Automatic multi-segmental arc fitting method and device applied to corneal contact lens

Abstract

The invention relates to the technical field of data analysis, in particular to an automatic multi-segmental arc fitting method and device applied to a corneal contact lens. The method comprises the following steps: automatically segmenting a plurality of arc segments by using a multi-segment arc automatic segmentation algorithm; the method comprises the following steps: firstly, fitting a central arc section by using experience knowledge, and automatically segmenting information of a first arc section by using a data point and a first arc section fitting error; and iteratively searching different arc segments in sequence, fitting the searched different arc segments, and completing automatic segmentation of different arc segments and curvature radius measurement of the corneal contact lens. According to the method, the central arc segment is fitted by using experience knowledge, the information of the first arc segment is automatically segmented by using the fitting error of the data point and the first arc segment, the different arc segments are iteratively searched in sequence, and finally the automatic segmentation and curvature radius measurement of the different arc segments of the corneal contact lens are completed, so that the measurement error caused by the fitting of too small arc segments is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to an automatic multi-segment arc fitting method and device applied to corneal contact lenses. Background Art

[0002] Contact lenses (also called contact lenses) can be divided into two categories according to the different materials used, namely hard contact lenses and soft contact lenses. They are widely used because of their small size, light weight and wide field of view. Compared with frame glasses, contact lenses are in direct contact with the human cornea, so material safety and parameter reliability are crucial. From a morphological analysis, the cornea is not a sphere. The center of the cornea is approximately in the range of 3mm-4mm, which is the corneal cap, and is considered a sphere. In general, measuring parameters such as the radius of curvature is actually measuring the degree of the corneal cap, and the flatter it is toward the periphery of the cornea, so if the lens is designed with only one arc and is designed only according to the arc of the center of the cornea, it may not match at the periphery of the cornea or the limbus of the cornea, which may cause over-tightness or indentation, so the second arc, third arc, or even more arcs will be designed from the central area to the periphery.

[0003] The purpose of designing these arcs is to match the morphology of the peripheral cornea to ensure reasonable adaptation, which can improve comfort on the one hand and ensure tear circulation on the other. It should also be noted that there is a bulge at the intersection of the arcs. From the above picture, you can see that there is a bulge at the intersection of each arc, which is called a knot. It is a byproduct of the multi-arc design. If it is worn in the eyes, it will put pressure on the cornea and cause a foreign body sensation. Therefore, when designing lenses, manufacturers often make special treatments for knots, such as grinding and polishing, to reduce discomfort when wearing.

[0004] The measurement of the geometric parameters of corneal contact lenses is an important part of ensuring their wearing effect and vision safety. This includes testing whether the parameters of the curvature radius of different arc segments meet the design values. Generally, keratometers, profilometers or OCT-based corneal contact lens measurement equipment are used for measurement. However, since the curvature radius of different arc segments of the contact lens is inconsistent, and the arc segment range is smaller as it goes outward, the arc segment measurement error is large and it is difficult to distinguish different arc segments.

[0005] In summary, the prior art has the following technical problems:

[0006] 1. The parameters measured by profilometers and other measuring equipment are mostly compared with the design values ​​and the obtained contours, and the curvature radius distribution of arc segments in different ranges is obtained by partitioning, which is difficult to automatically segment.

[0007] 2. In a corneal contact lens parameter measurement system based on SD-OCT, it is proposed to use polynomial curve fitting for arc segment discrimination measurement. However, most of the data points deviate from the fitting curve in the fitting effect. Summary of the Invention

[0008] An embodiment of the present invention provides an automatic multi-arc circular arc fitting method and device for corneal contact lenses to at least solve the technical problem of poor fitting effect of existing multi-arc circular arc fitting.

[0009] According to an embodiment of the present invention, an automatic multi-arc circular arc fitting method for corneal contact lenses is provided, including the following steps:

[0010] S101: Automatically segment the multi-arc segments using a multi-segment arc automatic segmentation algorithm;

[0011] S102: First fit the central arc segment using empirical knowledge, and automatically segment the information of the first arc segment using the fitting error between the data points and the first arc segment;

[0012] S103: Iteratively search for different arc segments in sequence, and fit the searched different arc segments to complete the automatic segmentation of different arc segments of the corneal contact lens and the measurement of the radius of curvature.

[0013] Further, in step S101, the left and right arc segments are combined for circular fitting calculation, and the center range is constrained in the circular arc fitting algorithm, and the center parameters of different arc segments are constrained on the same straight line.

[0014] Further, step S101 includes:

[0015] (1) According to the conventional design parameters, perform circular arc fitting on the area near the axis of symmetry with a diameter range of 5 mm to obtain the parameters (a1, b1, R1) of the first segment, and calculate the error of all sample points N according to the circular parameters:

[0016] (2) Calculate the fitting error threshold, the average error and standard deviation of the points in the diameter range of 6 mm:

[0017] (3) According to the fitting error threshold tolE, find the end point of the upper segment arc and the start point of the lower segment arc, and perform circular arc fitting of the second segment with a step size of step1;

[0018] (4) According to the circular arc fitting parameters of the second segment arc, repeat step (2) for the remaining points. If the obtained value of meanE is large, it means that the step size of step1 is too large and the circular arc fitting error is large. Then update the search step size to step1 / 2 and reread step (2) until meanE < tol1, repeat step (3), update the end point of the second segment arc and start the calculation of the next segment arc;

[0019] (5) Repeat steps (2)-(4) until all data points are calculated.

[0020] Further, the range of the next arc points is: (-endPoint1-step, endPoint1-Btol) and (endPoint1+Btol, endpoint1+step), where Btol is the interval point added to remove the connection between the first arc and the second arc.

[0021] Further, step S103 specifically includes:

[0022] (1) According to the conventional design parameters, perform circular arc fitting on the area within a 5-mm aperture range close to the axis of symmetry to obtain the parameters (a1, b1, R1) of the first segment, and calculate the error of all sample points N according to the circle parameters:

[0023]

[0024] (2) Calculate the fitting error threshold, the average error and standard deviation of the points within a 6-mm aperture range:

[0025]

[0026]

[0027] tolE = meanE + 3 * stdE

[0028] (3) Find the end point of the upper arc and the start point of the lower arc according to the fitting error threshold tolE, and perform circular arc fitting on the second segment with a step size of step1:

[0029]

[0030] (4) According to the circular arc fitting parameters of the second arc segment, repeat step (2) for the remaining points. If the obtained value of meanE is large, it indicates that the step size of step1 is too large and the circular arc fitting error is large. Then update the search step size to step1 / 2 and re-read step (2) until meanE < tol1, repeat step (3), update the end point of the second arc segment and start calculating the next arc segment;

[0031] (5) Repeat steps (2)-(4) until all data points are calculated.

[0032] Further, use the circle fitting algorithm to fit the segmented short arc segments.

[0033] Further, the circle fitting algorithm specifically includes:

[0034]

[0035] Where (x i ,y i ) is one of the n data points of a circular arc, (a, b, R) are the center position and the radius of the arc respectively;

[0036] For an arc, point A, point B, and point C are the leftmost, middle, and rightmost points of the same arc. The initial arc fitting is performed through these three points to obtain the initial circle fitting parameters:

[0037]

[0038] Solve the linear equations to obtain the initial solution of the center parameters (a0, b0), and the initial parameters of the radius are:

[0039]

[0040] The initial solution of the circle center is combined with the least squares optimization algorithm to iteratively solve the objective function: Minimum circle parameters

[0041] In order to eliminate the influence of data noise, the error of each point after fitting is calculated:

[0042]

[0043] If the point error meets the requirements, remove these data points and use the least squares algorithm to optimize the circle parameters again:

[0044]

[0045] According to another embodiment of the present invention, there is provided an automatic multi-segment arc fitting device for corneal contact lenses, comprising:

[0046] An automatic segmentation unit, used for automatically segmenting multiple arc segments using a multi-segment arc automatic segmentation algorithm;

[0047] The fitting unit is used to fit the central arc segment first by using empirical knowledge, and automatically segment the first arc segment information by using the data point and the fitting error of the first arc segment;

[0048] The iteration unit is used for iteratively searching different arc segments in sequence and fitting the searched different arc segments to complete the automatic segmentation of different arc segments of the corneal contact lens and the measurement of the curvature radius.

[0049] A storage medium stores a program file capable of realizing any one of the above-mentioned automatic multi-segment arc fitting methods applied to corneal contact lenses.

[0050] A processor is used to run a program, wherein when the program is run, any one of the above-mentioned automatic multi-segment arc fitting methods applied to corneal contact lenses is executed.

[0051] The automatic multi-segment arc fitting method and device for corneal contact lenses in the embodiments of the present invention use empirical knowledge to first fit the central arc segment, automatically segment the first arc segment information using data points and the first arc segment fitting error, iteratively search different arc segments in turn, and finally complete the automatic segmentation of different arc segments of the corneal contact lens and the measurement of the curvature radius, thereby reducing the measurement error caused by fitting of too small arc segments. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0053] Figure 1 It is a flow chart of the automatic multi-segment arc fitting method applied to corneal contact lenses of the present invention;

[0054] Figure 2 This is a flow chart of the arc fitting algorithm in the present invention;

[0055] Figure 3 It is a flow chart of the multi-segment arc automatic segmentation algorithm in the present invention;

[0056] Figure 4 The module diagram of the automatic multi-segment arc fitting device applied to corneal contact lenses of the present invention. DETAILED DESCRIPTION

[0057] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0058] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0059] Example 1

[0060] According to an embodiment of the present invention, an automatic multi-segment arc fitting method for corneal contact lenses is provided. Figure 1 , including the following steps:

[0061] S101: Automatically segmenting multiple arc segments using a multi-segment arc automatic segmentation algorithm;

[0062] S102: fitting the central arc segment firstly by using the experience knowledge, and automatically segmenting the first arc segment information by using the data point and the fitting error of the first arc segment;

[0063] S103: Iteratively search for different arc segments in sequence, and fit the searched different arc segments to complete automatic segmentation of different arc segments of the corneal contact lens and measurement of the curvature radius.

[0064] The automatic multi-segment arc fitting method applied to corneal contact lenses in the embodiment of the present invention uses empirical knowledge to first fit the central arc segment, automatically segments the first arc segment information using data points and the first arc segment fitting error, and iteratively searches different arc segments in turn to finally complete the automatic segmentation of different arc segments of the corneal contact lens and the measurement of the curvature radius, thereby reducing the measurement error caused by fitting of too small arc segments.

[0065] Specifically, contact lenses are commonly used for vision correction and keratoconus control in adolescents, and they are in direct contact with the human cornea. Since the cornea is not a regular sphere, the periphery of the cornea is flatter than the center of the cornea. In order to better fit the cornea and improve wearing comfort, contact lenses are mostly designed to be spliced ​​with several arcs of different curvature radii. For samples such as contact lenses that are composed of multiple arcs of different arcs, since the caliber of each arc is small and there is no obvious dividing point, the present invention proposes an automatic arc segmentation algorithm for such contact lenses, which first fits the central arc segment using empirical knowledge, and automatically segments the first arc segment information using the data point and the first arc segment fitting error, and then iterates and searches for different arc segments in turn, and finally completes the automatic segmentation of different arc segments of the contact lens and the measurement of the curvature radius.

[0066] The present invention provides an automatic multi-segment arc fitting method for corneal contact lenses. Since the measured multi-segment samples are mostly axisymmetric, that is, the left and right arc segments are symmetrical, the left and right arc segments can be fitted together to reduce the measurement error caused by fitting too small arc segments.

[0067] 1. Arc fitting algorithm

[0068] See also Figure 2 ,Due to the limited data points and the included arc segments range is small and the data points contain noise information, a ,circle fitting algorithm for short arc segments is proposed.

[0069]

[0070] Where (x i ,y i ) is one of the n data points of a circular arc, and (a, b, R) are the center position and the radius of the arc respectively.

[0071] For example, for an arc, point A, point B, and point C are the leftmost, middle, and rightmost points of the same arc. The initial arc fitting is performed through these three points to obtain the initial circle fitting parameters:

[0072]

[0073] Solve the linear equations to obtain the initial solution of the center parameters (a0, b0), and the initial parameters of the radius are:

[0074]

[0075] The initial solution of the circle center is combined with the least squares optimization algorithm to iteratively solve the objective function: Minimum circle parameters

[0076] In order to eliminate the influence of data noise, the error of each point after fitting is calculated:

[0077]

[0078] If the point error satisfies the formula, these data points are removed and the least squares algorithm is used again to optimize the circle parameters.

[0079]

[0080] 2. Multi-segment arc automatic segmentation algorithm

[0081] See also Figure 3, since most of the samples are composed of symmetric arc segments, that is, the left and right arcs are different regions of the same arc, the left and right arc segments can be combined for circle fitting calculation, and the center range constraint is performed on the circle fitting algorithm to constrain the center parameters of different arc segments on the same straight line.

[0082] The specific process is as follows:

[0083] (1) According to the conventional design parameters, perform circular arc fitting on the area within a 5 mm aperture range close to the symmetry axis to obtain the parameters (a1, b1, R1) of the first segment, and calculate the error of all sample points N according to the circle parameters:

[0084]

[0085] (2) Calculate the fitting error threshold, the average error and standard deviation of the points within a 6 mm aperture range:

[0086] tolE = meanE + 3 * stdE(9)

[0087] (3) According to the fitting error threshold tolE, find the end point of the upper segment arc and the start point of the lower segment arc, and perform circular arc fitting on the second segment with a step size of step1:

[0088]

[0089] The point range of the next arc is: (-endPoint1 - step, endPoint1 - Btol) and (endPoint1 + Btol, endpoint1 + step), where Btol is the interval point added to remove the connection between the first arc and the second arc.

[0090] (4) According to the circular arc fitting parameters of the second segment arc, repeat step (2) for the remaining points (removing the determined upper segment arc region (-endpoint1, endpoint1)). If the obtained value of meanE is large, it means that the step size of step1 is too large and the circular arc fitting error is large. Then update the search step size to step1 / 2 and re-read step (2) until meanE < tol1, repeat step (3), update the end point of the second segment arc and start calculating the next segment arc.

[0091] (5) Repeat steps (2)-(4) until all data points are calculated.

[0092] The key points and the points to be protected in the present invention are:

[0093] The present invention proposes an automatic arc segmentation algorithm for contact lens measurement. Based on the extracted two-dimensional contour of the contact lens, arc fitting is performed to automatically identify different partitions of the contact lens and calculate the corresponding curvature radius.

[0094] Compared with the prior art, the present invention can automatically perform arc segmentation, does not require detailed design information, and can also perform measurements in the case of missing design data.

[0095] Example 2

[0096] According to another embodiment of the present invention, there is provided an automatic multi-segment arc fitting device for corneal contact lenses, see Figure 4 ,include:

[0097] An automatic segmentation unit 201, used for automatically segmenting multiple arc segments using a multi-segment arc automatic segmentation algorithm;

[0098] A fitting unit 202 is used to fit the central arc segment first by using empirical knowledge, and automatically segment the first arc segment information by using the data point and the fitting error of the first arc segment;

[0099] The iteration unit 203 is used to iteratively search for different arc segments in sequence and fit the searched different arc segments to complete the automatic segmentation of different arc segments of the corneal contact lens and the measurement of the curvature radius.

[0100] The automatic multi-segment arc fitting device applied to corneal contact lenses in the embodiment of the present invention uses empirical knowledge to first fit the central arc segment, automatically segments the first arc segment information using data points and the first arc segment fitting error, and iteratively searches different arc segments in turn to finally complete the automatic segmentation of different arc segments of the corneal contact lens and the measurement of the curvature radius, thereby reducing the measurement error caused by fitting of too small arc segments.

[0101] Specifically, contact lenses are commonly used for vision correction and keratoconus control in adolescents, and they are in direct contact with the human cornea. Since the cornea is not a regular sphere, the periphery of the cornea is flatter than the center of the cornea. In order to better fit the cornea and improve wearing comfort, contact lenses are mostly designed to be spliced ​​with several arcs of different curvature radii. For samples such as contact lenses that are composed of multiple arcs of different arcs, since the caliber of each arc is small and there is no obvious dividing point, the present invention proposes an automatic arc segmentation algorithm for such contact lenses, which first fits the central arc segment using empirical knowledge, and automatically segments the first arc segment information using the data point and the first arc segment fitting error, and then iterates and searches for different arc segments in turn, and finally completes the automatic segmentation of different arc segments of the contact lens and the measurement of the curvature radius.

[0102] The present invention provides an automatic multi-segment arc fitting device for corneal contact lenses. Since the measured multi-segment samples are mostly axisymmetric, that is, the left and right arc segments are symmetrical, the left and right arc segments can be fitted together to reduce the measurement error caused by fitting too small arc segments.

[0103] 1. Arc fitting algorithm

[0104] See also Figure 2 ,Due to the limited data points and the included arc segments range is small and the data points contain noise information, a ,circle fitting algorithm for short arc segments is proposed.

[0105]

[0106] Where (x i ,y i ) is one of the n data points of a circular arc, and (a, b, R) are the center position and the radius of the arc respectively.

[0107] For example, for an arc, point A, point B, and point C are the leftmost, middle, and rightmost points of the same arc. The initial arc fitting is performed through these three points to obtain the initial circle fitting parameters:

[0108]

[0109]

[0110] Solve the linear equations to obtain the initial solution of the center parameters (a0, b0), and the initial parameters of the radius are:

[0111]

[0112] The initial solution of the circle center is combined with the least squares optimization algorithm to iteratively solve the objective function: Minimum circle parameters

[0113] In order to eliminate the influence of data noise, the error of each point after fitting is calculated:

[0114]

[0115] If the point error satisfies the formula, these data points are removed and the least squares algorithm is used again to optimize the circle parameters.

[0116]

[0117] 2. Multi-segment arc automatic segmentation algorithm

[0118] See also Figure 3, since most of the samples are composed of symmetric arc segments, that is, the left and right circular arcs are different regions of the same arc, the left and right arc segments can be merged for circle fitting calculation, and the center range constraint is carried out on the circle arc fitting algorithm, and the center parameters of different arc segments are constrained on the same straight line.

[0119] The specific process is as follows:

[0120] (1) According to the conventional design parameters, perform circular arc fitting on the area within a 5-mm diameter range close to the symmetry axis to obtain the parameters (a1, b1, R1) of the first segment, and calculate the error of all sample points N according to the circle parameters:

[0121]

[0122] (2) Calculate the fitting error threshold, the average error and standard deviation of the points within a 6-mm diameter range:

[0123]

[0124]

[0125] tolE = meanE + 3 * stdE(9)

[0126] (3) According to the fitting error threshold tolE, find the end point of the upper segment arc and the start point of the lower segment arc, and perform circular arc fitting on the second segment with a step size of step1:

[0127]

[0128] The point range of the next segment arc is: (-endPoint1-step, endPoint1-Btol) and (endPoint1+Btol, endpoint1+step), where Btol is the interval point added to remove the connection between the first segment arc and the second segment arc.

[0129] (4) According to the circular arc fitting parameters of the second segment arc, repeat step (2) for the remaining points (excluding the determined upper segment arc area (-endpoint1, endpoint1)). If the obtained value of meanE is large, it means that the step size of step1 is too large and the circular arc fitting error is large. Then update the search step size to step1 / 2 and re-read step (2) until meanE < tol1, repeat step (3), update the end point of the second segment arc and start calculating the next segment arc.

[0130] (5) Repeat steps (2)-(4) until all data points are calculated.

[0131] The key points and points to be protected in the present invention are:

[0132] The present invention proposes an automatic arc segmentation algorithm for contact lens measurement. Based on the extracted two-dimensional contour of the contact lens, arc fitting is performed to automatically identify different partitions of the contact lens and calculate the corresponding curvature radius.

[0133] Compared with the prior art, the present invention can automatically perform arc segmentation, does not require detailed design information, and can also perform measurements in the case of missing design data.

[0134] Example 3

[0135] A storage medium stores a program file capable of realizing any one of the above-mentioned automatic multi-segment arc fitting methods applied to corneal contact lenses.

[0136] Example 4

[0137] A processor is used to run a program, wherein when the program is run, any one of the above-mentioned automatic multi-segment arc fitting methods applied to corneal contact lenses is executed.

[0138] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0139] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0140] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the system embodiments described above are only schematic. For example, the division of units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0141] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed over multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0142] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0143] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0144] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. An automatic multi-segment arc fitting method for corneal contact lenses, characterized in that: It includes the following steps: S101: Automatically segment the multi-arc segments using the multi-segment arc automatic segmentation algorithm; S102: First, fit the central arc segment using empirical knowledge, and automatically segment the first arc segment information based on the fitting error between the data points and the first arc segment; S103: Iteratively search for different arc segments in sequence, and fit the searched different arc segments to complete the automatic segmentation of different arc segments of the contact lens and the measurement of the radius of curvature.

2. The automatic multi-segment arc fitting method for corneal contact lenses according to claim 1, characterized in that: In step S101, the left and right arc segments are merged for circular fitting calculation, and the center range is constrained in the circular arc fitting algorithm, and the center parameters of different arc segments are constrained on the same straight line.

3. The automatic multi-segment arc fitting method for corneal contact lenses according to claim 1, characterized in that: Step S101 includes: (1) According to the conventional design parameters, perform circular arc fitting on the area within a 5-mm diameter range close to the axis of symmetry to obtain the parameters (a1, b1, R1) of the first segment, and calculate the error of all sample points N according to the circular parameters: (2) Calculate the fitting error threshold, the average error and standard deviation of the points within a 6-mm diameter range: (3) Find the end point of the upper segment arc and the start point of the lower segment arc according to the fitting error threshold tolE, and perform circular arc fitting of the second segment with a step size of step1; (4) According to the circular arc fitting parameters of the second segment arc, repeat step (2) for the remaining points. If the obtained value of meanE is large, it means that the step size of step1 is too large and the circular arc fitting error is large. Then update the search step size to step1 / 2 and reread step (2) until meanE < tol1, repeat step (3), update the end point of the second segment arc and start calculating the next segment arc; (5) Repeat steps (2)-(4) until all data points are calculated.

4. The automatic multi-segment arc fitting method for corneal contact lenses according to claim 3, characterized in that: The range of the next segment arc points is: (-endPoint1-step, endPoint1-Btol) and (endPoint1+Btol, endpoint1+step), where Btol is the interval point added to remove the connection between the first segment arc and the second segment arc.

5. The automatic multi-segment arc fitting method for corneal contact lenses according to claim 3, characterized in that: Step S103 specifically includes: (1) According to the conventional design parameters, perform circular arc fitting on the area within a 5-mm diameter range close to the axis of symmetry to obtain the parameters (a1, b1, R1) of the first segment, and calculate the error of all sample points N according to the circular parameters: (2) Calculate the fitting error threshold, the average error and standard deviation of the points within a 6-mm diameter range: tolE = meanE + 3*stdE (3) Find the end point of the upper segment arc and the start point of the lower segment arc according to the fitting error threshold tolE, and perform circular arc fitting of the second segment with a step size of step1: (4) According to the circular arc fitting parameters of the second segment arc, repeat step (2) for the remaining points. If the obtained value of meanE is large, it means that the step size of step1 is too large and the circular arc fitting error is large. Then update the search step size to step1 / 2 and reread step (2) until meanE < tol1, repeat step (3), update the end point of the second segment arc and start calculating the next segment arc; (5) Repeat steps (2)-(4) until all data points are calculated.

6. The automatic multi-segment arc fitting method for corneal contact lenses according to claim 1, characterized in that: Use the circular fitting algorithm to fit the segmented short arc segments.

7. The automatic multi-segment arc fitting method for corneal contact lenses according to claim 6, characterized in that: The circular fitting algorithm specifically includes: Where (x i ,y i ) is one of the n data points of a circular arc, (a, b, R) are the center position and the radius of the arc respectively; For an arc, point A, point B, and point C are the leftmost, middle, and rightmost points of the same arc. The initial arc fitting is performed through these three points to obtain the initial circle fitting parameters: Solve the linear equations to obtain the initial solution of the center parameters (a0, b0), and the initial parameters of the radius are: The initial solution of the circle center is combined with the least squares optimization algorithm to iteratively solve the objective function: Minimum circle parameters In order to eliminate the influence of data noise, the error of each point after fitting is calculated: If the point error meets the requirements, remove these data points and use the least squares algorithm to optimize the circle parameters again:

8. An automatic multi-segment arc fitting device for corneal contact lenses, characterized in that: include: An automatic segmentation unit, used for automatically segmenting multiple arc segments using a multi-segment arc automatic segmentation algorithm; The fitting unit is used to fit the central arc segment first by using empirical knowledge, and automatically segment the first arc segment information by using the data point and the fitting error of the first arc segment; The iteration unit is used for iteratively searching different arc segments in sequence and fitting the searched different arc segments to complete the automatic segmentation of different arc segments of the corneal contact lens and the measurement of the curvature radius.

9. A storage medium, characterized in that: The storage medium stores a program file capable of implementing the automatic multi-segment arc fitting method applied to corneal contact lenses as described in any one of claims 1 to 7.

10. A processor, characterized in that: The processor is used to run a program, wherein the program, when running, executes the automatic multi-segment arc fitting method for corneal contact lenses as described in any one of claims 1 to 7.

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