A parameter identification method and device

Abstract

The present application discloses a parameter identification method and apparatus. The parameter identification method includes: obtaining an image to be processed, where the image to be processed is at least photographed with a display panel on a target device and a positioning identifier arranged on the target device; performing identification based on the image to be processed to obtain the pixel coordinates of a first feature point on the positioning identifier; determining the image area of a target area in the image to be processed based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point, where the target area is used to display the target parameters of the target device; and identifying the current target parameters of the target device based on the image area. The above solution can improve the accuracy of parameter identification.

Description

Technical Field

[0001] This application relates to the technical field of target recognition, and particularly to a parameter recognition method and device. Background Art

[0002] Currently, target recognition by processing images and videos through machine vision has been widely applied.

[0003] Taking the target recognition of machine vision applied to smart home as an example, the machine vision technology obtains the display panel image of the target device in the smart home, recognizes the parameters on the display panel, and obtains the status information of the target device. Since there is a variety of information on the display panel, a large proportion of the content in the panel image belongs to useless information, and the display panel information on different target devices is also different. It is difficult to filter out the useless information in the panel image while retaining the useful parameter information in the image, and thus it is impossible to accurately determine the target parameters to be recognized, affecting the accuracy of parameter recognition.

[0004] Therefore, how to improve the accuracy of parameter recognition has become an urgent problem to be solved. Summary of the Invention

[0005] The main technical problem to be solved by this application is to provide a parameter recognition method and device, which can improve the accuracy of parameter recognition.

[0006] To solve the above technical problem, in the first aspect of this application, a parameter recognition method is provided. The parameter recognition method includes: obtaining an image to be processed; wherein, the image to be processed at least captures a display panel on a target device and a positioning identifier provided on the target device; performing recognition based on the image to be processed to obtain the pixel coordinates of the first feature point on the positioning identifier; determining the image area of the target area in the image to be processed based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point; wherein, the target area is used to display the target parameters of the target device; and recognizing the current target parameters of the target device based on the image area.

[0007] To solve the above technical problem, in the second aspect of this application, a parameter recognition device is provided, including an acquisition module, a first recognition module, a determination module, and a second recognition module. The acquisition module is used to obtain an image to be processed; wherein, the image to be processed at least captures a display panel on a target device and a positioning identifier provided on the target device; the determination module is used to determine the image area of the target area in the image to be processed based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point; wherein, the target area is used to display the target parameters of the target device; and the second recognition module is used to recognize the current target parameters of the target device based on the image area.

[0008] In the above solution, a to-be-processed image is obtained. The to-be-processed image captures at least a display panel on a target device and a positioning identifier disposed on the target device. The positioning identifier can assist in positioning the position of the display panel. Recognition is performed based on the to-be-processed image to obtain the pixel coordinates of a first feature point on the positioning identifier. Based on the actual size of the positioning identifier, the actual positional relationship between the positioning identifier and a target area in the display panel, and the pixel coordinates of the first feature point, the image area of the target area in the to-be-processed image is determined. The target area is used to display target parameters of the target device. Based on the image area, the current target parameters of the target device are recognized. Therefore, the display panel is positioned using the positioning identifier, and based on the actual size of the positioning identifier, the actual positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point on the positioning identifier, the image area of the target area in the to-be-processed image can be accurately calibrated, and target parameter recognition can be achieved within the accurately calibrated image area, thereby improving the accuracy of parameter recognition. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 It is a flowchart of an embodiment of the parameter recognition method of the present application;

[0010] Figure 2 It is a schematic framework diagram of an embodiment of the target device of the present application;

[0011] Figure 3 It is a flowchart of another embodiment of the parameter recognition method of the present application;

[0012] Figure 4 It is a schematic diagram of an embodiment of the image area of the present application;

[0013] Figure 5 is Figure 4 a schematic diagram of an embodiment of the image area in

[0014] Figure 6 It is a flowchart of yet another embodiment of the parameter recognition method of the present application;

[0015] Figure 7 It is a schematic framework diagram of an embodiment of the parameter recognition device of the present application;

[0016] Figure 8 It is a schematic framework diagram of an embodiment of the electronic device of the present application;

[0017] Figure 9 is a schematic framework diagram of an embodiment of the computer-readable storage medium of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The solution of the embodiment of the present application will be described in detail below with reference to the accompanying drawings of the specification.

[0019] In the following description, specific details such as specific system architectures, interfaces, technologies, etc. are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the present application.

[0020] "Multiple" in this article means two or more than two. Additionally, the term "at least one" in this article means any one of multiple or any combination of at least two of multiple. For example, including at least one of A, B, and C can mean including any one or more elements selected from the set composed of A, B, and C.

[0021] Please refer to Figure 1 , Figure 1 which is a schematic flowchart of an embodiment of the parameter identification method of the present application.

[0022] Specifically, the embodiments of the present disclosure may include the following steps:

[0023] S11: Obtain an image to be processed; wherein, the image to be processed is at least photographed with a display panel on a target device and a positioning identifier provided on the target device;

[0024] It should be noted that the target device in the embodiments of the present disclosure may include, but is not limited to, air conditioners, refrigerators, washing machines, etc. The display panel on the target device may include an air conditioner parameter display panel, a refrigerator parameter display panel, a parameter display panel for smart home interconnection, etc. The positioning identifier provided on the target device may include, but is not limited to: two-dimensional code, bar code, paper, sticky note, wooden board, plastic board, etc. The setting method of the positioning identifier may include, but is not limited to: pasting, fixing with thumbtacks, fixing with screws, magnetic attraction, etc.

[0025] In one implementation scenario, the image to be processed is obtained by photographing with a photographing device, and the image to be processed is at least photographed with a display panel on a target device and a positioning identifier provided on the target device.

[0026] In one implementation scenario, the positioning identifier provided on the target device may be parallel to the display panel. Of course, it may also be inclined to the display panel, which is not limited herein.

[0027] S12: Perform identification based on the image to be processed to obtain the pixel coordinates of the first feature point on the positioning identifier;

[0028] In an implementation scenario, the positioning identifier can be a polygon, a circle, or a quasi-circle, and the shape of the positioning identifier is not limited herein. For example, when the positioning identifier is a polygon, the first feature points on the positioning identifier can be the vertices of the polygon. Alternatively, when the positioning identifier is a circle or a quasi-circle, the first feature points on the positioning identifier can be points on the circumference. Exemplarily, the positioning identifier can be a circle with several solid dots distributed on the circumference, and the first feature points can be the above-mentioned solid dots.

[0029] In a specific implementation scenario, the positioning identifier is a two-dimensional code, and the first feature points can be the four vertices of the two-dimensional code. By performing recognition based on the image to be processed, the pixel coordinates corresponding to the four vertices of the two-dimensional code can be obtained. The specific recognition process can refer to related image recognition technologies and will not be elaborated herein.

[0030] S13: Determine the image area of the target area in the image to be processed based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature points; wherein, the target area is used to display the target parameters of the target device;

[0031] In an implementation scenario, the true size of the positioning identifier can include but is not limited to the true length, true width, true radius, etc., and the true positional relationship between the positioning identifier and the target area in the display panel can include but is not limited to the horizontal spacing, vertical spacing, etc.

[0032] In an implementation scenario, the true size of the positioning identifier and the true positional relationship between the positioning identifier and the target area in the display panel can be obtained through actual measurement, or the known true size and true positional relationship can be written or configured in the positioning identifier in advance and obtained through automatic acquisition.

[0033] In a specific implementation scenario, the positioning identifier is a two-dimensional code. The true size of the two-dimensional code and the true positional relationship between the two-dimensional code and the target area in the display panel can be pre-configured. By recognizing the two-dimensional code in the image to be processed, the true size of the two-dimensional code and the true positional relationship between the two-dimensional code and the target area in the display panel can be obtained.

[0034] In a specific implementation scenario, the positioning identifier is ordinary paper. The true size of the positioning identifier and the true positional relationship between the positioning identifier and the target area in the display panel can be measured in advance or measured in real time. Through the reserved input data interface, the true size and true positional relationship of the positioning identifier input after measurement are obtained.

[0035] In an implementation scenario, based on the pixel coordinates of the first feature point on the positioning identifier, the pixel size of the positioning identifier is obtained. Based on the pixel size and the true size of the positioning identifier, a conversion coefficient is obtained. Based on the true position relationship, pixel coordinates, and the conversion coefficient, an image region is obtained.

[0036] In a specific implementation scenario, the edges of the positioning identifier and the display panel are parallel to each other. The true size includes a horizontal edge size and a vertical edge size. Based on the maximum difference in the pixel coordinates of the first feature points with the same pixel coordinates in the vertical direction in the horizontal direction, the horizontal pixel size in the pixel size is obtained. And based on the maximum difference in the pixel coordinates of the first feature points with the same pixel coordinates in the horizontal direction in the vertical direction, the vertical pixel size in the pixel size is obtained. Based on the ratio of the horizontal edge size to the horizontal pixel size, the horizontal conversion coefficient in the conversion coefficient is obtained. And based on the ratio of the vertical edge size to the vertical pixel size, the vertical conversion coefficient in the conversion coefficient is obtained. Based on the true position relationship, pixel coordinates, and the horizontal conversion coefficient, the horizontal coordinate of the second feature point corresponding to the first feature point on the target region in the image to be processed is obtained. And based on the true position relationship, pixel coordinates, and the vertical conversion coefficient, the vertical coordinate of the second feature point corresponding to the first feature point on the target region in the image to be processed is obtained. Based on the horizontal coordinate and the vertical coordinate of the second feature point, the image region is determined.

[0037] In a specific implementation scenario, on the basis that the edges of the aforementioned positioning identifier and the display panel are parallel to each other, and the true size includes a horizontal edge size and a vertical edge size, the true position relationship further includes the true horizontal distance and the true vertical distance between the first feature point and the second feature point. Obtaining the horizontal coordinate of the second feature point corresponding to the first feature point on the target region in the image to be processed based on the true position relationship, pixel coordinates, and the horizontal conversion coefficient includes: obtaining the first product of the horizontal conversion coefficient and the true horizontal distance, and obtaining the sum of the first product and the pixel coordinate of the first feature point in the horizontal direction as the horizontal coordinate of the second feature point. Obtaining the vertical coordinate of the second feature point corresponding to the first feature point on the target region in the image to be processed based on the true position relationship, pixel coordinates, and the vertical conversion coefficient includes: obtaining the second product of the vertical conversion coefficient and the true vertical distance, and obtaining the sum of the second product and the pixel coordinate of the first feature point in the vertical direction as the vertical coordinate of the second feature point.

[0038] Exemplarily, please refer to Figure 2 , Figure 2This is a schematic diagram of the framework of an embodiment of the target device of the present application. The positioning identifier provided on the target device is arranged parallel to the edge of the display panel on the target device. The positioning identifier includes three first feature points, namely the first upper left vertex, the first upper right vertex, and the first lower left vertex. The target area in the display panel includes two second feature points, namely the second upper left vertex and the second lower right vertex. Among them, the horizontal edge dimension of the positioning identifier is L1, the vertical edge dimension is L2, the true horizontal distance between the first upper left vertex and the second upper left vertex is r1, the true vertical distance between the first upper left vertex and the second upper left vertex is c1, the true horizontal distance between the first upper left vertex and the second lower right vertex is r2, and the true vertical distance between the first upper left vertex and the second lower right vertex is c2. By performing recognition on the image to be processed, the pixel coordinates corresponding to the first upper left vertex on the positioning identifier can be obtained as (x1, y1), the pixel coordinates corresponding to the first upper right vertex as (x2, y2), and the pixel coordinates corresponding to the first lower left vertex as (x3, y3). The pixel coordinates of the two first feature points with the same pixel coordinate in the vertical direction and the farthest pixel coordinate distance in the horizontal direction are (x1, y1) and (x2, y2) respectively. Among them, y1 is equal to y2, and the difference x2 - x1 between x2 and x1 is the horizontal pixel size in the pixel size; the pixel coordinates of the two first feature points with the same pixel coordinate in the horizontal direction and the farthest pixel coordinate distance in the vertical direction are (x1, y1) and (x3, y3) respectively. Among them, y3 is equal to y1, and the difference y3 - y1 between y3 and y1 is the vertical pixel size in the pixel size; based on the ratio of the horizontal edge dimension L1 to the horizontal pixel size x2 - x1, the horizontal conversion coefficient in the conversion coefficient is obtained:

[0039]

[0040] Based on the ratio of the vertical edge dimension L2 to the vertical pixel size y3 - y1, the vertical conversion coefficient in the conversion coefficient is obtained:

[0041]

[0042] Obtain the first product of the horizontal conversion coefficient and the true horizontal distance r1, and obtain the sum of the first product and the pixel coordinate of the first upper left vertex in the horizontal direction as the pixel coordinate of the second upper left vertex in the horizontal direction:

[0043] x1 + WeightTime1 * r1;

[0044] Obtain the second product of the vertical conversion coefficient and the true vertical distance c1, and obtain the sum of the second product and the pixel coordinate of the first upper left vertex in the vertical direction as the pixel coordinate of the second upper left vertex in the vertical direction:

[0045] y1 + HeightTime1 * c1;

[0046] Obtain the first product of the horizontal conversion coefficient and the true horizontal spacing r2, and obtain the sum of the first product and the pixel coordinates of the first upper-left vertex in the horizontal direction as the pixel coordinates of the second lower-right vertex in the horizontal direction:

[0047] x1 + WeightTime1 * r2;

[0048] Obtain the second product of the vertical conversion coefficient and the true vertical spacing c2, and obtain the sum of the second product and the pixel coordinates of the first upper-left vertex in the vertical direction as the pixel coordinates of the second lower-right vertex in the vertical direction:

[0049] y1 + HeightTime1 * c2;

[0050] Finally, obtain the pixel coordinates of the second upper-left vertex (x1 + WeightTime1 * r1, y1 + HeightTime1 * c1), the pixel coordinates of the second lower-right vertex (x1 + WeightTime1 * r2, y1 + HeightTime1 * c2), and based on the rectangular area covered by the pixel coordinates of the second upper-left vertex and the second lower-right vertex, as the image area.

[0051] In an implementation scenario, after determining the image area of the target area in the image to be processed, the image to be processed can also be cut, and only the part of the image containing the image area is retained. For the specific process, please refer to the image segmentation technology and will not be elaborated here.

[0052] In a specific implementation scenario, the cut image can be further adjusted to a preset size.

[0053] S14: Based on the image area, identify the current target parameters of the target device.

[0054] In an implementation scenario, the target parameter is a numerical parameter, and the numerical parameter is displayed by a digital tube. Based on the image area, identify the current numerical parameter of the target device.

[0055] In a specific implementation scenario, the numerical parameters can include but are not limited to temperature, humidity, time, etc.

[0056] In an implementation scenario, the target parameter is a mode parameter. Based on the image area, identify the current mode parameter of the target device.

[0057] In a specific implementation scenario, the mode parameters can include but are not limited to a refrigeration mode, a heating mode, a wind power mode, and so on.

[0058] In an implementation scenario, the image area can be adjusted to a preset size, and the preset size is different under different target parameters.

[0059] In a specific implementation scenario, the target parameter is a numerical parameter. The image area can be adjusted to a corresponding preset size according to the number of digits of the numerical parameter. For example, the preset size corresponding to a single-digit numerical parameter is smaller than the preset size corresponding to a two-digit numerical parameter. When identifying a two-digit numerical parameter, the image area of the preset size can be further divided into two equal parts and then identified separately.

[0060] In a specific implementation scenario, the target parameter is a mode parameter, and the mode parameter is displayed in the form of a graph on the display panel of the target device. The image area can be adjusted to a preset size according to the shape, size, etc. of the graph.

[0061] In the above solution, a to-be-processed image is obtained. The to-be-processed image at least captures the display panel on the target device and the positioning identifier set on the target device. The positioning identifier can assist in positioning the position of the display panel. Based on the to-be-processed image, the pixel coordinates of the first feature point on the positioning identifier are obtained. Based on the actual size of the positioning identifier, the actual positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point, the image area of the target area in the to-be-processed image is determined. The target area is used to display the target parameter of the target device. Based on the image area, the current target parameter of the target device is recognized. Therefore, the display panel is positioned by the positioning identifier, and based on the actual size of the positioning identifier, the actual positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point on the positioning identifier, the image area of the target area in the to-be-processed image can be accurately calibrated, and the target parameter recognition can be realized within the accurately calibrated image area, thereby improving the accuracy of parameter recognition.

[0062] Please refer to Figure 3 , Figure 3 which is a schematic flowchart of another embodiment of the parameter recognition method of this application. Specifically, it includes the following steps:

[0063] S31: Obtain a to-be-processed image; the to-be-processed image at least captures the display panel on the target device and the positioning identifier set on the target device;

[0064] For the specific process, please refer to step S11 in the foregoing embodiment, which will not be elaborated here.

[0065] S32: Based on the to-be-processed image, identify the pixel coordinates of the first feature point on the positioning identifier;

[0066] For the specific process, please refer to step S12 in the foregoing embodiment, which will not be elaborated here.

[0067] S33: Based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point, determine the image area of the target area in the image to be processed; wherein, the target area is used to display the target parameters of the target device;

[0068] For the specific process, please refer to step S13 in the foregoing embodiments and will not be elaborated herein.

[0069] S34: The target parameter is a numerical parameter, and the numerical parameter is displayed by a digital tube. Based on the image area, sub-images corresponding to each digit to be recognized in the numerical parameter are obtained by division;

[0070] In an implementation scenario, the numerical parameter is displayed by a seven-segment digital tube. Each segment of the digital tube corresponds to a sub-image respectively, and the digit to be recognized is determined by the lit or extinguished state of each segment of the digital tube.

[0071] S35: Based on the pixel values on the feature lines that respectively pass through and uniquely pass through different digital tubes in the sub-image, determine the displayed digit in the sub-image;

[0072] In an implementation scenario, based on the pixel values on each feature line in the sub-image, determine the display state of the digital tube passed by the corresponding feature line; wherein, the display state includes any one of lit and extinguished; based on the display states of the digital tubes passed by each feature line in the sub-image, determine the displayed digit in the sub-image.

[0073] In an implementation scenario, before determining the display state of the digital tube passed by the corresponding feature line based on the pixel values on each feature line in the sub-image as described above, the sub-image can also be converted into a grayscale image and the grayscale image can be binarized.

[0074] In a specific implementation scenario, each pixel point in the grayscale image is binarized. When the grayscale value of a certain pixel point is greater than the preset threshold, the grayscale value of the current pixel point is set to the first preset value. When the grayscale value of a certain pixel point is less than or equal to the preset threshold, the grayscale value of the current pixel point is set to the second preset value, which is specifically obtained by fusing with the environment such as brightness and light. Exemplarily, the preset threshold is any value between 0 and 255, the first preset value is 255, and the second preset value is 0. At this time, after binarizing each pixel point in the grayscale image, the lit part of the digital tube in the grayscale image is converted into pure white, and the rest is converted into pure black, which can greatly distinguish the lit digital tube from the extinguished digital tube, and setting a reasonable preset threshold can also remove the noise in the image, thereby improving the accuracy of recognizing the numerical parameter and reducing the calculation amount.

[0075] In an implementation scenario, based on the pixel values on each feature line in the sub-image, the display state of the digital tube passed by the corresponding feature line is determined, including: detecting the gray values of each pixel point on the feature line, and in response to the presence of a pixel point with a gray value equal to a preset value on the feature line, determining that the display state of the digital tube passed by the feature line is lit; in response to the absence of a pixel point with a gray value equal to the preset value on the feature line, determining that the display state of the digital tube passed by the feature line is off.

[0076] In a specific implementation scenario, please refer to Figure 4 , Figure 4 which is a schematic diagram of an embodiment of the image area of this application. The size of the aforementioned binarized image is adjusted to c×d, and it is assumed that the coordinate origin (0, 0) at this time corresponds to the upper left vertex position of the image. Points A with coordinates are marked in the image, points B with coordinates , points C with coordinates , points D with coordinates , points E with coordinates , points F with coordinates , points G with coordinates , and points H with coordinates . The line connecting point A and point B is used as feature line AB, the line connecting point A and point C is used as feature line AC, the line connecting point A and point D is used as feature line AD, the line connecting point A and point E is used as feature line AE, the line connecting point B and point F is used as feature line BF, the line connecting point B and point G is used as feature line BG, and the line connecting point B and point H is used as feature line BH. Among them, feature lines AB, AC, AD, AE, BF, BG, and BH respectively pass through and only pass through different digital tubes. Exemplarily, the pixel values of each pixel point on feature line AB are detected. In response to the presence of a pixel point with a gray value equal to the first preset value on feature line AB, it is determined that the display state of the digital tube passed by feature line AB is lit. In response to the absence of a pixel point with a gray value equal to the first preset value on feature line AB, it is determined that the display state of the digital tube passed by feature line AB is off.

[0077] Specifically, in response to the presence of pixel points with a grayscale value equal to the preset value on the feature lines AC, AD, AE, BF, BG, and BH, the display state of the digital tubes passed by the feature lines is lit, and the finally displayed lit number is 0. In response to the presence of pixel points with a grayscale value equal to the preset value on the feature lines AE and BG, the display state of the digital tubes passed by the feature lines is lit, and the finally displayed lit number is 1. In response to the presence of pixel points with a grayscale value equal to the preset value on the feature lines AB, AC, AE, BF, and BH, the display state of the digital tubes passed by the feature lines is lit, and the finally displayed lit number is 2. In response to the presence of pixel points with a grayscale value equal to the preset value on the feature lines AB, AC, AE, BG, and BH, the display state of the digital tubes passed by the feature lines is lit, and the finally displayed lit number is 3. In response to the presence of pixel points with a grayscale value equal to the preset value on the feature lines AB, AD, AE, and BG, the display state of the digital tubes passed by the feature lines is lit, and the finally displayed lit number is 4. In response to the presence of pixel points with a grayscale value equal to the preset value on the feature lines AB, AC, AD, BG, and BH, the display state of the digital tubes passed by the feature lines is lit, and the finally displayed lit number is 5. In response to the presence of pixel points with a grayscale value equal to the preset value on the feature lines AB, AC, AD, BF, and BH, the display state of the digital tubes passed by the feature lines is lit, and the finally displayed lit number is 6. In response to the presence of pixel points with a grayscale value equal to the preset value on the feature lines AC and AE and BG, the display state of the digital tubes passed by the feature lines is lit, and the finally displayed lit number is 7. In response to the presence of pixel points with a grayscale value equal to the preset value on the feature lines AB, AC, AD, AE, BF, BG, and BH, the display state of the digital tubes passed by the feature lines is lit, and the finally displayed lit number is 8. In response to the presence of pixel points with a grayscale value equal to the preset value on the feature lines AB, AC, AD, AE, BG, and BH, the display state of the digital tubes passed by the feature lines is lit, and the finally displayed lit number is 9.

[0078] Please refer to Figure 5 , Figure 5 which is Figure 4 a schematic diagram of an embodiment of the image area in Figure 5 a black-and-white image after binarization processing. The grayscale values of each pixel point on the feature lines AB, AC, AD, AE, BF, BG, and BH are detected. In response to the presence of pixel points with a grayscale value of 255 on the feature lines AB, AC, AE, BF, and BH, it is determined that the display state of the digital tubes passed by the feature lines is lit; in response to the absence of pixel points with a grayscale value of 255 on the feature lines AD and BG, it is determined that the display state of the digital tubes passed by the feature lines is extinguished.

[0079] S36: Obtain digital parameters based on the displayed numbers in each sub-image.

[0080] In an implementation scenario, the digital parameter is a single-digit number, and the digital parameter obtained based on the displayed numbers in each sub-image is the target digital parameter.

[0081] In an implementation scenario, the digital parameter is a two-digit number, and the digital tube is a two-digit digital tube. After obtaining the displayed numbers of the units digit or the tens digit in each sub-image based on the displayed numbers in each sub-image, the steps of S34 are re-executed, and the displayed numbers of the other digit in the two-digit digital tube can be recognized. By multiplying the displayed number of the tens digit by ten and then adding the displayed number of the units digit, the two-digit digital parameter can be obtained. The digital parameters of three-digit numbers, four-digit numbers, etc. can be obtained similarly, which will not be elaborated here.

[0082] In the above solution, on the one hand, the display panel is positioned with the positioning identifier, and based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point on the positioning identifier, the image area of the target area in the image to be processed can be accurately calibrated, and the target parameter recognition can be realized within the accurately calibrated image area, thereby improving the accuracy of parameter recognition. On the other hand, based on the image area, sub-images corresponding to each digit to be recognized in the digital parameter are divided. Based on the pixel values on the feature lines that respectively pass through and only pass through different digital tubes in the sub-images, the displayed numbers in the sub-images are determined. Based on the displayed numbers in each of the sub-images, the digital parameter is obtained. Through simple image transformation and pixel value recognition, the accurate reading of the digital parameter can be realized while reducing the calculation amount in the process of digital parameter recognition.

[0083] Please refer to Figure 6 , Figure 6 which is a schematic flowchart of another embodiment of the parameter recognition method of the present application. Specifically, it includes the following steps:

[0084] S61: Obtain the image to be processed; wherein, the image to be processed is at least photographed with the display panel on the target device and the positioning identifier set on the target device;

[0085] For the specific process, please refer to step S11 in the foregoing embodiment, which will not be elaborated here.

[0086] S62: Perform recognition based on the image to be processed to obtain the pixel coordinates of the first feature point on the positioning identifier;

[0087] For the specific process, please refer to step S12 in the foregoing embodiment, which will not be elaborated here.

[0088] S63: Determine the image area of the target area in the image to be processed based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point; wherein, the target area is used to display the target parameters of the target device.

[0089] For the specific process, please refer to step S13 in the foregoing embodiment, which will not be elaborated here.

[0090] S64: When the target parameter is a mode parameter, obtain the first grayscale value of the target area for displaying the mode parameter when the mode parameter is in the on state and the second grayscale value when it is in the off state, and convert the image data located in the image area in the image to be processed into a grayscale image.

[0091] In one implementation scenario, the first grayscale value can be the average grayscale value of the target area for displaying the mode parameter when the mode parameter is in the on state, and the second grayscale value can be the average grayscale value of the target area for displaying the mode parameter when the mode parameter is in the off state.

[0092] In one implementation scenario, the first grayscale value can be the weighted average grayscale value of the target area for displaying the mode parameter when the mode parameter is in the on state, and the second grayscale value can be the weighted average grayscale value of the target area for displaying the mode parameter when the mode parameter is in the off state.

[0093] In a specific implementation scenario, the mode parameter is displayed in graphical form. Exemplarily, the image representing the current mode parameter is a circular-like graph. At this time, according to the distance of each pixel point in the image area from the center, different weights are selected to obtain the weighted average grayscale value. The closer to the center, the greater the weight, and the farther from the center, the smaller the weight, so as to obtain the first grayscale value of the target area for displaying the mode parameter when the mode parameter is in the on state and the second grayscale value when it is in the off state.

[0094] In one implementation scenario, the image data located in the image area in the image to be processed can be converted into a grayscale image through a color space conversion function. For the specific process, please refer to the related technology of the color space conversion function, which will not be elaborated here.

[0095] S65: Obtain the current grayscale value of the image area.

[0096] In one implementation scenario, the current grayscale value can be the current average grayscale value of the image area.

[0097] In one implementation scenario, the current grayscale value can be the current weighted average grayscale value of the image area.

[0098] In a specific implementation scenario, the mode parameter is displayed in a graphical form. Exemplarily, the image representing the current mode parameter is a circular-like graph. At this time, according to the distance of each pixel point in the image area from the center, different weights are selected to obtain the weighted average gray value. The closer to the center, the greater the weight; the farther from the center, the smaller the weight, so as to obtain the current weighted average gray value of the image area.

[0099] S66: Based on the current gray value, the first gray value, and the second gray value, determine whether the current state of the mode parameter is the on state or the off state.

[0100] In an implementation scenario, the first gray value and the second gray value are fused to obtain a gray threshold. In response to the current gray value being greater than the gray threshold, determine that the current state of the mode parameter is the on state; in response to the current gray value being less than or equal to the gray threshold, determine that the current state of the mode parameter is the off state.

[0101] In a specific implementation scenario, control the air conditioner to turn on the cooling mode, record the first gray value of the target area where the mode parameter is displayed when the air conditioner cooling mode is in the on state, control the air conditioner to turn off the cooling mode, record the second gray value of the target area where the mode parameter is displayed when the air conditioner cooling mode is in the off state, adjust the indoor light source and conduct multiple tests, and use an image fusion algorithm to process and obtain the gray threshold. In response to the current gray value being greater than the gray threshold, determine that the current state of the mode parameter is the on state, that is, the air conditioner cooling mode is in the on state; in response to the current gray value being less than or equal to the gray threshold, determine that the current state of the mode parameter is the off state, that is, the air conditioner cooling mode is in the off state.

[0102] In the above solution, on the one hand, the display panel is positioned with a positioning identifier, and based on the actual size of the positioning identifier, the actual positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point on the positioning identifier, the image area of the target area in the image to be processed can be accurately calibrated, and target parameter recognition can be realized within the accurately calibrated image area, thereby improving the accuracy of parameter recognition; on the other hand, based on the current gray value, the first gray value, and the second gray value, determine whether the current state of the mode parameter is the on state or the off state. By simple calculation of the image gray value, accurate recognition of the mode parameter can be achieved while reducing the computational amount in the process of mode parameter recognition.

[0103] Please refer to Figure 7 , Figure 7It is a schematic framework diagram of an embodiment of the parameter recognition device 70 of the present application. The parameter recognition device includes an acquisition module 71, a first recognition module 72, a determination module 73, and a second recognition module 74. The acquisition module 71 is configured to acquire an image to be processed. Among them, the image to be processed is at least photographed with a display panel on the target device and a positioning identifier provided on the target device. The first recognition module 72 is configured to perform recognition based on the image to be processed to obtain the pixel coordinates of the first feature point on the positioning identifier. The determination module 73 is configured to determine the image area of the target area in the image to be processed based on the actual size of the positioning identifier, the actual positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point. Among them, the target area is used to display the target parameters of the target device. The second recognition module 74 is configured to recognize the current target parameters of the target device based on the image area.

[0104] In the above solution, the parameter recognition device 70 acquires an image to be processed. Among them, the image to be processed is at least photographed with a display panel on the target device and a positioning identifier provided on the target device. The positioning identifier can assist in positioning the position of the display panel. Recognition is performed based on the image to be processed to obtain the pixel coordinates of the first feature point on the positioning identifier. Based on the actual size of the positioning identifier, the actual positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point, the image area of the target area in the image to be processed is determined. Among them, the target area is used to display the target parameters of the target device. Based on the image area, the current target parameters of the target device are recognized. Therefore, the display panel is positioned by the positioning identifier, and the image area of the target area in the image to be processed can be accurately calibrated according to the actual size of the positioning identifier, the actual positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point on the positioning identifier, and the target parameter recognition can be realized within the accurately calibrated image area, thereby improving the accuracy of parameter recognition.

[0105] In some disclosed embodiments, the determination module 73 includes a pixel size acquisition sub-module, a conversion coefficient acquisition sub-module, and an image area acquisition sub-module. The pixel size acquisition sub-module is configured to obtain the pixel size of the positioning identifier based on the pixel coordinates of the first feature point on the positioning identifier. The conversion coefficient acquisition unit sub-module is configured to obtain a conversion coefficient based on the pixel size and the actual size of the positioning identifier. The image area acquisition sub-module is configured to obtain the image area based on the actual positional relationship, pixel coordinates, and conversion coefficient.

[0106] Therefore, the conversion coefficient between the real coordinate system and the pixel coordinate system can be obtained through the real size of the positioning identifier and the pixel coordinates of the first feature point on the positioning identifier, and the conversion coefficient can be obtained. Thus, based on the real position relationship between the positioning identifier and the target area in the display panel, the pixel coordinates of the first feature point, and the conversion coefficient, the image area corresponding to the target area in the pixel coordinate system can be accurately calibrated, and parameter recognition can be performed within the accurately calibrated image area, which can improve the parameter recognition accuracy.

[0107] In some disclosed embodiments, the edges of the positioning identifier and the display panel are parallel to each other. The real size includes the horizontal edge size and the vertical edge size. The pixel size acquisition sub-module is specifically configured to obtain the horizontal pixel size in the pixel size based on the maximum difference in the pixel coordinates of the first feature points having the same pixel coordinates in the vertical direction in the horizontal direction, and obtain the vertical pixel size in the pixel size based on the maximum difference in the pixel coordinates of the first feature points having the same pixel coordinates in the horizontal direction in the vertical direction. The conversion coefficient acquisition sub-module is specifically configured to obtain the horizontal conversion coefficient in the conversion coefficient based on the ratio of the horizontal edge size to the horizontal pixel size, and obtain the vertical conversion coefficient in the conversion coefficient based on the ratio of the vertical edge size to the vertical pixel size. The image area acquisition sub-module includes a horizontal coordinate acquisition unit, which is configured to obtain the horizontal coordinate of the second feature point corresponding to the first feature point on the target area in the image to be processed based on the real position relationship, the pixel coordinates, and the horizontal conversion coefficient. The image area acquisition sub-module further includes a vertical coordinate acquisition unit, which is configured to obtain the vertical coordinate of the second feature point corresponding to the first feature point on the target area in the image to be processed based on the real position relationship, the pixel coordinates, and the vertical conversion coefficient. The image area acquisition sub-module further includes an image area acquisition unit, which is configured to determine the image area based on the horizontal coordinate and the vertical coordinate of the second feature point.

[0108] Therefore, the horizontal conversion coefficient is obtained through the horizontal edge size of the positioning identifier in the real coordinate system and the horizontal pixel size in the pixel coordinate system, and the horizontal and vertical conversion coefficients are obtained through the vertical edge size of the positioning identifier in the real coordinate system and the vertical pixel size in the pixel coordinate system. Thus, based on the real position relationship, the pixel coordinates, and the horizontal conversion coefficient, the horizontal coordinate of the second feature point corresponding to the first feature point on the target area in the image to be processed is obtained, and based on the real position relationship, the pixel coordinates, and the vertical conversion coefficient, the vertical coordinate of the second feature point corresponding to the first feature point on the target area in the image to be processed is obtained, and the image area is determined based on the horizontal coordinate and the vertical coordinate of the second feature point. Thus, the image area can be accurately calibrated, and parameter recognition can be performed within the accurately calibrated image area, which can improve the parameter recognition accuracy.

[0109] In some disclosed embodiments, the true positional relationship includes the true horizontal spacing and the true vertical spacing between the first feature point and the second feature point. The horizontal coordinate acquisition unit is specifically configured to acquire the first product of the horizontal conversion coefficient and the true horizontal spacing, and acquire the sum of the first product and the pixel coordinate of the first feature point in the horizontal direction as the horizontal coordinate of the second feature point. The vertical coordinate acquisition unit is specifically configured to acquire the second product of the vertical conversion coefficient and the true vertical spacing, and acquire the sum of the second product and the pixel coordinate of the first feature point in the vertical direction as the vertical coordinate of the second feature point.

[0110] Therefore, by acquiring the first product of the horizontal conversion coefficient of the positioning identifier in the true coordinate system and the pixel coordinate system and the true horizontal spacing between the first feature point and the second feature point, and acquiring the sum of the first product and the pixel coordinate of the first feature point in the horizontal direction as the horizontal coordinate of the second feature point; similarly, by acquiring the second product of the vertical conversion coefficient and the true vertical spacing, and acquiring the sum of the second product and the pixel coordinate of the first feature point in the vertical direction as the vertical coordinate of the second feature point. The image area can be accurately calibrated according to the pixel coordinates of the second feature point, and parameter recognition can be performed within the accurately calibrated image area, which can improve the accuracy of parameter recognition.

[0111] In some disclosed embodiments, the parameter recognition device 70 further includes a reading module, and the reading module is configured to read the true size and the true positional relationship pre-written in the positioning identifier; or read the true size and the true positional relationship of the positioning identifier input after measurement.

[0112] Therefore, before determining the image area of the target area in the image to be processed based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the feature points, reading the true size and the true positional relationship pre-written in the positioning identifier or reading the true size and the true positional relationship of the positioning identifier input after measurement can enrich the scenarios for the parameter recognition device to recognize the positioning identifier, and thus can improve the accuracy of parameter recognition in multiple scenarios.

[0113] In some disclosed embodiments, the target parameter is a digital parameter, and the digital parameter is displayed by a digital tube. The second recognition module 74 includes a division sub-module, a digit determination sub-module, and a digital parameter recognition sub-module. The division sub-module is configured to divide, based on the image area, to obtain sub-images respectively corresponding to the digits to be recognized in the digital parameter. The digit determination sub-module is configured to determine the displayed digit in the sub-image based on the pixel values on the feature lines that respectively pass through and uniquely pass through different digital tubes in the sub-image. The digital parameter recognition sub-module is configured to obtain the digital parameter based on the displayed digits in the respective sub-images.

[0114] Therefore, by partitioning, sub-images corresponding to each digit to be recognized in the digital parameter are obtained. Based on the pixel values on the feature lines that respectively pass through and uniquely pass through different digital tubes in the sub-images, the displayed digits in the sub-images are determined. Based on the displayed digits in each sub-image, the digital parameter is obtained. Therefore, through simple image transformation and pixel value recognition, the accurate reading of the digital parameter can be achieved while reducing the computational complexity in the process of digital parameter recognition.

[0115] In some disclosed embodiments, the digit determination sub-module includes a digit state determination unit for determining the display state of the digital tube passed by the corresponding feature line based on the pixel values on each feature line in the sub-image; wherein, the display state includes any one of lit and extinguished. The digit determination sub-module further includes a digit determination unit for determining the displayed digit in the sub-image based on the display states of the digital tubes passed by each feature line in the sub-image.

[0116] Therefore, by partitioning, sub-images corresponding to each digit to be recognized in the digital parameter are obtained. Based on the pixel values on the feature lines that respectively pass through and uniquely pass through different digital tubes in the sub-images, the displayed digits in the sub-images are determined. Based on the displayed digits in each sub-image, the digital parameter is obtained. Therefore, through simple image transformation and pixel value recognition, the accurate reading of the digital parameter can be achieved while reducing the computational complexity in the process of digital parameter recognition.

[0117] In some disclosed embodiments, the digit determination sub-module further includes a binarization processing unit for binarizing the sub-image. The digit state determination unit further includes a gray value detection sub-unit for detecting the gray values of each pixel point on the feature line, and the digit state determination unit further includes a digit state determination sub-unit for determining that the display state of the digital tube passed by the feature line is lit in response to the presence of a pixel point with a gray value of a preset value on the feature line, and determining that the display state of the digital tube passed by the feature line is extinguished in response to the absence of a pixel point with a gray value of a preset value on the feature line.

[0118] Therefore, by partitioning, sub-images corresponding to each digit to be recognized in the digital parameter are obtained. Based on the pixel values on the feature lines that respectively pass through and uniquely pass through different digital tubes in the sub-images, the displayed digits in the sub-images are determined. Based on the displayed digits in each sub-image, the digital parameter is obtained. Therefore, through simple image transformation and pixel value recognition, the accurate reading of the digital parameter can be achieved while reducing the computational complexity in the process of digital parameter recognition.

[0119] In some disclosed embodiments, the target parameter is a mode parameter. The parameter identification device 70 further includes a grayscale value acquisition module configured to acquire a first grayscale value of a target area displaying the mode parameter when the mode parameter is in an on state and a second grayscale value when the mode parameter is in an off state. The parameter identification device further includes a conversion module configured to convert the image data located in the image area in the image to be processed into a grayscale image. The second identification module further includes a grayscale value acquisition sub-module configured to acquire the current grayscale value of the image area, and the second identification module further includes a mode state determination sub-module configured to determine, based on the current grayscale value, the first grayscale value, and the second grayscale value, whether the current mode parameter is in an on state or an off state.

[0120] Therefore, determining whether the current mode parameter is in an on state or an off state based on the current grayscale value, the first grayscale value, and the second grayscale value means that by simply calculating the image grayscale value, the accurate identification of the mode parameter can be achieved while reducing the computational complexity in the mode parameter identification process.

[0121] In some disclosed embodiments, the mode state determination sub-module includes a grayscale threshold acquisition unit configured to fuse the first grayscale value and the second grayscale value to obtain a grayscale threshold, and the mode state determination sub-module further includes a mode state determination unit configured to determine that the current mode parameter is in an on state in response to the current grayscale value being greater than the grayscale threshold, and determine that the current mode parameter is in an off state in response to the current grayscale value being less than or equal to the grayscale threshold.

[0122] Therefore, determining whether the current mode parameter is in an on state or an off state based on the relationship between the current grayscale value and the grayscale threshold determined according to the first grayscale value and the second grayscale value means that by simply calculating and comparing the image grayscale value, the accurate identification of the mode parameter can be achieved while reducing the computational complexity in the mode parameter identification process.

[0123] Please refer to Figure 8 , Figure 8It is a schematic diagram of the framework of an embodiment of the electronic device 80 of the present application. The electronic device 80 includes a memory 82 and a processor 81 that are coupled to each other. The processor 81 is configured to execute program instructions stored in the memory 82 to implement the steps in any of the above-described parameter recognition method embodiments. Specifically, the electronic device 80 may include, but is not limited to, a microcomputer, a server, which is not limited herein. Specifically, the processor 81 is configured to control itself and the memory 82 to implement the steps in any of the above-described parameter recognition method embodiments. The processor 81 may also be referred to as a CPU (Central Processing Unit). The processor 81 may be an integrated circuit chip with signal processing capabilities. The processor 81 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. Additionally, the processor 81 may be implemented jointly by integrated circuit chips.

[0124] In the above solution, the electronic device 80 acquires an image to be processed. Among them, the image to be processed is at least taken of a display panel on the target device and a positioning identifier provided on the target device. The positioning identifier can assist in positioning the position of the display panel. Based on the image to be processed, recognition is performed to obtain the pixel coordinates of the first feature point on the positioning identifier. Based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point, the image area of the target area in the image to be processed is determined. Among them, the target area is used to display the target parameters of the target device. Based on the image area, the current target parameters of the target device are recognized. Therefore, the display panel is positioned by the positioning identifier, and based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point on the positioning identifier, the image area of the target area in the image to be processed can be accurately calibrated, and target parameter recognition can be achieved within the accurately calibrated image area, thereby improving the accuracy of parameter recognition.

[0125] Please refer to Figure 9 , Figure 8 It is a schematic diagram of the framework of an embodiment of the computer-readable storage medium 90 of the present application. The computer-readable storage medium 90 stores program instructions 91 that can be run by a processor. The program instructions 91 are used to implement the steps in the above-described parameter recognition method embodiments.

[0126] In the above solution, the computer-readable storage medium 90 obtains the image to be processed. Among them, the image to be processed is at least photographed with a display panel on the target device and a positioning identifier arranged on the target device. The positioning identifier can assist in positioning the position of the display panel. Based on the image to be processed, recognition is performed to obtain the pixel coordinates of the first feature point on the positioning identifier. Based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point, the image area of the target area in the image to be processed is determined. Among them, the target area is used to display the target parameters of the target device. Based on the image area, the current target parameters of the target device are recognized. Therefore, the display panel is positioned with the positioning identifier, and based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point on the positioning identifier, the image area of the target area in the image to be processed can be accurately calibrated, and the target parameter recognition can be realized within the accurately calibrated image area, thereby improving the accuracy of parameter recognition.

[0127] In some embodiments, the functions or modules included in the device provided by the embodiments of the present disclosure can be used to execute the methods described in the above method embodiments. The specific implementation can refer to the description of the above method embodiments. For the sake of brevity, it will not be repeated here.

[0128] The above descriptions of the various embodiments tend to emphasize the differences between the various embodiments. The same or similar parts can be referred to each other. For the sake of brevity, they will not be repeated in this article.

[0129] In several embodiments provided by the present application, it should be understood that the disclosed methods and devices can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in electrical, mechanical or other forms.

[0130] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0131] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to execute all or part of the steps of the methods in various embodiments of this application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs.

Claims

1. A parameter identification method, characterized in that, it includes: Obtain an image to be processed; wherein, the image to be processed is at least taken of a display panel on a target device and a positioning identifier arranged on the target device; Based on the image to be processed for identification, obtain the pixel coordinates of the first feature point on the positioning identifier; Based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point, determine the image area of the target area in the image to be processed; wherein, the target area is used to display the target parameter of the target device; Based on the image area, identify the current target parameter of the target device.

2. The method according to claim 1, characterized in that, The determining the image area of the target area in the image to be processed based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point includes: Based on the pixel coordinates of the first feature point on the positioning identifier, obtain the pixel size of the positioning identifier; Based on the pixel size and the true size of the positioning identifier, obtain a conversion coefficient; Based on the true positional relationship, the pixel coordinates, and the conversion coefficient, obtain the image area.

3. The method according to claim 2, characterized in that, The edges of the positioning identifier and the display panel are arranged in parallel, the true size includes a horizontal edge size and a vertical edge size, and the obtaining the pixel size of the positioning identifier based on the pixel coordinates of the first feature point on the positioning identifier includes: Based on the maximum difference in the horizontal pixel coordinates of the first feature points having the same pixel coordinates longitudinally, obtain the horizontal pixel size in the pixel size, and based on the maximum difference in the vertical pixel coordinates of the first feature points having the same pixel coordinates horizontally, obtain the vertical pixel size in the pixel size; The obtaining the conversion coefficient based on the pixel size and the true size of the positioning identifier includes: Based on the ratio of the horizontal edge size to the horizontal pixel size, obtain the horizontal conversion coefficient in the conversion coefficient, and based on the ratio of the vertical edge size to the vertical pixel size, obtain the vertical conversion coefficient in the conversion coefficient.

4. The method according to claim 2 or 3, characterized in that, The conversion coefficient includes a horizontal conversion coefficient and a vertical conversion coefficient, and the obtaining the image area based on the true positional relationship, the pixel coordinates, and the conversion coefficient includes: Based on the true positional relationship, the pixel coordinates, and the horizontal conversion coefficient, obtain the horizontal coordinate of the second feature point corresponding to the first feature point on the target area in the image to be processed, and based on the true positional relationship, the pixel coordinates, and the vertical conversion coefficient, obtain the vertical coordinate of the second feature point corresponding to the first feature point on the target area in the image to be processed; Determine the image region based on the horizontal coordinate and the vertical coordinate of the second feature point.

5. The method according to claim 4, wherein, the true positional relationship includes the true horizontal spacing between the first feature point and the second feature point, and obtaining the horizontal coordinate of the second feature point corresponding to the first feature point on the target region in the image to be processed based on the true positional relationship, the pixel coordinates, and the horizontal conversion coefficient includes: Obtain a first product of the horizontal conversion coefficient and the true horizontal spacing, and obtain the sum of the first product and the pixel coordinate of the first feature point in the horizontal direction as the horizontal coordinate of the second feature point.

6. The method according to claim 4, wherein, the true positional relationship includes the true vertical spacing between the first feature point and the second feature point, and obtaining the vertical coordinate of the second feature point corresponding to the first feature point on the target region in the image to be processed based on the true positional relationship, the pixel coordinates, and the vertical conversion coefficient includes: Obtain a second product of the vertical conversion coefficient and the true vertical spacing, and obtain the sum of the second product and the pixel coordinate of the first feature point in the vertical direction as the vertical coordinate of the second feature point.

7. The method according to claim 1, wherein, before determining the image region of the target region in the image to be processed based on the true size of the positioning identifier, the true positional relationship between the positioning identifier and the target region in the display panel, and the pixel coordinates of the first feature point, the method further includes: Reading the true size and the true positional relationship pre-written in the positioning identifier; or reading the true size and the true positional relationship of the positioning identifier input after measurement.

8. The method according to claim 1, wherein, the target parameter is a numerical parameter, and the numerical parameter is displayed by a digital tube, and identifying the current target parameter of the target device based on the image region includes: Dividing the image region to obtain sub-images respectively corresponding to each digit to be recognized in the numerical parameter; Determining the displayed digit in the sub-image based on the pixel values on the feature lines that respectively pass through and uniquely pass through different digital tubes in the sub-image; Obtaining the numerical parameter based on the displayed digits in each sub-image.

9. The method according to claim 8, wherein, determining the displayed digit in the sub-image based on the pixel values on the feature lines that respectively pass through and uniquely pass through different digital tubes in the sub-image includes: Determining the display state of the digital tube passed through by the corresponding feature line based on the pixel values on each feature line in the sub-image; wherein the display state includes any one of lit and extinguished; Determining the displayed digit in the sub-image based on the display states of the digital tubes respectively passed through by each feature line in the sub-image.

10. The method according to claim 9, wherein, Before determining the display state of the digital tube passed by the corresponding feature line based on the pixel values on each feature line in the sub-image, the method further includes: Performing binarization processing on the sub-image; The determining the display state of the digital tube passed by the corresponding feature line based on the pixel values on each feature line in the sub-image includes: Detecting the gray values of each pixel point on the feature line; In response to the presence of a pixel point with a gray value of a preset value on the feature line, determining that the display state of the digital tube passed by the feature line is lit; In response to the absence of a pixel point with a gray value of a preset value on the feature line, determining that the display state of the digital tube passed by the feature line is extinguished.

11. According to the method described in claim 1, wherein, the target parameter is a mode parameter, and before identifying the current target parameter of the target device based on the image area, the method further includes: Obtaining a first gray value when the mode parameter is in the on state and a second gray value when the mode parameter is in the off state for a target area displaying the mode parameter, and converting the image data located in the image area in the to-be-processed image into a grayscale image; The identifying the current target parameter of the target device based on the image area includes: Obtaining the current gray value of the image area; Based on the current gray value, the first gray value, and the second gray value, determining that the current state of the mode parameter is in the on state or the off state.

12. According to the method described in claim 11, wherein, the determining that the current state of the mode parameter is in the on state or the off state based on the current gray value, the first gray value, and the second gray value includes: Fusing the first gray value and the second gray value to obtain a gray threshold; In response to the current gray value being greater than the gray threshold, determining that the current state of the mode parameter is in the on state; In response to the current gray value being less than or equal to the gray threshold, determining that the current state of the mode parameter is in the off state.

13. A parameter identification device, wherein, comprises: An acquisition module, configured to acquire a to-be-processed image; wherein, the to-be-processed image at least captures a display panel on a target device and a positioning identifier provided on the target device; A first identification module, configured to perform identification based on the to-be-processed image to obtain the pixel coordinates of a first feature point on the positioning identifier; A determination module, configured to determine the image area of the target area in the to-be-processed image based on the actual size of the positioning identifier, the actual positional relationship between the positioning identifier and the target area in the display panel, and the pixel coordinates of the first feature point; wherein, the target area is used to display the target parameter of the target device; A second identification module, configured to identify the current target parameter of the target device based on the image area.

Images