A pointer instrument reading method based on visual recognition technology

Abstract

The application discloses a pointer instrument reading method based on visual recognition technology and relates to the technical field of computer vision, which obtains original image data of a pointer instrument; converts a dial image from a Cartesian coordinate system into a polar coordinate system to generate a linearized scale line image; detects scale distribution density in the linearized scale line image, triggers dynamic interpolation compensation according to scale interval variance values, and generates uniformized scale interval data; detects pointer endpoint coordinates based on a deep Hough transform; calculates pixel distance according to the uniformized scale interval data and the pointer endpoint coordinates; and calculates an actual reading according to a scale interval and a total length of a range. The application realizes fast and accurate reading recognition of the pointer instrument by combining a target detection algorithm and an image processing technology. The method has the advantages of high efficiency, accuracy and strong robustness and can be widely applied to the fields of industrial automation, smart power grids and the like.

Description

Technical Field

[0001] This invention relates to the field of computer vision technology, and in particular to a method for reading pointer-type instruments based on visual recognition technology. Background Technology

[0002] Pointer instruments have long played an indispensable role due to their simple structure, low cost, dust and water resistance, and excellent electromagnetic interference resistance. However, most pointer instrument readings still rely on manual visual interpretation, which suffers from insufficient real-time performance, low efficiency, and high safety risks. Therefore, there is an urgent need to introduce advanced machine vision technology to achieve automated reading recognition of pointer instruments. Replacing manual recognition with intelligent recognition can not only significantly improve the accuracy and efficiency of readings but also effectively reduce human error and improve measurement reliability.

[0003] Pointer instrument reading recognition typically involves three key steps: instrument positioning, dial feature extraction, and reading interpretation. In the instrument positioning stage, traditional template matching methods, relying on precise template matching, often suffer from low efficiency and slow speed, making it difficult to meet real-time requirements. During dial feature extraction, methods such as center projection, subtraction, and region growing require high image quality and are easily affected by factors such as lighting, noise, and shooting angle, resulting in insufficient robustness. Meanwhile, while the least squares method can provide some fitting accuracy, its large computational load and tendency to accumulate errors limit the speed of pointer extraction. In the reading interpretation stage, angle-based methods suffer from errors in measuring the angle between the pointer and the scale, leading to less than ideal reading accuracy. Summary of the Invention

[0004] The purpose of this section is to outline some aspects of embodiments of the present invention and to briefly describe some preferred embodiments. Simplifications or omissions may be made in this section, as well as in the abstract and title of this application, to avoid obscuring the purpose of these documents; however, such simplifications or omissions should not be construed as limiting the scope of the invention.

[0005] In view of the problems existing in the prior art, the present invention is proposed.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for reading pointer-type instruments based on visual recognition technology, comprising the following steps:

[0007] Step 1: Acquire the raw image data of the pointer-type instrument, locate the dial area using the target detection model, and extract the dial contour geometric parameters;

[0008] Step 2: Based on the type of the dial outline geometric parameters, select the corresponding polar coordinate transformation rule to convert the dial image from the Cartesian coordinate system to the polar coordinate system, generating a straightened scale line image;

[0009] Step 3: Detect the scale distribution density in the linear scale line image, trigger dynamic interpolation compensation based on the scale spacing variance value, and generate uniform scale spacing data;

[0010] Step 4: Detect the pointer endpoint coordinates based on the depth Hough transform, calculate the pixel distance based on the uniform scale spacing data and pointer endpoint coordinates, and calculate the actual reading based on the scale spacing and total range length.

[0011] As a preferred embodiment of the pointer-type instrument reading method based on visual recognition technology described in this invention, when the dial outline is circular, the coordinates of the instrument's center are determined, and each point in the image is transformed from the Cartesian coordinate system to the polar coordinate system. The transformation formula is as follows: ;

[0012] in, This represents the distance of each point in the image from the origin. This represents the angle between the line connecting a point in the image to the origin and the positive axis. By transforming the coordinates, the circular dial is converted into a rectangular layout, making the scale lines parallel straight lines.

[0013] As a preferred embodiment of the pointer-type instrument reading method based on visual recognition technology described in this invention, when the dial outline is elliptical, the major axis a and minor axis b of the elliptical dial are determined, and its Cartesian ellipse equation is: ;

[0014] Cartesian coordinates Convert to polar coordinates: , Substituting this into the equation of the ellipse and simplifying it, we obtain the polar radius formula. This formula maps all points on the ellipse to the polar coordinate system.

[0015] As a preferred embodiment of the pointer-type instrument reading method based on visual recognition technology described in this invention, when the dial outline is a polygon, the side length of the polygon is determined, the entire circumference is divided equally according to the number of sides n, and each sector corresponds to an angle. This ensures that each edge corresponds to a sector;

[0016] Within each sector, the polar radius r is determined based on the actual length of the edge. Dynamic adjustment, the formula is: ;

[0017] in, This represents the local angle within the current sector. This formula ensures that the scale lines on each side are distributed linearly in the polar coordinate system.

[0018] As a preferred embodiment of the pointer-type instrument reading method based on visual recognition technology described in this invention, the dynamic interpolation compensation method specifically includes:

[0019] First, extract the pixel distance between adjacent tick marks. Then, the image is divided into multiple intervals according to the angle, and the variance of the scale spacing of all intervals is calculated. The variance reflects the degree of dispersion of the scale distribution.

[0020] If the variance is greater than or equal to the first threshold, it is determined to be a highly discrete distribution, triggering nonlinear interpolation;

[0021] If the variance is less than the first threshold, it is determined to be a low discrete distribution, and linear interpolation is triggered;

[0022] As a preferred embodiment of the pointer-type instrument reading method based on visual recognition technology described in this invention, the specific process of the depth Hough transform detection is as follows:

[0023] S1: Feature Extraction: Extract depth features of the image using a convolutional neural network (CNN), including pointer direction and tick mark distribution;

[0024] S2: Feature mapping to parameter space: Calculate different angles for each feature point. Given the linear parameter r, we obtain the parameter space. ;

[0025] S3: Voting Accumulation: For each feature point's feature value (the confidence score of the CNN output), votes are accumulated in the parameter space to form a cumulative matrix. The formula is: ;

[0026] in, It is the Dirac function, used to determine... Does it meet the current requirements? ; For eigenvalues;

[0027] S4: Peak Detection: In the cumulative matrix The peak value is found in the line, and the position of the peak value is the detected line parameter.

[0028] As a preferred embodiment of the pointer-type instrument reading method based on visual recognition technology described in this invention, the following steps are taken: determining the linear parameters of the pointer and the 0-scale based on the peak value, and determining the coordinates of the pointer's endpoint. and the coordinates of the 0 scale position Then calculate the pixel distance between the coordinates of the two points. : ;

[0029] Based on the known scale spacing pixels, total range length is The scale unit indicates the value displayed by the pointer. It can be calculated using the following formula: .

[0030] As a preferred embodiment of the pointer-type instrument reading method based on visual recognition technology described in this invention, when the dial outline is elliptical or polygonal, a correction factor is introduced. The value of the pointer Perform error compensation;

[0031] For the oval dial outline, Through ellipticity deviation The shape asymmetry is quantified, the reading deviation caused by elliptical stretching is corrected, and the final reading result is output. ;

[0032] For polygonal dial outlines , The side length of a polygonal dial is represented by the side length difference rate. The system calculates the number of sides (n), compensates for the deviation in scale spacing caused by unequal side lengths, and outputs the final reading result. .

[0033] The present invention also discloses a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described pointer-type instrument reading method based on visual recognition technology.

[0034] The present invention also discloses a computer-readable storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described pointer-type instrument reading method based on visual recognition technology.

[0035] The beneficial effects of this invention are:

[0036] 1. This invention achieves rapid and accurate reading recognition of pointer-type instruments by combining target detection algorithms and image processing technology. This method has advantages such as high efficiency, accuracy, and robustness, and can be widely applied in fields such as industrial automation and smart grids.

[0037] 2. This invention uses a dynamic polar coordinate transformation formula to convert the scale lines of irregularly shaped dials such as ellipses and polygons into a straight line layout, thus solving the detection failure problem caused by shape limitations in traditional methods.

[0038] 3. Based on the adaptive selection of interpolation strategy (linear or nonlinear) according to the variance of the scale interval, virtual scale lines are inserted in sparse areas and redundant scales are merged in dense areas, thereby reducing non-uniform distribution error and significantly improving reading accuracy. Attached Figure Description

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

[0040] Figure 1 This is a schematic diagram of the overall process of a pointer-type instrument reading method based on visual recognition technology proposed in Embodiment 1 of the present invention;

[0041] Figure 2 This is a schematic diagram of the YOLOv5s deep network model framework in the pointer-type instrument reading method based on visual recognition technology proposed in this invention;

[0042] Figure 3 This is a schematic diagram of the network model framework of the deep Hough transform in the pointer instrument reading method based on visual recognition technology proposed in this invention. Detailed Implementation

[0043] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0044] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0045] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0046] Example 1

[0047] Reference Figures 1-3 As an embodiment of the present invention, a method for reading pointer-type instruments based on visual recognition technology is provided. This method includes the following steps:

[0048] Step 1: Acquire the raw image data of the pointer instrument, locate the dial area using the target detection model (YOLOv5s), and extract the dial contour geometric parameters.

[0049] Specifically, in the image preprocessing stage of the raw image data, rotation correction needs to be performed on the acquired instrument images. Given that the actual acquired instrument images may be tilted, this directly affects the accuracy of subsequent instrument positioning and reading recognition. Therefore, the `cv2.rotate` function from the OpenCV library is used to perform precise rotation correction on the image, ensuring that the instrument image is horizontal or vertical, laying a high-quality image foundation for subsequent processing. A circular mask is created by calling the `create_circular_mask` function and applied to the image. The purpose of this step is to define the Region of Interest (ROI) to eliminate background interference. The shape and size of the mask can be adjusted according to actual needs to ensure that the target region is completely preserved while removing unnecessary background information. This step plays a crucial role in improving the signal-to-noise ratio of the image and reducing the amount of subsequent computation.

[0050] Image Preprocessing and Feature Enhancement Methods: In the image preprocessing stage, this invention performs rotation correction on the acquired instrument images. Given that the actual acquired instrument images may be tilted, which directly affects the accuracy of subsequent instrument positioning and reading recognition, the `cv2.rotate` function from the OpenCV library is used to perform precise rotation correction on the image, ensuring that the instrument image is horizontal or vertical, laying a high-quality image foundation for subsequent processing. A circular mask is created by calling the `create_circular_mask` function and applied to the image. The purpose of this step is to define the Region of Interest (ROI) to eliminate background interference. The shape and size of the mask can be adjusted according to actual needs to ensure that the target region is completely preserved while removing unnecessary background information. This step plays a crucial role in improving the signal-to-noise ratio of the image and reducing the subsequent computational load.

[0051] After image preprocessing, this invention employs an enhancement process, applying a contrast-limited adaptive histogram equalization (CLAHE) algorithm to significantly improve image contrast. This process makes the bright and dark areas of the image clearer, thereby enhancing the visual effect. Next, binarization converts the image to black and white, further improving brightness and clarity, effectively highlighting key features. Morphological operations, including dilation and erosion techniques, are used to strengthen key image features, making them more prominent and facilitating subsequent recognition processing. The core objective of the feature enhancement stage is to improve the algorithm's accuracy and robustness in recognizing instrument readings, ensuring stable and accurate reading recognition under various environments and conditions.

[0052] After feature enhancement, this invention performs filtering and noise reduction. In practical applications, the acquired instrument images are often affected by noise interference, such as changes in lighting and electronic noise. This noise reduces image quality and consequently affects the algorithm's accurate recognition of instrument features. Therefore, this invention employs Gaussian filtering to remove noise from the image, improve image clarity and signal-to-noise ratio, and create favorable conditions for subsequent instrument reading recognition.

[0053] Step 2: Convert the dial image from Cartesian coordinates to polar coordinates to generate a straightened scale line image. Perform a polar coordinate transformation on the image; this is a mathematical method to convert an image from Cartesian to polar coordinates. In polar coordinates, each point in the image is represented by its distance from the origin (radial distance r) and the angle (angle θ) between the line connecting it to the origin and the positive axis. For a circular dial, the polar coordinate transformation converts the scale lines into parallel straight lines in a rectangular layout, significantly simplifying the scale line detection process.

[0054] This invention first centers the image to ensure that the center of the instrument is located at the geometric center of the image. Then, it applies the polar coordinate transformation formula to transform each point in the image from the Cartesian coordinate system to the polar coordinate system:

[0055] ;

[0056] ;

[0057] In this process, the present invention selects appropriate methods based on the specific circumstances of the instrument. and The range of values ​​is determined to ensure that the transformed image completely covers all the tick marks. Through polar coordinate transformation, the tick marks, which were originally closely arranged and difficult to detect directly in the circular layout, are stretched into parallel and easily identifiable straight lines in the rectangular layout. Subsequently, this invention uses depth Hough linear transformation technology to detect these tick marks, determining their existence and parameters by statistically counting the votes.

[0058] Dashboard element acquisition: First, the Hough Circle Transform algorithm is used to determine the coordinates of the center of the dial. This algorithm detects edge points in the image and applies the Hough Transform principle to accurately identify the position of the center, providing a crucial reference for subsequent processing. The Hough Circle Transform uses the parametric equation of a circle: ;

[0059] Calculate the center coordinates of all edge points in the image. and radius The votes are accumulated in the Hough space. The parameters corresponding to the peak point are the center position and radius of the instrument, thus achieving precise positioning of the instrument.

[0060] Step 3: Detect the scale distribution density in the linear scale image, trigger dynamic interpolation compensation based on the scale spacing variance value, and generate uniform scale spacing data.

[0061] Specifically, the dynamic interpolation compensation method includes:

[0062] First, extract the pixel distance between adjacent tick marks. Then, the image is divided into multiple intervals according to the angle, and the variance of the scale spacing of all intervals is calculated. The variance reflects the degree of dispersion of the scale distribution.

[0063] If the variance is greater than or equal to the first threshold, it is determined to be a highly discrete distribution, triggering nonlinear interpolation;

[0064] If the variance is less than the first threshold, it is determined to be a low discrete distribution, and linear interpolation is triggered;

[0065] Step 4: Detect the pointer endpoint coordinates based on the depth Hough transform, calculate the pixel distance based on the uniform scale spacing data and pointer endpoint coordinates, and calculate the actual reading based on the scale spacing and total range length.

[0066] Specifically, the process of the deep Hough transform detection is as follows:

[0067] S1: Feature Extraction: Extract depth features of the image using a convolutional neural network (CNN), including pointer direction and tick mark distribution;

[0068] S2: Feature mapping to parameter space: Calculate different angles for each feature point. Given the linear parameter r, we obtain the parameter space. ;

[0069] S3: Voting Accumulation: For each feature point's feature value (the confidence score of the CNN output), votes are accumulated in the parameter space to form a cumulative matrix. The formula is: ;

[0070] in, It is the Dirac function, used to determine... Does it meet the current requirements? ; For eigenvalues;

[0071] S4: Peak Detection: In the cumulative matrix The peak value is found in the line; the position of the peak value is the detected line parameter. Based on the peak value, the line parameter between the pointer and the 0 mark is determined, and the coordinates of the pointer's endpoint are determined. and the coordinates of the 0 scale position Then calculate the pixel distance between the coordinates of the two points. : ;

[0072] Based on the known scale spacing Pixels (the distance between pixels adjusted using dynamic interpolation compensation methods), total range length is The scale unit indicates the value displayed by the pointer. It can be calculated using the following formula: .

[0073] Example 2

[0074] The difference from Embodiment 1 is that the dial outline is elliptical or polygonal.

[0075] When the dial outline is elliptical, the major axis a and minor axis b of the elliptical dial are determined, and its Cartesian ellipse equation is: ;

[0076] Cartesian coordinates Convert to polar coordinates: , Substituting this into the equation of the ellipse and simplifying it, we obtain the polar radius formula. ;

[0077] This formula maps all points on the ellipse to the polar coordinate system.

[0078] When the dial outline is polygonal, determine the side length of the polygon, divide the entire circumference into equal parts with n sides, and assign each sector an angle. This ensures that each edge corresponds to a sector;

[0079] Within each sector, the polar radius r is determined based on the actual length of the edge. Dynamic adjustment, the formula is: ;

[0080] in, This represents the local angle within the current sector. This formula ensures that the scale lines on each side are distributed linearly in the polar coordinate system.

[0081] Furthermore, the difference between the major and minor axes of the ellipse (a≠b) will lead to non-uniformity in the distribution of scale lines after polar coordinate transformation, and the difference in the side length of the polygon will lead to an imbalance in the proportion of the sector region after polar coordinate transformation. Therefore, a correction factor needs to be introduced. The value of the pointer Perform error compensation;

[0082] For the oval dial outline, Through ellipticity deviation The shape asymmetry is quantified, the reading deviation caused by elliptical stretching is corrected, and the final reading result is output. ;

[0083] For polygonal dial outlines , The side length of a polygonal dial is represented by the side length difference rate. The system calculates the number of sides (n), compensates for the deviation in scale spacing caused by unequal side lengths, and outputs the final reading result. .

[0084] This embodiment also provides a computer device applicable to a pointer-type instrument reading method based on visual recognition technology, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the pointer-type instrument reading method based on visual recognition technology proposed in the above embodiment.

[0085] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0086] This embodiment also provides a storage medium storing a computer program. When executed by a processor, the program implements a pointer-type instrument reading method based on visual recognition technology as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0087] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for reading pointer-type instruments based on visual recognition technology, characterized in that, Includes the following steps: Step 1: Acquire the raw image data of the pointer-type instrument, locate the dial area using the target detection model, and extract the dial contour geometric parameters; Step 2: Based on the type of the dial outline geometric parameters, select the corresponding polar coordinate transformation rule to convert the dial image from the Cartesian coordinate system to the polar coordinate system, generating a straightened scale line image; Step 3: Detect the scale distribution density in the linear scale line image, trigger dynamic interpolation compensation based on the scale spacing variance value, and generate uniform scale spacing data; The dynamic interpolation compensation method specifically includes: First, extract the pixel distance between adjacent tick marks. Then, the image is divided into multiple intervals according to the angle, and the variance of the scale spacing of all intervals is calculated. The variance reflects the degree of dispersion of the scale distribution. If the variance is greater than or equal to the first threshold, it is determined to be a highly discrete distribution, triggering nonlinear interpolation; If the variance is less than the first threshold, it is determined to be a low discrete distribution, and linear interpolation is triggered; Step 4: Detect the pointer endpoint coordinates based on depth Hough transform, calculate the pixel distance based on the uniformized scale spacing data and pointer endpoint coordinates, and calculate the actual reading based on the scale spacing and total range length. When the dial outline is elliptical or polygonal, a correction factor is introduced. The value of the pointer Perform error compensation; For the oval dial outline, In the formula, a and b represent the major and minor axes of the elliptical dial, respectively, determined by the ellipticity deviation. The shape asymmetry is quantified, the reading deviation caused by elliptical stretching is corrected, and the final reading result is output. ; For polygonal dial outlines , The side length of a polygonal dial is represented by the side length difference rate. The system calculates the number of sides (n), compensates for the deviation in scale spacing caused by unequal side lengths, and outputs the final reading result. .

2. The pointer-type instrument reading method based on visual recognition technology according to claim 1, characterized in that: When the dial outline is circular, determine the coordinates of the instrument's center, and transform each point in the image from the Cartesian coordinate system to the polar coordinate system. The transformation formula is as follows: ； in, This represents the distance of each point in the image from the origin. This represents the angle between the line connecting a point in the image to the origin and the positive axis. By transforming coordinates, the circular dial is converted into a rectangular layout, making the scale lines parallel straight lines.

3. The pointer-type instrument reading method based on visual recognition technology according to claim 1, characterized in that: When the dial outline is elliptical, the major axis a and minor axis b of the elliptical dial are determined, and its Cartesian ellipse equation is: ; Cartesian coordinates Convert to polar coordinates: , Substituting this into the equation of the ellipse and simplifying it, we obtain the polar radius formula. This formula maps all points on the ellipse to the polar coordinate system.

4. The pointer-type instrument reading method based on visual recognition technology according to claim 1, characterized in that: When the dial outline is polygonal, determine the side length of the polygon, divide the entire circumference into equal parts with n sides, and assign each sector an angle. This ensures that each edge corresponds to a sector; Within each sector, the polar radius r is determined based on the actual length of the edge. Dynamic adjustment, the formula is: ； in, This represents the local angle within the current sector. This formula ensures that the scale lines on each side are distributed linearly in the polar coordinate system.

5. A method for reading pointer-type instruments based on visual recognition technology according to any one of claims 1-4, characterized in that: The specific process of the depth Hough transform detection is as follows: S1: Feature Extraction: Extract depth features of the image through a convolutional neural network, including pointer direction and tick mark distribution; S2: Feature mapping to parameter space: Calculate different angles for each feature point. Given the linear parameter r, we obtain the parameter space. ; S3: Voting Accumulation: For each feature point, the eigenvalues ​​are accumulated in the parameter space to form a cumulative matrix. The formula is: ; in, It is the Dirac function, used to determine... Does it meet the current requirements? ; For eigenvalues; S4: Peak Detection: In the cumulative matrix The peak value is found in the line, and the position of the peak value is the detected line parameter.

6. The pointer-type instrument reading method based on visual recognition technology according to claim 5, characterized in that: Determine the pointer and the straight line parameters at the 0 mark based on the peak value, and then determine the coordinates of the pointer's endpoint. and the coordinates of the 0 scale position Then calculate the pixel distance between the coordinates of the two points. : ； Based on the known scale spacing pixels, total range length is The scale unit indicates the value displayed by the pointer. Calculated using the following formula: .

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the pointer-type instrument reading method based on visual recognition technology as described in claim 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the pointer-type instrument reading method based on visual recognition technology as described in claim 6.

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