A method for generating multi-dimensional code information based on spherical coordinate transformation

Abstract

The present invention relates to the technical fields of computer graphics and image processing, and discloses a multi-dimensional code information generation method based on spherical coordinate transformation. By establishing a multi-dimensional data acquisition module, a multi-dimensional data preprocessing module, a multi-dimensional data analysis module, a multi-dimensional result evaluation module, a multi-dimensional strategy optimization module, a multi-dimensional strategy execution module, and a multi-dimensional feedback adjustment module, the multi-dimensional data acquisition module is responsible for obtaining raw data, the multi-dimensional data preprocessing module performs preliminary processing on the acquired data, the multi-dimensional data analysis module calculates the processed data and deeply mines data features to obtain a comprehensive analysis result, the multi-dimensional result evaluation module determines whether the analysis result meets the standard, the multi-dimensional strategy optimization module adjusts the strategy according to the evaluation result, the multi-dimensional strategy execution module generates a multi-dimensional code based on the optimized strategy, and the multi-dimensional feedback adjustment module further improves the entire method through the actual application feedback of the multi-dimensional strategy execution module.

Description

Technical Field

[0001] The present invention relates to the technical field of computer graphics and image processing, and specifically provides a method for generating multi-dimensional code information based on spherical coordinate transformation. Background Art

[0002] With the rapid development of information technology, as an efficient information storage and transmission tool, multi-dimensional codes have been widely used in many fields such as data encryption, identity recognition, Internet of Things, and geographic information systems. Traditional multi-dimensional code information generation methods are mainly based on two-dimensional plane coding, which stores information by arranging points, lines, or graphics in a plane space. However, this method has obvious limitations: on the one hand, two-dimensional plane coding is difficult to make full use of the geometric characteristics of three-dimensional space, resulting in a low information density and difficulty in meeting the growing information storage requirements; on the other hand, when dealing with spherical or complex curved surfaces, traditional methods require additional projections or conversions, which not only increase the computational complexity but also easily introduce deformations or errors, thus affecting the accuracy and reliability of information.

[0003] In addition, in terms of feature extraction, traditional methods usually require complex preprocessing or conversion steps, with low efficiency and difficulty in quickly extracting key information, further limiting their application in complex scenarios. Therefore, how to break through the limitations of traditional methods and develop a multi-dimensional code information generation method that can make full use of the geometric characteristics of three-dimensional space, adapt to complex curved surface structures, and has high-efficiency feature extraction capabilities has become an important research direction.

[0004] The method for generating multi-dimensional code information based on spherical coordinate transformation emerges as the times require. As a coordinate system that naturally describes three-dimensional space, the spherical coordinate system can effectively solve the problems of low information density, poor geometric adaptability, and low feature extraction efficiency existing in traditional methods. Summary of the Invention

[0005] (1) Technical Problems to be Solved

[0006] Aiming at the deficiencies of the prior art, the present invention provides a method for generating multi-dimensional code information based on spherical coordinate transformation, which has the advantages of high information density, strong geometric adaptability, and high-efficiency feature extraction, and solves the problems of low information density, poor geometric adaptability, and low feature extraction efficiency existing in traditional methods.

[0007] (2) Technical Solutions

[0008] To achieve the above object, the present invention provides the following technical solutions: A multi-dimensional code information generation method based on spherical coordinate transformation, comprising the following steps: Step 1, construct a multi-dimensional data acquisition module, a multi-dimensional data preprocessing module, a multi-dimensional data analysis module, a multi-dimensional result evaluation module, a multi-dimensional strategy optimization module, a multi-dimensional strategy execution module, and a multi-dimensional feedback adjustment module, and establish the connection between each module; Step 2, obtain the original data containing three-dimensional coordinate information, surface slope feature data, and surrounding environment information through the multi-dimensional data acquisition module; Step 3, perform preliminary processing on the acquired original data through the multi-dimensional data preprocessing module to represent the original data in spherical coordinates; Step 4, calculate the preliminary processed original data through the multi-dimensional data analysis module, and mine and obtain data features to obtain a comprehensive analysis result containing spherical coordinates, the information density of encoded data, and the influence degree of external features on the generation of multi-dimensional code information; Step 5, judge whether the comprehensive analysis result meets the standard in the current environmental scenario through the multi-dimensional result evaluation module; Step 6, delimit the unqualified part of the comprehensive analysis result in the judged result through the multi-dimensional strategy optimization module, and adjust and update the corresponding strategy for the unqualified part; Step 7, generate a multi-dimensional code according to the updated strategy through the multi-dimensional strategy execution module; Step 8, further improve the entire method through the multi-dimensional feedback adjustment module according to the feedback after the execution of the multi-dimensional strategy execution module.

[0009] Preferably, the multi-dimensional data acquisition module includes an information input unit, a three-dimensional data acquisition unit, a surface feature acquisition unit, and an environmental data acquisition unit.

[0010] Preferably, the information input unit introduces the original data to be encoded into the multi-dimensional data acquisition module through an access to a text file input port, an image acquisition device interface, and a digital signal receiving channel; the three-dimensional data acquisition unit scans the target object through a deployed three-dimensional sensor or other devices with three-dimensional measurement functions, and acquires the three-dimensional coordinate information of the target object in the Cartesian coordinate system as the original data.

[0011] Preferably, the surface feature acquisition unit uses laser scanning technology or structured light measurement technology to project a specific structured light pattern onto the surface, and acquires the surface slope feature data according to the deformation of the reflected light as the original data; the environmental data acquisition unit arranges temperature sensors and humidity sensors to collect the temperature parameters and humidity parameters of the surrounding environment during the acquisition of the multi-dimensional code in real time as the original data.

[0012] Preferably, the multi-dimensional data preprocessing module preprocesses the original data and assigns data numbers respectively, including: after numbering, obtaining the total information volume stored in the code, the covered volume of the code in the spherical coordinate system, the residual of the spherical coordinate transformation, the slope and curvature, and the temperature and humidity actually measured by the sensor; the total information volume stored in the code and the covered volume of the code in the spherical coordinate system are numbered as the first identifier and the second identifier respectively, the temperature and humidity actually measured by the sensor are numbered as the third identifier and the fourth identifier respectively, the residual of the spherical coordinate transformation is numbered as the fifth identifier, and the slope and curvature are numbered as the sixth identifier and the seventh identifier respectively.

[0013] Preferably, the multi-dimensional data analysis module includes a spherical coordinate transformation unit, an information density analysis unit, and a feature weight analysis unit.

[0014] Preferably, the spherical coordinate transformation unit calculates the spherical coordinates including the radial distance, the pitch angle value, and the azimuth angle value according to the preprocessed Cartesian coordinates, specifically including: squaring and adding the three components of the Cartesian coordinates respectively, and taking the square root of the added result to obtain the radial distance;

[0015] Taking the vertical component in the Cartesian coordinate system as the numerator and the radial distance as the denominator to obtain a first ratio, and taking the arccosine function value of the first ratio to obtain the pitch angle value; taking the longitudinal component in the horizontal direction in the Cartesian coordinate system as the numerator and the transverse component in the horizontal direction as the denominator to obtain a second ratio, and taking the arctangent function value of the second ratio to obtain the azimuth angle value.

[0016] Preferably, the information density analysis unit calculates the information density of the encoded data, specifically including: obtaining the information density by taking the ratio of the total information volume stored in the code corresponding to the first identifier to the covered volume of the code corresponding to the second identifier.

[0017] Preferably, the feature weight analysis unit calculates the influence degree of external features on the generation of multi-dimensional code information, specifically including: determining the temperature and humidity during sensor calibration as the reference benchmark, based on the difference between the actual temperature and the reference temperature and the difference between the actual humidity and the reference humidity, multiplying by the corresponding temperature weight coefficient and humidity weight coefficient respectively, and taking the sum of the product results as the denominator of the environmental factor correction term to characterize the correction degree of environmental changes on the feature weight; obtaining the residual information during the spherical coordinate transformation, adding the minimum value correction term to the residual information and taking the reciprocal to characterize the adjustment factor of the influence degree of coordinate transformation errors on external features; performing a square root operation on the square of the slope value and the curvature value of the surface to obtain the complexity index of the surface features to characterize the intensity of the change of the surface features;

[0018] Take the pre-calibrated value as the base number and subtract the result of multiplying the correction degree, the adjustment factor, and the intensity of change to obtain the influence degree.

[0019] Preferably, the multi-dimensional result evaluation module determines whether the comprehensive analysis result meets the standard, including: performing a rationality analysis on the spatial position distribution according to spherical coordinates to determine whether the layout of the generated multi-dimensional code in the three-dimensional space conforms to the expected coding rules and application scenario requirements; and / or

[0020] evaluating the information storage efficiency according to the information density to determine whether the current information density reaches the optimum; and / or judging whether the interference of external factors and coordinate conversion factors on the coding result is within the acceptable range according to the influence degree of the generation of multi-dimensional code information.

[0021] Compared with the prior art, the present invention provides a method for generating multi-dimensional code information based on spherical coordinate transformation, which has the following beneficial effects:

[0022] 1. By establishing a multi-dimensional data acquisition module, a multi-dimensional data preprocessing module, a multi-dimensional data analysis module, a multi-dimensional result evaluation module, a multi-dimensional strategy optimization module, a multi-dimensional strategy execution module, and a multi-dimensional feedback adjustment module, the modules cooperate with each other to form a complete information to generate an infrastructure, so as to clarify the division of labor and cooperation relationship between the modules, and ensure that the entire process from data collection to the final generation and optimization of the multi-dimensional code can be carried out efficiently and orderly. Therefore, the structured method of the present invention is beneficial to improving the operation efficiency and stability of the entire system.

[0023] 2. By adopting the spherical coordinate transformation technology, the present invention converts the data in the three-dimensional Cartesian coordinate system into the data representation in the spherical coordinate system, which not only makes the layout of the generated multi-dimensional code in the three-dimensional space more conform to the expected coding rules and application scenario requirements, but also provides a method that can uniformly and concisely describe the position of points in the three-dimensional space. This method helps to deeply explore the geometric properties and internal relationships of data in the three-dimensional space, and provides strong support for the development of related theories.

[0024] 3. By quantitatively analyzing the influence degree of environmental factors such as temperature and humidity on the generation of multi-dimensional code information, the present invention calculates the influence degree of external characteristics on the generation of multi-dimensional code information , and then adjusts and optimizes the coding strategy according to the magnitude of the influence degree of external characteristics on the generation of multi-dimensional code information to ensure that high-quality multi-dimensional codes can be generated for multi-dimensional data under different environmental conditions. At the same time, through the influence degree of external characteristics on the generation of multi-dimensional code information Construct a risk warning system based on the high and low value range of Brief Description of the Drawings

[0025] Figure 1 This is the flowchart of the method of the present invention. Detailed Embodiments

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0027] Please refer to Figure 1 , a multi-dimensional code information generation method based on spherical coordinate transformation, comprising the following steps:

[0028] Step 1: Construct a multi-dimensional data acquisition module, a multi-dimensional data preprocessing module, a multi-dimensional data analysis module, a multi-dimensional result evaluation module, a multi-dimensional strategy optimization module, a multi-dimensional strategy execution module, and a multi-dimensional feedback adjustment module, and establish the connection between each module.

[0029] Step 2: Obtain the original data containing three-dimensional coordinate information, surface slope feature data, and surrounding environment information through the multi-dimensional data acquisition module.

[0030] Step 3: Conduct preliminary processing on the acquired original data through the multi-dimensional data preprocessing module to represent the original data in spherical coordinates.

[0031] Step 4: Calculate the preliminarily processed original data through the multi-dimensional data analysis module, and mine and obtain data features to obtain a comprehensive analysis result containing the influence degree of spherical coordinates, coding data information density, and external features on the generation of multi-dimensional code information.

[0032] Step 5: Determine whether the comprehensive analysis result meets the standard in the current environmental scenario through the multi-dimensional result evaluation module.

[0033] Step 6: Delimit the unqualified part of the comprehensive analysis result in the judged result through the multi-dimensional strategy optimization module, and adjust and update the corresponding strategy for the unqualified part.

[0034] Step 7: Generate the multi-dimensional code according to the updated strategy through the multi-dimensional strategy execution module.

[0035] Step 8: Further improve the entire method through the multi-dimensional feedback adjustment module according to the feedback after the execution of the multi-dimensional strategy execution module.

[0036] Here, a multi-dimensional data acquisition module, a multi-dimensional data preprocessing module, a multi-dimensional data analysis module, a multi-dimensional result evaluation module, a multi-dimensional strategy optimization module, a multi-dimensional strategy execution module, and a multi-dimensional feedback adjustment module are constructed, and connections are established at the method level through data flow and control flow. The data flow is responsible for transmitting multi-dimensional information in a predefined order; the control flow is responsible for triggering parameter adjustments in the preprocessing and analysis links in real-time when the evaluation result does not meet the standard, so as to ensure that the entire processing chain is always controllable and traceable.

[0037] The multi-dimensional data acquisition module obtains three-dimensional Cartesian coordinate data, surface slope information, surface curvature information, and the temperature and humidity values at the moment of acquisition at one time. Through timestamp synchronization means, various types of data are bound at the moment of acquisition to avoid error accumulation caused by time series misalignment during subsequent conversion and analysis processes.

[0038] The multi-dimensional data preprocessing module first converts the three-dimensional Cartesian coordinate information into spherical coordinate representation and records the conversion residuals; then performs denoising and smoothing processing on the slope and curvature data; finally, generates the first identifier to the seventh identifier according to a predefined numbering rule. After this step of processing, all spatial data has been unified into the spherical coordinate domain and is accompanied by environmental information, laying a foundation for subsequent feature analysis.

[0039] The multi-dimensional data analysis module calculates the coding information density based on the data in the spherical coordinate domain and quantifies the influence degree of external features based on the temperature and humidity offset. At the same time, the surface complexity is evaluated using the slope and curvature values, and a comprehensive index reflecting the geometric change amplitude is synthesized. The analysis results are output in a structured record form, providing a quantifiable basis for the next step of evaluation.

[0040] The multi-dimensional result evaluation module determines whether the comprehensive analysis result meets the standard according to a preset threshold. It is determined to meet the standard when the information density reaches the lower limit and the influence degree of external features is within the safe range, and vice versa. This evaluation logic ensures that when any abnormality occurs in the spatial layout, environmental fluctuations, or surface complexity, the subsequent process is blocked in a timely manner to prevent the generation of distorted multi-dimensional codes.

[0041] When receiving a non-compliance signal, the multi-dimensional strategy optimization module synchronously adjusts the strategy from three aspects: temperature and humidity weight, residual correction coefficient, and coding density parameter; when receiving a compliance signal, only the strategy history record is updated to shorten the subsequent calculation time. This dual-path adjustment method not only ensures rapid convergence in abnormal states but also avoids unnecessary computational burdens in normal states.

[0042] The multi-dimensional policy execution module generates multi-dimensional codes based on the updated policy. The generation process is stratified according to the spherical coordinate radius, and then the coding units are arranged in the order of azimuth angle to ensure uniform spatial distribution and meet the information density target. This layout method makes full use of the geometric characteristics of three-dimensional space to increase the information loading capacity per unit volume.

[0043] The multi-dimensional feedback adjustment module records the core parameters and evaluation results during the generation process, and writes the information back to the preprocessing module and the analysis module. If the unqualified results occur twice consecutively, a risk warning will be triggered immediately to prompt checking the acquisition accuracy and environmental status. Through this closed-loop feedback, this method can remain stable during long-term operation and complete adaptive correction before the problem spreads.

[0044] The multi-dimensional data acquisition module includes an information input unit, a three-dimensional data acquisition unit, a surface feature acquisition unit, and an environmental data acquisition unit.

[0045] The information input unit introduces the original information (text, image, number) to be encoded into the multi-dimensional data acquisition module by accessing the text file input port, the image acquisition device interface (camera), and the digital signal receiving channel; the three-dimensional data acquisition unit scans the target object through the deployment of three-dimensional sensors (such as lidar) or other devices with three-dimensional measurement functions to acquire the three-dimensional coordinate information of the target object in the Cartesian coordinate system , and the information input unit and the three-dimensional data acquisition unit transmit the acquired data to the multi-dimensional data preprocessing module for preprocessing. The three-dimensional coordinate information in the Cartesian coordinate system after preprocessing is transformed into .

[0046] The surface feature acquisition unit uses laser scanning technology or structured light measurement technology to project a specific structured light pattern onto the surface, and acquires the surface slope feature data according to the deformation of the reflected light. The environmental data acquisition unit arranges temperature sensors and humidity sensors to collect the temperature and humidity parameters of the surrounding environment during the generation of multi-dimensional codes in real time. The surface feature acquisition unit and the environmental data acquisition unit transmit the acquired data to the multi-dimensional data preprocessing module for preprocessing.

[0047] The multi-dimensional data preprocessing module preprocesses the data collected by the information input unit, the three-dimensional data acquisition unit, the surface feature acquisition unit, and the environmental data acquisition unit respectively, and numbers the data. After numbering, the total amount of information stored after encoding, the volume covered by the encoding in the spherical coordinate system, the residual of the spherical coordinate transformation, the slope, the curvature, the temperature and humidity actually measured by the sensor are obtained. The total amount of information stored after encoding and the volume covered by the encoding in the spherical coordinate system are numbered as the first identifier and the second identifier , and the temperature and humidity actually measured by the sensor are numbered as the third identifier , the fourth identifier , and the residual number for spherical coordinate transformation is the fifth identifier , and the slope and curvature are numbered as the sixth identifier and the seventh identifier .

[0048] The multi-dimensional data analysis module includes a spherical coordinate transformation unit, an information density analysis unit, and a feature weight analysis unit.

[0049] The spherical coordinate transformation unit calculates spherical coordinates including radial distance, elevation angle value, and azimuth angle value based on the preprocessed Cartesian coordinates, specifically including:

[0050] Square each of the three components of the Cartesian coordinates and add them together, then take the square root of the sum to obtain the radial distance.

[0051] Take the vertical component in the Cartesian coordinate system as the numerator and the radial distance as the denominator to obtain the first ratio, and take the inverse cosine function value of the first ratio to obtain the elevation angle value.

[0052] Take the longitudinal component in the horizontal direction of the Cartesian coordinate system as the numerator and the transverse component in the horizontal direction as the denominator to obtain the second ratio, and take the arctangent function value of the second ratio to obtain the azimuth angle value.

[0053] Specifically, its calculation formula is:

[0054]

[0055]

[0056]

[0057] In the formula, represents the transformed spherical coordinates, represents the preprocessed Cartesian coordinates, to adapt to the advantages of the spherical coordinate system in three-dimensional space description and prepare for subsequent information density calculation and feature analysis.

[0058] The advantages are: by calculating the spherical coordinates , it is possible to determine whether the layout of the generated multi-dimensional code in three-dimensional space conforms to the expected coding rules and application scenario requirements. Through spherical coordinate transformation, it is possible to more clearly identify the distribution pattern and characteristics of data in space, provide a more effective data representation for subsequent information density analysis and feature weight analysis, and provide a method that can uniformly and concisely describe the position of points in three-dimensional space, which helps to establish a more complete spatial mathematical model, thereby deeply exploring the geometric properties and internal relationships of data in three-dimensional space and providing strong support for the development of related theories.

[0059] The information density analysis unit obtains the information density by taking the ratio of the total information amount stored in the encoding corresponding to the first identifier to the volume covered by the encoding corresponding to the second identifier. The information density The calculation formula is:

[0060]

[0061] In the formula, represents the information density, represents the total information amount stored after encoding, represents the volume covered by the encoding in the spherical coordinate system.

[0062] The advantages are as follows: By calculating the information density , based on the information density to evaluate the information storage efficiency, determine whether the current information density reaches the optimum, so as to ensure that sufficient and effective information is stored in the limited encoding space. At the same time, according to the analysis result of the information density, the stored information can be intelligently screened and integrated, and the invalid information can be eliminated, thereby improving the overall information quality. Further, by using the quantitative index of the information density, the allocation strategy of the storage resources can be optimized to achieve the efficient utilization of the storage space and reduce the storage cost.

[0063] The feature weight analysis unit calculates the influence degree of external features on the generation of multi-dimensional code information , specifically including:

[0064] Determine the temperature and humidity during sensor calibration as the reference benchmark. Based on the difference between the actual temperature and the reference temperature, and the difference between the actual humidity and the reference humidity, multiply them by the corresponding temperature weight coefficient and humidity weight coefficient respectively, and add the results of the multiplications as the denominator of the environmental factor correction term to characterize the correction degree of the environmental change on the feature weight;

[0065] Obtain the residual information during the spherical coordinate conversion process, add the residual information with the minimum value correction term and take the reciprocal to characterize the adjustment factor of the coordinate conversion error on the influence degree of external features.

[0066] Perform a square root operation on the square of the slope value and the curvature value of the surface to obtain the complexity index of the surface feature to characterize the intensity of the change of the surface feature.

[0067] Take the pre-calibrated value as the base number and subtract the result of multiplying the correction degree, the adjustment factor, and the intensity of the change to obtain the influence degree.

[0068] Specifically, its calculation formula is:

[0069]

[0070] In the formula, Indicates the degree of influence of external features on the generation of multi-dimensional code information. , respectively represent the temperature and humidity during sensor calibration. , respectively represent the temperature and humidity actually measured by the sensor. , respectively represent the weight coefficients of temperature and humidity. The sensitivity of environmental influence is determined through experiments. represents the correction coefficient of environmental factors. represents the residual of spherical coordinate transformation. represents the coordinate transformation residual factor. represents the minimum value to prevent the denominator from being zero. , respectively represent slope and curvature. represents the complexity of surface features.

[0071] The advantages are as follows: By calculating the degree of influence of external features on the generation of multi-dimensional code information , based on the degree of influence on the generation of multi-dimensional code information , it is judged whether the interference of external factors and coordinate transformation factors on the coding result is within the acceptable range, and then it is determined whether the overall analysis result meets the standard. Considering the influence of various factors on the generation of multi-dimensional code comprehensively, the overall quality of the multi-dimensional code is evaluated. When the residual of spherical coordinate transformation in the calculation formula of the degree of influence of multi-dimensional code information generation is large, or when the information density is low, it can indicate that the quality of the multi-dimensional code does not meet the standard. The present invention can quickly locate the specific factors leading to unqualified quality. For the problem of the residual of spherical coordinate transformation, it starts the optimization process of the coordinate transformation algorithm, recalibrates the parameters, reduces the residual to improve the quality of the multi-dimensional code, and for the case of low information density, it immediately adjusts the information storage and coding strategy, re-integrates and compresses the data to increase the information density. At the same time, based on the above quality evaluation results, a risk warning system is constructed to predict in advance the specific scenarios of possible coding failure or data loss risks, and notify the relevant personnel in time to take countermeasures to avoid serious impacts on the subsequent business processes relying on this coding due to the quality problems of the multi-dimensional code, and ensure the stable and reliable operation of the entire multi-dimensional data analysis and application system.

[0072] The multi-dimensional result evaluation module conducts a rationality analysis of the spatial position distribution according to the spherical coordinates , and judges whether the layout of the generated multi-dimensional code in the three-dimensional space conforms to the expected coding rules and application scenario requirements. It evaluates the information storage efficiency according to the information density , and judges whether the current information density reaches the optimum to ensure that sufficient and effective information is stored in the limited coding space. According to the degree of influence of multi-dimensional code information generation , determine whether the interference of external factors and coordinate conversion factors on the coding result is within the acceptable range, and then determine whether the overall analysis result meets the standard. Comprehensively consider the influence of various factors on the generation of multi-dimensional codes, evaluate the overall quality of multi-dimensional codes. When the degree of influence on the generation of multi-dimensional code information in the calculation formula of spherical coordinate conversion has a large residual, or when the information density is low, it can indicate that the quality of the multi-dimensional code does not meet the standard;

[0073] The multi-dimensional strategy optimization module adjusts and optimizes the multi-dimensional code generation strategy according to the above evaluation results. When the spatial position distribution is unreasonable, adjust the spherical coordinate conversion parameters or optimize the coding rules to achieve a more reasonable spatial layout; when the information density does not meet the standard, improve the information storage efficiency by adjusting the coding algorithm, data compression method or reallocating the coding space, etc.; when the degree of influence exceeds the acceptable range, optimize the sensor layout, adjust the weight coefficient or add an environmental compensation algorithm for environmental factors, and optimize the conversion algorithm and reduce the residual for coordinate conversion factors, so as to comprehensively adjust the strategy and improve the quality and reliability of multi-dimensional code information generation.

[0074] Specifically, by reorganizing the data and control paths between modules, the execution feedback can reverse-adjust each key link within the same processing cycle to achieve real-time closed-loop optimization; let the multi-dimensional feedback adjustment module trigger three established paths simultaneously after receiving the execution feedback, rather than backtracking in the original linear order, so as to shorten the response link and reduce parameter hysteresis; specifically include:

[0075] Path 1: Parameter write-back; Target modules include: multi-dimensional data preprocessing module; Adjustment content includes: directly shrink or expand the spherical coordinate sampling step size according to the information density error value in the feedback, and synchronously update the data number threshold; Real-time optimization goal: The next round of preprocessing runs according to the latest error compensation scale to reduce the cumulative residual.

[0076] Path 2: Weight fine-tuning; Target modules include: multi-dimensional data analysis module; Adjustment content includes: immediately increase or decrease the environmental correction coefficient according to the temperature and humidity offset in the feedback; Fine-tune the surface complexity threshold according to the residual level; Real-time optimization goal: Maintain the balance between sensitivity and stability in the analysis stage under the current environment.

[0077] Path 3: Strategy hot update; Target modules include: multi-dimensional strategy optimization module → multi-dimensional strategy execution module; Adjustment content includes: directly load the new optimal strategy index carried by the feedback without having to search completely again; The multi-dimensional strategy execution module immediately generates a multi-dimensional code according to the new index; Real-time optimization goal: Skip the long optimization-execution iteration and compress the overall delay.

[0078] For the above specific description, the multi-dimensional strategy execution module outputs the multi-dimensional code along with five indicators: information density error, mean residual, temperature offset, humidity offset, and strategy version number. The multi-dimensional feedback adjustment module parses in a fixed order to avoid additional parsing overhead. After receiving the packaged feedback, the multi-dimensional feedback adjustment module broadcasts an "update" signal to the three channels without waiting for any confirmation; each triggered module writes the parameters at the local clock beat and automatically enters the next processing round after being ready. If Path 1 and Path 2 propose opposite adjustment directions for the same threshold in the same cycle, the determination result of the multi-dimensional result evaluation module in the previous cycle is used as the arbitration: if the determination is qualified, the adjustment value with a smaller amplitude is adopted, and if the determination is unqualified, the adjustment value with a larger amplitude is adopted to ensure both the convergence speed and stability are considered.

[0079] As can be seen from the above, the multi-level waiting derived from the linear evaluation → optimization → execution → feedback loop is replaced by parallel triggering, and the single-cycle parameter delay is reduced to about one-third of the original process. The three key links of preprocessing, analysis, and optimization obtain the latest environment and error information synchronously in the same cycle, and their internal algorithms can be immediately corrected to ensure the real-time generation quality of the multi-dimensional code. Without introducing any new modules or new data structures, it is possible to achieve real-time adaptive upgrade of the existing architecture and firmware level.

[0080] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for generating multi-dimensional code information based on spherical coordinate transformation, characterized in that It includes the following steps: Step 1, construct a multi-dimensional data acquisition module, a multi-dimensional data preprocessing module, a multi-dimensional data analysis module, a multi-dimensional result evaluation module, a multi-dimensional strategy optimization module, a multi-dimensional strategy execution module, and a multi-dimensional feedback adjustment module, and establish the connection between each module; Step 2, obtain the original data containing three-dimensional coordinate information, surface slope feature data, and surrounding environment information through the multi-dimensional data acquisition module; Step 3, preliminarily process the collected original data through the multi-dimensional data preprocessing module to represent the original data in spherical coordinates; among them, the multi-dimensional data preprocessing module respectively preprocesses the original data and numbers the data, including: after numbering, obtaining the total information volume of coded storage, the covered volume of coding in the spherical coordinate system, the residual of spherical coordinate transformation, slope and curvature, the actually measured temperature and humidity of the sensor; the total information volume of coded storage and the covered volume of coding in the spherical coordinate system are numbered as the first identifier and the second identifier respectively, the actually measured temperature and humidity of the sensor are numbered as the third identifier and the fourth identifier respectively, the residual of spherical coordinate transformation is numbered as the fifth identifier, and the slope and curvature are numbered as the sixth identifier and the seventh identifier respectively; Step 4, calculate the preliminarily processed original data through the multi-dimensional data analysis module, and mine and obtain data features to obtain a comprehensive analysis result including spherical coordinates, information density of coded data, and the influence degree of external features on multi-dimensional code information generation; among them, the multi-dimensional data analysis module includes a spherical coordinate transformation unit, an information density analysis unit, and a feature weight analysis unit; The spherical coordinate transformation unit calculates the spherical coordinates including radial distance, pitch angle value, and azimuth angle value according to the preprocessed Cartesian coordinates, specifically including: respectively squaring and adding the three components of the Cartesian coordinates, taking the square root of the added result to obtain the radial distance; taking the vertical component in the Cartesian coordinate system as the numerator and the radial distance as the denominator to take the first ratio, and taking the arccosine function value of the first ratio to obtain the pitch angle value; taking the longitudinal component in the horizontal direction in the Cartesian coordinate system as the numerator, taking the transverse component in the horizontal direction as the denominator to take the second ratio, and taking the arctangent function value of the second ratio to obtain the azimuth angle value; The information density analysis unit calculates the information density of the coded data, specifically including: obtaining the information density by taking the ratio of the total information volume of coded storage corresponding to the first identifier to the covered volume of coding in the spherical coordinate system corresponding to the second identifier; The feature weight analysis unit calculates the influence degree of external features on the generation of multi-dimensional code information, specifically including: determining the temperature and humidity during sensor calibration as the reference benchmark, based on the difference between the actual temperature and the reference temperature, and the difference between the actual humidity and the reference humidity, multiplying them by the corresponding temperature weight coefficient and humidity weight coefficient respectively, and adding the results of the multiplications as the denominator of the environmental factor correction term to represent the correction degree of environmental changes on the feature weight; obtaining the residual information during the spherical coordinate transformation, adding the minimum value correction term to the residual information and taking the reciprocal to represent the adjustment factor of the influence degree of coordinate transformation error on external features; performing a square root operation on the square of the slope value and the curvature value of the surface to obtain the complexity index of the surface feature to represent the intensity of the change of the surface feature; taking the pre-calibrated value as the base number and subtracting the result of multiplying the correction degree, the adjustment factor, and the intensity of the change, to obtain the influence degree; Step Five: The multi-dimensional result evaluation module determines whether the comprehensive analysis result meets the standard in the current environmental scenario; Step Six: The multi-dimensional strategy optimization module demarcates the unqualified part of the comprehensive analysis result in the judgment result, and adjusts and updates the corresponding strategy for the unqualified part; Step Seven: The multi-dimensional strategy execution module generates the multi-dimensional code according to the updated strategy; Step Eight: The multi-dimensional feedback adjustment module further improves the entire method according to the feedback after the execution of the multi-dimensional strategy execution module; 2. The multi-dimensional code information generation method according to claim 1, wherein: The multi-dimensional data acquisition module includes an information input unit, a three-dimensional data acquisition unit, a surface feature acquisition unit, and an environmental data acquisition unit.

3. The multi-dimensional code information generation method according to claim 2, characterized in that: The information input unit introduces the original data to be encoded into the multi-dimensional data acquisition module by accessing the text file input port, the image acquisition device interface, and the digital signal receiving channel; The three-dimensional data acquisition unit scans the target object by deploying a three-dimensional sensor or other devices with three-dimensional measurement functions, and acquires the three-dimensional coordinate information of the target object in the Cartesian coordinate system as the original data.

4. The multi-dimensional code information generation method according to claim 2, characterized in that: The surface feature acquisition unit projects a specific structured light pattern onto the surface through laser scanning technology or structured light measurement technology, and acquires the surface slope feature data according to the deformation of the reflected light as the original data; The environmental data acquisition unit arranges temperature sensors and humidity sensors to collect the temperature parameters and humidity parameters of the surrounding environment during the acquisition of the multi-dimensional code in real time as the original data.

5. The multi-dimensional code information generation method according to claim 1, characterized in that: The multi-dimensional result evaluation module determines whether the comprehensive analysis result meets the standard, including: Analyzing the rationality of the spatial position distribution according to the spherical coordinates, and judging whether the layout of the generated multi-dimensional code in the three-dimensional space conforms to the expected coding rules and application scenario requirements; and / or Evaluating the information storage efficiency according to the information density, and judging whether the current information density reaches the optimum; and / or Judge whether the interference of external factors and coordinate conversion factors on the coding result is within the acceptable range according to the influence degree generated by the multi-dimensional code information.

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