Ear point positioning method, positioning device and storage medium

Abstract

The application provides an auricular point positioning method, a positioning device and a storage medium, and comprises the following steps: acquiring a human ear image; detecting the human ear image based on a pre-established auricular point detection model to label a physiological structure region on the human ear image; analyzing the physiological structure region to obtain distribution points of each auricular point to obtain an ear sticker navigation map; and enabling a user to apply an ear sticker on a target auricular point according to the ear sticker navigation map. In the application, the positions of standard defined auricular points are accurately found in different ears by combining AI technology. The auricular point positioning is convenient to use, and the knowledge and experience requirements of the user are greatly reduced. The traditional medicine and AI are combined, the auricular point knowledge can be more accurately inherited, and the ear sticker correction function helps the user to accurately use the ear sticker, and the treatment effect is guaranteed.

Description

Technical Field

[0001] This application relates to the field of auricular therapy, specifically to a method, device, and storage medium for locating auricular acupoints. Background Technology

[0002] Auricular acupuncture is a treasure of Traditional Chinese Medicine. Both GB / T 13734-2008 (Nomenclature and Location of Auricular Acupuncture Points) and the WHO International Standard Acupuncture Points provide standardized locations for auricular acupuncture points. While the physiological structure of the ears is generally the same across individuals, differences in shape can make it difficult for practitioners to accurately locate acupuncture points, thus affecting treatment efficacy.

[0003] Therefore, overcoming the shortcomings of the existing technology is an urgent problem to be solved in this technical field. Summary of the Invention

[0004] The main technical problem addressed in this application is to provide a method, device, and storage medium for locating auricular acupoints, which combines traditional medicine with AI to facilitate more accurate transmission of auricular acupoint knowledge. The ear patch correction function helps users use the ear patch accurately, ensuring the therapeutic effect.

[0005] To solve the above-mentioned technical problems, one technical solution adopted in this application is: to provide a method for locating ear acupoints, including:

[0006] Acquire an image of a human ear;

[0007] The human ear image is detected based on a pre-established auricular acupoint detection model to mark the physiological structure region on the human ear image.

[0008] The distribution points of each acupoint are obtained by analyzing the physiological structure region to obtain the ear patch navigation map;

[0009] This allows users to apply ear patches to target acupoints according to the ear patch navigation map.

[0010] Furthermore, it also includes:

[0011] Get the initial ear patch image with the ear patch already applied;

[0012] The ear patch navigation map is compared and analyzed with the initial ear patch image to determine whether the ear patch can cover the target acupoint;

[0013] If at least one ear patch does not cover the target acupoint, mark the corresponding offset ear patch on the initial ear patch image;

[0014] The corresponding correction method is determined based on the ear patch navigation map, so that the user can adjust the position of the offset ear patch based on the correction method.

[0015] Furthermore, determining the corresponding correction method based on the ear patch navigation map includes:

[0016] The offset ear patch is mapped onto the ear patch navigation map using an image mapping method, and the positional relationship between the ear patch virtual frame and the corresponding target acupoint is detected. The correction method of the offset ear patch is determined based on the positional relationship.

[0017] Furthermore, the physiological structural regions include: helix, scaphoid fossa, triangular fossa, antihelix, earlobe, tragus or antitragus.

[0018] Furthermore, the analysis of the physiological structural region to obtain the distribution points of each acupoint, in order to obtain the ear patch navigation map, includes:

[0019] Acquire the triangular fossa, helix, and antiauricular fossa;

[0020] The distal end of the triangular fossa is obtained by analyzing the triangular fossa and the helix.

[0021] The bifurcation point of the antihelix is ​​obtained by analyzing the antiauricular cavity;

[0022] The Shenmen acupoint is obtained based on the distal end point and the bifurcation point.

[0023] Furthermore, the step of analyzing the triangular fossa and the helix to obtain the distal end of the triangular fossa includes:

[0024] Obtain the first set of pixels of the triangular fossa, and delete the target pixels that meet the preset conditions from the first set of pixels to obtain the second set of pixels after slimming down;

[0025] The second set of pixels is filtered to obtain a first foreground point and a first background point. The first connecting region of the triangular fossa is obtained based on the first foreground point.

[0026] Calculate the distance between the first foreground point contained in the first connecting region and the center of the helix, and set the first foreground point with the largest distance as the far endpoint.

[0027] Furthermore, analysis of the antiauricular cavity reveals the bifurcation point of the antihelix, including:

[0028] Obtain the third set of pixels of the antiauricular cavity, and delete the target pixels that meet the preset conditions from the third set of pixels to obtain the fourth set of pixels after slimming down;

[0029] The fourth pixel set is filtered to obtain the second foreground point and the second background point. The second connecting region of the antiauricular cavity is obtained based on the second foreground point.

[0030] The foreground point with the largest y-coordinate value in the second connected region is the bifurcation point of the antihelix.

[0031] Further, obtaining the Shenmen acupoint based on the distal end point and the bifurcation point includes:

[0032] Calculate the perpendicular bisector of the distal end of the triangular fossa and the bifurcation point of the antihelix. Calculate the set of intersection points of the perpendicular bisector with the edge of the triangular fossa. Traverse the set of intersection points, and the uppermost point is the Shenmen acupoint.

[0033] To solve the above-mentioned technical problems, one technical solution adopted in this application is: to provide an ear patch positioning device, including: one or more processors;

[0034] Memory; and

[0035] One or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the processor to implement the methods described in this application.

[0036] To solve the above-mentioned technical problems, one technical solution adopted in this application is to provide a computer-readable storage medium, characterized in that a computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in the method described in this application.

[0037] The beneficial effects of this application are as follows: This application provides a method, device and storage medium for locating acupoints in the ear, including acquiring an image of a human ear; detecting the human ear image based on a pre-established acupoint detection model to mark physiological structural regions on the human ear image; analyzing the physiological structural regions to obtain the distribution points of each acupoint to obtain an ear patch navigation map; so that the user can apply ear patches to the target acupoints according to the ear patch navigation map.

[0038] This application combines AI technology to accurately locate standardized acupoints on different ears; the acupoint location is easy to use, greatly reducing the knowledge and experience requirements for users. Combining traditional medicine with AI facilitates more accurate transmission of auricular acupoint knowledge, and the ear patch correction function helps users use the ear patch accurately, ensuring treatment effectiveness. Attached Figure Description

[0039] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments of this application will be briefly described below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1This is a flowchart illustrating a method for locating auricular acupoints according to an embodiment of this application;

[0041] Figure 2 This is a schematic diagram of the structure of a positioning device for an ear patch according to an embodiment of this application. Detailed Implementation

[0042] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0043] In the description of this application, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are used only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include one or more features. In the description of this application, "a plurality of" means two or more, unless otherwise explicitly specified.

[0044] In this application, the term "exemplary" is used to mean "used as an example, illustration, or description." Any embodiment described as "exemplary" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use this application. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that this application can be made without using these specific details. In other instances, well-known structures and processes are not described in detail to avoid obscuring the description of this application with unnecessary detail. Therefore, this application is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0045] It should be noted that since the method in this application embodiment is executed in an electronic device, the processing objects of each electronic device exist in the form of data or information, such as time, which is essentially time information. It can be understood that if size, quantity, position, etc. are mentioned in subsequent embodiments, they are all corresponding data that exist so that the electronic device can process them. Specific details will not be elaborated here.

[0046] Example 1:

[0047] This embodiment provides a method for locating ear acupoints, including:

[0048] S101: Acquire an image of a human ear;

[0049] In this embodiment, an image of a human ear can be acquired using an image acquisition component.

[0050] S102: Detect the human ear image based on a pre-established auricular acupoint detection model to mark the physiological structure region on the human ear image;

[0051] In this embodiment, a large number of sample images can be collected in advance, and an ear acupoint detection model can be established based on the sample images.

[0052] The physiological structural regions include: helix, scaphoid fossa, triangular fossa, antihelix, earlobe, tragus or antitragus.

[0053] S103: Analyze the physiological structure region to obtain the distribution points of each acupoint, so as to obtain the ear patch navigation map;

[0054] S104: so that the user applies ear patches to the target acupoints according to the ear patch navigation map.

[0055] In this embodiment, the external ear physiological structure is analyzed using AI technology and a large number of samples. Data is analyzed to interpret the physiological structures of the external ear, including the helix, scaphoid fossa, triangular fossa, antihelix, earlobe, tragus, antitragus, and intertragic notch. The ear acupoint data is then calculated by combining the ear physiological structure data with standard-defined acupoint locations and a CV algorithm.

[0056] In this embodiment, ear patches are applied to the target acupoints according to the ear patch navigation map. Then, an initial ear patch image with the ear patches applied is obtained. The ear patch navigation map is compared and analyzed with the initial ear patch image to determine whether the ear patches can cover the target acupoints. If at least one ear patch does not cover the target acupoint, the corresponding offset ear patch is marked on the initial ear patch image. And a corresponding correction method is determined according to the ear patch navigation map so that the user can adjust the position of the offset ear patch based on the correction method.

[0057] In this embodiment, during ear patch calibration, rotation, scaling, stretching, and other processing are used to overlap the images, and then it is determined whether the acupoints are covered by the ear patch. If they are not covered, the corresponding acupoints are marked to facilitate user adjustment.

[0058] In an optional embodiment, determining the corresponding correction method based on the ear patch navigation map includes: mapping the offset ear patch onto the ear patch navigation map as an ear patch virtual frame using image mapping, detecting the positional relationship between the ear patch virtual frame and the corresponding target acupoint, and determining the correction method for the offset ear patch based on the positional relationship.

[0059] In practical applications, the model is called to obtain the basic structure of the triangular fossa, helix, and antihelix. The distal end of the triangular fossa is calculated, the bifurcation point of the antihelix is ​​calculated, the perpendicular bisector of the distal end of the triangular fossa and the bifurcation point of the antihelix is ​​calculated, the set of intersection points of the perpendicular bisector and the edge of the triangular fossa is calculated, the set of intersection points is traversed, and the uppermost point is taken as the Shenmen acupoint.

[0060] In one embodiment, the step of analyzing the physiological structural region to obtain the distribution points of each acupoint to obtain an ear patch navigation map includes: obtaining the triangular fossa, the helix, and the antiauricular fossa; analyzing the triangular fossa and the helix to obtain the distal end point of the triangular fossa; analyzing the antiauricular fossa to obtain the bifurcation point of the antiauricular helix; and obtaining the Shenmen acupoint based on the distal end point and the bifurcation point.

[0061] Specifically, the first set of pixels of the triangular fossa is obtained, and the target pixels that meet the preset conditions are deleted from the first set of pixels to obtain the second set of pixels after slimming; the second set of pixels is filtered to obtain the first foreground point and the first background point, and the first connecting region of the triangular fossa is obtained based on the first foreground point; the distance between the first foreground point contained in the first connecting region and the center of the helix is ​​calculated, and the first foreground point with the largest distance is set as the far end point.

[0062] Further, analyzing the antiauricular cavity to obtain the bifurcation point of the antihelix includes: obtaining a third set of pixels of the antiauricular cavity; deleting target pixels that meet preset conditions from the third set of pixels to obtain a thinner fourth set of pixels; filtering the fourth set of pixels to obtain a second foreground point and a second background point; obtaining a second connecting region of the antiauricular cavity based on the second foreground point; the foreground point with the largest y-coordinate value in the second connecting region is the bifurcation point of the antihelix.

[0063] In a specific application scenario, the distal endpoint of the triangular fossa can be calculated using the following steps: Calculate each endpoint, traverse each foreground point, and obtain the 8 foreground points P1 to Pn surrounding the current foreground point. If any point from P1 to Pn can reach all other points through an 8-way connectivity relationship, then mark the current foreground point as the background color. The algorithm rules are: the number of points between any two points in P1 to Pn that satisfy the 8-way connectivity relationship (dx <= 1, dy <= 1) is greater than or equal to n-1; set all points marked as background color to the background color; the remaining foreground points are the endpoints, where dx is the difference between the x-coordinates of the two points, and dy is the difference between the y-coordinates of the two points. The endpoint farthest from the center of the helix is ​​the distal endpoint. The algorithm rules are: traverse all endpoints, and use the formula sqrt((xi-x0)*(xi-x0)+(yi-y0)*(yi-y0) to calculate the distance to the center of the helix (x0, y0). The point with the maximum distance is the distal endpoint.

[0064] In a specific application scenario, the antihelix bifurcation point can be calculated using the following steps: Traverse the foreground color points after the image has thinned. If there are 3 or more foreground color points in the 8 directions surrounding the current foreground color point, add them to the bifurcation point set C. Traverse the bifurcation point set C; the point with the largest y-coordinate value is the antihelix bifurcation point P2. Calculate the set of intersection points between the straight line and the irregular image boundary. Traverse each point P(xj, yj) in the irregular image boundary set C and substitute it into the straight line y = kkx + b to obtain the value of y2. If the absolute value of y2 and y1 is less than the threshold (0.5), add point P to the intersection point set C2 and return the intersection point set C2.

[0065] In this embodiment, the second set of pixels is the first set of pixels after being slimmed down, and the fourth set of pixels is the third set of pixels after being slimmed down. The aforementioned slimming down can be understood as deleting irrelevant pixels. The specific slimming down method is as follows: traverse all pixels in the triangular fovea, and mark the pixels that meet the following four conditions as deleted, and record whether they are satisfied: (1) 2 <= N(p1) <= 6, (2) S(P1) = 1, (3) P2*P4*P6 = 0, (4) P4*P6*P8 = 0; where N(p1) represents the number of foreground pixels among the 8 pixels adjacent to P1, and S(P1) represents the cumulative number of occurrences of 0 to 1 from pixels P2 to P9 to P2, where 0 represents the background and 1 represents the foreground. After deleting the marked points, traverse all pixels in the triangular fovea again, and mark the pixels that meet the aforementioned four conditions as deleted. The set formed by the deleted points is the slimmed-down set.

[0066] The aforementioned first and second connecting regions are the minimum connecting point sets formed by the foreground points. The specific way to establish the connecting regions is as follows: traverse each point P of the thinned foreground set C and obtain an 8-directional foreground point set C2. The number of points in C2 is n. If the number of adjacent relationships (i.e., dx is not greater than 1 and dy is not greater than 1) between any two points in C2 is greater than or equal to (n-1), then it means that the current point P is the background color. After the set C2 is traversed, the remaining foreground points are the 8-directional minimum connecting point set, and the connecting regions are formed based on the remaining foreground points.

[0067] In this embodiment, AI technology is used to accurately locate standard-defined acupoints on different ears. Acupoint location is convenient and greatly reduces the knowledge and experience requirements for users. Combining traditional medicine with AI facilitates more accurate transmission of auricular acupoint knowledge, and the ear patch correction function helps users use the ear patch accurately, ensuring treatment effectiveness.

[0068] In practical applications, users take pictures of their outer ear via the app and upload them to the system. The system uses an AI model to analyze the physiological structure of the outer ear, calculates the acupoint locations using ear acupoint localization and CV algorithms, and returns an image of the outer ear with acupoint markings to the user. Based on the image with acupoint markings, users apply ear patches to the corresponding locations, take another picture of their outer ear, and upload it to the system. The system checks if the acupoints are covered by ear patches; if so, it provides the correct information. If not, it marks the acupoints that should be covered and returns an image and information to the user. The system also uses an AI model to analyze the physiological structure of the outer ear and perform image segmentation on the ear patches. Then, it uses rotation, scaling, and stretching to ensure that the image with ear patch markings overlaps with the image with acupoint markings.

[0069] To better implement the methods in the embodiments of this application, based on the above methods, the embodiments of this application also provide a user terminal that integrates any of the methods provided in the embodiments of this application. The user terminal includes:

[0070] One or more processors;

[0071] Memory; and

[0072] One or more applications, wherein the applications are stored in memory and configured to be executed by a processor, as follows: acquiring an image of a human ear; detecting the human ear image based on a pre-established auricular acupoint detection model to mark physiological structural regions on the human ear image; analyzing the physiological structural regions to obtain the distribution points of various acupoints to obtain an ear patch navigation map; and enabling a user to apply ear patches to target acupoints according to the ear patch navigation map.

[0073] In this embodiment, AI technology is used to accurately locate standard-defined acupoints on different ears. Acupoint location is convenient and greatly reduces the knowledge and experience requirements for users. Combining traditional medicine with AI facilitates more accurate transmission of auricular acupoint knowledge, and the ear patch correction function helps users use the ear patch accurately, ensuring treatment effectiveness.

[0074] like Figure 2 As shown, it illustrates a structural schematic diagram of the positioning device involved in the embodiments of this application. Specifically:

[0075] The positioning device may include components such as a processor 201 with one or more processing cores, a memory 202 with one or more computer-readable storage media, a power supply 203, and an input unit 204. Those skilled in the art will understand that the positioning device structure shown in the figures does not constitute a limitation on the positioning device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:

[0076] The processor 201 is the control center of the positioning device. It connects various parts of the positioning device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 202, and by calling data stored in the memory 202, it performs various functions and processes data, thereby providing overall monitoring of the positioning device. Optionally, the processor 201 may include one or more processing cores. The processor 201 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor. Preferably, the processor 201 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, physical interface, and application programs, while the modem processor mainly handles wireless communication. It is understood that the modem processor may not be integrated into the processor 201.

[0077] The memory 202 can be used to store software programs and modules. The processor 201 executes various functional applications and data processing by running the software programs and modules stored in the memory 202. The memory 202 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function, etc.; the data storage area may store data created based on the use of the positioning device, etc. In addition, the memory 202 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 202 may also include a memory controller to provide the processor 201 with access to the memory 202.

[0078] The positioning device also includes a power supply 203 that supplies power to the various components. Preferably, the power supply 203 can be logically connected to the processor 201 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 203 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0079] The positioning device may also include an input unit 204, which can be used to receive input digital or character information, and generate keyboard, mouse, joystick, optical or trackball signal inputs related to physical settings and function control.

[0080] Although not shown, the positioning device may also include a display unit, etc., which will not be described in detail here.

[0081] Specifically, in this embodiment, the processor 201 in the positioning device loads the executable files corresponding to the processes of one or more applications into the memory 202 according to the following instructions, and the processor 201 runs the applications stored in the memory 202 to achieve various functions, as follows:

[0082] A human ear image is acquired; the human ear image is detected based on a pre-established ear acupoint detection model to mark physiological structure regions on the human ear image; the physiological structure regions are analyzed to obtain the distribution points of each acupoint to obtain an ear patch navigation map; so that the user can apply ear patches to the target acupoints according to the ear patch navigation map.

[0083] In this embodiment, AI technology is used to accurately locate standard-defined acupoints on different ears. Acupoint location is convenient and greatly reduces the knowledge and experience requirements for users. Combining traditional medicine with AI facilitates more accurate transmission of auricular acupoint knowledge, and the ear patch correction function helps users use the ear patch accurately, ensuring treatment effectiveness.

[0084] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by instructions, or by instructions controlling related hardware. These instructions can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0085] Therefore, embodiments of this application provide a computer-readable storage medium, which may include: read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk, etc. A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in any of the methods provided in embodiments of this application. For example, the computer program loaded by the processor can execute the following steps:

[0086] A human ear image is acquired; the human ear image is detected based on a pre-established ear acupoint detection model to mark physiological structure regions on the human ear image; the physiological structure regions are analyzed to obtain the distribution points of each acupoint to obtain an ear patch navigation map; so that the user can apply ear patches to the target acupoints according to the ear patch navigation map.

[0087] For details on the implementation of each of the above operations, please refer to the previous examples, which will not be repeated here.

[0088] The method and apparatus provided in the embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and its core ideas. At the same time, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

[0089] The above description is merely an embodiment of this application and does not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. An ear-sticker positioning device for implementing an ear-acupoint positioning method, characterized in that, The positioning device comprises: one or more processors; a memory; and one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the processor to implement the positioning method; wherein the positioning method comprises obtaining an image of a human ear; detecting the image of the human ear based on a pre-established auricular point detection model to label physiological structure regions on the image of the human ear; analyzing the physiological structure regions to obtain distribution points of each acupoint to obtain an ear sticker navigation map, so that a user can place an ear sticker on a target acupoint according to the ear sticker navigation map; wherein the physiological structure regions comprise an antihelix, a scapha, a triangular fossa, a counter-helix, an earlobe, a tragus, and a counter-tragus; wherein the analyzing the physiological structure regions to obtain distribution points of each acupoint to obtain an ear sticker navigation map comprises: obtaining the triangular fossa, the antihelix, and the counter-helix; analyzing the triangular fossa and the antihelix to obtain a distal point of the triangular fossa; analyzing the counter-helix to obtain a bifurcation point of the counter-helix; obtaining Shenmen acupoint based on the distal point and the bifurcation point; wherein the obtaining Shenmen acupoint based on the distal point and the bifurcation point comprises: calculating a perpendicular line of the distal point of the triangular fossa and the bifurcation point of the counter-helix, calculating a set of intersection points of the perpendicular line and a boundary of the triangular fossa, and traversing the set of intersection points, wherein the uppermost point is the Shenmen acupoint.

2. The positioning device of claim 1, wherein, The positioning method further comprises: obtaining an initial ear sticker image on which an ear sticker has been placed; comparing and analyzing the ear sticker navigation map and the initial ear sticker image to determine whether the ear sticker can cover the target acupoint; if at least one ear sticker does not cover the target acupoint, marking a corresponding offset ear sticker on the initial ear sticker image; and determining a corresponding correction method based on the ear sticker navigation map, so that a user can adjust the position of the offset ear sticker based on the correction method.

3. The positioning device of claim 2, wherein, The determining a corresponding correction method based on the ear sticker navigation map comprises: mapping the offset ear sticker to the ear sticker navigation map in the form of an ear sticker virtual frame by using image mapping, detecting the position relationship between the ear sticker virtual frame and the corresponding target acupoint, and determining the correction method of the offset ear sticker based on the position relationship.

4. The positioning device of claim 1, wherein, The analyzing the triangular fossa and the antihelix to obtain a distal point of the triangular fossa comprises: obtaining a first set of pixel points of the triangular fossa, deleting target pixel points meeting a preset condition from the first set of pixel points to obtain a second set of pixel points after thinning; screening the second set of pixel points to obtain first foreground points and first background points, and obtaining a first connection region of the triangular fossa based on the first foreground points; calculating the distance between the first foreground points contained in the first connection region and the center of the antihelix, and setting the first foreground point with the maximum distance as the distal point.

5. The positioning device of claim 1, wherein, The analyzing the counter-helix to obtain a bifurcation point of the counter-helix comprises: obtaining a third set of pixel points of the counter-helix, deleting target pixel points meeting a preset condition from the third set of pixel points to obtain a fourth set of pixel points after thinning; Screening the fourth pixel point set to obtain second foreground points and second background points, and obtaining a second connecting region of the antihelix according to the second foreground points; The foreground point with the maximum y coordinate value in the second connecting region is the antihelix bifurcation point.

6. A computer-readable storage medium, characterized in that, A computer program is stored thereon, and the computer program is loaded by a processor to execute the steps in the method in any one of claims 1 to 5.

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