used for establishing the standard curve between pH value and chromaticity value in advance;

Acquisition module 42, for collecting the chromaticity value of the solution to be tested;

A detection module 43, configured to substitute the chromaticity value of the solution to be tested into the standard curve to obtain the pH value of the solution to be tested.

It should be noted that the structures and principles of the fitting module 41 , the collection module 42 and the detection module 43 correspond to the steps and embodiments of the above-mentioned optical POCT color interpretation method, so they will not be repeated here.

In one embodiment, the optical POCT color interpretation system described in this embodiment further includes an interactive module 44, configured to implement any one or more of the following functions:

(1) Control the start and close of test paper image acquisition;

(2) Display the collected test paper image;

(3) displaying the pH value of the solution to be tested.

The interaction module is provided with the above-mentioned function buttons, and the user can perform a touch operation through a graphical interface (GUI) when selecting a corresponding function option. The operation process is simple and convenient, and the requirements for the professional skills of operators and auxiliary equipment are greatly reduced.

The optical POCT color interpretation system provided in the embodiment of this application can realize the optical POCT color interpretation method described in this application, but the realization device of the optical POCT color interpretation method described in this application includes but is not limited to the optical POCT color interpretation method listed in this embodiment As for the structure of the interpretation system, all structural deformations and replacements in the prior art based on the principles of the present application are included in the scope of protection of the present application.

This embodiment provides an optical POCT color interpretation device 5, including: a processor 51 and a memory 52;

The memory 52 is used to store computer programs;

The processor 51 is configured to execute the computer program stored in the memory, so that the optical POCT color interpretation device executes the optical POCT color interpretation method described in any one of the above.

Fig. 5 shows a structural block diagram of an optical POCT color interpretation device. The device includes a processor 51 and a memory 52 , and also includes one or more of a multimedia component 53 , an input/output (I/O) interface 54 , and a communication component 55 .

Preferably, the processor 51 may be a general-purpose processor, including a central processing unit (Central Processing Unit, referred to as CPU), a network processor (Network Processor, referred to as NP), etc.; it may also be a digital signal processor (Digital Signal Processor, referred to as DSP), Application Specific Integrated Circuit (ASIC for short), Field Programmable Gate Array (Field Programmable Gate Array, FPGA for short) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The memory 52 can be realized by any type of volatile or non-volatile storage device or their combination, such as Static Random Access Memory (Static Random Access Memory, SRAM), Electrically Erasable Programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), Erasable Programmable Read-Only Memory (Erasable Programmable Read-Only Memory, EPROM), Programmable Read-Only Memory (Programmable Read-Only Memory, PROM), Read-Only Memory (Read-Only Memory, Only Memory, ROM), magnetic memory, flash memory, magnetic disk or optical disk.

Multimedia components 53 may include screen and audio components. The screen can be, for example, a touch screen, and the audio component is used for outputting and/or inputting audio signals. For example, an audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in memory 52 or sent via communication component 55 . The audio component also includes at least one speaker for outputting audio signals. The I/O interface 54 provides an interface between the processor 51 and other interface modules, which may be a keyboard, a mouse, buttons, and the like. These buttons can be virtual buttons or physical buttons. The communication component 55 is used for wired or wireless communication between the optical POCT color interpretation device 5 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, near field communication (Near Field Communication, NFC for short), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 55 may include: Wi-Fi module, Bluetooth module, NFC module.

In one embodiment, the optical POCT color interpretation device 5 can be implemented by one or more application-specific integrated circuits (Application Specific Integrated Circuit, ASIC), digital signal processor (Digital Signal Processor, DSP), digital signal processing equipment (Digital Signal Processing Device, DSPD), Programmable Logic Device (Programmable Logic Device, PLD), Field Programmable Gate Array (Field ProgrammableGate Array, FPGA), controller, microcontroller, microprocessor or other electronic components to implement the above Optical POCT color interpretation method.

In the several embodiments provided in this application, it should be understood that the disclosed system, device or method may be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of modules/units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple modules or units can be combined or May be integrated into another system, or some features may be ignored, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or modules or units may be in electrical, mechanical or other forms.

A module/unit described as a separate component may or may not be physically separate, and a component shown as a module/unit may or may not be a physical module, that is, it may be located in one place, or it may be distributed to multiple network units superior. Part or all of the modules/units may be selected according to actual needs to achieve the purpose of the embodiments of the present application. For example, each functional module/unit in each embodiment of the present application may be integrated into one processing module, each module/unit may exist separately physically, or two or more modules/units may be integrated into one module/unit in the unit.

Those of ordinary skill in the art should further realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the hardware and software interchangeability, the composition and steps of each example have been generally described in terms of functions in the above description. Whether these functions are executed by hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present application.

The embodiment of the present application also provides a computer-readable storage medium. Those of ordinary skill in the art can understand that all or part of the steps in the method for implementing the above embodiments can be completed by instructing the processor through a program, and the program can be stored in a computer-readable storage medium, and the storage medium is non-transitory (non-transitory) media, such as random access memory, read-only memory, flash memory, hard disk, solid-state disk, magnetic tape, floppy disk, optical disc, and any combination thereof. The above-mentioned storage medium may be any available medium that can be accessed by a computer, or a data storage device such as a server or a data center integrated with one or more available media. The available medium may be a magnetic medium (such as a floppy disk, a hard disk, or a magnetic tape), an optical medium (such as a digital video disc (digital video disc, DVD)), or a semiconductor medium (such as a solid state disk (solid state disk, SSD)), etc.

The embodiment of the present application may also provide a computer program product, where the computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on the computing device, the processes or functions according to the embodiments of the present application will be generated in whole or in part. The computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, e.g. (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.) to another website site, computer or data center.

When the computer program product is executed by a computer, the computer executes the methods described in the foregoing method embodiments. The computer program product may be a software installation package, and the computer program product may be downloaded and executed on a computer if the foregoing method needs to be used.

The description of the process or structure corresponding to each of the above drawings has its own emphasis. For the part that is not described in detail in a certain process or structure, you can refer to the relevant description of other processes or structures.

In summary, the optical POCT color interpretation method, system and device described in this application solve the problems of slow detection, susceptibility to ambient light interference, low detection sensitivity and accuracy, and large detection equipment in existing optical detection equipment. , high cost, and high requirements for the professional skills of operators, it realizes high-sensitivity and high-precision quantitative detection, which meets the application requirements of users for instant fixed-point detection; strong anti-interference ability, effectively reduces the impact of environmental light and other factors on the detection process interference; easy to integrate and calibrate, and greatly reduce the requirements for the operator's professional skills and auxiliary equipment.

The above-mentioned embodiments are only illustrative to illustrate the principles and effects of the present application, but are not intended to limit the present application. Any person familiar with the technology can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by those skilled in the art without departing from the spirit and technical ideas disclosed in the application shall still be covered by the claims of the application.

Claims (10)

1. An optical POCT color interpretation method is characterized by comprising the following steps:

pre-establishing a standard curve between the pH value and the chromatic value;

collecting the colorimetric value of the solution to be detected;

and substituting the chromatic value of the solution to be detected into the standard curve to obtain the pH value of the solution to be detected.

2. The optical POCT color interpretation method of claim 1, wherein pre-establishing a standard curve between pH and chromaticity values comprises the steps of:

dropping the standard solution on the test paper; the standard solution has a defined pH value;

collecting an image of the test paper;

acquiring a channel component of the image;

calculating a combined value of the channel components to generate a colorimetric value of the standard solution;

fitting the pH values and the colorimetric values to generate the standard curve.

3. The optical POCT color interpretation method of claim 1, wherein pre-establishing a standard curve between pH and chroma values comprises calibrating the generated standard curve, the calibrating comprising the steps of:

extracting the chromatic value of the reference point of the colorimetric card;

substituting the chromatic value of the reference point of the color comparison card into the standard curve to obtain the measured pH value of the reference point of the color comparison card;

calculating the offset of the measured pH value relative to the real pH value;

calibrating the standard curve based on the offset.

4. The optical POCT color interpretation method of claim 1, wherein the step of collecting the colorimetric values of the solution to be tested comprises the steps of:

dripping the solution to be detected on the test paper;

collecting an image of the test paper;

acquiring a channel component of the image;

and calculating the combined value of the channel components to generate a chromatic value of the solution to be detected.

5. The optical POCT color interpretation method according to claims 2 and 4, wherein acquiring the image of the test strip comprises pre-processing the image of the test strip, the pre-processing comprising the steps of:

denoising the image of the test paper;

carrying out image enhancement on the denoised image;

and carrying out image segmentation on the enhanced image.

6. The optical POCT color interpretation method according to claims 2 and 4, wherein acquiring the channel components of the image comprises the steps of:

determining a sample area of the test paper;

and extracting a channel component of the image in a sample area of the test paper.

7. The optical POCT color interpretation method according to claims 2 and 4, wherein the combined value of the channel components is calculated using the formula N = r + g-b; where r represents the red channel component of the image; g represents a green channel component of the image; b represents a blue channel component of the image; n represents a combined calculation value of the channel components.

8. An optical POCT color interpretation system, comprising:

the fitting module is used for establishing a standard curve between the pH value and the chromatic value in advance;

the acquisition module is used for acquiring the colorimetric value of the solution to be detected;

and the detection module is used for substituting the chromatic value of the solution to be detected into the standard curve so as to obtain the pH value of the solution to be detected.

9. The optical POCT color interpretation system of claim 8, further comprising an interaction module for performing any one or more of the following functions:

controlling the starting and closing of the test paper image acquisition;

displaying the collected test paper image;

and displaying the pH value of the solution to be detected.

10. An optical POCT color interpretation device, comprising: a processor and a memory;

the memory is used for storing a computer program;

the processor is configured to execute the computer program stored in the memory to cause the optical POCT color interpretation apparatus to perform the optical POCT color interpretation method of any one of claims 1 to 7.

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