Data processing method and device based on optical microscopy and computer equipment

Abstract

The invention relates to a data processing method and device based on an optical microscopy technology and computer equipment. The method comprises the following steps: acquiring an initial scanning image of a to-be-detected sample; in response to triggering of a preset correction process, processing of the preset correction process is carried out on the initial scanning image to obtain a target scanning image, the preset correction process comprises at least one correction sub-process, and the correction sub-processes in the preset correction process are in a serial processing relation; the output data of the previous correction sub-process is used as the input data of the next correction sub-process; in response to triggering of a preset calculation process, processing of the preset calculation process is carried out on the target scanning image, a target measurement result of the to-be-measured sample is obtained, the preset calculation process comprises at least one calculation sub-process, and the calculation sub-processes in the preset calculation process are in a parallel processing relation; the input data of each calculation sub-process is a target scanning image. The method can improve the measurement efficiency.

Description

Technical Field

[0001] This application relates to the field of optical microscopy, and in particular to a data processing method, apparatus, computer equipment, computer-readable storage medium, and computer program product based on optical microscopy. Background Technology

[0002] With the rapid development of optical microscopy technology, it has been widely applied in various fields such as scientific and technological research and industrial measurement. Many optical microscopy data processing devices based on optical microscopy technology can achieve sub-nanometer level measurements on the surfaces of various precision devices and materials. They feature high precision, high resolution, and non-contact scanning imaging, enabling three-dimensional morphology reconstruction of the sample under test. They can be widely used in semiconductor manufacturing and packaging process inspection, micro-nano detection, precision measurement, and aerospace. However, when measuring a sample, it is necessary to first scan the sample to obtain scanning data. During the scanning process, errors inevitably arise due to factors such as instrument tilt, sample surface contamination, and environmental vibration, leading to discrepancies between the scanned data and the actual condition of the sample surface. Directly using the scanned data will result in measurement results with significant errors.

[0003] In related technologies, after scanning the sample, the scanning data needs to be corrected by placing a flat crystal, and then the corrected data is analyzed to obtain the measurement results. The whole measurement process is cumbersome and time-consuming, resulting in low measurement efficiency. Summary of the Invention

[0004] Therefore, it is necessary to provide a data processing method, apparatus, computer equipment, computer-readable storage medium, and computer program product based on optical microscopy that can improve measurement efficiency in response to the above-mentioned technical problems.

[0005] In a first aspect, this application provides a data processing method based on optical microscopy, including:

[0006] Acquire the initial scan image of the sample to be tested;

[0007] In response to the triggering of a preset correction process, the initial scan image is processed by the preset correction process to obtain a target scan image. The preset correction process includes at least one correction subprocess, and the correction subprocesses in the preset correction process are processed in a serial manner, with the output data of the previous correction subprocess serving as the input data of the next correction subprocess.

[0008] In response to the triggering of a preset calculation process, the target scan image is processed by the preset calculation process to obtain the target measurement result of the sample to be tested. The preset calculation process includes at least one calculation subprocess, and the calculation subprocesses in the preset calculation process are processed in parallel. The input data of each calculation subprocess is the target scan image.

[0009] Secondly, this application also provides a data processing device based on optical microscopy technology, comprising:

[0010] The scan image acquisition module is used to acquire the initial scan image of the sample to be tested;

[0011] A scanned image correction module is used to process the initial scanned image in response to the triggering of a preset correction process to obtain a target scanned image. The preset correction process includes at least one correction subprocess, and the correction subprocesses in the preset correction process are processed sequentially, with the output data of the previous correction subprocess serving as the input data of the next correction subprocess.

[0012] The measurement result acquisition module is used to process the target scan image in response to the triggering of the preset calculation process to obtain the target measurement result of the sample to be tested. The preset calculation process includes at least one calculation subprocess, and the calculation subprocesses in the preset calculation process are processed in parallel. The input data of each calculation subprocess is the target scan image.

[0013] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the data processing method based on optical microscopy technology provided in the first aspect.

[0014] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the data processing method based on optical microscopy provided in the first aspect.

[0015] Fifthly, this application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the data processing method based on optical microscopy provided in the first aspect.

[0016] The aforementioned data processing method, apparatus, computer equipment, computer-readable storage medium, and computer program product based on optical microscopy technology acquire an initial scan image of the sample to be tested, and in response to the triggering of a preset calibration procedure, process the initial scan image using a preset calibration procedure to obtain a target scan image. In response to the triggering of a preset calculation procedure, process the target scan image using a preset calculation procedure to obtain the target measurement result of the sample to be tested. It can achieve automatic calibration processing through a preset calibration procedure, avoiding the cumbersome operation caused by calibration using hardware auxiliary tools. Then, it processes the calibrated scan image using a preset calculation procedure to obtain the measurement result, enabling visual and efficient measurement, thereby improving measurement efficiency. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart illustrating a data processing method based on optical microscopy in one embodiment;

[0019] Figure 2 This is a schematic diagram of an optical microscopy data processing device in one embodiment;

[0020] Figure 3 This is a schematic diagram of the interface for setting the measurement method in one embodiment;

[0021] Figure 4 A schematic diagram of the measurement program configuration interface in one embodiment;

[0022] Figure 5 This is a schematic diagram of the preprocessing process in one embodiment;

[0023] Figure 6 This is a schematic diagram of the display panel corresponding to the leveling process in one embodiment;

[0024] Figure 7 This is a schematic diagram of the display panel corresponding to the spike noise reduction processing in one embodiment;

[0025] Figure 8 This is a schematic diagram of the display panel corresponding to the standard filtering process in one embodiment;

[0026] Figure 9 This is a flowchart illustrating a data processing method based on optical microscopy in another embodiment;

[0027] Figure 10 This is a structural block diagram of a data processing device based on optical microscopy in one embodiment;

[0028] Figure 11 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0030] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0031] The data processing method based on optical microscopy provided in this application can be applied to terminals or servers. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, drones, low-altitude aircraft, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, projection devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted displays, etc. Head-mounted displays can be virtual reality (VR) devices, augmented reality (AR) devices, smart glasses, etc. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. For example, a terminal or server can acquire an initial scan image of the sample to be tested, and in response to the triggering of a preset calibration process, process the initial scan image using the preset calibration process to obtain a target scan image. The preset calibration process includes at least one calibration sub-process, and these sub-processes are processed sequentially, with the output data of the previous sub-process serving as the input data for the next sub-process. In response to the triggering of a preset calculation process, the target scan image is processed using a preset calculation process to obtain the target measurement result of the sample to be tested. The preset calculation process includes at least one calculation sub-process, and these sub-processes are processed in parallel, with the input data for each calculation sub-process being the target scan image.

[0032] In one exemplary embodiment, such as Figure 1 As shown, a data processing method based on optical microscopy is provided. Taking the application of this method to a terminal as an example, the method includes the following steps 102 to 106. Wherein:

[0033] Step 102: Obtain the initial scan image of the sample to be tested.

[0034] The sample to be tested refers to the sample whose surface morphology needs to be measured. For example, the sample to be tested can be an industrial device or material for which surface morphology measurement is required. Surface morphology measurement can include, for example, measuring parameters such as roughness (including line roughness and surface roughness), step value (including line step value and surface step value), surface flatness, surface tilt, surface curvature, coating thickness, or peak-valley characteristics. The initial scan image refers to the original scan image of the sample to be tested, which has not undergone correction, optimization, or other processing. The initial scan image can be three-dimensional (3D) image data; for example, it can be represented by a height map. Each pixel in the height map corresponds to a plane coordinate (x, y) and a vertical height value z in space; that is, the height map can correspond to the position and height information of each point in space.

[0035] In practical applications, optical microscopy data processing devices can be used to photograph the sample to obtain raw image data. Based on the raw image data, three-dimensional morphology reconstruction is performed to obtain the initial scanned image. These optical microscopy data processing devices can be instruments such as white light interferometers, confocal microscopes, or white light interferometric confocal profilometers, which utilize optical microscopy techniques to measure targets.

[0036] In one example, the terminal can acquire an initial scan image of the sample under test via an interface and display it on the display screen. Alternatively, the terminal can communicate with an optical microscopy data processing device, which can then capture images of the sample under test to obtain raw image data. This raw image data is then displayed in a display window on the display screen. The initial scan image is reconstructed based on the raw image data and displayed in a view window. The display screen can simultaneously display both the initial scan window and the view window.

[0037] Step 104: In response to the triggering of the preset correction process, the initial scan image is processed by the preset correction process to obtain the target scan image. The preset correction process includes at least one correction subprocess, and the correction subprocesses in the preset correction process are processed in a serial manner. The output data of the previous correction subprocess is used as the input data of the next correction subprocess.

[0038] The preset calibration process refers to a pre-set or configured calibration procedure. This procedure is used to correct the initial scanned image to reduce the impact of measurement errors caused by environmental factors during the measurement process. A preset calibration process may include one or more calibration sub-processes, each implemented through a corresponding configured program. The target scanned image is the scanned image obtained after correcting the initial scanned image. The initial scanned image can be processed sequentially in response to the triggering of different calibration sub-processes to obtain the target scanned image. It is easy to understand that, in the case of continuously responding to the triggering of multiple calibration sub-processes, the result of the previous calibration sub-process can be used as the input of the next calibration sub-process, until the processing of the last calibration sub-process is completed, resulting in the target scanned image. A preset calibration process contains at least one calibration sub-process. The calibration sub-processes in the preset calibration process are processed sequentially, with the output data of the previous calibration sub-process serving as the input data for the next calibration sub-process. In this scenario, when a preset correction process is applied to the initial scanned image, each correction sub-process completes serial data processing in a pipeline manner. That is, multiple correction sub-processes are arranged sequentially. The first correction sub-process receives the initial scanned image, processes it, and uses the processed image data (i.e., the current processing result image) as input for the second correction sub-process. This process continues sequentially until the last correction sub-process is executed, resulting in the target scanned image. The preset correction process can include, for example, at least one of the following: a leveling sub-process, a denoising sub-process, a filtering sub-process, or a rotation sub-process.

[0039] In an exemplary embodiment, the preset correction process includes a first correction sub-process and a second correction sub-process, which are different correction sub-processes. The first or second correction sub-process can be, for example, any of a leveling sub-process, a denoising sub-process, a filtering sub-process, or a rotation sub-process. In response to triggering the first correction sub-process, the terminal processes the initial scanned image using the first correction sub-process to obtain a first corrected image. In response to triggering the second correction sub-process, the terminal processes the first corrected image using the second correction sub-process to obtain the target scanned image.

[0040] In an exemplary embodiment, the preset correction process includes a first correction sub-process, a second correction sub-process, and a third correction sub-process, wherein the first, second, and third correction sub-processes are distinct from each other. The first, second, or third correction sub-process can be, for example, any of the following: a leveling sub-process, a denoising sub-process, a filtering sub-process, or a rotation sub-process. In response to triggering the first correction sub-process, the terminal processes the initial scanned image using the first correction sub-process to obtain a first corrected image. In response to triggering the second correction sub-process, the terminal processes the first corrected image using the second correction sub-process to obtain a second corrected image. In response to triggering the third correction sub-process, the terminal processes the second corrected image using the third correction sub-process to obtain the target scanned image.

[0041] In a straightforward manner, when the preset calibration process includes multiple calibration sub-processes, the appropriate sub-process can be selected based on the actual application scenario. After determining the sub-processes to be triggered, the triggering order can also be chosen according to actual needs.

[0042] In practical applications, the corresponding preset calibration process can be triggered by controls, buttons, etc., corresponding to the preset calibration process. Alternatively, it can be triggered by natural language commands. After obtaining the target scan image, the target scan image can be displayed. For example, the initial scan image (or the processing result image of the selected calibration sub-process) and the target scan image can be displayed side-by-side, facilitating comparison between the two.

[0043] Step 106: In response to the triggering of the preset calculation process, the target scan image is processed by the preset calculation process to obtain the target measurement result of the sample to be tested. The preset calculation process includes at least one calculation subprocess, and the calculation subprocesses in the preset calculation process are processed in parallel. The input data of each calculation subprocess is the target scan image.

[0044] The preset calculation process refers to a pre-set calculation procedure. This process is used to calculate the measurement results of the target scan image. By processing the target scan image based on the preset calculation process, the corresponding measurement results can be obtained. The preset calculation process can include one or more sub-processes, each implemented through a corresponding configured program. For each sub-process, the target scan image can be processed to obtain the measurement result of that sub-process. The preset calculation process contains at least one sub-process. The sub-processes within the preset calculation process operate in parallel, with each sub-process receiving the target scan image processed by the preset correction process. In this case, when the preset calculation process is applied to the target scan image, the sub-processes are arranged in a parallel, non-shared state, and their results do not affect each other. The first sub-process receives the target scan image, processes it to obtain a first calculation result, the second sub-process receives the target scan image to obtain a second calculation result, and so on. Multiple sub-processes can be executed sequentially according to a set order or synchronously.

[0045] The preset calculation process may include at least one of the following: roughness calculation subprocess, step value calculation subprocess, flatness calculation subprocess, tilt calculation subprocess, curvature calculation subprocess, or coating thickness calculation subprocess. The roughness calculation subprocess may include a line roughness calculation subprocess and a surface roughness calculation subprocess. The step value calculation subprocess may include a line step value calculation subprocess and a surface step value calculation subprocess.

[0046] For example, the preset calculation process includes a first calculation sub-process and a second calculation sub-process. The first and second calculation sub-processes are different calculation sub-processes. The first or second calculation sub-process can be any one of the following: roughness calculation sub-process, step value calculation sub-process, flatness calculation sub-process, tilt calculation sub-process, curvature calculation sub-process, or coating thickness calculation sub-process. The terminal can respond to the triggering of the first calculation sub-process by processing the target scanned image using the first calculation sub-process to obtain a first calculation result; and respond to the triggering of the second calculation sub-process by processing the target scanned image using the second calculation sub-process to obtain a second calculation result. The first and second calculation results are used as the target measurement results for the sample to be tested. It should be noted that in practical applications, the calculation sub-processes that trigger the calculation are not limited to one or two types; more calculation sub-processes can be triggered as needed to obtain more calculation results as the final target measurement results.

[0047] In practical applications, the preset calculation process can be triggered by controls, buttons, or other mechanisms corresponding to it. Alternatively, it can be triggered via natural language commands. After obtaining the target measurement result, it can be displayed. Alternatively, the preset calculation process can be triggered automatically after the preset calibration process is completed.

[0048] In the aforementioned data processing method based on optical microscopy, an initial scan image of the sample to be tested is acquired. In response to the triggering of a preset calibration procedure, the initial scan image is processed using the preset calibration procedure to obtain a target scan image. In response to the triggering of a preset calculation procedure, the target scan image is processed using the preset calculation procedure to obtain the target measurement result of the sample to be tested. This method enables automatic calibration processing through the preset calibration procedure, avoiding the cumbersome operation caused by calibration using hardware auxiliary tools. Then, the calibrated scan image is processed using the preset calculation procedure to obtain the measurement result. This method enables visual and efficient measurement, thereby improving measurement efficiency.

[0049] In some embodiments, the preset correction process includes a leveling sub-process and a spike denoising sub-process; in step 104, in response to the triggering of the preset correction process, the initial scanned image is processed by the preset correction process to obtain the target scanned image, including:

[0050] In response to the triggering of the leveling subprocess, the initial scan image is processed by the leveling subprocess to obtain the first scan image; in response to the triggering of the spike denoising subprocess, the first scan image is processed by the spike denoising subprocess to obtain the target scan image.

[0051] The leveling sub-process refers to the process of removing system height errors caused by the overall tilt of the measuring instrument. The spike denoising sub-process refers to the process of removing isolated values ​​caused by dust, bad pixels, etc.

[0052] In practical applications, the terminal can first respond to the triggering of the leveling sub-process by performing a leveling sub-process on the initial scanned image to obtain a first scanned image (i.e., a first corrected image); then, in response to the triggering of the spike denoising sub-process, it can perform a spike denoising sub-process on the first scanned image to obtain the target scanned image. Alternatively, the terminal can first respond to the triggering of the spike denoising sub-process by performing a spike denoising sub-process on the initial scanned image to obtain a first scanned image, and then, in response to the triggering of the leveling sub-process, it can perform a leveling sub-process on the first scanned image to obtain the target scanned image.

[0053] For example, the leveling sub-process can be implemented using methods such as least squares, minimum region, or trigonometric methods. The least squares method involves selecting one or more reference regions in the initial scanned image using a selection box of a suitable shape. These reference regions can be naturally flat areas; if multiple reference regions are selected, they lie on the same plane. The height data from each reference region are then fitted using least squares to obtain a fitted plane equation, which is used to correct the initial scanned image. For example, the initial scanned image can be rotated as a whole or subtracted pixel by pixel. Through this leveling sub-process, the overall tilt of the sample in the initial scanned image is eliminated, retaining only microscopic undulations and artificial steps on the sample surface. The minimum region method similarly involves selecting one or more reference regions, then fitting the height data within these regions using minimum region fitting to determine the narrowest envelope (i.e., a pair of narrowest parallel planes). All data within the reference regions lie within this narrowest envelope. A median plane is then determined based on the narrowest envelope, and the initial scanned image is corrected based on this median plane. The triangulation method involves selecting three reference regions, determining the average height data in each region, using this average value as the center point of the corresponding reference region, and fitting a plane through the three center points of the three reference regions. The initial scanned image is then corrected based on this plane.

[0054] The spike denoising sub-process can, for example, adjust the removal range by setting the sigma parameter. The standard deviation σ of each height data point in the input height map is calculated, and height data greater than Kσ are considered outliers. Here, K represents the set sigma parameter. Outliers can be replaced with the mean or median of the neighboring height data to obtain the spike-denoised height data. In practical applications, in response to the triggering of the spike denoising sub-process, the standard deviation of the height data in the first scanned image can be calculated, pixels with height values ​​greater than Kσ are identified as outliers, and the height values ​​of the outliers are replaced with the median of the neighboring pixels to obtain the target scanned image (here, a low-pass view can be selected). For example, outliers in the first scanned image can be filtered out and displayed as a high-pass view.

[0055] In this embodiment, in response to the triggering of the leveling sub-process, the initial scanned image is processed by the leveling sub-process to obtain the first scanned image. In response to the triggering of the spike denoising sub-process, the first scanned image is processed by the spike denoising sub-process to obtain the target scanned image. This enables the chain-like processing of multiple preset correction sub-processes on the initial scanned image, improving correction accuracy. Furthermore, both the leveling sub-process and the spike denoising sub-process are purely software processing flows, requiring no additional hardware intervention, thus improving correction speed and efficiency.

[0056] In some embodiments, the preset correction process further includes a filtering subprocess, which, in response to the triggering of the spike denoising subprocess, processes the first scan image using the spike denoising subprocess to obtain the target scan image, including:

[0057] In response to the triggering of the spike denoising subprocess, the first scan image is processed by the spike denoising subprocess to obtain the second scan image; in response to the triggering of the filtering subprocess, the second scan image is processed by the filtering subprocess to obtain the target scan image.

[0058] The filtering subprocess refers to the process of removing random high-frequency noise. After processing by the filtering subprocess, the true morphology of the sample under test can be preserved.

[0059] For example, the terminal may, in response to the triggering of the leveling sub-process, perform the leveling sub-process on the initial scan image to obtain a first scan image, and then, in response to the triggering of the spike denoising sub-process, perform the spike denoising sub-process on the first scan image to obtain a second scan image, and in response to the triggering of the filtering sub-process, perform the filtering sub-process on the second scan image to obtain a target scan image.

[0060] The filtering sub-process can be implemented using methods such as Gaussian filtering, spline filtering, bilateral filtering, or robust Gaussian filtering. For example, the input height map can be converted into a power spectral density in the spatial frequency domain. Based on a preset cutoff wavelength and power spectral density, the height map is divided into a high-pass view and a low-pass view. The low-pass view corresponds to wavelengths greater than the cutoff wavelength, while the high-pass view corresponds to wavelengths less than or equal to the cutoff wavelength. In other words, the low-pass view smooths out wavelengths less than or equal to the cutoff wavelength in the original height map, while the high-pass view smooths out wavelengths greater than the cutoff wavelength. The choice between retaining the low-pass view or the high-pass view as the processing result of the filtering sub-process can be made according to requirements.

[0061] In this embodiment, in response to the triggering of the spike denoising sub-process, the first scan image is processed by the spike denoising sub-process to obtain the second scan image. In response to the triggering of the filtering sub-process, the second scan image is processed by the filtering sub-process to obtain the target scan image. This enables the initial scan image to be sequentially chained through the leveling sub-process, spike denoising sub-process, and filtering sub-process for correction, thereby further improving the accuracy of the initial scan image.

[0062] In some embodiments, the preset calculation process includes a roughness calculation subprocess and a step value calculation subprocess; in step 106, in response to the triggering of the preset calculation process, the target scan image is processed by the preset calculation process to obtain the target measurement result of the sample to be tested, including:

[0063] In response to the triggering of the roughness calculation sub-process, the target scan image is processed by the roughness calculation sub-process to obtain the roughness measurement result of the sample to be tested; in response to the triggering of the step value calculation sub-process, the target scan image is processed by the step value calculation sub-process to obtain the step value measurement result of the sample to be tested; the roughness measurement result and the step value measurement result are used as the target measurement result.

[0064] Roughness is used to characterize the random microscopic unevenness or smoothness of a sample surface. Step value is used to characterize the oriented macroscopic step difference or elevation difference on the surface. Roughness can include surface roughness and line roughness. Surface roughness refers to the roughness of a certain area of ​​the surface. Linear roughness refers to the roughness along a line. Step value can include surface step value and line step value. Surface step value refers to the step value between two surface areas. Linear step value refers to the perpendicular distance between two reference planes on a one-dimensional profile line.

[0065] It is easy to understand that the roughness calculation sub-process or the step value calculation sub-process can be implemented based on existing methods, and no specific restrictions are imposed here. Both the roughness calculation sub-process and the step value calculation sub-process process the target scanned image. The results of each calculation sub-process are independent of each other, yielding corresponding calculation results, which are then used as the target measurement results. In other words, when there are multiple preset calculation sub-processes, the triggering order of these sub-processes will not affect the target measurement results; that is, multiple calculation sub-processes with different triggering orders will yield the same target measurement results.

[0066] In one example, in response to the triggering of the roughness calculation sub-process, the terminal calculates the roughness of the target scanned image according to the roughness calculation sub-process, obtaining the roughness measurement result of the sample under test. In response to the triggering of the step value calculation sub-process, the terminal calculates the step value of the target scanned image according to the step value calculation sub-process, obtaining the step value measurement result of the sample under test. If other calculation sub-processes besides the roughness calculation sub-process and the step value calculation sub-process are triggered, the target scanned image can be calculated according to the other calculation sub-processes to obtain the measurement results corresponding to those other calculation sub-processes.

[0067] In this embodiment, in response to the triggering of the roughness calculation sub-process, the target scan image is processed by the roughness calculation sub-process to obtain the roughness measurement result of the sample to be tested. In response to the triggering of the step value calculation sub-process, the target scan image is processed by the step value calculation sub-process to obtain the step value measurement result of the sample to be tested. This enables the automatic calculation of the corresponding measurement results based on the trigger-based preset calculation process, improving the automation level of the measurement and thus improving the measurement efficiency.

[0068] In some embodiments, obtaining the initial scan image of the sample to be tested in step 102 includes:

[0069] The original image data of the sample under test is obtained by the optical microscopy data processing device; the surface three-dimensional morphology is reconstructed based on the original image data to obtain the initial scan image of the sample under test.

[0070] For example, a schematic diagram of an optical microscopy data processing device is shown below. Figure 2 As shown. Raw image data refers to image data obtained by directly capturing images of the sample under test using an optical microscopy data processing device. For example, for a white light interferometer, the raw image data obtained from capturing images of the sample under test is a black and white fringe interferogram; for a confocal microscope, the raw image data obtained from capturing images of the sample under test is usually a high-resolution fluorescence image or a reflected light image. That is, the raw image data obtained from capturing images of the sample under test by different optical microscopy data processing devices generally differ in image format.

[0071] For example, for the black-and-white fringe interferogram obtained by a white-light interferometer capturing the sample under test, phase extraction can be performed on the black-and-white fringe interferogram to obtain phase information related to the surface height. This phase information is then converted into height information to obtain the initial scan image of the sample under test. For confocal microscopy, a complete XY two-dimensional image is captured at each Z height (Z layer), ultimately resulting in multiple two-dimensional images (i.e., raw image data). For each pixel (x, y), its grayscale value is extracted across all Z layers, resulting in a grayscale-depth curve I(Z). The Z coordinate corresponding to the peak point of this curve I(Z) is determined, and the Z value corresponding to this Z coordinate is the actual surface height of the corresponding pixel (x, y). The actual surface heights corresponding to all pixels are used as the height data corresponding to the initial scan image.

[0072] In practical applications, the sample to be tested can be photographed using an optical microscopy data processing device to obtain raw image data. Based on the raw image data, the surface three-dimensional morphology can be reconstructed to obtain the initial scan image of the sample to be tested, and the initial scan image can be displayed.

[0073] In this embodiment, the surface three-dimensional morphology is reconstructed by taking the original image data of the sample under test based on the optical microscopic data processing device, and the initial scan image of the sample under test is obtained. This initial scan image can match the actual sample information, laying a solid foundation for subsequent accurate measurement.

[0074] In some embodiments, the above method further includes:

[0075] The preset calibration process and preset calculation process are saved in the order of triggering to obtain the candidate processing process; in response to the triggering of the candidate processing process, the initial scan image of the new test sample is processed by the candidate processing process to obtain the measurement result of the new test sample.

[0076] In practical applications, the preset calibration and calculation processes triggered in each data processing method can be saved in the order of triggering using a save control or button, resulting in candidate processing flows. It's easy to understand that since the preset calibration and / or calculation processes triggered in different rounds may differ, these can be saved as different candidate processing flows. During subsequent measurements, the candidate processing flow that matches the measurement requirements can be selected for automatic processing to obtain the corresponding measurement results. This avoids triggering the preset calibration and calculation processes sequentially, reducing the number of triggers, shortening measurement time, and improving measurement efficiency.

[0077] For example, the terminal can save preset calibration procedures and preset calculation procedures in the order of triggering to obtain candidate processing procedures. During subsequent measurements, in response to the triggering of a candidate processing procedure, the terminal can automatically execute the candidate processing procedure on the initial scan image of a new sample to be tested, directly obtaining the measurement result of the new sample. Alternatively, after responding to the triggering of a candidate processing procedure, the terminal can edit the triggered candidate processing procedure, for example, by deleting or adding some preset calibration procedures (i.e., one or more calibration sub-procedures) and / or some preset calculation procedures (i.e., one or more calculation sub-procedures) to obtain a target processing procedure. Then, based on the target processing procedure, the initial scan image of the new sample to be tested is processed to obtain the measurement result of the new sample.

[0078] In this embodiment, by saving the preset calibration process and preset calculation process in the order of triggering, a candidate processing process is obtained. In response to the triggering of the candidate processing process, the initial scan image of the new test sample is processed by the candidate processing process to obtain the measurement result of the new test sample. This enables the measurement of the new test sample based on the aforementioned saved processing process, avoiding the need to trigger the preset calibration process and preset calculation process again in a new round of measurement, reducing measurement time and improving measurement efficiency.

[0079] In an exemplary embodiment, the data processing method based on optical microscopy can be implemented sequentially according to the following steps S1 to S4.

[0080] Step S1: Set the measurement method

[0081] Place the sample to be tested on the stage, turn on the optical microscopy data processing device, and select a suitable objective lens in the corresponding measurement software program. For example, select the objective lens type and magnification. If the optical microscopy data processing device is a white light interferometer, a dedicated interference objective lens needs to be selected. This is to obtain clear raw image data of the sample to be tested.

[0082] Move the lens to the position where measurement is needed and set the measurement method. Measurement methods include direct measurement and stitched measurement. Direct measurement involves photographing the sample surface within the current field of view to obtain a single-field 3D view (i.e., the initial scan image). Stitched measurement involves moving from the current field of view position according to set stitching parameters to perform stitching measurements, obtaining multiple images to be stitched within a set range, and then stitching these images together to obtain a 3D view of the selected area.

[0083] For example, a schematic diagram of the measurement method setting interface is shown below. Figure 3 As shown. The appropriate objective lens can be selected via lens control 302, and the measurement method can be determined via measurement method control 304. The captured 3D view can be displayed in the 3D view window 308 of the display interface. The display window 306 is used to display the real-time image captured by the lens (i.e., the raw image data). The navigation window 310 can be used to display a panoramic view or navigation map of the sample actually captured. The navigation map can be used to record the path traveled by the lens relative to the stage. The position in the navigation window corresponds to the stage, and the lens can be positioned to the corresponding position on the stage by clicking directly in the navigation window. It is easy to understand that the terminal can reconstruct the three-dimensional morphology of the surface based on the captured raw image data to obtain the initial scan image (i.e., 3D view) of the sample to be tested, and display it in the 3D view window 308.

[0084] Step S2: Perform the measurement to obtain a 3D view of the sample to be tested.

[0085] After setting the measurement method in step S1, the measurement can be started to acquire several raw image data. Based on the acquired raw image data, an initial scan image can be obtained. The initial scan image can be presented as a 3D view (such as a height map or a 3D reconstructed image).

[0086] Step S3: Configure a preprocessing procedure (i.e., a preset correction process) for the 3D view and execute it to obtain the corrected scan data (i.e., the target scan image).

[0087] For example, in Figure 3 Clicking the 3D measurement function in the illustrated display interface will redirect the measurement software on the terminal to... Figure 4 The measurement procedure (i.e., measurement process) configuration interface is shown. While displaying the measurement procedure configuration interface, the 3D view displayed in the 3D view window can be imported. Alternatively, pre-captured and saved 3D views can be directly imported into the measurement procedure configuration interface for processing and analysis to obtain the required measurement data, thus skipping the aforementioned steps S1 and S2.

[0088] The configuration of the measurement program mainly consists of two steps: preprocessing (i.e., preset calibration process) and analysis (i.e., preset calculation process). The preprocessing process first calibrates the imported 3D view to remove errors as much as possible, and then the analysis process is executed to obtain the desired measurement data such as surface roughness and step height.

[0089] For example, Figure 4 The measurement program configuration interface includes a measurement program bar 402, a toolbar 404, a processing display area 406, a processing configuration display area 408, and an analysis result display area 410. The measurement program bar 402 displays the names of the currently configured measurement programs, arranged in the configuration order. Users can directly click to jump to the selected processing program (i.e., the calibration sub-process). The image data input by the current processing program is displayed in the processing display area 406, which also shows the processing flow of the selected program. The corresponding configurable operations are displayed in the configuration display area 408. Analysis results obtained during the analysis process (such as target measurement results) are displayed in the analysis result display area 410.

[0090] The preprocessing process can include leveling (i.e., leveling sub-process), spike denoising (i.e., spike denoising sub-process), standard filtering (i.e., filtering sub-process), shape removal, rotation, etc., and one or more of these can be selected to process the 3D view. In this embodiment, the preprocessing process is chained (i.e., sequentially processed), executed according to the set order, using the data processed in the current step as input for the next step; progressively optimizing the 3D view, reducing the overall computational load, and improving the data accuracy of the 3D view. Figure 5 The illustrated preprocessing steps involve flattening the 3D view and then performing spike denoising. This spike denoising step processes the flattened image. In other words, the imported 3D view undergoes flattening, spike denoising, and standard filtering preprocessing steps sequentially to obtain the corrected 3D view.

[0091] The following are Figure 5The preprocessing steps shown are used as an example to illustrate the specific processing. Leveling removes the system height error introduced by the overall tilt of the sample and instrument from the scan data. Peak denoising removes isolated extrema caused by dust, bad pixels, etc., preventing them from increasing the step / roughness. Standard filtering smooths out random high-frequency noise, preserving the true shape.

[0092] Regarding the leveling process, it is possible to... Figure 4 In the measurement program configuration interface shown, selecting the leveling tool in toolbar 404 displays the corresponding panel. The processing display area 406 displays the leveling process panel, including the original view before processing (i.e., the image input for this process) and the view after leveling (i.e., the current processing result image). The configuration display area 408 displays the leveling program configuration panel. This allows you to obtain... Figure 6 The panel corresponding to the leveling process shown.

[0093] For the peak denoising process, it is possible to Figure 4 In the measurement program configuration interface shown, select the spike denoising tool in toolbar 404, and then the corresponding panel will be displayed. Processing display area 406 displays the spike denoising processing panel, including the input view and the denoised view (low-pass, high-pass). Configuration display area 408 displays the spike denoising program configuration panel. The following can be obtained: Figure 7 The panel corresponding to the peak denoising process is shown. Configure it according to the above preprocessing diagram; the view after the previous leveling step will be used as input for processing, meaning the input view will be displayed as the leveled view.

[0094] For the standard filtering process, it is possible to Figure 4 In the measurement program configuration interface shown, the standard filter tool is selected in toolbar 404, and then the corresponding panel is displayed. Processing display area 406 displays the standard filter processing panel, including the input view and the filtered post-processing view (low-pass, high-pass), and configuration display area 408 displays the standard filter program configuration panel. The following can be obtained: Figure 8 The panel corresponding to the standard filtering process is shown. Configured according to the above preprocessing diagram, the view after peak denoising in the previous step will be used as input for processing; that is, the input view is the view after peak denoising. In this embodiment, the low-pass or high-pass view obtained after standard filtering can be used as the corrected scan data (i.e., the target scan image).

[0095] Step S4: Configure the analysis program to analyze the calibrated scan data.

[0096] After obtaining the corrected scan data, analysis steps can be set. These steps select the corresponding calculation tools (i.e., configure calculation sub-processes) based on the preprocessed scan data to calculate roughness, step values, etc. Unlike the preprocessing steps, the configurable calculation tools in the analysis steps are parallel (i.e., they process data in parallel). All tools analyze the corrected data; the input to each tool is preprocessed data by default. Examples of common calculation tools include surface roughness, line roughness, surface step height, and line step height. If the configured analysis steps include line step height and surface roughness, the corrected data is used to calculate the line step height and surface roughness, respectively. A schematic diagram of the combined implementation flow of the preprocessing and analysis steps is shown below. Figure 9 As shown. Optionally, the analysis results display area 410 can have multiple windows to display the target measurement results and the measurement results obtained from each calculation sub-process, respectively. For example, by selecting any calculation sub-process in each measurement procedure bar 402, the analysis results display area 410 can jump to the measurement results window of the corresponding sub-process. Alternatively, the measurement procedure bar 402 can also have a selection bar to correspond to different windows.

[0097] After the above data processing program (i.e. measurement program) is configured, the data processing program can be saved as a template (i.e. candidate processing flow). When processing scan data with the same requirements, the template can be directly called to improve processing efficiency. In addition, each step can be adaptively adjusted and edited to suit different situations.

[0098] In the above embodiments, by configuring a preprocessing process and an analysis process, the scanning data of the sample to be tested is corrected based on the configured preprocessing process to obtain corrected scanning data. The corrected scanning data is then analyzed based on the configured analysis process to obtain the corresponding measurement results. The sample measurement process can be automatically and intelligently implemented through software, avoiding the problem of long operation time caused by introducing hardware to correct the scanning data, and enabling efficient measurement of the sample to be tested.

[0099] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0100] Based on the same inventive concept, this application also provides an optical microscopy-based data processing apparatus for implementing the aforementioned data processing method based on optical microscopy. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more embodiments of the optical microscopy-based data processing apparatus provided below can be found in the limitations of the optical microscopy-based data processing method described above, and will not be repeated here.

[0101] In one exemplary embodiment, such as Figure 10 As shown, a data processing device 1000 based on optical microscopy technology is provided, including: a scanned image acquisition module 1002, a scanned image correction module 1004, and a measurement result acquisition module 1006, wherein:

[0102] The scan image acquisition module 1002 is used to acquire the initial scan image of the sample to be tested;

[0103] The scan image correction module 1004 is used to process the initial scan image in response to the triggering of the preset correction process to obtain the target scan image. The preset correction process includes at least one correction subprocess, and the correction subprocesses in the preset correction process are processed in a serial manner, with the output data of the previous correction subprocess serving as the input data of the next correction subprocess.

[0104] The measurement result acquisition module 1006 is used to process the target scan image in response to the triggering of the preset calculation process to obtain the target measurement result of the sample to be tested. The preset calculation process includes at least one calculation subprocess, and the calculation subprocesses in the preset calculation process are processed in parallel. The input data of each calculation subprocess is the target scan image.

[0105] In some embodiments, the preset correction process includes a leveling subprocess and a spike denoising subprocess; the scan image correction module 1004 is further configured to, in response to the triggering of the leveling subprocess, process the initial scan image using the leveling subprocess to obtain a first scan image; and, in response to the triggering of the spike denoising subprocess, process the first scan image using the spike denoising subprocess to obtain a target scan image.

[0106] In some embodiments, the preset correction process further includes a filtering subprocess; the scan image correction module 1004 is further configured to, in response to the triggering of the spike denoising subprocess, process the first scan image using the spike denoising subprocess to obtain a second scan image; and in response to the triggering of the filtering subprocess, process the second scan image using the filtering subprocess to obtain a target scan image.

[0107] In some embodiments, the preset calculation process includes a roughness calculation subprocess and a step value calculation subprocess; the measurement result obtaining module 1006 is further configured to, in response to the triggering of the roughness calculation subprocess, process the target scan image using the roughness calculation subprocess to obtain the roughness measurement result of the sample to be tested; in response to the triggering of the step value calculation subprocess, process the target scan image using the step value calculation subprocess to obtain the step value measurement result of the sample to be tested; and use the roughness measurement result and the step value measurement result as the target measurement result.

[0108] In some embodiments, the scanning image acquisition module 1002 is further configured to acquire the original image data obtained by the optical microscopy data processing device from the sample to be tested; and to perform surface three-dimensional morphology reconstruction based on the original image data to obtain the initial scanning image of the sample to be tested.

[0109] In some embodiments, the above-described apparatus further includes a process inheritance module, which is used to save a preset calibration process and a preset calculation process in a triggering order to obtain a candidate processing process; in response to the triggering of the candidate processing process, the initial scan image of the new test sample is processed by the candidate processing process to obtain the measurement result of the new test sample.

[0110] The modules in the aforementioned data processing device based on optical microscopy technology can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0111] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 11As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a data processing method based on optical microscopy. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0112] Those skilled in the art will understand that Figure 11 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0113] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0114] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0115] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0116] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0117] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0118] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0119] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A data processing method based on optical microscopy, characterized in that, The method includes: Acquire the initial scan image of the sample to be tested; In response to the triggering of a preset correction process, the initial scan image is processed by the preset correction process to obtain a target scan image. The preset correction process includes at least one correction subprocess, and the correction subprocesses in the preset correction process are processed in a serial manner, with the output data of the previous correction subprocess serving as the input data of the next correction subprocess. In response to the triggering of a preset calculation process, the target scan image is processed by the preset calculation process to obtain the target measurement result of the sample to be tested. The preset calculation process includes at least one calculation subprocess, and the calculation subprocesses in the preset calculation process are processed in parallel. The input data of each calculation subprocess is the target scan image.

2. The method according to claim 1, characterized in that, The preset correction process includes a leveling sub-process and a spike denoising sub-process; the step of processing the initial scanned image with the preset correction process in response to the triggering of the preset correction process to obtain the target scanned image includes: In response to the triggering of the leveling sub-process, the initial scan image is processed by the leveling sub-process to obtain a first scan image; In response to the triggering of the spike denoising sub-process, the first scan image is processed by the spike denoising sub-process to obtain the target scan image.

3. The method according to claim 2, characterized in that, The preset correction process further includes a filtering sub-process; the step of processing the first scanned image using the peak denoising sub-process in response to triggering the peak denoising sub-process to obtain the target scanned image includes: In response to the triggering of the spike denoising sub-process, the first scan image is processed by the spike denoising sub-process to obtain the second scan image; In response to the triggering of the filtering sub-process, the second scanned image is processed by the filtering sub-process to obtain the target scanned image.

4. The method according to claim 1, characterized in that, The preset calculation process includes a roughness calculation sub-process and a step value calculation sub-process; the step of processing the target scan image according to the preset calculation process in response to the triggering of the preset calculation process to obtain the target measurement result of the sample to be tested includes: In response to the triggering of the roughness calculation sub-process, the target scan image is processed by the roughness calculation sub-process to obtain the roughness measurement result of the sample to be tested; In response to the triggering of the step value calculation sub-process, the target scan image is processed by the step value calculation sub-process to obtain the step value measurement result of the sample to be tested; the roughness measurement result and the step value measurement result are used as the target measurement result.

5. The method according to claim 1, characterized in that, The acquisition of the initial scan image of the sample to be tested includes: Acquire raw image data of the sample under test obtained by an optical microscopy data processing device; The surface three-dimensional morphology is reconstructed based on the original image data to obtain the initial scan image of the sample to be tested.

6. The method according to any one of claims 1 to 5, characterized in that, The method further includes: The preset correction process and the preset calculation process are saved in the order of triggering to obtain the candidate processing process; In response to the triggering of the candidate processing procedure, the initial scan image of the new test sample is processed by the candidate processing procedure to obtain the measurement result of the new test sample.

7. A data processing device based on optical microscopy technology, characterized in that, The device includes: The scan image acquisition module is used to acquire the initial scan image of the sample to be tested; A scanned image correction module is used to process the initial scanned image in response to the triggering of a preset correction process to obtain a target scanned image. The preset correction process includes at least one correction subprocess, and the correction subprocesses in the preset correction process are processed sequentially, with the output data of the previous correction subprocess serving as the input data of the next correction subprocess. The measurement result acquisition module is used to process the target scan image in response to the triggering of the preset calculation process to obtain the target measurement result of the sample to be tested. The preset calculation process includes at least one calculation subprocess, and the calculation subprocesses in the preset calculation process are processed in parallel. The input data of each calculation subprocess is the target scan image.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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