Fully automatic focusing positioning system based on corneal topography

Abstract

The present application relates to the technical field of precision positioning, in particular to a full-automatic focusing positioning system based on corneal topography, which comprises an optical imaging module: through optical devices, multi-angle light signals of the corneal surface are collected, light reflections of different regions are processed, the corneal edge is determined by using the reflection intensity difference, the reflection angle and intensity are calculated, the key area light signal is identified, and the light reflection characteristic data is obtained. In the present application, through the accurate analysis of the light reflection characteristic data, the accurate analysis of the complex morphology of the corneal surface is realized, the accuracy of the focal length control is improved, the PID control algorithm is applied, the curvature change data is combined, the matching degree of the focal length adjustment and the corneal surface curvature is ensured to be high, the stability and response speed of the focal length adjustment are improved, through the light path deviation correction, the imaging error caused by the light path deviation is reduced, and the accuracy, stability and imaging quality of the corneal topography automatic focusing positioning are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of precision positioning technology, and in particular to a full-automatic focusing positioning system based on corneal topography. BACKGROUND

[0002] The field of precision positioning technology aims to achieve precise adjustment and control of object position, direction and focal point through high-precision measurement, control and adjustment technology, ensuring accurate positioning of objects within a small range.

[0003] The purpose of the full-automatic focusing positioning system based on corneal topography is to use the three-dimensional surface data provided by the corneal topography to automatically adjust the focal length and position of the optical system, ensuring the clarity and accuracy of the imaging, and to obtain accurate corneal surface geometry data through optical scanning, adjust the focal length and position of the optical equipment, ensure that the imaging system can quickly and accurately focus, and provide high-quality images.

[0004] Traditional systems rely on simple optical scanning and focal length adjustment methods when dealing with complex corneal surface shapes, lack precise analysis of corneal curvature changes, resulting in large focal length adjustment errors when the system encounters irregular corneal shapes, affecting imaging clarity, and lacking in optical path calibration, unable to effectively correct deviations in the optical path and corneal surface, resulting in unnecessary optical path errors during imaging, affecting imaging accuracy, lacking correlation analysis of focal length and corneal surface curvature, focal length adjustment instability and slow response speed, affecting the efficiency and stability of the device in actual operation, reducing accuracy and reliability. SUMMARY

[0005] The purpose of the present application is to solve the shortcomings in the prior art and to provide a full-automatic focusing positioning system based on corneal topography.

[0006] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions: the full-automatic focusing positioning system based on corneal topography comprises:

[0007] Optical imaging module: based on optical devices, collecting multi-angle light signals of corneal surface, processing light reflection of different regions of corneal surface, using the difference in reflected light intensity to determine the edge of corneal region, calculating the light reflection angle and intensity, identifying the light signal characteristics of key regions, and obtaining light reflection characteristic data;

[0008] Curvature analysis module: based on the light reflection characteristic data, segmenting the corneal surface region, extracting local curvature information of the corneal surface by analyzing the relationship between light reflection angle and position, combining the curvature values of different regions, analyzing the overall curvature change, calculating the curvature of key positions, and generating curvature change distribution data;

[0009] The focal length control module: based on the curvature change distribution data, a PID control algorithm is used to analyze the correlation between the corneal curvature value and the focal length, the focal length adjustment point is judged through the curvature change of each region, the offset range of the focal length is calculated, the focal length device is adjusted, the current focal length value is corrected, the consistency of the focal length and the curvature is ensured, and the focal length adjustment result is generated.

[0010] The imaging calibration module: based on the focal length adjustment result, the current optical path state is analyzed, the key point position in the optical path is determined through the optical path offset after the focal length adjustment, the relative deviation of the optical path and the corneal surface is calculated, the angle and position of the optical sensor are adjusted, and the optical path calibration parameter is generated.

[0011] The focusing adjustment module: based on the optical path calibration parameter, the focusing adjustment is performed, the imaging quality of different regions of the corneal surface is judged, the deviation of the focal length and the imaging position is analyzed through the focusing intensity of the light signal, the displacement and angle of the focusing device are gradually corrected, the focusing state is updated, and the focusing position correction data is generated.

[0012] The position correction module: based on the focusing position correction data, the displacement deviation of the imaging equipment and the corneal surface is analyzed, the position change of the equipment relative to the cornea is calculated through the displacement sensor data, the equipment position is adjusted by selecting the correction point, the displacement parameter of the imaging equipment is corrected, the position state is updated, and the position adjustment data is generated.

[0013] The system self-checking module: based on the position adjustment data, the system state detection is performed, the key parameters of the focal length, the optical path and the displacement are measured through the multi-point detection module, the equipment running state is analyzed, the overall situation of the corneal imaging is judged, the normality of all system parameters is confirmed, and the system detection report is generated.

[0014] As a further scheme of the application, the light reflection feature data includes the reflection intensity, the light incidence angle and the reflection angle distribution of different regions of the corneal surface, the curvature change distribution data includes the curvature value of each partition, the curvature change amplitude of the corneal surface and the curvature difference value of the key point, the focal length adjustment result includes the focal length offset value, the focal length correction parameter and the change relationship between the focal length and the curvature, the optical path calibration parameter includes the optical path offset angle, the corrected sensor position and the optical path deviation correction value, the focusing position correction data includes the focusing distance correction value, the focusing adjustment amount of the imaging region and the focal length correction parameter, the position adjustment data includes the equipment displacement correction amount, the corneal relative position offset value and the position calibration parameter, and the system detection report includes the focal length calibration data, the optical path state detection result and the equipment displacement correction result.

[0015] As a further scheme of the application, the optical imaging module includes a light signal acquisition sub-module, a light intensity analysis sub-module and a light reflection feature recognition sub-module.

[0016] The light signal acquisition sub-module: based on the optical device, multi-angle light signal acquisition of different regions of the corneal surface is carried out, light reflection information of each region is collected and recorded, and light signal data is generated;

[0017] The light intensity analysis sub-module: based on the light signal data, the light reflection intensity of each corneal region is calculated, the light intensity difference of different angles is compared, and light intensity distribution data is generated;

[0018] The light reflection feature recognition sub-module: based on the light intensity distribution data, the light reflection features of the key regions of the corneal surface are recognized, the edge features of each region are extracted, and light reflection feature data is generated.

[0019] As a further scheme of the present application, the curvature analysis module comprises a region division sub-module, a curvature information extraction sub-module, and a curvature change calculation sub-module, wherein:

[0020] The region division sub-module: based on the light reflection feature data, the region division of the corneal surface is carried out, the boundaries of each region are divided according to the light reflection feature difference, and region division data is generated;

[0021] The curvature information extraction sub-module: based on the region division data, the local curvature information in each partition is extracted, the curvature change amplitude of each region is calculated, and local curvature data is generated;

[0022] The curvature change calculation sub-module: based on the local curvature data, the curvature change of different partitions is combined to analyze the overall curvature distribution of the cornea, and curvature change distribution data is generated.

[0023] As a further scheme of the present application, the focal length control module comprises a curvature analysis sub-module, a focal length adjustment point judgment sub-module, and a focal length offset calculation sub-module, wherein:

[0024] The curvature analysis sub-module: based on the curvature change distribution data, the curvature change of different regions of the corneal surface is analyzed, the key point information of the curvature change is extracted, the curvature change model of each region of the corneal surface is established, and curvature key point information is generated;

[0025] The focal length adjustment point judgment sub-module: based on the curvature key point information, the correlation of the curvature values of different regions and the focal length is compared, the influence range of the curvature change position is calculated, the best position of the focal length adjustment is determined, and focal length adjustment point information is generated;

[0026] The focal length offset calculation sub-module: based on the focal length adjustment point information, a PID control algorithm is used to calculate the offset amount that the focal length device needs to adjust, the focal length control parameters of the system are combined to determine the focal length offset value, the focal length device is adjusted, and focal length adjustment results are generated.

[0027] As a further scheme of the present application, the PID control algorithm is used, according to the formula:

[0028]

[0029] Wherein, u(t) is the offset required by the focal length device to adjust, K p is the proportional coefficient, e(t) is the error between the current focal length value and the target focal length value, K i is the integral coefficient, representing the influence of cumulative error on system adjustment, used to compensate for long-term errors. is the error integral from time 0 to the current time t, K d is the differential coefficient, is the rate of change of error with time, K f is the external environment coefficient, f(v) is the rate of change of ambient light, K s is the system load coefficient, s(θ) is the lens angle change rate.

[0030] As a further scheme of the present application, the imaging calibration module comprises a light path state analysis submodule, a light path offset measurement submodule, and a sensor position adjustment submodule, wherein:

[0031] The light path state analysis submodule: based on the focal length adjustment result, analyzes the current state of the light path, judges the light path change after focal length adjustment, identifies the key point offset in the light path, and generates light path state information;

[0032] The light path offset measurement submodule: based on the light path state information, measures the actual offset of each key point in the light path, calculates the deviation value of each position in the light path, obtains the overall offset information of the light path, and generates light path offset data;

[0033] The sensor position adjustment submodule: based on the light path offset data, adjusts the angle and position of the optical sensor, corrects the position of the sensor in the light path, ensures the alignment of the sensor and the light path, and generates light path calibration parameters.

[0034] As a further scheme of the present application, the focusing adjustment module comprises an imaging quality judgment submodule, a focal length deviation analysis submodule, and a focusing correction submodule, wherein:

[0035] The imaging quality judgment submodule: based on the light path calibration parameters, judges the imaging quality of each region of the cornea, analyzes the imaging effect of different regions through focus intensity measurement, identifies the poor imaging region, and generates imaging quality evaluation data;

[0036] The focal length deviation analysis submodule: based on the imaging quality evaluation data, analyzes the deviation of the imaging position and the focal length, evaluates the influence of focal length change of each region on the imaging position, calculates the focal length adjustment requirement, and generates focal length deviation information;

[0037] The focus correction sub-module adjusts the displacement and angle of the focusing device based on the focal length deviation information, corrects the focal length and position of the imaging device, gradually updates the focusing state, and generates focus position correction data.

[0038] As a further scheme of the application, the position correction module comprises a displacement deviation analysis sub-module, a position change evaluation sub-module, and a device position adjustment sub-module, wherein:

[0039] The displacement deviation analysis sub-module analyzes the displacement deviation between the imaging device and the corneal surface based on the focus position correction data, determines the deviation of the relative position of the device by comparing the data of the displacement sensor, and generates displacement deviation information.

[0040] The position change evaluation sub-module evaluates the specific position change of the imaging device relative to the corneal surface based on the displacement deviation information, calculates the correction amount required for the device to move, and generates position change evaluation data.

[0041] The device position adjustment sub-module adjusts the position and angle of the device based on the position change evaluation data, corrects the displacement parameters of the imaging device, ensures the alignment of the device and the corneal position, and generates position adjustment data.

[0042] As a further scheme of the application, the system self-checking module comprises a focal length detection sub-module, an optical path detection sub-module, and a displacement detection sub-module, wherein:

[0043] The focal length detection sub-module measures the focal length of the imaging system based on the position adjustment data, collects focal length parameters at each point, checks the deviation of the focal length from the preset value, and generates focal length detection data.

[0044] The optical path detection sub-module measures the optical signal transmission state of each point in the optical path based on the focal length detection data, analyzes the optical path deviation of the key points, obtains the overall operation state of the optical path, and generates optical path detection data.

[0045] The displacement detection sub-module measures the displacement of the imaging device and the corneal surface based on the optical path detection data, uses a displacement sensor to determine the deviation of the device and the target position, and generates displacement detection data.

[0046] Compared with the prior art, the application has the following advantages and positive effects:

[0047] In the application, the complex shape of the corneal surface is accurately analyzed through the accurate analysis of the light reflection feature data, the accuracy of the focal length control is improved, the PID control algorithm is applied, the curvature change data is combined to ensure the high matching degree of the focal length adjustment and the corneal surface curvature, the stability and response speed of the focal length adjustment are improved, the imaging error caused by the light path deviation is reduced through the light path deviation correction, and the accuracy, stability and imaging quality of the automatic focusing and positioning of the corneal topography are improved. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 The system flowchart of the application is shown in the figure.

[0049] Figure 2 The system framework schematic diagram of the application is shown in the figure. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical scheme and advantages of the application more clear and explicit, the application is further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the application, and are not used to limit the application.

[0051] Example 1

[0052] Please refer to Figure 1 The application provides a technical scheme: a full-automatic focusing and positioning system based on corneal topography includes:

[0053] Optical imaging module: based on optical device, collect multi-angle light signal of corneal surface, process light reflection of different regions of corneal surface, determine corneal region edge by using the difference of reflected light intensity, calculate light reflection angle and intensity, identify light signal features of key region, and obtain light reflection feature data;

[0054] Curvature analysis module: based on light reflection feature data, segment corneal surface region, extract local curvature information of corneal surface by analyzing the relationship between light reflection angle and position, analyze overall curvature change by combining curvature values of different regions, calculate curvature of key position, and generate curvature change distribution data;

[0055] Focal length control module: based on curvature change distribution data, adopt PID control algorithm to analyze the correlation between corneal curvature value and focal length, judge focal length adjustment point through curvature change of each region, calculate the offset range of focal length, adjust focal length device, correct the current focal length value, ensure the consistency of focal length and curvature, and generate focal length adjustment result;

[0056] Imaging calibration module: based on the focal length adjustment result, analyze the current optical path state, through the measurement of the optical path offset after the focal length adjustment, determine the position of the key point in the optical path, calculate the relative deviation of the optical path and the corneal surface, adjust the angle and position of the optical sensor, generate the optical path calibration parameter;

[0057] Focusing adjustment module: based on the optical path calibration parameter, adjust the focusing, judge the imaging quality of different regions of the corneal surface, analyze the deviation of the focal length and the imaging position through the focusing intensity of the light signal, gradually correct the displacement and angle of the focusing device, update the focusing state, generate the focusing position correction data;

[0058] Position correction module: based on the focusing position correction data, analyze the displacement deviation of the imaging equipment and the corneal surface, calculate the position change of the equipment relative to the cornea through the displacement sensor data, select the correction point to adjust the equipment position, correct the displacement parameter of the imaging equipment, update the position state, generate the position adjustment data;

[0059] System self-checking module: based on the position adjustment data, detect the system state, measure the key parameters of focal length, optical path and displacement through the multi-point detection module, analyze the equipment running state, judge the overall situation of corneal imaging, confirm the normality of all system parameters, generate the system detection report.

[0060] The light reflection characteristic data includes the reflection intensity of different regions of the corneal surface, the light incidence angle, the reflection angle distribution, the curvature change distribution data includes the curvature value of each partition, the curvature change amplitude of the corneal surface, the curvature difference value of the key point, the focal length adjustment result includes the focal length offset value, the focal length correction parameter, the change relationship between the focal length and the curvature, the optical path calibration parameter includes the optical path offset angle, the corrected sensor position, the optical path deviation correction value, the focusing position correction data includes the focusing distance correction value, the focusing adjustment amount of the imaging area, the focal length correction parameter, the position adjustment data includes the equipment displacement correction amount, the corneal relative position offset value, the position calibration parameter, the system detection report includes the focal length calibration data, the optical path state detection result, the equipment displacement correction result;

[0061] Please refer to Figure 2 , the optical imaging module includes a light signal acquisition sub-module, a light intensity analysis sub-module, and a light reflection feature recognition sub-module, wherein:

[0062] Light signal acquisition sub-module: based on the optical device, multi-angle light signal acquisition of different regions of the corneal surface is performed, light reflection information of each region is collected and recorded, and light signal data is generated;

[0063] Light intensity analysis sub-module: based on the light signal data, calculate the light reflection intensity of each corneal region, compare the light intensity difference of different angles, and generate light intensity distribution data;

[0064] Light reflection feature recognition submodule: based on light intensity distribution data, identify the key area of corneal surface light reflection feature, extract the edge feature of each region, generate light reflection feature data;

[0065] Light signal acquisition submodule: based on optical device, using multi-angle scanning strategy to collect light signal of different regions of corneal surface, set the collection angle range from 0 to 360 degrees, interval is 1 degree, use photoelectric detector to record the light signal intensity and corresponding angle position information of each angle, after collection, store the data in memory buffer, generate light signal data;

[0066] Light intensity analysis submodule: based on light signal data, using linear regression algorithm to analyze the light reflection intensity of each corneal region, taking the collection angle as the input parameter and the light intensity as the target parameter, the input data set of linear regression is extracted from the light signal data, the relationship between light intensity and angle is determined by using fitting parameters, in the analysis process, the step of 0.01 iteration optimization method is used to adjust the regression parameters, to ensure that the light intensity of all regions is calculated accurately, generate light intensity distribution data;

[0067] Light reflection feature recognition submodule: based on light intensity distribution data, using Canny edge detection algorithm to identify the edge feature of corneal surface, first use Gaussian filter to smooth the light intensity data, set the standard deviation parameter to 1.4 in the smoothing process, then determine the intensity change of each region by gradient calculation, use gradient direction to determine the edge position, apply non-maximum suppression operation to ensure that only the edge information of key region is reserved, filter the edge by double threshold method, identify the key reflection feature of corneal surface, generate light reflection feature data.

[0068] Please refer to Figure 2 , curvature analysis module includes region division submodule, curvature information extraction submodule, curvature change calculation submodule, wherein:

[0069] Region division submodule: based on light reflection feature data, divide the corneal surface into regions, divide the region boundary according to the difference of light reflection feature, generate region division data;

[0070] Curvature information extraction submodule: based on region division data, extract the local curvature information in each partition, calculate the curvature change amplitude of each region, generate local curvature data;

[0071] Curvature change calculation submodule: based on local curvature data, combined with the curvature change of different partitions, analyze the overall curvature distribution of cornea, generate curvature change distribution data;

[0072] Region division sub-module: based on the light reflection feature data, the K-means clustering algorithm is used to divide the corneal surface into regions, the light reflection feature data is used as the input parameter, the initial clustering center is set to 5, the iteration number is set to 100 times, the Euclidean distance is used as the clustering standard, the distance of each data point to the clustering center is calculated, the clustering center position is adjusted through repeated iteration, the data point attribution of each region is updated, until the distance converges and meets the set threshold 0.01, the region division data is generated;

[0073] Curvature information extraction sub-module: based on the region division data, the finite difference method is used to calculate the local curvature in each partition, the coordinate data of each partition is extracted, the difference calculation is performed on the boundary points of the partition, the height difference and the horizontal difference between the known boundary points are used to calculate the change of the local curvature, the difference step is set to 0.1mm, the local curvature analysis in each partition is performed, the curvature change value is stored after calculation and the local curvature data is generated;

[0074] Curvature change calculation sub-module: based on the local curvature data, the quadratic surface fitting method is used to analyze the curvature change of different partitions, the local curvature value of each partition is used as the input parameter, the least square method is used for quadratic surface fitting, the error threshold used in the fitting process is set to 0.05, the Gauss-Newton iterative algorithm is used to optimize and adjust the fitting result, the fitting error is gradually reduced, the curvature change of each partition is calculated and stored, and the curvature change distribution data is generated by combining the curvature data of all partitions.

[0075] Please refer to Figure 2 , the focal length control module includes a curvature analysis sub-module, a focal length adjustment point judgment sub-module, and a focal length offset calculation sub-module, wherein:

[0076] Curvature analysis sub-module: based on the curvature change distribution data, the curvature change of different regions of the corneal surface is analyzed, the key point information of the curvature change is extracted, the curvature change model of each region of the corneal surface is established, and the curvature key point information is generated;

[0077] Focal length adjustment point judgment sub-module: based on the curvature key point information, the correlation between the curvature values of different regions and the focal length is compared, the influence range of the curvature change position is calculated, the best position of the focal length adjustment is determined, and the focal length adjustment point information is generated;

[0078] Focal length offset calculation sub-module: based on the focal length adjustment point information, the PID control algorithm is used to calculate the offset amount that the focal length device needs to adjust, the focal length control parameters of the system are combined to determine the focal length offset value, the focal length device is adjusted, and the focal length adjustment result is generated;

[0079] Curvature analysis submodule: based on curvature change distribution data, using cubic spline interpolation algorithm to analyze the curvature change of different regions of corneal surface, using piecewise interpolation method to fit the curvature change of each partition, the input is the curvature change data of each partition, the interval of interpolation nodes is set to 0.05 millimeter, in the interpolation calculation process, the boundary conditions and smoothness parameters are set to smooth the curvature change trend, after interpolation, the key point information of curvature change is extracted, the maximum and minimum value positions of curvature change are marked, the curvature change model of each region of corneal surface is established, and the curvature key point information is generated;

[0080] Focal length adjustment point judgment submodule: based on curvature key point information, using multivariate linear regression algorithm to compare the correlation of curvature values and focal length in different regions, inputting curvature key point information as independent variable and historical data of focal length adjustment as dependent variable, calculating the influence range of curvature change position, estimating the influence weight of curvature change on focal length by least square method, and obtaining the key parameter value required for focal length adjustment through multivariate regression analysis, determining the best position of focal length adjustment, and generating focal length adjustment point information;

[0081] Focal length offset calculation submodule: based on focal length adjustment point information, using PID control algorithm to calculate the offset required for focal length device adjustment, setting PID control parameters, proportional coefficient Kp=1.5, integral coefficient Ki=0.1, and differential coefficient Kd=0.05, taking focal length adjustment point information as input, combining focal length control parameters in the system, calculating offset in real time, further correcting deviation by integral and differential calculation, determining focal length offset value, adjusting physical position of focal length device, and generating focal length adjustment result.

[0082] Using PID control algorithm, according to the formula:

[0083]

[0084] Wherein: u(t) is the offset required for focal length device adjustment, K p is the proportional coefficient, e(t) is the error between the current focal length value and the target focal length value, K i is the integral coefficient, representing the influence of cumulative error on system adjustment, used to compensate for long-term existing error; is the error integral from time 0 to current time t, K d is the differential coefficient, is the rate of change of error with time, K f is the external environment coefficient, f(v) is the rate of change of environmental light, K s is the system load coefficient, s(θ) is the rate of change of lens angle;

[0085] Execution process: first, the focal length error e(t) of the system is calculated, that is, the difference between the current focal length value and the target focal length value, the proportional control part generates a preliminary offset value, which represents the influence of the instantaneous error, the integral control part calculates the cumulative integral of the error p e(t) generates a compensation value, which corrects the cumulative effect of long-term error, and the differential control part calculates the rate of change of the error to reduce the trend of the error The newly added external environment coefficient K f ·f(v) corrects the influence of the change of external light on the focal length, the light intensity change rate f(v) can be collected in real time by the light sensor, and after predetermined filtering and normalization processing, it reflects the dynamic response of the light to the focal length device, and the newly added system load coefficient K s ·s(θ) corrects the error caused by the change of the lens angle, and the angle change rate s(θ) is calculated by the built-in angle sensor, which reflects the influence of the lens on the focal length adjustment at different angles K s and K f The weight coefficients of the above-mentioned coefficients can be determined by experiment calibration, and the optimal coefficient value can be determined by fitting analysis of the test data of the focal length adjustment accuracy in different environments.

[0086] Please refer to Figure 2 , the imaging calibration module includes an optical path state analysis submodule, an optical path offset measurement submodule, and a sensor position adjustment submodule, wherein:

[0087] The optical path state analysis submodule: based on the focal length adjustment result, analyze the current state of the optical path, judge the change of the optical path after the focal length adjustment, identify the key point offset in the optical path, and generate optical path state information;

[0088] The optical path offset measurement submodule: based on the optical path state information, measure the actual offset of each key point in the optical path, calculate the deviation value of each position in the optical path, obtain the overall offset information of the optical path, and generate optical path offset data;

[0089] The sensor position adjustment submodule: based on the optical path offset data, adjusts the angle and position of the optical sensor, corrects the position of the sensor in the optical path, ensures the alignment of the sensor and the optical path, and generates optical path calibration parameters;

[0090] The optical path state analysis submodule: based on the focal length adjustment result, uses the ray tracing algorithm to analyze the current optical path state, the input parameters include the coordinate data of each point in the optical path and the result of the focal length adjustment, and the ray tracing method is used to track the path of each light ray between optical elements, and the refraction angle and offset of the light ray when passing through each medium are calculated step by step, the key point offset in the optical path is identified, the intersection of the light ray and the optical element is calculated, the change of the optical path is judged, and the optical path state information is generated;

[0091] Optical path offset measurement submodule: based on the optical path state information, the actual offset of each key point in the optical path is measured by least squares method, the optical path state information is input as initial data, the least squares method is used to calculate the deviation of each key point, the error threshold 0.001 is used in the calculation process, the offset value of the key point position is updated iteratively, the comprehensive data of the overall offset of the optical path is obtained by accumulating the deviation of each position, and the optical path offset data is generated;

[0092] Sensor position adjustment submodule: based on the optical path offset data, the angle and position of the optical sensor are adjusted by using the servo control algorithm, the optical path offset data is input as the target parameter, the angle adjustment range of the servo control system is set to 0 to 15 degrees, the displacement adjustment range is set to 0 to 10 millimeters, the angle and displacement of the sensor are adjusted by using the feedback control of the servo motor, the feedback error is reduced to within 0.001 degrees by continuous adjustment, the sensor is adjusted to the appropriate position, and the optical path calibration parameter is generated.

[0093] Please refer to Figure 2 The focusing adjustment module includes an imaging quality judgment submodule, a focal length deviation analysis submodule, and a focusing correction submodule, wherein:

[0094] Imaging quality judgment submodule: based on the optical path calibration parameter, the imaging quality of each region of the cornea is judged, the imaging effect of different regions is analyzed by measuring the focusing intensity, the poor imaging region is identified, and the imaging quality evaluation data is generated;

[0095] Focal length deviation analysis submodule: based on the imaging quality evaluation data, the deviation of the imaging position and the focal length is analyzed, the influence of the focal length change of each region on the imaging position is evaluated, the focal length adjustment requirement is calculated, and the focal length deviation information is generated;

[0096] Focusing correction submodule: based on the focal length deviation information, the displacement and angle of the focusing device are adjusted, the focal length and position of the imaging equipment are corrected, the focusing state is gradually updated, and the focusing position correction data is generated;

[0097] Imaging quality judgment submodule: based on the optical path calibration parameter, the imaging quality of each region of the cornea is judged by using the Fourier transform analysis method, the input parameter is the optical signal after optical path calibration, the imaging signal is converted from time domain to frequency domain by fast Fourier transform, the frequency distribution of the imaging signal is analyzed and the focusing intensity is extracted, the frequency resolution is set to 0.01 hertz, the imaging effect is calculated combined with the frequency peak value of each region, the frequency abnormal or poor focusing region is identified, and the imaging quality evaluation data is generated;

[0098] Focal length deviation analysis submodule: based on the imaging quality evaluation data, the least square error analysis method is used to analyze the deviation of the imaging position and the focal length, the imaging position data is taken as the input, the focal length change is taken as the target parameter, the initial condition is set as zero focal length deviation, the influence of the focal length change of each region on the imaging position is evaluated step by step, the focal length adjustment requirement of each region is calculated through error analysis, the deviation range is calculated and the calculation result is stored, and the focal length deviation information is generated;

[0099] Focusing correction submodule: based on the focal length deviation information, the displacement and angle of the focusing device are adjusted by using fuzzy control algorithm, the input is set as the focal length deviation information, the output is the displacement and angle adjustment amount of the focusing device, the fuzzy control rule is set as three rule sets, which are used for fine adjustment of displacement, angle and focal length respectively, the step length of each adjustment is calculated by using fuzzy reasoning engine, the step length range is set as 0.1mm to 0.5mm, the position and angle of the focal length device are adjusted step by step, and the focusing position correction data is generated.

[0100] Please refer to Figure 2 The position correction module includes a displacement deviation analysis submodule, a position change evaluation submodule and a device position adjustment submodule, wherein:

[0101] Displacement deviation analysis submodule: based on the focusing position correction data, the displacement deviation between the imaging device and the corneal surface is analyzed, the relative position deviation of the device is determined by comparing the data of the displacement sensor, and the displacement deviation information is generated;

[0102] Position change evaluation submodule: based on the displacement deviation information, the specific position change of the imaging device relative to the corneal surface is evaluated, the correction amount required by the device movement is calculated, and the position change evaluation data is generated;

[0103] Device position adjustment submodule: based on the position change evaluation data, the position and angle of the device are adjusted, the displacement parameter of the imaging device is corrected, the device and the corneal position are aligned, and the position adjustment data is generated;

[0104] Displacement deviation analysis submodule: based on the focusing position correction data, the Kalman filtering algorithm is used to analyze the displacement deviation between the imaging device and the corneal surface, the input parameters include the focusing position correction data and the real-time displacement sensor data, the sensor data is smoothed by using Kalman filter, the noise covariance matrix set in the filtering process is Q=0.001 and R=0.01, the displacement deviation of the device relative to the corneal position is calculated, the estimation error is updated by iteration, and the displacement deviation information is generated;

[0105] The position change evaluation submodule: based on the displacement deviation information, the Newton iteration method is used to evaluate the specific position change of the imaging device relative to the corneal surface, the displacement deviation information is input as the initial data, the distance change between the imaging device and the cornea is calculated, the initial error is set to 0.01 millimeter, the iteration step is 0.005 millimeter, the actual displacement correction amount is gradually approached, the correction amount is calculated through multiple iterations, and the position change evaluation data is generated;

[0106] The device position adjustment submodule: based on the position change evaluation data, the step motor control algorithm is used to adjust the position and angle of the imaging device, the position change evaluation data is input as the control target, the step length of the step motor is set to 0.01 millimeter, the angle adjustment range is 0 to 10 degrees, the feedback control mechanism is used to monitor the change of the device position in real time, the step speed of the motor is gradually adjusted and the angle and position are corrected, and the position adjustment data is generated.

[0107] Please refer to Figure 2 , the system self-checking module includes a focal length detection submodule, an optical path detection submodule, and a displacement detection submodule, wherein:

[0108] The focal length detection submodule: based on the position adjustment data, the focal length measurement of the imaging system is performed, the focal length parameters of each point are collected, the deviation of the focal length from the preset value is checked, and the focal length detection data is generated;

[0109] The optical path detection submodule: based on the focal length detection data, the optical signal transmission state of each point in the optical path is measured, the optical path deviation of the key points is analyzed, the overall operation state of the optical path is obtained, and the optical path detection data is generated;

[0110] The displacement detection submodule: based on the optical path detection data, the displacement between the imaging device and the corneal surface is measured, the displacement sensor is used to determine the deviation between the device and the target position, and the displacement detection data is generated;

[0111] The focal length detection submodule: based on the position adjustment data, the phase detection autofocus algorithm is used for focal length measurement of the imaging system, the input parameters are the position adjustment data and the focal length preset value, the phase difference method is used to measure the focal length parameters of each point, the optical sensor is used to collect the phase difference information in the image in real time, the accuracy of the phase difference detection is set to 0.01 millimeter, the difference between the current focal length and the preset focal length is calculated, the sampling frequency of the sensor is gradually adjusted to 100 times per second, the complete focal length data is collected and the focal length deviation of each point is recorded, and the focal length detection data is generated;

[0112] The light path detection sub-module: based on the focal length detection data, the light signal transmission state of each point in the light path is measured by using the ray tracing method, the focal length detection data is input as the initial parameter, the transmission path of each light ray is calculated by using the light ray tracing model, the reflectivity of each light path point is set to 0.95, the refraction and reflection process of the light ray between each optical element is calculated, the transmission intensity of the light ray at each position is tracked, the light path deviation of the key point is analyzed, the light signal intensity and deviation information are recorded, the overall operation state of the light path is obtained, the light path detection data is generated;

[0113] The displacement detection sub-module: based on the light path detection data, the displacement between the imaging device and the corneal surface is measured by using the laser displacement sensor, the light path detection data is input as the calibration parameter, the sampling frequency of the laser displacement sensor is set to 500 times per second, the three-point measurement method is used to determine the accurate position of the device relative to the corneal surface, the displacement difference of each point is calculated, the noise data is filtered by using the internal filtering algorithm of the sensor, and the displacement detection data is generated.

[0114] The above is only the preferred embodiment of the present application, and does not limit the form of the present application, any skilled person in the art can use the disclosed technical content to make changes or modifications as equivalent embodiments applied to other fields, but any simple modification, equivalent change and modification made according to the technical essence of the present application to the above embodiments without departing from the technical solution content of the present application still belongs to the protection scope of the present application technical solution.

Claims

1. A fully automatic focusing and positioning system based on corneal topography, characterized in that, The system includes: Optical Imaging Module: Based on optical devices, it collects multi-angle light signals from the corneal surface, processes light reflection from different areas of the corneal surface, uses the differences in reflected light intensity to determine the edges of corneal regions, calculates the light reflection angle and intensity, identifies the light signal characteristics of key areas, and obtains light reflection characteristic data. Curvature analysis module: Based on the light reflection feature data, the corneal surface area is segmented, and by analyzing the relationship between the light reflection angle and position, local curvature information of the corneal surface is extracted. Combined with the curvature values ​​of different areas, the overall curvature change is analyzed, the curvature of key positions is calculated, and curvature change distribution data is generated. Focal length control module: Based on the curvature change distribution data, a PID control algorithm is used to perform correlation analysis between corneal curvature value and focal length. By analyzing the curvature changes in each region, the focal length adjustment point is determined, the focal length offset range is calculated, the focal length device is adjusted, the current focal length value is corrected, and the relationship between focal length and curvature is ensured to be consistent, thereby generating the focal length adjustment result. Imaging calibration module: Based on the focal length adjustment result, analyze the current optical path state, determine the position of key points in the optical path by measuring the optical path offset after focal length adjustment, calculate the relative deviation between the optical path and the corneal surface, adjust the angle and position of the optical sensor, and generate optical path calibration parameters; Focus adjustment module: Based on the optical path calibration parameters, it performs focus adjustment, judges the imaging quality of different areas of the corneal surface, analyzes the deviation between focal length and imaging position through the focusing intensity of the light signal, gradually corrects the displacement and angle of the focusing device, updates the focus status, and generates focus position correction data. Position correction module: Based on the focus position correction data, analyze the displacement deviation between the imaging device and the corneal surface, calculate the position change of the device relative to the cornea through displacement sensor data, select correction points to adjust the device position, correct the displacement parameters of the imaging device, update the position status, and generate position adjustment data; System self-test module: Based on the position adjustment data, the system status is detected. Through the multi-point detection module, key parameters such as focal length, optical path and displacement are measured, the operating status of the equipment is analyzed, the overall situation of corneal imaging is judged, the normality of all system parameters is confirmed, and a system test report is generated. The focal length control module includes a curvature analysis submodule, a focal length adjustment point determination submodule, and a focal length offset calculation submodule, wherein: Curvature Analysis Submodule: Based on the curvature change distribution data, analyze the curvature changes in different regions of the corneal surface, extract key point information of curvature changes, establish curvature change models for each region of the corneal surface, and generate curvature key point information; Focal length adjustment point determination submodule: Based on the curvature key point information, compare the correlation between curvature values ​​and focal length in different regions, determine the optimal position for focal length adjustment by calculating the influence range of the curvature change position, and generate focal length adjustment point information; Focal length offset calculation submodule: Based on the focal length adjustment point information, a PID control algorithm is used to calculate the offset that the focal length device needs to be adjusted. Combined with the focal length control parameters of the system, the focal length offset value is determined, the focal length device is adjusted, and the focal length adjustment result is generated.

2. The fully automatic focusing and positioning system based on corneal topography according to claim 1, characterized in that, The light reflection characteristic data includes the reflection intensity, light incident angle, and reflection angle distribution of different regions of the corneal surface. The curvature change distribution data includes the curvature values ​​of each zone, the curvature change amplitude of the corneal surface, and the curvature difference value of key points. The focal length adjustment results include the focal length offset value, focal length correction parameters, and the relationship between focal length and curvature. The optical path calibration parameters include the optical path offset angle, the corrected sensor position, and the optical path deviation correction value. The focus position correction data includes the focus distance correction value, the focus adjustment amount of the imaging area, and the focal length correction parameters. The position adjustment data includes the device displacement correction amount, the relative position offset value of the cornea, and the position calibration parameters. The system detection report includes the focal length calibration data, the optical path status detection results, and the device displacement correction results.

3. The fully automatic focusing and positioning system based on corneal topography according to claim 1, characterized in that, The optical imaging module includes a light signal acquisition submodule, a light intensity analysis submodule, and a light reflection feature recognition submodule, wherein: Optical signal acquisition submodule: Based on optical devices, it performs multi-angle optical signal acquisition of different regions of the corneal surface, acquires and records the light reflection information of each region, and generates optical signal data; Light intensity analysis submodule: Based on the light signal data, calculate the light reflection intensity of each corneal region, compare the light intensity differences at different angles, and generate light intensity distribution data; Light reflection feature recognition submodule: Based on the light intensity distribution data, it identifies the light reflection features of key areas on the corneal surface, extracts the edge features of each area, and generates light reflection feature data.

4. The fully automatic focusing and positioning system based on corneal topography according to claim 1, characterized in that, The curvature analysis module includes a region division submodule, a curvature information extraction submodule, and a curvature change calculation submodule, wherein: Region segmentation submodule: Based on the light reflection feature data, the corneal surface is segmented into regions, and the boundaries of each region are defined according to the differences in light reflection features, generating region segmentation data; Curvature information extraction submodule: Based on the region division data, extract local curvature information in each partition, calculate the curvature change amplitude of each region, and generate local curvature data; Curvature change calculation submodule: Based on the local curvature data and combined with the curvature changes in different zones, analyze the overall curvature distribution of the cornea and generate curvature change distribution data.

5. The fully automatic focusing and positioning system based on corneal topography according to claim 1, characterized in that, The PID control algorithm is adopted, according to the formula: ； in: This is the offset that the focusing device needs to be adjusted by. This is the proportionality coefficient. This represents the error between the current focal length value and the target focal length value. The integral coefficient represents the impact of accumulated error on system adjustment and is used to compensate for errors that have existed for a long time. From time 0 to the current time The error integral, These are the differential coefficients. The rate of change of error over time. External environment coefficient, The rate of change of ambient light. The system load factor. This represents the rate of change of the lens angle.

6. The fully automatic focusing and positioning system based on corneal topography according to claim 1, characterized in that, The imaging calibration module includes an optical path state analysis submodule, an optical path offset measurement submodule, and a sensor position adjustment submodule, wherein: Optical path state analysis submodule: Based on the focal length adjustment result, analyze the current state of the optical path, determine the changes in the optical path after the focal length adjustment, identify the shift of key points in the optical path, and generate optical path state information; Optical path offset measurement submodule: Based on the optical path state information, it measures the actual offset of each key point in the optical path, calculates the deviation value of each position in the optical path, obtains the overall offset information of the optical path, and generates optical path offset data; Sensor position adjustment submodule: Based on the optical path offset data, adjust the angle and position of the optical sensor, correct the sensor's position in the optical path, ensure that the sensor is aligned with the optical path, and generate optical path calibration parameters.

7. The fully automatic focusing and positioning system based on corneal topography according to claim 1, characterized in that, The focus adjustment module includes an image quality judgment submodule, a focus deviation analysis submodule, and a focus correction submodule, wherein: Imaging quality assessment submodule: Based on the optical path calibration parameters, it assesses the imaging quality of each region of the cornea, analyzes the imaging effect of different regions through focus intensity measurement, identifies poor imaging regions, and generates imaging quality assessment data; Focal length deviation analysis submodule: Based on the imaging quality assessment data, analyze the deviation between the imaging position and the focal length, assess the impact of focal length changes in each region on the imaging position, calculate the focal length adjustment requirements, and generate focal length deviation information. Focus correction submodule: Based on the focal length deviation information, adjust the displacement and angle of the focusing device, correct the focal length and position of the imaging device, gradually update the focusing status, and generate focus position correction data.

8. The fully automatic focusing and positioning system based on corneal topography according to claim 1, characterized in that, The position correction module includes a displacement deviation analysis submodule, a position change evaluation submodule, and a device position adjustment submodule, wherein: Displacement Deviation Analysis Submodule: Based on the focus position correction data, analyze the displacement deviation between the imaging device and the corneal surface, determine the deviation of the relative position of the device by comparing the data of the displacement sensor, and generate displacement deviation information; Position change assessment submodule: Based on the displacement deviation information, assess the specific positional change of the imaging device relative to the corneal surface, calculate the correction amount required for device movement, and generate position change assessment data; Device position adjustment submodule: Based on the position change evaluation data, adjust the position and angle of the device, correct the displacement parameters of the imaging device, ensure that the device is aligned with the cornea, and generate position adjustment data.

9. The fully automatic focusing and positioning system based on corneal topography according to claim 1, characterized in that, The system self-test module includes a focal length detection submodule, an optical path detection submodule, and a displacement detection submodule, wherein: Focal length detection submodule: Based on the position adjustment data, the focal length of the imaging system is measured, focal length parameters at each point are collected, the deviation between the focal length and the preset value is checked, and focal length detection data is generated. Optical path detection submodule: Based on the focal length detection data, it measures the optical signal transmission status at each point in the optical path, analyzes the optical path deviation at key points, obtains the overall operating status of the optical path, and generates optical path detection data; Displacement detection submodule: Based on the optical path detection data, it measures the displacement between the imaging device and the corneal surface, uses a displacement sensor to determine the deviation between the device and the target position, and generates displacement detection data.

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