Data processing method, device and x-ray crystal orientation apparatus

Abstract

Embodiments of the present application provide a data processing method and device and an X-ray crystal orientation instrument, and relate to the technical field of data processing. The method comprises obtaining target data to be measured; controlling movement of the orientation instrument based on the target data to be measured to adjust an incident parameter of X-rays emitted by an X-ray source in the orientation instrument on a target to be measured; obtaining at least two groups of diffraction data by performing data detection during the adjustment of the incident parameter; analyzing and processing the two groups of diffraction data, generating an image to be analyzed according to one of the two groups of diffraction data when a difference between analysis results of the two groups of diffraction data meets a set condition; and performing spot identification and analysis processing on the image to be analyzed to obtain a data analysis result. The embodiments of the present application solve the problem that human intervention cannot be reduced in the analysis and processing of X-ray diffraction images.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and more specifically, to a data processing method, apparatus, and X-ray crystal orientation instrument. Background Technology

[0002] X-ray diffraction (XRD) images are grayscale images composed of multiple spots. The position and grayscale value of each spot contain positional information about the crystal being tested. Based on this positional information, crystal information such as the crystal type and crystal axis orientation can be determined. By acquiring the XRD image of the target crystal and comparing it with the XRD image of a reference crystal with known crystal information, the crystal information of the target crystal can be obtained.

[0003] Currently, the comparison between the X-ray diffraction image of the target and the X-ray diffraction image of the reference crystal is performed by visually identifying the position and gray value of the spots. However, the naked eye has limitations in identifying spots with different gray values ​​and cannot identify spots with all gray values. Therefore, some positional information will be ignored, and an accurate judgment cannot be made on the crystal information of the target.

[0004] Therefore, there is an urgent need for a data processing method, device, and X-ray crystal orientation instrument to solve the problem of not being able to reduce human intervention in the X-ray diffraction image analysis and processing process. Summary of the Invention

[0005] This application provides a data processing method, apparatus, and X-ray crystal orientation instrument, which can solve the problem of insufficient human intervention in the X-ray diffraction image analysis and processing process in related technologies. The technical solutions are as follows:

[0006] According to one embodiment of the present invention, a data processing method is applied to an X-ray crystallography system, the method comprising:

[0007] Acquire the target data;

[0008] The direction finder is controlled to move based on the target data to adjust the incident parameters of the X-rays emitted by the X-ray source in the direction finder onto the target.

[0009] At least two sets of diffraction data are obtained by performing data probing during the incident parameter adjustment process;

[0010] The two sets of diffraction data are analyzed and processed. When the difference between the analysis results of the two sets of diffraction data meets the set conditions, an image to be analyzed is generated based on one set of diffraction data.

[0011] The image to be analyzed is subjected to spot recognition and analysis to obtain data analysis results.

[0012] Furthermore, controlling the movement of the orientation device based on the target data includes at least one of the following:

[0013] Adjust the absolute positions of the X-ray source, sample holder, and detector in the orientation instrument in three-dimensional space;

[0014] Adjust the pitch angle of the X-ray source, sample holder, and detector in the orientation instrument in three-dimensional space;

[0015] Adjust the pose of the target under test on the sample holder in the orientation instrument.

[0016] Furthermore, by performing data probing during the incident parameter adjustment process, at least two sets of diffraction data are obtained, including:

[0017] From the target data, the initial detection angle and the initial pose of the target are obtained, and a set of diffraction data is obtained based on the initial detection angle and the initial pose of the target.

[0018] After the incident parameters are adjusted, the target data to be measured is acquired again;

[0019] From the reacquired target data, the updated detection angle and the updated pose of the target are obtained, and another set of diffraction data is obtained based on the updated detection angle and the updated pose of the target.

[0020] Furthermore, before analyzing and processing the two sets of diffraction data, the diffraction data is preprocessed, and the preprocessing includes:

[0021] The diffraction intensity parameter is extracted from the diffraction data, and the shift processing parameter is extracted from the target data to be tested. The shift processing parameter includes the decimal point shift direction and the number of decimal points shifted.

[0022] Based on the shifting processing parameters, the diffraction intensity parameters are shifted by a decimal point to obtain preprocessed diffraction data;

[0023] The analysis and processing of the two sets of diffraction data includes:

[0024] The two sets of preprocessed diffraction data were analyzed and processed.

[0025] Further, the step of generating the image to be analyzed based on one set of diffraction data includes:

[0026] Image segmentation is performed on the diffraction image composed of one set of diffraction data to determine the non-target region and the target region in the diffraction image;

[0027] An image to be analyzed, containing the target region, is obtained from the diffraction image.

[0028] Further, spot recognition is performed on the image to be analyzed, including:

[0029] The image to be analyzed is processed to obtain a grayscale image;

[0030] Threshold statistics are performed on the grayscale image to obtain threshold statistics results, and the spotted and non-spotted regions in the grayscale image are determined based on the threshold statistics results;

[0031] The spotted area is subjected to spot identification to obtain the spot identification result.

[0032] Further, the step of performing spot recognition on the spotted region to obtain the spot recognition result includes:

[0033] The identified spots in the spot recognition results are filtered out, and spots that do not meet the set threshold are removed to obtain the filtered spot recognition results.

[0034] Further, the image to be analyzed is subjected to grayscale processing to obtain a grayscale image, including:

[0035] The image color features of the image to be analyzed are determined, and the image to be analyzed is segmented based on the image color features to obtain several image regions, each of which corresponds to an image color feature;

[0036] By utilizing different image color features, several image regions are processed to obtain the grayscale image.

[0037] In another embodiment of the present invention, a data processing apparatus is applied to an X-ray crystallography system, the apparatus comprising:

[0038] The acquisition module is used to acquire data of the target to be tested;

[0039] The adjustment module is used to control the movement of the orientation instrument based on the target data to adjust the incident parameters of the X-rays emitted by the X-ray source in the orientation instrument onto the target.

[0040] The diffraction data acquisition module is used to obtain at least two sets of diffraction data by performing data detection during the incident parameter adjustment process;

[0041] The image generation module is used to analyze and process the two sets of diffraction data. When the difference between the analysis results of the two sets of diffraction data meets the set conditions, an image to be analyzed is generated based on one of the sets of diffraction data.

[0042] The image recognition module is used to perform spot recognition and analysis on the image to be analyzed, and to obtain data analysis results.

[0043] In another embodiment of the present invention, an X-ray crystallography system includes:

[0044] Processor; and

[0045] A memory storing computer-readable instructions, which, when executed by the processor, implement any of the data processing methods described above.

[0046] The beneficial effects of the technical solution provided in this application are:

[0047] The above technical solutions reduce the need for human intervention in the X-ray diffraction image analysis and processing process. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments of this application will be briefly introduced below.

[0049] Figure 1 This is a schematic diagram based on the implementation environment involved in this application.

[0050] Figure 2 This is a flowchart illustrating a data processing method based on an exemplary embodiment.

[0051] Figure 3 This is a flowchart illustrating a data processing method based on another exemplary embodiment.

[0052] Figure 4 This is a block diagram of a data processing apparatus based on another exemplary embodiment.

[0053] Figure 5 This is a block diagram of an X-ray crystal orientation instrument based on another exemplary embodiment. Detailed Implementation

[0054] To make the technical problems to be solved, the technical solutions, and the beneficial effects of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the present invention.

[0055] Figure 1This is a schematic diagram of the implementation environment involved in the data processing method. The implementation environment includes an X-ray crystal orientation instrument and a target to be measured. The X-ray crystal orientation instrument includes a central control module 1, a target data acquisition module 2, a detection angle acquisition module 3, a motion control module 4, a pose adjustment module 5, a data acquisition module 6, a diffraction data processing module 7, an image processing module 8, a speckle recognition module 9, a diffraction data analysis module 10, a data processing and analysis module 11, an adjustment module 12, and an output module 13. The central control module 1 is connected to the target data acquisition module 2, the detection angle determination module 3, the motion control module 4, the pose adjustment module 5, the data acquisition module 6, the diffraction data processing module 7, the image processing module 8, the speckle recognition module 9, the diffraction data analysis module 10, the data processing and analysis module 11, the adjustment module 12, and the output module 13, and is used to control the normal operation of each module using a microcontroller or controller.

[0056] The system comprises the following modules: a target data acquisition module 2, connected to the central control module 1, for acquiring target data; a detection determination module 3, connected to the central control module 1, for determining the detection angle and pose based on the acquired target data; a motion control module 4, connected to the central control module 1, for controlling the orientation platform's motion based on the initial detection angle and updating the detection angle; a pose adjustment module 5, connected to the central control module 1, for adjusting the initial pose based on the initial pose and platform control results to obtain the updated pose; a data extraction module 6, connected to the central control module 1, for extracting diffraction data from the target data; a diffraction data processing module 7, connected to the central control module 1, for preprocessing the diffraction data; and an image processing module 8, connected to the central control module 1. The control module 1 is connected to the central control module 1 and is used to preprocess the image data to be analyzed; the speckle recognition module 9 is connected to the central control module 1 and is used to recognize speckles based on the preprocessed image data; the diffraction data analysis module 10 is connected to the central control module 1 and is used to analyze and process the preprocessed diffraction data to obtain the diffraction data analysis results; the image analysis and processing module 11 is connected to the central control module 1 and is used to analyze and process the image to be analyzed; the adjustment module 12 is connected to the central control module 1 and controls the motion control module 4 and the pose adjustment module 5; the output module 13 is connected to the central control module 1 and is used to output the updated detection angle, the data of the target to be detected, the speckle recognition results, the diffraction data analysis results, and the analysis results of the image to be analyzed using a display.

[0057] The aforementioned orientation instrument enables the acquisition of target data, movement of the orientation instrument, acquisition and comparison of diffraction data, and generation, recognition and analysis of the image to be analyzed. This effectively solves the problem in related technologies that cannot identify spots of all brightness levels, which is not conducive to making accurate judgments on the crystal information of the target.

[0058] Figure 2 This is a data processing method illustrated according to one embodiment. The method is applicable to... Figure 1 The X-ray crystal orientation instrument shown is shown.

[0059] A data processing method 100 may include the following steps:

[0060] S11: Obtain the data of the target to be tested.

[0061] The target data includes detection angle, pose, displacement processing parameters, and diffraction data. The diffraction data includes diffraction angle, number of diffraction satellite peaks, and diffraction intensity. These parameters are obtained through the detector of the X-ray orientation instrument.

[0062] The target to be tested refers to crystals or solids formed from minerals, alloys, vitamins, drugs, or proteins. Information such as the length of interatomic chemical bonds, lattice mismatch, or defects can be obtained through the data methods provided by this invention.

[0063] Regarding the acquisition of the target data, the first detection image can originate from a real-time image acquired by an image acquisition device, or it can be a first detection image captured by an image acquisition device within a historical time period and pre-stored on a server. In other words, after acquiring the first detection image, the image acquisition device can process it in real-time, such as identifying the target in the first detection image in real time; alternatively, it can pre-store the image for further processing, for example, performing target recognition processing on the first detection image when the server has less processing power, or performing target recognition processing on the first detection image according to a time specified by the operator.

[0064] S12: Control the movement of the orientation instrument based on the target data to adjust the incident parameters of the X-rays emitted by the X-ray source in the orientation instrument onto the target.

[0065] In one embodiment, the orientation movement includes, but is not limited to: adjusting the absolute position and pitch angle of the X-ray source, sample holder and detector in the orientation in three-dimensional space, and adjusting the pose of the target under test on the sample holder in the orientation.

[0066] In one embodiment, the incident parameters include the incident angle and incident position of the X-rays incident on the target.

[0067] S13: At least two sets of diffraction data are obtained by performing data detection during the incident parameter adjustment process.

[0068] In one embodiment, at least two sets of diffraction data are obtained by data detection before and after the incident parameters are adjusted; that is, one set of diffraction data is obtained by data detection before the incident parameters are adjusted, and another set of diffraction parameters is obtained by data detection after the incident parameters are adjusted.

[0069] S14: Analyze and process the two sets of diffraction data. When the difference between the analysis results of the two sets of diffraction data meets the set conditions, generate an image to be analyzed based on one of the sets of diffraction data.

[0070] In one embodiment, the target under test has a standard value for the diffraction angle. The set conditions are that three aspects are met simultaneously: first, the difference between the diffraction angle and the standard value is small, meaning the diffraction angle's values ​​to one decimal place are the same as the standard value; second, the diffraction intensity values ​​differ by at least one order of magnitude; and third, the number of diffraction satellite peaks is greater. The diffraction data that meets these conditions is used to generate the image to be analyzed. In one embodiment, the diffraction data used to generate the image to be analyzed can be randomly selected from two sets of diffraction data. In another embodiment, diffraction data with larger values ​​is used to generate the image to be analyzed, making the image closer to the ideal state, thereby eliminating the influence of background noise from experimental and operational methods on the target under test.

[0071] S15: Perform spot recognition and analysis on the image to be analyzed to obtain data analysis results.

[0072] In one embodiment, spot recognition is achieved by identifying spots, including counting the number of spots.

[0073] The above process reduces the need for human intervention in X-ray diffraction image analysis and processing. The entire data processing is automated, overcoming the limitations of manual operation, enhancing the accuracy of spot recognition, and facilitating the acquisition of precise crystal information of the target object.

[0074] In one embodiment, before the blob recognition and analysis of the image to be analyzed, the image is preprocessed. This preprocessing includes, but is not limited to, denoising the image using a Gaussian filtering model. The Gaussian filtering model is as follows:

[0075]

[0076] in, k max Indicates the maximum frequency. V represents the scale parameter, μ represents the orientation parameter, and z = (x, y)||z|| = (x, y) 2 +y 2x and y represent the coordinates of the two-dimensional Gabor filter, i represents the virtual unit, and r is an introduced parameter used to control the shape of the Gabor filter.

[0077] The purpose of denoising filtering the image to be analyzed is to remove background noise. Background noise is generated in the diffraction image by the interaction between the sample holder and other components or obstructions and X-rays, as well as by other interaction effects between the target and X-rays besides the diffraction effect produced by the target on the X-rays. This background noise affects the correct identification of spots in the image to be analyzed.

[0078] Figure 3 This is a data processing method illustrated according to another embodiment. In another embodiment, this method is applicable to preprocessing the image to be analyzed before blob recognition and analysis. The preprocessing includes denoising the image using algorithms such as Gaussian filtering, median filtering, histogram homogenization, and edge enhancement. Figure 1 The X-ray crystal orientation instrument shown is shown.

[0079] A data processing method 200 may include the following steps:

[0080] S21: Obtain the target data to be tested.

[0081] The target data to be tested includes detection angle, pose, diffraction data, and displacement processing parameters.

[0082] S22: Control the movement of the orientation instrument based on the target data to adjust the incident parameters of the X-rays emitted by the X-ray source in the orientation instrument onto the target.

[0083] Among them, the incident parameters include the incident angle and incident position of the X-rays incident on the target.

[0084] Among them, controlling the movement of the orientation device based on the data of the target to be measured includes at least one of the following:

[0085] S221: Adjust the absolute positions of the X-ray source, sample holder, and detector in three-dimensional space within the orientation instrument.

[0086] S222: Adjust the pitch angle of the X-ray source, sample holder, and detector in the orientation instrument in three-dimensional space.

[0087] S223: Adjust the pose of the target under test on the sample holder in the orientation instrument.

[0088] S23: By performing data probing during the incident parameter adjustment process, at least two sets of diffraction data are obtained, including:

[0089] Specifically, S231: Obtain the initial detection angle and the initial pose of the target from the target data, and obtain a set of diffraction data based on the initial detection angle and the initial pose of the target.

[0090] S232: After adjusting the incident parameters, reacquire the target data.

[0091] S233: Obtain the updated detection angle and the updated pose of the target from the reacquired target data, and obtain another set of diffraction data based on the updated detection angle and the updated pose of the target.

[0092] S24: Preprocess the diffraction data, the preprocessing process including:

[0093] Specifically, S241: Extract diffraction intensity parameters from the diffraction data and extract shift processing parameters from the target data. The shift processing parameters include the decimal point shift direction and the number of decimal places shifted.

[0094] S242: The diffraction intensity parameters are shifted by a decimal point based on the shift processing parameters to obtain the preprocessed diffraction data.

[0095] S25: Analyze and process the two sets of diffraction data. When the difference between the analysis results of the two sets of diffraction data meets the set conditions, generate the image to be analyzed based on one of the sets of diffraction data.

[0096] In one embodiment, the target to be measured is known, and the set conditions are to simultaneously satisfy three aspects: First, the difference between the diffraction angle and the standard value of the diffraction angle is small, meaning that the values ​​of the diffraction angle to one decimal place are the same as the standard value; second, the values ​​obtained by taking the logarithm of the diffraction intensity to base 10 differ by at least one order of magnitude; and third, the number of diffraction peaks is greater. The diffraction data that meet the set conditions are used to generate the image to be analyzed.

[0097] The step of generating the image to be analyzed based on one set of diffraction data includes:

[0098] S251: Perform image segmentation on the diffraction image composed of one set of diffraction data to determine the non-target region and target region in the diffraction image.

[0099] S252: Obtain the image to be analyzed from the diffraction image, which contains the target region.

[0100] Non-target areas are caused by the interaction between the sample holder and other components or obstructions and X-rays, as well as other interaction effects between the target and X-rays besides the diffraction effect produced by the target on X-rays. These interactions generate background noise in the diffraction image, affecting the correct identification of spots in the image to be analyzed.

[0101] S26: Perform blob recognition and analysis on the image to be analyzed to obtain data analysis results.

[0102] Among them, blob recognition of the image to be analyzed includes:

[0103] S261: Perform grayscale processing on the image to be analyzed to obtain a grayscale image, including:

[0104] S2611: Determine the image color features of the image to be analyzed, and perform image segmentation on the image to be analyzed based on the image color features to obtain several image regions, each image region corresponding to an image color feature.

[0105] In this embodiment, image color features are expressed using grayscale values. The image to be analyzed is segmented based on the magnitude of the grayscale value, with each image region corresponding to a specific grayscale value.

[0106] S2612: Using different image color features, perform grayscale processing on several image regions to obtain the grayscale image.

[0107] S262: Perform threshold statistics on the grayscale image to obtain threshold statistics results, and determine the spotted and non-spotted regions in the grayscale image based on the threshold statistics results.

[0108] S263: Perform spot recognition on the spotted area to obtain the spot recognition result.

[0109] S264: Filter the identified spots in the spot recognition results and remove spots that do not meet the set threshold to obtain the filtered spot recognition results.

[0110] In one embodiment, a threshold is set to a diffraction intensity of 100 a.u arbitrary unit or 200 counts per second (cps), and spots with a diffraction intensity less than 100 a.u arbitrary unit or 200 counts per second (cps) are discarded.

[0111] In one embodiment, before the blob recognition and analysis of the image to be analyzed, the image is preprocessed. This preprocessing includes, but is not limited to, denoising the image using a Gaussian filtering model. The Gaussian filtering model is as follows:

[0112]

[0113] in, k max Indicates the maximum frequency. V represents the scale parameter, μ represents the orientation parameter, and z = (x, y)||z|| = (x, y) 2 +y 2 x and y represent the coordinates of the two-dimensional Gabor filter, i represents the virtual unit, and r is an introduced parameter used to control the shape of the Gabor filter.

[0114] The purpose of denoising filtering the image to be analyzed is to remove background noise. Background noise is generated in the diffraction image by the interaction between the sample holder and other components or obstructions and X-rays, as well as by other interaction effects between the target and X-rays besides the diffraction effect produced by the target on the X-rays. This background noise affects the correct identification of spots in the image to be analyzed.

[0115] In another embodiment, before the identification and analysis of blob in the image to be analyzed, the image to be analyzed is preprocessed. The preprocessing includes denoising filtering of the image to be analyzed using algorithms such as Gaussian filtering, median filtering, histogram homogenization, and edge enhancement.

[0116] Figure 4 According to another embodiment, a data processing apparatus 300 is applied to an X-ray crystal orientation instrument, including an acquisition module 31, an adjustment module 32, a diffraction data acquisition module 33, an image generation module 34, and an image recognition module 35.

[0117] The acquisition module 31 is used to acquire the target data to be tested.

[0118] The adjustment module 32 is used to control the movement of the orientation instrument based on the target data to adjust the incident parameters of the X-rays emitted by the X-ray source in the orientation instrument onto the target.

[0119] The diffraction data acquisition module 33 is used to obtain at least two sets of diffraction data by performing data detection during the incident parameter adjustment process.

[0120] The image generation module 34 is used to analyze and process the two sets of diffraction data. When the difference between the analysis results of the two sets of diffraction data meets the set conditions, an image to be analyzed is generated based on one of the sets of diffraction data.

[0121] The image recognition module 35 is used to perform spot recognition and analysis processing on the image to be analyzed, and obtain data analysis results.

[0122] Figure 5 According to another embodiment, an X-ray crystal orientation instrument 400 is shown, which includes a processor 41 and a memory 42.

[0123] The memory 42 stores computer-readable instructions, which, when executed by the processor, implement any of the data processing methods described above.

[0124] The technical solution provided by this invention reduces the need for human intervention in X-ray diffraction image analysis and processing. The entire data processing is automated, overcoming the limitations of manual operation, enhancing the accuracy of spot recognition, and facilitating the acquisition of precise crystal information of the target object.

[0125] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A data processing method applied to an X-ray crystal orientation instrument, characterized in that, The method includes: Acquire the target data; The direction finder is controlled to move based on the target data to adjust the incident parameters of the X-rays emitted by the X-ray source in the direction finder onto the target. By performing data detection during the incident parameter adjustment process, at least two sets of diffraction data are obtained; wherein, the two sets of diffraction data include a first set of diffraction data based on the initial detection angle and the initial pose of the target under test, and a second set of diffraction data corresponding to the updated detection angle and the updated pose of the target under test in the target data reacquired after the incident parameter adjustment. The two sets of diffraction data are analyzed and processed. When the difference between the analysis results of the two sets of diffraction data meets the set conditions, an image to be analyzed is generated based on one set of diffraction data. The set conditions refer to simultaneously satisfying three aspects: first, the diffraction angle is small compared to the standard value of the diffraction angle, meaning that the values ​​of the diffraction angle before and after the decimal point are the same as the standard value; second, the diffraction intensity values ​​differ by at least one order of magnitude; and third, the number of diffraction satellite peaks is greater. The set of diffraction data with the larger value is used to generate the image to be analyzed. The image to be analyzed is subjected to spot recognition and analysis to obtain data analysis results; the entire data processing process is performed automatically.

2. The data processing method as described in claim 1, characterized in that, Controlling the movement of the orientation device based on the target data includes at least one of the following: Adjust the absolute positions of the X-ray source, sample holder, and detector in the orientation instrument in three-dimensional space; Adjust the pitch angle of the X-ray source, sample holder, and detector in the orientation instrument in three-dimensional space; Adjust the pose of the target under test on the sample holder in the orientation instrument.

3. The data processing method as described in claim 1, characterized in that, Before analyzing and processing the two sets of diffraction data, the diffraction data is preprocessed, and the preprocessing includes: The diffraction intensity parameter is extracted from the diffraction data, and the shift processing parameter is extracted from the target data to be tested. The shift processing parameter includes the decimal point shift direction and the number of decimal points shifted. Based on the shifting processing parameters, the diffraction intensity parameters are shifted by a decimal point to obtain preprocessed diffraction data; The analysis and processing of the two sets of diffraction data includes: The two sets of preprocessed diffraction data were analyzed and processed.

4. The data processing method as described in claim 1, characterized in that, The step of generating the image to be analyzed based on one set of diffraction data includes: Image segmentation is performed on the diffraction image composed of one set of diffraction data to determine the non-target region and the target region in the diffraction image; An image to be analyzed, containing the target region, is obtained from the diffraction image.

5. The data processing method as described in claim 1, characterized in that, Performing blob recognition on the image to be analyzed includes: The image to be analyzed is processed to obtain a grayscale image; Threshold statistics are performed on the grayscale image to obtain threshold statistics results, and the spotted and non-spotted regions in the grayscale image are determined based on the threshold statistics results; The spotted area is subjected to spot identification to obtain the spot identification result.

6. The data processing method as described in claim 5, characterized in that, The step of performing spot recognition on the spotted area to obtain the spot recognition result includes: The identified spots in the spot recognition results are filtered out, and spots that do not meet the set threshold are removed to obtain the filtered spot recognition results.

7. The data processing method as described in claim 5, characterized in that, The image to be analyzed is subjected to grayscale processing to obtain a grayscale image, including: The image color features of the image to be analyzed are determined, and the image to be analyzed is segmented based on the image color features to obtain several image regions, each image region corresponding to an image color feature; By utilizing different image color features, several image regions are processed to obtain the grayscale image.

8. A data processing apparatus applied to an X-ray crystallography system, the data processing apparatus being used to execute the data processing method as described in any one of claims 1-7, characterized in that, The device includes: The acquisition module is used to acquire data of the target to be tested; The adjustment module is used to control the movement of the orientation instrument based on the target data to adjust the incident parameters of the X-rays emitted by the X-ray source in the orientation instrument onto the target. The diffraction data acquisition module is used to obtain at least two sets of diffraction data by performing data detection during the incident parameter adjustment process; wherein, the two sets of diffraction data include a first set of diffraction data based on the initial detection angle and the initial pose of the target under test, and a second set of diffraction data corresponding to the updated detection angle and the updated pose of the target under test in the target data re-acquired after the incident parameter adjustment. The image generation module is used to analyze and process the two sets of diffraction data. When the difference between the analysis results of the two sets of diffraction data meets the set conditions, an image to be analyzed is generated based on one of the sets of diffraction data. The image recognition module is used to perform spot recognition and analysis on the image to be analyzed, and to obtain data analysis results.

9. An X-ray crystal orientation instrument, characterized in that, include: processor; and A memory storing computer-readable instructions that, when executed by the processor, implement the data processing method as described in any one of claims 1 to 7.

Images