Refractive Device Calibration Method, Device, Terminal Device, and Storage Medium

Abstract

The present invention discloses a refractive device calibration method, apparatus, terminal device, and storage medium. The method includes: obtaining a human eye simulated visual field based on a pre-generated white noise target; performing refractive detection based on the human eye simulated visual field, and obtaining a refractive compensation detection value; and performing fitting calibration based on the refractive compensation detection value and a pre-obtained refractive compensation theoretical value to complete calibration. By simulating the human eye based on the white noise target, the present invention obtains a human eye simulated visual field, thereby reducing calibration errors. In addition, the present invention also performs refractive detection on the human eye simulated visual field to obtain a refractive compensation detection value, and performs fitting calibration based on the refractive compensation detection value and the refractive compensation theoretical value to complete calibration, providing accurate refractive compensation for peripheral refractive detection devices, thereby improving the calibration accuracy of peripheral refractive devices.

Description

Technical Field

[0001] The present invention relates to the technical field of equipment calibration, and particularly to a calibration method, device, terminal device, and storage medium for refractive equipment. Background Art

[0002] In recent years, the myopia incidence rate among teenagers in China has been gradually increasing, and the prevention and control of myopia have received extensive attention from all sectors of society. Regarding the research on human eye refractive error, it is no longer limited to central refraction, and equal importance is attached to the research on peripheral refraction. The myopia defocus theory shows that there is a close relationship between the peripheral refractive state of the human eye and the development of myopia. Peripheral hyperopic defocus of the human eye will accelerate the development of myopia, while myopic defocus can delay the development of myopia. The detection of the peripheral refractive state of the human eye is one of the key technologies for the prevention and control of adolescent myopia. At present, the calibration technology of central refractive detection equipment is very mature, and the calibration method is usually to calibrate using simulated eyes with different refractions. The state has also put forward relevant national standards for the calibrated simulated eyes.

[0003] However, in the existing calibration technology of peripheral refractive detection equipment, since the peripheral refractive detection equipment belongs to a large-field-of-view refractive detection equipment, if the calibration equipment needs to use a wide-angle simulated eye that matches its field of view, the traditional simulated eye adopts a long strip structure of "sphere + cylinder". The diameter of the frosted plane cylinder of the simulated eye is small, and the refractive state of the simulated human eye is limited to the central refraction of the human eye, and the peripheral refractive state is not involved. Therefore, a wide-angle simulated eye with a more complex structure needs to be designed, which poses very strict requirements on the structural design and manufacturing process of the simulated eye. The consistency and accuracy of the preparation of such simulated human eyes cannot be guaranteed during the production process, which is not conducive to mass production. In addition, this type of simulated eye has extremely high requirements for the detection position during calibration. Slight deviation or displacement of the simulated eye will cause the optical axis to be misaligned, which will cause the overall deviation of the peripheral refractive detection results and introduce a significant calibration error. To sum up, the calibration method in the prior art for calibrating peripheral refractive calibration equipment based on traditional simulated human eyes has low accuracy. Summary of the Invention

[0004] The main purpose of the present invention is to provide a calibration method, device, terminal device, and storage medium for refractive equipment, aiming to improve the provision of accurate refractive compensation for peripheral refractive detection equipment and improve the calibration accuracy of peripheral refractive equipment.

[0005] To achieve the above object, the present invention provides a calibration method for refractive equipment, which is applied to a peripheral refractive detection equipment. The calibration method for refractive equipment includes the following steps:

[0006] Obtain a simulated human eye field of view based on a pre-generated white noise target;

[0007] Perform refractive detection based on the simulated visual field of the human eye and obtain a refractive compensation detection value;

[0008] Perform fitting calibration based on the refractive compensation detection value and the pre-obtained refractive compensation theoretical value to complete calibration.

[0009] Optionally, before the step of obtaining the simulated visual field of the human eye based on the pre-generated white noise target, it includes:

[0010] Obtain a white noise image and generate the white noise target based on the white noise image.

[0011] Optionally, the step of performing refractive detection based on the simulated visual field of the human eye and obtaining a refractive compensation detection value includes:

[0012] Obtain an imaging map of the white noise target based on the simulated visual field of the human eye, and extract a feature region of the imaging map of the white noise target based on the imaging map of the white noise target;

[0013] Perform refractive detection based on the feature region to obtain the refractive compensation detection value.

[0014] Optionally, the step of obtaining an imaging map of the white noise target based on the simulated visual field of the human eye includes:

[0015] Perform supplementary lighting on the simulated visual field of the human eye based on the pre-obtained external light source to obtain a supplemented simulated visual field of the human eye;

[0016] Perform optical imaging based on the supplemented simulated visual field of the human eye to obtain the imaging map of the white noise target.

[0017] Optionally, before the step of performing supplementary lighting on the simulated visual field of the human eye based on the pre-obtained external light source to obtain a supplemented simulated visual field of the human eye, it includes:

[0018] Obtain the external light source, where the wavelength parameter of the external light source matches the preset device parameters.

[0019] Optionally, before the step of performing fitting calibration based on the refractive compensation detection value and the pre-obtained refractive compensation theoretical value to complete calibration, it includes:

[0020] Perform data analysis based on the preset target distance parameter to obtain first analysis data;

[0021] Obtain second analysis data based on the first analysis data and the preset compensation lens;

[0022] Obtain the refractive compensation theoretical value based on the first analysis data and the second analysis data.

[0023] Optionally, the step of performing fitting calibration based on the refractive compensation detection value and a pre-acquired refractive compensation theoretical value to complete calibration includes:

[0024] Performing fitting calibration on the refractive compensation measurement value and the refractive compensation theoretical value based on a preset fitting function to obtain a calibration curve;

[0025] Updating device parameters based on the calibration curve to complete calibration.

[0026] In addition, to achieve the above object, the present invention further provides a refractive device calibration apparatus, and the apparatus includes:

[0027] A field of view generation module, configured to obtain a simulated human eye field of view based on a pre-generated white noise target;

[0028] A refractive detection module, configured to perform refractive detection based on the simulated human eye field of view and obtain a refractive compensation detection value;

[0029] A calibration fitting module, configured to perform fitting calibration based on the refractive compensation detection value and a pre-acquired refractive compensation theoretical value to complete calibration.

[0030] Optionally, the field of view generation module is further configured to:

[0031] Obtain a white noise image and generate the white noise target based on the white noise image.

[0032] Optionally, the refractive detection module is further configured to:

[0033] Obtain a white noise target imaging diagram based on the simulated human eye field of view, and extract a feature region of the white noise target imaging diagram based on the white noise target imaging diagram;

[0034] Perform refractive detection based on the feature region to obtain the refractive compensation detection value.

[0035] Optionally, the refractive detection module is further configured to:

[0036] Perform supplementary lighting on the simulated human eye field of view based on a pre-acquired external light source to obtain a supplemented simulated human eye field of view;

[0037] Perform optical imaging based on the supplemented simulated human eye field of view to obtain the white noise target imaging diagram.

[0038] Optionally, the refractive detection module is further configured to:

[0039] Obtain the external light source, where a wavelength parameter of the external light source matches preset device parameters.

[0040] Optionally, the calibration fitting module is further configured to:

[0041] Perform data analysis based on the preset target distance parameter to obtain first analysis data;

[0042] Based on the first analysis data and a preset compensation lens, obtain second analysis data;

[0043] Obtain the refractive compensation theoretical value based on the first analysis data and the second analysis data.

[0044] Optionally, the calibration fitting module is further configured to:

[0045] Perform fitting calibration on the refractive compensation measurement value and the refractive compensation theoretical value based on a preset fitting function to obtain a calibration curve;

[0046] Update the device parameters based on the calibration curve to complete calibration.

[0047] In addition, to achieve the above object, the present invention further provides a terminal device, where the terminal device includes a memory, a processor, and a refractive device calibration program stored on the memory and executable on the processor. When the refractive device calibration program is executed by the processor, the refractive device calibration method as described above is implemented.

[0048] In addition, to achieve the above object, the present invention further provides a computer-readable storage medium, where a refractive device calibration program is stored on the computer-readable storage medium. When the refractive device calibration program is executed by a processor, the refractive device calibration method as described above is implemented.

[0049] A refractive device calibration method, device, terminal device, and storage medium proposed by the present invention obtain a simulated human eye visual field based on a pre-generated white noise target; perform refractive detection based on the simulated human eye visual field and obtain a refractive compensation detection value; perform fitting calibration based on the refractive compensation detection value and a pre-obtained refractive compensation theoretical value to complete calibration. The present invention reduces calibration errors by simulating the human eye based on a white noise target to obtain a simulated human eye visual field; in addition, the present invention also performs refractive detection on the simulated human eye visual field to obtain a refractive compensation detection value, and performs fitting calibration based on the refractive compensation detection value and the refractive compensation theoretical value to complete calibration, providing accurate refractive compensation for peripheral refractive detection devices, thereby improving the calibration accuracy of peripheral refractive detection devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a schematic diagram of the functional modules of the terminal device to which the refractive device calibration device of the present invention belongs;

[0051] Figure 2 It is a schematic flowchart of the first exemplary embodiment of the refractive device calibration method of the present invention;

[0052] Figure 3 It is a schematic optical path diagram of the human eye and the refractive detection device in the first exemplary embodiment of the calibration method for the refractive device of the present invention;

[0053] Figure 4 It is a schematic optical path diagram of the refractive lens group and the refractive detection device in the first exemplary embodiment of the calibration method for the refractive device of the present invention;

[0054] Figure 5 It is a schematic flowchart of the second exemplary embodiment of the calibration method for the refractive device of the present invention;

[0055] Figure 6 It is a schematic flowchart of the third exemplary embodiment of the calibration method for the refractive device of the present invention;

[0056] Figure 7 It is a schematic diagram of the relationship between the target distance and the refractive compensation in the third exemplary embodiment of the calibration method for the refractive device of the present invention;

[0057] Figure 8 It is a schematic diagram of the relationship between the compensation lens and the refractive compensation in the third exemplary embodiment of the calibration method for the refractive device of the present invention;

[0058] Figure 9 It is a comparison chart of the peripheral refraction before and after calibration in the third exemplary embodiment of the calibration method for the refractive device of the present invention.

[0059] The realization, functional features and advantages of the object of the present invention will be further described with reference to the embodiments and the accompanying drawings. Specific Embodiments

[0060] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0061] The main solution of the embodiments of the present invention is: obtaining a simulated human eye visual field based on a pre-generated white noise target; performing refractive detection based on the simulated human eye visual field and obtaining a refractive compensation detection value; and performing fitting calibration based on the refractive compensation detection value and a pre-obtained refractive compensation theoretical value to complete the calibration.

[0062] The embodiments of the present application consider that in the current industry, when calibrating the peripheral refractive detection device with a traditional simulated human eye, the requirements for the detection position are extremely high. A slight deviation or displacement of the simulated eye will cause the optical axis to be misaligned, resulting in an overall shift of the peripheral refractive detection results and introducing a significant calibration error.

[0063] Based on this, the embodiments of the present application provide a solution. By simulating the human eye based on a white noise target, a simulated human eye visual field is obtained, thereby reducing calibration errors. In addition, in this embodiment, refractive detection is performed on the simulated human eye visual field to obtain a refractive compensation detection value, and fitting calibration is performed based on the refractive compensation detection value and the refractive compensation theoretical value to complete calibration, providing accurate refractive compensation for peripheral refractive detection devices, thereby improving the calibration accuracy of peripheral refractive detection devices.

[0064] Specifically, referring to Figure 1 , Figure 1 is a schematic diagram of the functional modules of the terminal device to which the refractive device calibration device of the present application belongs. The refractive device calibration device can be an independent device that can perform refractive device calibration and recommendation, and can be carried on the terminal device in the form of hardware or software. The terminal device can be an intelligent mobile terminal with data processing functions, or a fixed terminal device or server with data processing functions. In addition, the refractive device calibration device can also be carried in a refractive device calibration system.

[0065] In this embodiment, the terminal device to which the refractive device calibration device belongs at least includes an output module 110, a processor 120, a memory 130, and a communication module 140.

[0066] The memory 130 stores an operating system and a refractive device calibration program; the output module 110 can be a display screen, etc. The communication module 140 can include a WIFI module, a mobile communication module, and a Bluetooth module, etc., and communicates with external devices or servers through the communication module 140.

[0067] Among them, when the refractive device calibration program in the memory 130 is executed by the processor, the following steps are implemented:

[0068] Obtain a simulated human eye visual field based on a pre-generated white noise target;

[0069] Perform refractive detection based on the simulated human eye visual field, and obtain a refractive compensation detection value;

[0070] Perform fitting calibration based on the refractive compensation detection value and the pre-obtained refractive compensation theoretical value to complete calibration.

[0071] Further, when the refractive device calibration program in the memory 130 is executed by the processor, the following steps are also implemented:

[0072] Obtain a white noise image, and generate the white noise target based on the white noise image.

[0073] Further, when the refractive device calibration program in the memory 130 is executed by the processor, the following steps are also implemented:

[0074] Obtain the imaging diagram of the white noise target based on the simulated visual field of the human eye, and extract the characteristic region of the imaging diagram of the white noise target based on the imaging diagram of the white noise target;

[0075] Perform refractive detection based on the characteristic region to obtain the refractive compensation detection value.

[0076] Furthermore, when the refractive device calibration program in the memory 130 is executed by the processor, the following steps are further implemented:

[0077] Supplementary light is performed on the simulated visual field of the human eye based on the pre-acquired external light source to obtain the supplemented simulated visual field of the human eye;

[0078] Perform optical imaging based on the supplemented simulated visual field of the human eye to obtain the imaging diagram of the white noise target.

[0079] Furthermore, when the refractive device calibration program in the memory 130 is executed by the processor, the following steps are further implemented:

[0080] Obtain the external light source, wherein the wavelength parameter of the external light source matches the preset device parameter.

[0081] Furthermore, when the refractive device calibration program in the memory 130 is executed by the processor, the following steps are further implemented:

[0082] Perform data analysis based on the preset target distance parameter to obtain the first analysis data;

[0083] Obtain the second analysis data based on the first analysis data and the preset compensation lens;

[0084] Obtain the refractive compensation theoretical value based on the first analysis data and the second analysis data.

[0085] Furthermore, when the refractive device calibration program in the memory 130 is executed by the processor, the following steps are further implemented:

[0086] Perform fitting calibration on the refractive compensation measurement value and the refractive compensation theoretical value based on the preset fitting function to obtain a calibration curve;

[0087] Update the device parameters based on the calibration curve to complete the calibration.

[0088] Through the above solution, this embodiment simulates the human eye based on the white noise target to obtain the simulated visual field of the human eye, thereby reducing the calibration error; in addition, this embodiment also performs refractive detection on the simulated visual field of the human eye to obtain the refractive compensation detection value, and performs fitting calibration based on the refractive compensation detection value and the refractive compensation theoretical value to complete the calibration, providing accurate refractive compensation for the peripheral refractive detection device, thereby improving the calibration accuracy of the peripheral refractive detection device.

[0089] Based on the above terminal device architecture but not limited to the above architecture, the method embodiments of the present application are proposed.

[0090] Referring to Figure 2 , Figure 2 is a schematic flowchart of the first exemplary embodiment of the refractive device calibration method of the present application. The refractive device calibration method includes:

[0091] S10, obtaining a simulated human eye visual field based on a pre-generated white noise target;

[0092] Specifically, considering that the calibration technology for central refractive detection devices in the industry has been very mature. However, the existing calibration technology for peripheral refractive detection devices uses a simulated eye with a visual field for calibration. As the number of visual fields to be calibrated increases, the requirements for the detection position of the simulated eye during calibration are extremely high. A slight deviation or displacement of the simulated eye will cause the optical axis to be misaligned, resulting in an overall shift in the peripheral refractive detection results and introducing a significant calibration error. As the number of visual fields to be calibrated increases, the design and preparation of the wide-angle simulated eye matching the visual field become more complex, introducing a significant processing error. This embodiment proposes a refractive device calibration method, which is applied to a peripheral refractive detection device, and the peripheral refractive detection device is a device specifically used to measure the peripheral refractive state of the eyeball. Future development will further promote the accuracy and reliability of peripheral refractive detection devices, providing better auxiliary tools for ophthalmologists and optometrists to evaluate and solve visual problems. The peripheral refractive detection device generates a simulated human eye visual field through optical imaging to detect the refractive power of the human eye. The simulated human eye visual field in this embodiment simulates the optical system between the human eye and the refractive detection device. The principle of the simulated human eye visual field in this embodiment will be described below:

[0093] More specifically, referring to Figure 3 , Figure 3 is a schematic optical path diagram of the human eye and the refractive detection device of the method of the present application; as shown in Figure 3 , the principle of the refractive detection imaging optical system for detecting the refractive power of the human eye is as follows: The illumination optical path is used to supplement light to the fundus of the eye. The retina of the human eye is illuminated, and the emitted light from any point on the retina is focused on the detector of the refractive detection device after passing through the human eye and the imaging optical system. In this embodiment, the fundus retina is regarded as the object side. The light rays emitted from a point A on the object side pass through the eye refractive medium and are imaged at point A' after exiting the cornea. l1' is the distance from the cornea to the image. Taking the corneal vertex as the origin, the left side of the origin is negative and the right side of the origin is positive. According to the definition of refraction, the calculation formula for the refractive value P corresponding to this point on the human eye retina is as follows:

[0094]

[0095] When the imaging optical system images the human eye, the image point A' formed by the retina through the refractive medium of the human eye is converted into the object point B of the imaging optical system. The positions of the object point B provided by human eyes with different refractive powers in the refractive detection system are different, and the measurement results of the refractive detection imaging optical system are also different.

[0096] Referring to Figure 4 , Figure 4 is the optical path schematic diagram of the refractive lens group and the refractive detection device of the method of this application; as Figure 4 shown, the peripheral refractive detection device in this embodiment is based on Figure 3 the relationship between the imaging principle of the human eye retina and the refractive detection device shown, and proposes to place the object point C in front of the objective lens and place a compensation lens at the entrance pupil to form a refractive compensation group. By changing lenses with different refractive powers, after the object point C passes through the lens, it is imaged at different image points C'. This provides a variable refractive object point B(C') for the refractive detection system. For the refractive compensation group, its object and image are in the same medium. From the Gaussian formula, the object-image relationship expression of the imaging optical system is obtained as:

[0097]

[0098] Among them, l2 in formula (2) is the object distance of the refractive compensation group, l2' is the image distance of the refractive compensation group, and f is the focal length of the compensation lens. The sign rule of this embodiment is that with the center of the compensation lens as the origin, to the left is the negative sign and to the right is the positive sign. Combining formula (1), the refractive compensation calculation formula provided by the refractive compensation group is as follows:

[0099]

[0100] Step S20, perform refractive detection based on the simulated human eye visual field and obtain a refractive compensation detection value;

[0101] Specifically, in this embodiment, after obtaining the simulated human eye visual field generated based on the white noise target, refractive detection is performed through the peripheral refractive detection device to obtain a refractive compensation detection value, and it is analyzed and compared with the theoretical detection data obtained through theoretical calculation. Calibration fitting is completed to calibrate the peripheral refractive detection device. Among them, the peripheral refractive detection will emit a specific signal or light beam and measure the property changes after it passes through the human eye simulated based on the white noise target, such as refractive index, focal length, etc., so as to obtain the corresponding compensated refractive data as the refractive compensation detection value for calibration.

[0102] Step S30, perform fitting calibration based on the refractive compensation detection value and the pre-obtained refractive compensation theoretical value to complete calibration.

[0103] Specifically, fitting and calibration based on the refractive compensation detection value and the pre-acquired refractive compensation theoretical value is a common method for calibrating a refractive compensation device or system to ensure its accuracy and consistency. In this embodiment, the refractive compensation detection value and the pre-acquired refractive compensation theoretical value are first collected. Specifically, a peripheral refractive detection device or system can be used to detect a series of different diopters, and the compensation detection value at each diopter is recorded. These refractive compensation detection values can be in the form of digital data, sensor outputs, etc.; the refractive compensation theoretical value can be obtained based on optical principles, simulation calculations, experimental measurements, etc. After obtaining the refractive compensation detection value and the pre-acquired refractive compensation theoretical value in this embodiment, the collected refractive compensation detection values are compared and fitted with the corresponding refractive compensation theoretical values. Statistical regression methods (such as linear regression, polynomial regression), curve fitting methods (such as the least squares method), etc. can be used to find the relationship between the compensation detection value and the theoretical value. According to the fitted calibration curve or model, the refractive compensation device or system is calibrated and adjusted. In this embodiment, the parameters of the peripheral refractive detection device, the compensation algorithm, or other relevant factors can also be adjusted according to actual needs to make the refractive compensation result more accurate and meet the expectations.

[0104] Further, in this embodiment, before step S10, obtaining the simulated visual field of the human eye based on the pre-generated white noise target may include:

[0105] S5. Obtain a white noise image and generate the white noise target based on the white noise image.

[0106] Specifically, in this embodiment, considering that the selection of the object points in the refractive compensation group is equally important, this embodiment proposes to use the pre-generated white noise target as the object points. The white noise image is a completely random noise distribution, with rotational invariance and displacement invariance; its frequency domain diagram has the same power at each frequency. It can provide a random, uniform, and stable image signal. The specific steps for generating the white noise target may include: First, use a random number generator to generate a random matrix with a Gaussian distribution, and the value range of each element is between 0 and 255, representing the brightness of the pixel. The matrix generated in this way is a white noise image; then, adjust the size of the white noise image by interpolation or cropping to obtain a white noise image with the target size; finally, in order to make the white noise target more prominent and clear, some methods for enhancing contrast, such as histogram equalization or contrast stretching, can be applied. It should be noted that the generated white noise target should have statistical randomness, average gray level, as well as good scale and contrast. In addition, in order to reduce the repeatability problem caused by randomness, a random seed can be used to control the generation process. The above is a basic method for generating the white noise target, and it can be adjusted and optimized according to specific requirements and application scenarios during the actual implementation process.

[0107] In this embodiment, through the above solution, the human eye is simulated based on the white noise target to obtain the human eye simulated visual field, thereby reducing the calibration error. In addition, this embodiment also performs refractive detection on the human eye simulated visual field to obtain a refractive compensation detection value, and performs fitting calibration based on the refractive compensation detection value and the refractive compensation theoretical value to complete the calibration, providing accurate refractive compensation for the peripheral refractive detection device, thereby improving the calibration accuracy of the peripheral refractive detection device. Among them, introducing the white noise target as a simulated human eye can reduce the calibration error introduced by the aberration and optical axis asymmetry of the simulated human eye, which is more conducive to the calibration of the peripheral refractive detection device.

[0108] Referring to Figure 5 , Figure 5 is a schematic flowchart of the second exemplary embodiment of the refractive device calibration method of the present application.

[0109] Based on the first embodiment, the second embodiment of the present application is proposed. The difference between the second embodiment of the present application and the first embodiment is that in this embodiment, step S20 of performing refractive detection based on the human eye simulated visual field and obtaining a refractive compensation detection value is refined.

[0110] In this embodiment, step S20 of performing refractive detection based on the human eye simulated visual field and obtaining a refractive compensation detection value includes:

[0111] Step S201, obtaining a white noise target imaging map based on the human eye simulated visual field, and extracting a feature region of the white noise target imaging map based on the white noise target imaging map;

[0112] Specifically, in this embodiment, a white noise target imaging map is first obtained based on the human eye simulated visual field, which can be specifically realized by optical imaging. In addition, this embodiment can also preprocess the white noise target imaging map after obtaining it to improve the accuracy of subsequent refractive detection. The preprocessing steps may include operations such as denoising, image enhancement, and edge detection. After preprocessing, this embodiment uses image processing algorithms and technologies to extract features from the preprocessed image. Among them, the algorithms for extracting feature regions can consider the following several algorithms: edge detection, used to detect edges in the image. In the white noise target image, edges usually represent the changes between different brightness levels and can be used to extract feature regions; region segmentation, such as threshold-based segmentation or region-growing segmentation, to segment the white noise target image into multiple connected regions; by selecting appropriate thresholds or growth criteria, specific feature regions can be found and extracted; template matching, according to known feature templates, using the template matching algorithm to find similar features in the white noise target image. By comparing the template and local regions in the image, feature regions matching the feature template can be found; in addition, methods such as interest point detection and morphological operations can also be used for feature region extraction.

[0113] Step S202: Perform refractive detection based on the feature region to obtain the refractive compensation detection value.

[0114] Specifically, in this embodiment, the feature region is first obtained based on the above method, and then a suitable refractive detection method is selected according to the type of the feature region and the application requirements. Considering that the artificial eye simulation visual field in this embodiment uses a white noise target as the object point, the peripheral refractive detection device in this embodiment will also generate white noise points corresponding to the white noise target during detection, and perform imaging in the peripheral refractive detection device to generate the refractive compensation detection value for calibrating the peripheral refractive detection device.

[0115] Further, in this embodiment, step S201: Obtaining the white noise target imaging diagram based on the artificial eye simulation visual field may include:

[0116] Step S2011: Supplement the light of the artificial eye simulation visual field based on the pre-obtained external light source to obtain the supplemented artificial eye simulation visual field;

[0117] Specifically, in this embodiment, an external light source is used for light supplementation. When simulating the visual field, in order to ensure the clarity and visibility of the image, sufficient illumination needs to be provided. If there are dark areas or uneven light in the visual field, it may lead to a decline in image quality and difficulty in identifying the target object. Considering the consistency of detection conditions and the reliability of refractive detection results, consistent illumination conditions need to be provided. By supplementing the light of the artificial eye simulation visual field, it can be ensured that each detection object (different white noise points on the white noise target) is in a similar illumination environment, reducing the influence of external light changes on the refractive detection results.

[0118] Step S2012: Perform optical imaging based on the supplemented artificial eye simulation visual field to obtain the white noise target imaging diagram.

[0119] Specifically, in this embodiment, optical imaging is first performed according to the located and supplemented artificial eye simulation visual field, where the white noise target in the artificial eye simulation visual field needs to be placed in a suitable position to ensure its alignment with the focal plane of the imaging system. Appropriate imaging parameters such as focal length, aperture size, and exposure time also need to be set in advance during the imaging process, and these imaging parameters will affect the clarity, depth, and brightness of the optical imaging.

[0120] Further, in this embodiment, before step S2011: Supplement the light of the artificial eye simulation visual field based on the pre-obtained external light source to obtain the supplemented artificial eye simulation visual field, it further includes:

[0121] Step S2010: Obtain the external light source, where the wavelength parameter of the external light source matches the preset device parameters.

[0122] Specifically, the wavelength of the external light source obtained in this embodiment should be the same as the wavelength parameter in the device parameters preset by the peripheral refractive detection device. This is because the peripheral refractive detection device usually measures the diopter of the eyeball based on specific principles and algorithms. These principles and algorithms are designed for optical signals within a specific wavelength range. Therefore, to ensure the normal operation and accuracy of the device, the wavelength of the external light source should be the same as the wavelength parameter in the device parameters. During the calibration process, a standard light source with a specific wavelength is used for comparison and adjustment. If the wavelength of the external light source does not match the wavelength used for device calibration, it may lead to deviation in the measurement results and affect the accuracy of device calibration.

[0123] Through the above solution, this embodiment simulates the human eye based on the white noise target to obtain the simulated visual field of the human eye, thereby reducing the calibration error. In addition, this embodiment also performs refractive detection on the simulated visual field of the human eye to obtain the refractive compensation detection value, and performs fitting calibration based on the refractive compensation detection value and the refractive compensation theoretical value to complete the calibration, providing accurate refractive compensation for the peripheral refractive detection device. In addition, the white noise image has a completely random noise distribution, with rotational invariance and displacement invariance; its frequency domain diagram has the same power at each frequency. It can provide a random, uniform, and stable image signal. This embodiment performs refractive detection on the simulated visual field of the human eye generated based on the white noise image, which can ensure the stability of the peripheral refractive detection device and improve the calibration accuracy of the peripheral refractive detection device.

[0124] Refer to Figure 6 , Figure 6 which is a schematic flowchart of the third exemplary embodiment of the refractive device calibration method of this application.

[0125] Based on the first embodiment, the third embodiment of this application is proposed. The difference between the third embodiment of this application and the first embodiment is that:

[0126] In this embodiment, before step S30, which performs fitting calibration based on the refractive compensation detection value and the pre-acquired refractive compensation theoretical value to complete the calibration, it includes:

[0127] Step S25, performing data analysis based on the preset target distance parameter to obtain the first analysis data;

[0128] Specifically, refer to Figure 7 , Figure 7 which is a schematic diagram of the relationship between the target distance and refractive compensation of the refractive device calibration method of this application; as Figure 7 shown, the first analysis data is the mathematical relationship between the target distance and refractive compensation. In this embodiment, it is first necessary to pre-determine the target distance Z. From practical experience, the value of Z ranges from 0.2 to 2 m. Let the distance from point P on the target to the center of the target be d, then the object distance l2 from point P to the exit pupil is:

[0129]

[0130] If a compensating lens with a diopter of 1 / f is added at the exit pupil of the device, then based on formula (3) in the above-mentioned first embodiment, the compensating diopter provided by point P can be obtained as:

[0131]

[0132] In addition, the method for calculating the field of view angle θ (FOV) of point P is:

[0133]

[0134] When directly placing the white noise target at a distance Z from the exit pupil of the device without adding a compensating lens, calculate the compensating diopters that can be provided at different angles. As Figure 7 shown, in this embodiment, when Z is 0.2m, 0.4m, 0.6m, 1m, and 2m, the refractive compensation trends at different angles are provided. The abscissa is the half field of view angle of the device, and the ordinate is the provided refractive compensation (which can also be called compensating diopter). When Z is 2m, the theoretical value of the refractive compensation provided by the 0° field of view is 4.3D, and the provided refractive span is 0.07D. When Z is 0.2m, the theoretical value of the refractive compensation provided by the 0° field of view is 5D, and the theoretical value of the refractive compensation provided by the 30° field of view is 4.3D, and the provided refractive span is 0.7D. As the distance Z increases, the refractive span provided by the white noise target gradually decreases, and the requirement for the placement skew accuracy of the white noise target gradually decreases; as the distance Z increases, the space occupied by the white noise target gradually increases. During use, it is necessary to select an appropriate distance Z according to the device requirements.

[0135] Step S26, based on the first analysis data and a preset compensating lens, obtain second analysis data;

[0136] Specifically, referring to Figure 8 , Figure 8 is a schematic diagram of the relationship between the compensating lens and the refractive compensation of the refractive device calibration method of the present application; as Figure 8 shown, the second analysis data is the mathematical relationship between the compensating lens and the refractive compensation. Referring to the first embodiment, considering the space occupation of the refractive compensation group, and the refractive working range of the peripheral refractive detection device to be calibrated in this embodiment is -15D to 15D, in this embodiment, the white noise target is selected to be placed at 0.6m from the exit pupil, and compensating lenses of -17D, -7D, 0D, 7D, and 14D are added respectively so that the refractive calibration range covers the device refractive working range. The theoretical values of the refractive compensation at different angles are as Figure 8 shown, the abscissa is the half field of view angle of the device, and the ordinate is the provided refractive compensation.

[0137] Step S27: Obtain the theoretical value of refractive compensation based on the first analysis data and the second analysis data.

[0138] Specifically, in this embodiment, based on the mathematical relationship between the two influencing factors of the compensation lens and the target distance and the theoretical value of refractive compensation at different field angles, the ideal state simulation of the human eye based on the white noise target is completed, and the theoretical value of refractive compensation is obtained for calibrating the peripheral refractive detection device.

[0139] Furthermore, in this embodiment, step S30: Based on the refractive compensation detection value and the pre-obtained theoretical value of refractive compensation, fitting calibration is performed to complete the calibration, which is refined.

[0140] In this embodiment, step S30: Based on the refractive compensation detection value and the pre-obtained theoretical value of refractive compensation, fitting calibration to complete the calibration may include:

[0141] Step S301: Perform fitting calibration on the refractive compensation measurement value and the theoretical value of refractive compensation based on a preset fitting function to obtain a calibration curve.

[0142] Specifically, in this embodiment, first, an external light source with the same wavelength band as the peripheral refractive detection device is used for supplementary lighting, the refractive compensation detection value is collected and analyzed, and the refractive compensation detection value and the theoretical value of refractive compensation are fitted and calibrated based on a preset fitting function to complete the calibration. Among them, the preset fitting function can use statistical regression methods (such as linear regression, polynomial regression), curve fitting methods (such as the least squares method), etc. to find the relationship between the compensation detection value and the theoretical value, and obtain the calibration curve.

[0143] Step S302: Update the device parameters based on the calibration curve to complete the calibration.

[0144] Specifically, refer to Figure 9 , Figure 9 is the peripheral refractive comparison chart before and after calibration of the refractive device calibration method of this application; in this embodiment, the device parameters are updated based on the calibration curve to complete the calibration, and its calibration effect is as Figure 9 shown. Figure 9 The compensation lens in [] is 0D, and the corresponding refractive values of each point are given every 10° (full field of view) from the center to the periphery. As Figure 9 (a) shows the peripheral refractive distribution before calibration. Due to debugging errors, the measured result of the central refractive power is 0.9D, with a deviation of -0.8D from the refractive theory value of 1.7D; and the optical system of the refractive detection device is rotationally symmetric, but there are assembly errors, resulting in an overall asymmetry of the measured results. As Figure 9 (b) shows the peripheral refractive distribution after calibration, correcting the phenomenon of inaccurate refraction and overall asymmetry.

[0145] In this embodiment, through the above solution, the human eye is simulated based on a white noise target to obtain a simulated human eye field of view, thereby reducing calibration errors. In addition, in this embodiment, refractive detection is performed on the simulated human eye field of view to obtain a refractive compensation detection value, and fitting calibration is performed based on the refractive compensation detection value and the refractive compensation theoretical value to complete calibration, providing accurate refractive compensation for peripheral refractive detection devices. For peripheral refractive detection devices, the demand for large-field refractive detection is gradually increasing. Then, the simulated eye field of view for calibration also needs to be adapted to it. The increase in the simulated eye field of view makes the aberration structure more complex. Subsequently, the design difficulty of the simulated eye increases. To reduce the aberration of the simulated eye, the designed surface shape of the simulated eye is more complex, and cemented lenses are also used in terms of lens materials, increasing the processing difficulty. However, residual aberration still cannot be avoided, affecting the result of refractive calibration. The method proposed in this embodiment can avoid the complex optical structure of the simulated eye, reduce the processing difficulty, and provide a small optical aberration; it is more suitable for the calibration of large-field refractive detection devices (i.e., peripheral refractive detection devices), and the obtained refractive compensation measurement value only reflects the optical condition of the refractive detection device, making the calibration more accurate.

[0146] It should be noted that the above embodiments can be combined and implemented reasonably according to actual situations, and this embodiment will not elaborate on this.

[0147] In addition, an embodiment of the present application also provides a refractive device calibration device, which includes:

[0148] A field of view generation module, configured to obtain a simulated human eye field of view based on a pre-generated white noise target;

[0149] A refractive detection module, configured to perform refractive detection based on the simulated human eye field of view and obtain a refractive compensation detection value;

[0150] A calibration fitting module, configured to perform fitting calibration based on the refractive compensation detection value and a pre-obtained refractive compensation theoretical value to complete calibration.

[0151] For the principle and implementation process of refractive device calibration in this embodiment, please refer to the above embodiments and will not be elaborated here.

[0152] In addition, an embodiment of the present application also proposes a terminal device, which includes a memory, a processor, and a refractive device calibration program stored on the memory and executable on the processor. When the refractive device calibration program is executed by the processor, the steps of the refractive device calibration method described above are implemented.

[0153] Since all the technical solutions of the foregoing embodiments are adopted when the refractive device calibration program is executed by the processor, it has at least all the beneficial effects brought by all the technical solutions of the foregoing embodiments, which will not be elaborated one by one here.

[0154] In addition, an embodiment of the present application further provides a computer-readable storage medium, on which a refractive device calibration program is stored. When the refractive device calibration program is executed by a processor, the steps of the refractive device calibration method described above are implemented.

[0155] Since all the technical solutions of the foregoing embodiments are adopted when the refractive device calibration program is executed by the processor, it has at least all the beneficial effects brought by all the technical solutions of the foregoing embodiments, which will not be elaborated herein one by one.

[0156] It should be noted that in this text, the terms "including", "comprising" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or system. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or system including that element.

[0157] The above sorting of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments.

[0158] Through the description of the above embodiments, those skilled in the art can clearly understand that the above embodiment methods can be implemented by means of software plus a necessary general hardware platform. Based on such understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disc) as described above and includes several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0159] The above are only the preferred embodiments of the present invention, and do not limit the patent scope of the present invention accordingly. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A refractive device calibration method, characterized in that, The refractive device calibration method includes the following steps: Obtain a white noise image and generate a white noise target based on the white noise image; the white noise image has a completely random noise distribution, with rotational invariance and displacement invariance, and its frequency domain diagram has the same power at each frequency; Obtain a simulated human eye field of view based on the pre-generated white noise target; Perform refractive detection based on the simulated human eye field of view and obtain a refractive compensation detection value; Perform fitting calibration based on the refractive compensation detection value and the pre-obtained refractive compensation theoretical value to complete the calibration.

2. The refractive device calibration method according to claim 1, wherein The step of performing refractive detection based on the simulated human eye field of view and obtaining a refractive compensation detection value includes: Obtain a white noise target imaging map based on the simulated human eye field of view, and extract a feature region of the white noise target imaging map based on the white noise target imaging map; Perform refractive detection based on the feature region to obtain the refractive compensation detection value.

3. The refractive device calibration method according to claim 2, wherein, The step of obtaining a white noise target imaging map based on the simulated human eye field of view includes: Supplementary light the simulated human eye field of view based on the pre-obtained external light source to obtain a supplementary-lighted simulated human eye field of view; Perform optical imaging based on the supplementary-lighted simulated human eye field of view to obtain the white noise target imaging map.

4. The refractive device calibration method according to claim 3, wherein Before the step of supplementary light the simulated human eye field of view based on the pre-obtained external light source to obtain a supplementary-lighted simulated human eye field of view, it includes: Obtain the external light source, wherein the wavelength parameter of the external light source matches the preset device parameter.

5. The refractive device calibration method according to claim 1, wherein Before the step of performing fitting calibration based on the refractive compensation detection value and the pre-obtained refractive compensation theoretical value to complete the calibration, it includes: Perform data analysis based on the preset target distance parameter to obtain first analysis data; Obtain second analysis data based on the first analysis data and the preset compensation lens; Obtain the refractive compensation theoretical value based on the first analysis data and the second analysis data.

6. The refractive device calibration method according to claim 1, wherein, The step of performing fitting calibration based on the refractive compensation detection value and the pre-obtained refractive compensation theoretical value to complete the calibration includes: Perform fitting calibration on the refractive compensation measurement value and the refractive compensation theoretical value based on the preset fitting function to obtain a calibration curve; Update the device parameter based on the calibration curve to complete the calibration.

7. A refractive device calibration apparatus, characterized in that, The refractive device calibration apparatus includes: A field of view generation module for obtaining a simulated human eye field of view based on the pre-generated white noise target; the field of view generation module is further configured to obtain a white noise image and generate a white noise target based on the white noise image; the white noise image has a completely random noise distribution, with rotational invariance and displacement invariance, and its frequency domain diagram has the same power at each frequency; A refractive detection module for performing refractive detection based on the simulated human eye field of view and obtaining a refractive compensation detection value; A calibration fitting module for performing fitting calibration based on the refractive compensation detection value and the pre-obtained refractive compensation theoretical value to complete the calibration.

8. A terminal device, characterized in that, The terminal device includes a memory, a processor, and a refractive device calibration program stored on the memory and executable on the processor. When the refractive device calibration program is executed by the processor, it implements the refractive device calibration method according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, A refractive device calibration program is stored on the computer-readable storage medium. When the refractive device calibration program is executed by the processor, it implements the refractive device calibration method according to any one of claims 1-6.

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