Detection methods and systems, devices, and storage media

Abstract

A detection method and system, device and storage medium, the detection method comprising: sequentially performing multiple image acquisition, each image acquisition being composed of first image acquisition and second image acquisition performed at adjacent time points, wherein the first image acquisition comprises: acquiring a first image containing a first mark, and the second image acquisition comprises: acquiring a second image containing a second mark; and obtaining alignment error of the first mark and the second mark by using positions of the first mark in multiple first images and positions of the second mark in multiple second images. The first image and the second image are obtained at adjacent time points through multiple acquisition, so as to increase the number of samples, and meanwhile, the first image and the second image are obtained at adjacent time points, thus being beneficial to weakening the influence of shaking of the detection device, and further improving the detection accuracy of the alignment error.

Description

Technical Field

[0001] The present invention relates to the field of optical detection technology, and in particular to a detection method, system, device and storage medium. Background Technology

[0002] In the manufacturing process of semiconductor devices, in order to ensure that the patterns formed by different film layers or different processes can be accurately aligned, it is necessary to detect the alignment error of the overlay mark.

[0003] During the inspection of overlay marks on different layers, if the thickness of the film layer is too large, it is necessary to inspect the center position of the marks on different layers separately, and obtain the alignment error by subtracting the center positions.

[0004] However, detecting markers at different layers requires acquiring images at corresponding heights at different time points. Image acquisition necessitates an image acquisition system and a motion platform. Due to the inherent jitter of the image acquisition system or motion platform, two images acquired at different heights may not be perfectly aligned horizontally. This results in the horizontal jitter being factored into the calculation of alignment error, thus affecting the accuracy of alignment error detection. Summary of the Invention

[0005] The problem solved by the embodiments of the present invention is to provide a detection method, system, device and storage medium, which is beneficial to improving the detection accuracy of alignment error.

[0006] To address the aforementioned problems, this invention provides a detection method for detecting overprinted marks on an object to be tested. The overprinted marks include a first mark and a second mark. The detection method includes: sequentially performing multiple image acquisitions, each image acquisition consisting of a first image acquisition and a second image acquisition performed at adjacent times. The first image acquisition includes: acquiring a first image containing the first mark, and the second image acquisition includes: acquiring a second image containing the second mark. The alignment error between the first mark and the second mark is obtained by using the positions of the first mark in the multiple first images and the positions of the second mark in the multiple second images.

[0007] Accordingly, this embodiment of the invention also provides a detection system for detecting overlay marks on an object to be tested. The overlay marks include a first mark and a second mark. The detection system includes: an image acquisition module for sequentially performing multiple image acquisitions, each image acquisition consisting of a first image acquisition and a second image acquisition performed at adjacent times, wherein the first image acquisition includes: acquiring a first image containing the first mark, and the second image acquisition includes: acquiring a second image containing the second mark; and a processing module for obtaining the alignment error of the first mark and the second mark using the positions of the first mark in multiple first images and the positions of the second mark in multiple second images.

[0008] Accordingly, embodiments of the present invention also provide a device, including at least one memory and at least one processor, wherein the memory stores one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the detection method described in the embodiments of the present invention.

[0009] Accordingly, embodiments of the present invention also provide a storage medium storing one or more computer instructions, which are used to implement the detection method described in the embodiments of the present invention.

[0010] Compared with the prior art, the technical solution of the embodiments of the present invention has the following advantages:

[0011] In the detection method provided by the embodiments of the present invention, the number of samples is increased by acquiring the first image and the second image at adjacent time points multiple times. Since the first image and the second image are acquired at adjacent time points, compared with the scheme of acquiring only one image, increasing the number of samples is beneficial to make the errors caused by the shaking of the detection equipment compensate for each other, that is, it is beneficial to reduce the impact of the shaking of the detection equipment on the detection results of the alignment error of the first mark and the second mark, thereby improving the detection accuracy of the alignment error. Attached Figure Description

[0012] Figure 1 This is a flowchart of an embodiment of the detection method of the present invention;

[0013] Figure 2 This is a top view of an embodiment of the overlay marking in the detection method of the present invention;

[0014] Figure 3 yes Figure 1 In step S1, a schematic diagram of an embodiment of the first image and the second image is shown;

[0015] Figure 4This is a schematic diagram of an embodiment showing the relative positions of the centers of the first and second markers in a first image and a second image acquired at any adjacent time.

[0016] Figure 5 This is a functional block diagram of an embodiment of the detection system of the present invention;

[0017] Figure 6 This is a hardware structure diagram of a device provided in an embodiment of the present invention. Detailed Implementation

[0018] As is known from the background art, detecting marks in different layers separately can easily lead to a decrease in the accuracy of alignment error detection.

[0019] Research has revealed the following potential issues during image acquisition: 1) In a static state with a vibration isolation system installed (i.e., without motion commands sent to the motion platform), the optical path system is prone to slight horizontal jitter relative to the motion platform; 2) In automated measurement processes, to achieve high-speed measurement of multiple markers on the object under test, the motion platform needs to move at high speed along the horizontal direction (i.e., the X and Y directions) to achieve imaging at the focusing height; 3) The focusing module carrying the optical path system also moves along the vertical direction (i.e., the Z direction). These issues can easily lead to the calculation of alignment error between two images including horizontal jitter, thus affecting the accuracy of alignment error detection.

[0020] To address the aforementioned technical problem, embodiments of the present invention provide a detection method. The detection method is used to detect overprinted marks on an object to be tested, the overprinted marks including a first mark and a second mark.

[0021] refer to Figure 1 The flowchart illustrates an embodiment of the detection method of the present invention. The detection method described in this embodiment includes the following basic steps:

[0022] Step S1: Perform multiple image acquisitions sequentially. Each image acquisition consists of a first image acquisition and a second image acquisition performed at adjacent time points. The first image acquisition includes acquiring a first image containing the first marker, and the second image acquisition includes acquiring a second image containing the second marker.

[0023] Step S2: Using the positions of the first mark in multiple first images and the positions of the second mark in multiple second images, obtain the alignment error between the first mark and the second mark.

[0024] In this embodiment of the invention, the number of samples is increased by acquiring the first image and the second image at adjacent times. Since the first image and the second image are acquired at adjacent times, compared with the scheme of acquiring only one image, increasing the number of samples is beneficial to make the errors caused by the shaking of the detection equipment compensate for each other, that is, it is beneficial to reduce the impact of the shaking of the detection equipment on the detection results of the alignment error of the first mark and the second mark, thereby improving the detection accuracy of the alignment error.

[0025] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0026] Reference Figures 1 to 3 , Figure 1 This is a flowchart of an embodiment of the detection method of the present invention. Figure 2 This is a top view of an embodiment of the overlay marking in the detection method of the present invention. Figure 3 yes Figure 1 In step S1, a schematic diagram of an embodiment of the first image and the second image is shown.

[0027] In this embodiment, the detection method is used to detect the overprinted mark 100 on the test object (not shown), the overprinted mark 100 including a first mark 110 and a second mark 120.

[0028] In order to ensure that patterns formed by different film layers or different processes can be accurately aligned, the reliability of the process needs to be tested by detecting the alignment error between the overlay marks 100.

[0029] In this embodiment, the overlay mark 100 includes a first mark 110 and a second mark 120, thereby obtaining the alignment error of the overlay mark 100 by detecting the alignment error between the first mark 110 and the second mark 120.

[0030] Specifically, the overlay mark 100 is located on the object under test (DUT), and the first mark 110 and the second mark 120 are located at different height positions on the DUT, or the first mark 110 and the second mark 120 are formed in different processes. As an example, the DUT can be a wafer or a chip.

[0031] The fact that the first mark 110 and the second mark 120 are located at different heights of the object under test means that, along the normal direction of the surface of the object under test, the first mark 110 and the second mark 120 are located in different layers of the object under test in space.

[0032] As an example, the orthographic projection of the first mark 110 onto the layer containing the second mark 120 is located inside the second mark 120.

[0033] Specifically, step S1 is executed, and multiple image acquisitions are performed sequentially. Each image acquisition consists of a first image acquisition and a second image acquisition performed at adjacent times. The first image acquisition includes acquiring a first image 210 containing the first marker 110, and the second image acquisition includes acquiring a second image 220 containing the second marker 120.

[0034] The position of the first mark 110 is obtained through the first image 210, and the position of the second mark 120 is obtained through the second image 220. Thus, the alignment error of the first mark 110 and the second mark 120 is obtained through the position of the first mark 110 in the first image 110 and the position of the second mark 120 in the second image 120.

[0035] Here, the first image 210 is an image of the first mark 110 taken at the focus height of the first mark 110, and the second image 220 is an image of the second mark 120 taken at the focus height of the second mark 120.

[0036] In this embodiment, the detection method is performed using a detection device, which includes: an image acquisition component for acquiring images of the overprinted mark 100; and a motion platform for moving the image acquisition component and the object to be tested relative to each other.

[0037] The image acquisition component and the object under test are moved relative to each other by a motion platform, so that the image acquisition component can acquire images at different times at the focal heights corresponding to the first mark 110 and the second mark 120, respectively. Specifically, the image acquisition component includes a camera.

[0038] It should be noted that the focusing height refers to the height at which the relative height of the image acquisition component and the overlay mark 100 meets the requirements for focusing and positioning.

[0039] In this embodiment, each image acquisition consists of a first image acquisition and a second image acquisition performed at adjacent moments. Adjacent moments refer to the trigger moments of adjacent image acquisition signals.

[0040] It is understood that there is a time interval Δt between adjacent moments, which includes at least: the time required for the current first image acquisition or the second image acquisition; and the time required to move from either the first image acquisition or the second image acquisition to the other acquisition position.

[0041] As an example, the time interval Δt between adjacent moments also includes: the set time after the relative position between the image acquisition component and the object under test reaches a preset position when moving from either the first image acquisition or the second image acquisition position to the other acquisition position.

[0042] In this embodiment, the first image acquisition includes: acquiring multiple frames of images at the same time, and the first image 210 includes multiple first sub-images (not shown). That is, at any time when the image acquisition signal is triggered, multiple images of the first marker 110 will be continuously captured at the same location, thereby obtaining multiple first sub-images.

[0043] Similarly, the second image acquisition includes: acquiring multiple frames of images at the same time, and the second image 220 includes multiple second sub-images (not shown). That is, at any time when the image acquisition signal is triggered, multiple images of the second marker 120 will be continuously captured at the same location, thereby obtaining multiple second sub-images.

[0044] The number of first sub-images contained in each first image 210 and the number of second sub-images contained in each second image 220 can be configured according to the magnitude of high-frequency jitter and noise between the image acquisition component and the motion platform. The number of images acquired per unit time is determined by the camera's frame rate. For example, with 80 frames per second, 8 images can be captured in 100 milliseconds.

[0045] It should be noted that the high-frequency jitter refers to a jitter frequency greater than or equal to 100 Hz.

[0046] It should also be noted that during the simultaneous acquisition of multiple frames of images, the time interval between adjacent first sub-images should not be too large. If the time interval between adjacent first sub-images is too large, it can easily lead to an excessively large time interval between the subsequent acquisition of the first and second images, resulting in a larger error caused by the jitter of the detection device. Consequently, when subsequently statistically analyzing the alignment error of the first mark 110 and the second mark 120, the mutual compensation effect of the errors is likely to be poor. Therefore, in this embodiment, during the simultaneous acquisition of multiple frames of images, the time interval between adjacent first sub-images is less than 15 milliseconds.

[0047] For the same reason mentioned above, during the acquisition of multiple frames of images at the same time, the acquisition time interval between adjacent second sub-images is less than 15 milliseconds.

[0048] Simultaneous acquisition of multiple frames of images helps compensate for errors caused by high-frequency jitter and noise. In each acquisition of the first image, the accuracy of alignment error detection tends to converge as the number of first sub-images increases. Therefore, if the number of first sub-images is too large, it will lead to unnecessary waste of time and resources. For this reason, in this embodiment, the number of first sub-images in each acquisition is 2 to 10.

[0049] For the same reasons mentioned above, in each second image acquisition, the number of second sub-images is 2 to 10.

[0050] As an example, in two consecutive image acquisitions, the order of the first and second image acquisitions in the first acquisition is different from the order of the first and second image acquisitions in the second acquisition.

[0051] For example: in the first image acquisition, the first marker 110 is captured at time t1 and the second marker 120 is captured at time t2; in the second image acquisition, the second marker 120 is captured at time t3 and the first marker 110 is captured at time t4; in the third image acquisition, the first marker 110 is captured at time t5 and the second marker 120 is captured at time t6; in the fourth image acquisition, the second marker 120 is captured at time t7 and the first marker 110 is captured at time t8, and so on.

[0052] By making the order of the first and second image acquisitions in the previous image acquisition different from the order of the first and second image acquisitions in the subsequent image acquisition, the first image in the subsequent image acquisition can be taken at the same position after the previous image acquisition is completed, thereby shortening the time interval between the two consecutive image acquisitions and improving detection efficiency. Furthermore, when unidirectional drift (X or Y direction) occurs along the horizontal direction, it is also beneficial to further reduce the impact of detection device jitter on the detection results of the alignment error of the first mark 110 and the second mark 120.

[0053] In other embodiments, the first and second image acquisitions are performed alternately during the multiple image acquisitions. That is, each image acquisition consists of a first image acquisition and a second image acquisition performed sequentially; or, each image acquisition consists of a second image acquisition and a first image acquisition performed sequentially.

[0054] For example: in the first image acquisition, the first marker is photographed at time t1 and the second marker is photographed at time t2; in the second image acquisition, the first marker is photographed at time t3 and the second marker is photographed at time t4; in the third image acquisition, the first marker is photographed at time t5 and the second marker is photographed at time t6; in the fourth image acquisition, the first marker is photographed at time t7 and the second marker is photographed at time t8, and so on.

[0055] It should be noted that the number of image acquisitions should not be too few or too many. If the number of image acquisitions is too few, the sample size will be insufficient. Consequently, when calculating the alignment error of the first mark 110 and the second mark 120 in subsequent statistical analysis, the mutual compensation effect of errors caused by the vibration of the detection equipment will be poor, which is not conducive to improving the accuracy of alignment error detection. Since the accuracy of alignment error detection tends to converge with the increase of the number of image acquisitions, if the number of image acquisitions is too many, it will cause unnecessary waste of time and cost, which is not conducive to improving detection efficiency. Therefore, in this embodiment, the number of image acquisitions is 2 to 5.

[0056] In this embodiment, during the multiple image acquisitions, the time interval between the first and second image acquisitions performed at adjacent moments is less than the period of the low-frequency jitter between the image acquisition component and the motion platform; wherein, the low-frequency jitter refers to a jitter frequency of less than 100 Hz.

[0057] By making the time interval between the first and second image acquisitions performed at adjacent times shorter than the low-frequency jitter period, it is beneficial to ensure that the center position errors of the first mark 110 and the second mark 120 caused by the low-frequency jitter are the same. Therefore, the alignment error obtained by the deviation of the center positions of the first mark 110 and the second mark 120 can reduce the error caused by the low-frequency jitter.

[0058] It should be noted that in the multiple image acquisitions, the time interval between the first and second image acquisitions performed at adjacent moments is 50 to 100 milliseconds, which makes the time interval between the first and second image acquisitions performed at adjacent moments much smaller than the time period of the low-frequency jitter.

[0059] In the first and second image acquisitions performed at adjacent time points, the images need to be captured at different heights. Therefore, if the time interval is too short, it may exceed the limits of the detection equipment, potentially causing additional jitter and unnecessary errors. For example, after the image acquisition component and the object under test move relative to each other, a certain amount of time is needed for their relative positions to stabilize (this time is specifically the setpoint time). If the time interval is too short, the relative positions of the image acquisition component and the object under test may not have stabilized after the relative movement.

[0060] If the time interval between the first image acquisition and the second image acquisition is too long, it will easily increase the probability of errors introduced by low-frequency jitter.

[0061] Therefore, the time interval between the first and second image acquisitions performed at adjacent moments is 50 milliseconds to 100 milliseconds.

[0062] Continue to refer to Figure 1 and in conjunction with references Figure 4 , Figure 4 This is a schematic diagram of an embodiment of the relative positions of the centers of the first mark and the second mark in a first image and a second image acquired at any adjacent time. In this embodiment, before obtaining the alignment error of the first mark and the second mark by using the positions of the first mark in multiple first images and the positions of the second mark in multiple second images, the detection method further includes: performing step S3, performing median processing on the position of the first sub-image corresponding to each first image 210 to obtain the position of each first image 210; and performing median processing on the position of the second sub-image corresponding to each second image 220 to obtain the position of each second image 220.

[0063] In this embodiment, the position is the center position. That is, the center position of each first image 210 is obtained by performing median processing on the center position of the first sub-image corresponding to each first image 210, and the center position of each second image 220 is obtained by performing median processing on the center position of the second sub-image corresponding to each second image 220.

[0064] Here, the center position of the first sub-image refers to the center position of the first mark 110 in the first sub-image, and the center S1 of the first image 210 refers to the center position of the first mark 110 in the first image 210; the center position of the second sub-image refers to the center position of the second mark 120 in the second sub-image, and the center S2 of the second image 220 refers to the center position of the second mark 120 in the second image 220.

[0065] In other embodiments, the location may also be a corner location or an intersection location.

[0066] It should be noted that, in the process of obtaining the position of each first image 210 by performing median processing on the position of the first sub-image corresponding to each first image 210, the position of the first sub-image has the same type as the position of the first image 210. Similarly, the position of the second sub-image has the same type as the position of the second image 220.

[0067] As described above, both the first image acquisition and the second image acquisition will perform multi-frame image acquisition at the same time. The first image 210 includes multiple first sub-images (not shown), and the second image 220 includes multiple second sub-images (not shown). Therefore, by performing median processing on the position of the first sub-image corresponding to each first image 210 and median processing on the center position of the second sub-image corresponding to each second image 220, it is beneficial to reduce the error caused by high-frequency jitter and the error caused by noise, thereby improving the accuracy of the position of each first image 210 and the accuracy of the position of each second image 220.

[0068] In this embodiment, the median processing is performed by averaging. By averaging, the errors caused by high-frequency jitter and noise can be significantly reduced.

[0069] In other embodiments, the median processing can also be performed by obtaining the median value.

[0070] Continue to refer to Figure 1 and Figure 4 Step S2 is executed, using the position of the first mark 110 in multiple first images 210 and the position of the second mark 120 in multiple second images 220 to obtain the alignment error of the first mark 110 and the second mark 120.

[0071] The aforementioned multiple image acquisitions, by acquiring the first and second images at adjacent moments, increase the number of samples. Since the first and second images are acquired at adjacent moments, compared to the scheme of acquiring only one image, increasing the number of samples helps to compensate for errors caused by detection device jitter, that is, it helps to reduce the impact of detection device jitter on the detection results of alignment errors of the first mark 110 and the second mark 120, thereby improving the detection accuracy of alignment errors.

[0072] In this embodiment, obtaining the alignment error of the first mark 110 and the second mark 120 using the positions of the first mark 110 in multiple first images 210 and the second mark 120 in multiple second images 220 includes: obtaining the alignment error of the first mark 110 and the second mark 120 in a first direction (e.g., ... Figure 4 Alignment error in the X direction (as shown in the middle X direction), and alignment error of the first mark 110 and the second mark 120 in the second direction (as shown in the middle X direction). Figure 4 The alignment error in the Y direction (as shown in the middle) is perpendicular to the first and second directions.

[0073] Specifically, based on the same coordinate system, the position error Δx of the first mark 110 and the second mark 120 in the first direction and the position error Δy in the second direction are obtained. For example, the coordinate system is an XY coordinate system, where the first direction is parallel to the X-axis direction and the second direction is parallel to the Y-axis direction.

[0074] In this embodiment, during the process of obtaining the alignment error of the first mark 110 and the second mark 120 using the positions of the first mark 110 in multiple first images 210 and the positions of the second mark 120 in multiple second images 220, the position is the center position. In other embodiments, the position can also be a corner position or an intersection position.

[0075] Accordingly, in this embodiment, the alignment error of the first mark 110 and the second mark 120 is obtained by using the center S1 position of the first mark 110 in multiple first images 210 and the center S2 position of the second mark 120 in multiple second images 220. Correspondingly, based on the same coordinate system, the positional error Δx of the center S1 of the first mark 110 and the center S2 of the second mark 120 in the first direction and the positional error Δy in the second direction are obtained.

[0076] As an example, obtaining the alignment error of the first mark 110 and the second mark 120 using the positions of the first mark 110 in multiple first images 210 and the positions of the second mark 120 in multiple second images 220 includes: using the first images 210 and the second images 220 acquired at adjacent times or at a preset number of time intervals, calculating the positional deviation of the first mark 110 and the second mark 120 as a sampling alignment error to obtain an alignment error set containing multiple sampling alignment errors, wherein the preset number is less than or equal to 5; performing median processing on the multiple sampling alignment errors in the alignment error set to obtain the alignment error of the first mark 110 and the second mark 120.

[0077] It should be noted that the preset number is less than or equal to 5, so that the time interval between the first image 210 and the second image 220 acquired at preset intervals will not be too long. This is beneficial for the mutual compensation of errors caused by the shaking of the detection equipment, and correspondingly helps to reduce the impact of the shaking of the detection equipment on the detection results of the alignment error of the first mark 110 and the second mark 120.

[0078] For example: in the first image acquisition, the first marker 110 is captured at time t1 and the second marker 120 is captured at time t2; in the second image acquisition, the second marker 120 is captured at time t3 and the first marker 110 is captured at time t4; in the third image acquisition, the first marker 110 is captured at time t5 and the second marker 120 is captured at time t6; in the fourth image acquisition, the second marker 120 is captured at time t7 and the first marker 110 is captured at time t8, and so on.

[0079] Accordingly, taking the first image 210 and the second image 220 acquired at adjacent times as an example, the positional deviation of the first mark 110 and the second mark 120 is calculated as the sampling alignment error. The first sampling alignment error is obtained by using the first image 210 captured at time t1 and the second image 220 captured at time t2.

[0080] Similarly, a second sampling alignment error is obtained using the second image 220 taken at time t3 and the first image 210 taken at time t4; a third sampling alignment error is obtained using the first image 210 taken at time t5 and the second image 220 taken at time t6; a fourth sampling alignment error is obtained using the second image 220 taken at time t7 and the first image 210 taken at time t8, and so on.

[0081] Therefore, by using the first image 210 and the second image 220 acquired at adjacent times, multiple sampling alignment errors are obtained, and then the median of the multiple sampling alignment errors is processed to obtain the final alignment error.

[0082] In this embodiment, the median processing is performed by averaging. Averaging the sampling alignment errors obtained from the first image 210 and the second image 220 acquired at adjacent time points allows for mutual compensation of errors caused by jitter (e.g., low-frequency jitter) generated by the detection device, thereby reducing errors caused by the jitter of the detection device. In other embodiments, the median processing can also be performed by calculating the median value.

[0083] It should be noted that each of the sampling alignment errors includes a sampling alignment error in the first direction and a sampling alignment error in the second direction. Accordingly, the sampling alignment errors in the first direction and the sampling alignment errors in the second direction are respectively processed by median value.

[0084] In other embodiments, when the first image acquisition and the second image acquisition are performed alternately during the multiple image acquisitions, the first image and the second image acquired at adjacent times can be randomly selected for data statistics.

[0085] For example, in the first image acquisition, the first marker is photographed at time t1 and the second marker is photographed at time t2; in the second image acquisition, the first marker is photographed at time t3 and the second marker is photographed at time t4; in the third image acquisition, the first marker is photographed at time t5 and the second marker is photographed at time t6; in the fourth image acquisition, the first marker is photographed at time t7 and the second marker is photographed at time t8, and so on. Correspondingly, when performing data statistics, one sampling alignment error can be obtained based on the second image photographed at time t2 and the first image photographed at time t3, and another sampling alignment error can be obtained based on the second image photographed at time t4 and the first image photographed at time t5, and so on, thus obtaining multiple sampling alignment errors.

[0086] In other embodiments, obtaining the alignment error of the first mark and the second mark using the positions of the first mark in multiple first images and the positions of the second mark in multiple second images includes: performing median processing on the positions of the multiple first images to obtain the position of the first mark; performing median processing on the positions of the multiple second images to obtain the position of the second mark, wherein the second images subjected to median processing correspond one-to-one with the first images subjected to median processing, and the first and second images satisfying the one-to-one correspondence are obtained in the same image acquisition step; after performing median processing on the positions of the multiple first images and the multiple second images, calculating the positional deviation of the first mark and the second mark to obtain the alignment error of the first mark and the second mark.

[0087] Performing median processing on the positions of the first image and the second image separately can help compensate for the errors caused by the shaking of the detection equipment, thus reducing the impact of the shaking of the detection equipment on the detection results of the alignment error of the first and second marks.

[0088] Specifically, the median processing method includes calculating the average or the median value.

[0089] Accordingly, embodiments of the present invention also provide a detection system. (See reference) Figure 5 The diagram shows a functional block diagram of an embodiment of the detection system of the present invention.

[0090] Reference Figures 2 to 3 The detection system is used to detect overprinted marks 100 on the test object (not shown), the overprinted marks 100 including a first mark 110 and a second mark 120.

[0091] For a detailed description of the test object and the overlay mark 100, please refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0092] The detection system includes: an image acquisition module 10, used to sequentially perform multiple image acquisitions, each image acquisition consisting of a first image acquisition and a second image acquisition performed at adjacent times, wherein the first image acquisition includes: acquiring a first image 210 containing the first mark 110, and the second image acquisition includes: acquiring a second image 220 containing the second mark 120; and a processing module 20, used to obtain the alignment error of the first mark 110 and the second mark 120 by using the position of the first mark 110 in the multiple first images 210 and the position of the second mark 120 in the multiple second images 220.

[0093] The image acquisition module 10 is used to acquire a first image 120 and a second image 220. The position of the first mark 110 is obtained through the first image 210, and the position of the second mark 120 is obtained through the second image 220. Thus, the alignment error of the first mark 110 and the second mark 120 is obtained through the position of the first mark 110 in the first image 110 and the position of the second mark 120 in the second image 120.

[0094] In this embodiment, the image acquisition module 10 uses a detection device to acquire images. The detection device includes: an image acquisition component for acquiring images of the overlay mark 100; and a motion platform for moving the image acquisition component and the object to be tested relative to each other.

[0095] The image acquisition component and the object under test are moved relative to each other by a motion platform, so that the image acquisition component can acquire images at different times at the focal heights corresponding to the first mark 110 and the second mark 120, respectively. Specifically, the image acquisition component includes a camera.

[0096] In this embodiment, each image acquisition consists of a first image acquisition and a second image acquisition performed at adjacent moments. Adjacent moments refer to the trigger moments of adjacent image acquisition signals.

[0097] It is understood that there is a time interval Δt between adjacent moments, which includes at least: the time required for the current first image acquisition or the second image acquisition; and the time required to move from either the first image acquisition or the second image acquisition to the other acquisition position.

[0098] As an example, the time interval Δt between adjacent moments also includes: the set time after the relative position between the image acquisition component and the object under test reaches a preset position when moving from either the first image acquisition or the second image acquisition position to the other acquisition position.

[0099] In this embodiment, the image acquisition module 10 is used to acquire multiple frames of images at the same time to achieve a first image acquisition. The first image 210 includes multiple first sub-images (not shown). That is, at any time when the image acquisition signal is triggered, multiple images of the first marker 110 will be continuously captured at the same location to obtain multiple first sub-images.

[0100] Similarly, the image acquisition module 10 is used to acquire multiple frames of images at the same time to achieve a second image acquisition. The second image 220 includes multiple second sub-images (not shown). That is, at any time when the image acquisition signal is triggered, multiple images of the second marker 120 will be continuously captured at the same location to obtain multiple second sub-images.

[0101] The number of first sub-images contained in each first image 210 and the number of second sub-images contained in each second image 220 can be configured according to the magnitude of high-frequency jitter and noise between the image acquisition component and the motion platform. The number of images acquired per unit time is determined by the camera's frame rate. For example, with 80 frames per second, 8 images can be captured in 100 milliseconds.

[0102] It should be noted that the high-frequency jitter refers to a jitter frequency greater than or equal to 100 Hz.

[0103] It should also be noted that during the simultaneous acquisition of multiple frames of images, the time interval between adjacent first sub-images should not be too large. If the time interval between adjacent first sub-images is too large, it can easily lead to an excessively large time interval between the subsequent acquisition of the first and second images, resulting in a larger error caused by the jitter of the detection device. Consequently, when subsequently statistically analyzing the alignment error of the first mark 110 and the second mark 120, the mutual compensation effect of the errors is likely to be poor. Therefore, in this embodiment, during the simultaneous acquisition of multiple frames of images, the time interval between adjacent first sub-images is less than 15 milliseconds.

[0104] For the same reason mentioned above, during the acquisition of multiple frames of images at the same time, the acquisition time interval between adjacent second sub-images is less than 15 milliseconds.

[0105] Simultaneous acquisition of multiple frames of images helps compensate for errors caused by high-frequency jitter and noise. In each acquisition of the first image, the accuracy of alignment error detection tends to converge as the number of first sub-images increases. Therefore, if the number of first sub-images is too large, it will lead to unnecessary waste of time and resources. For this reason, in this embodiment, the number of first sub-images in each acquisition is 2 to 10.

[0106] For the same reasons mentioned above, in each second image acquisition, the number of second sub-images is 2 to 10.

[0107] As an example, in two consecutive image acquisitions, the order of the first and second image acquisitions in the first acquisition is different from the order of the first and second image acquisitions in the second acquisition.

[0108] For example: in the first image acquisition, the first marker 110 is captured at time t1 and the second marker 120 is captured at time t2; in the second image acquisition, the second marker 120 is captured at time t3 and the first marker 110 is captured at time t4; in the third image acquisition, the first marker 110 is captured at time t5 and the second marker 120 is captured at time t6; in the fourth image acquisition, the second marker 120 is captured at time t7 and the first marker 110 is captured at time t8, and so on.

[0109] By making the order of the first and second image acquisitions in the previous image acquisition different from the order of the first and second image acquisitions in the subsequent image acquisition, the first image in the subsequent image acquisition can be taken at the same position after the previous image acquisition is completed, thereby shortening the time interval between the two consecutive image acquisitions and improving detection efficiency. Furthermore, when unidirectional drift (X or Y direction) occurs along the horizontal direction, it is also beneficial to further reduce the impact of detection device jitter on the detection results of the alignment error of the first mark 110 and the second mark 120.

[0110] In other embodiments, the first and second image acquisitions are performed alternately during the multiple image acquisitions. That is, each image acquisition consists of a first image acquisition and a second image acquisition performed sequentially; or, each image acquisition consists of a second image acquisition and a first image acquisition performed sequentially.

[0111] For example: in the first image acquisition, the first marker is photographed at time t1 and the second marker is photographed at time t2; in the second image acquisition, the first marker is photographed at time t3 and the second marker is photographed at time t4; in the third image acquisition, the first marker is photographed at time t5 and the second marker is photographed at time t6; in the fourth image acquisition, the first marker is photographed at time t7 and the second marker is photographed at time t8, and so on.

[0112] It should be noted that the number of image acquisitions should not be too few or too many. If the number of image acquisitions is too few, the sample size will be insufficient. Consequently, when performing subsequent data statistics to obtain the alignment error of the first mark 110 and the second mark 120, the mutual compensation effect of errors caused by the vibration of the detection equipment will be poor, which is not conducive to improving the accuracy of alignment error detection. Since the accuracy of alignment error detection tends to converge with the increase of the number of image acquisitions, if the number of image acquisitions is too many, it will cause unnecessary waste of time and cost, which is not conducive to improving detection efficiency. Therefore, in this embodiment, the number of image acquisitions is 2 to 5.

[0113] In this embodiment, during the multiple image acquisitions, the time interval between the first and second image acquisitions performed at adjacent moments is less than the period of the low-frequency jitter between the image acquisition component and the motion platform; wherein, the low-frequency jitter refers to a jitter frequency of less than 100 Hz.

[0114] By making the time interval between the first and second image acquisitions performed at adjacent times shorter than the low-frequency jitter period, it is beneficial to ensure that the center position errors of the first mark 110 and the second mark 120 caused by the low-frequency jitter are the same. Therefore, the alignment error obtained by the deviation of the center positions of the first mark 110 and the second mark 120 can reduce the error caused by the low-frequency jitter.

[0115] It should be noted that in the multiple image acquisitions, the time interval between the first and second image acquisitions performed at adjacent moments is 50 to 100 milliseconds, which makes the time interval between the first and second image acquisitions performed at adjacent moments much smaller than the time period of the low-frequency jitter.

[0116] In the first and second image acquisitions performed at adjacent time points, the images need to be captured at different heights. Therefore, if the time interval is too short, it may exceed the limits of the detection equipment, potentially causing additional jitter and unnecessary errors. For example, after the image acquisition component and the object under test move relative to each other, a certain amount of time is needed for their relative positions to stabilize (this time is specifically the setpoint time). If the time interval is too short, the relative positions of the image acquisition component and the object under test may not have stabilized after the relative movement.

[0117] If the time interval between the first image acquisition and the second image acquisition is too long, it will easily increase the probability of errors introduced by low-frequency jitter.

[0118] Therefore, the time interval between the first and second image acquisitions performed at adjacent moments is 50 milliseconds to 100 milliseconds.

[0119] In this embodiment, the aforementioned processing module 20 is used as the first processing module. The detection system further includes a second processing module 30, which is used to perform median processing on the position of the first sub-image corresponding to each first image 210 to obtain the position of each first image 210, and is also used to perform median processing on the position of the second sub-image corresponding to each second image 220 to obtain the position of each second image 220.

[0120] In this embodiment, the position is the center position. That is, the center position of each first image 210 is obtained by performing median processing on the center position of the first sub-image corresponding to each first image 210, and the center position of each second image 220 is obtained by performing median processing on the center position of the second sub-image corresponding to each second image 220. In other embodiments, the position may also be a corner position or an intersection position.

[0121] As described above, both the first image acquisition and the second image acquisition will perform multi-frame image acquisition at the same time. The first image 210 includes multiple first sub-images (not shown), and the second image 220 includes multiple second sub-images (not shown). Therefore, by performing median processing on the position of the first sub-image corresponding to each first image 210 and on the position of the second sub-image corresponding to each second image 220, it is beneficial to reduce the error caused by high-frequency jitter and the error caused by noise, thereby improving the accuracy of the position of each first image 210 and the accuracy of the position of each second image 220.

[0122] In this embodiment, the median processing is performed by calculating the average value. By calculating the average value, the errors caused by high-frequency jitter and the errors caused by noise can be significantly reduced. In other embodiments, the median processing can also be performed by calculating the median value.

[0123] The aforementioned image acquisition module 10 performs multiple image acquisitions, increasing the sample size by acquiring first and second images at adjacent times. Since the first and second images are acquired at adjacent times, the processing module 20 (i.e., the first processing module) can statistically analyze the positions of the first mark 110 in multiple first images 210 and the positions of the second mark 120 in multiple second images 220. This helps to compensate for errors caused by detection device jitter, thereby reducing the impact of detection device jitter on the detection results of alignment errors of the first and second marks, and thus improving the accuracy of alignment error detection.

[0124] In this embodiment, the alignment error of the first mark 110 and the second mark 120 in the first direction and the alignment error of the first mark 110 and the second mark 120 in the second direction are obtained respectively, and the first direction and the second direction are perpendicular to each other.

[0125] Specifically, based on the same coordinate system, the position error Δx of the first mark 110 and the second mark 120, and the position error Δy in the second direction are obtained. For example, the coordinate system is an XY coordinate system, with the first direction parallel to the X-axis direction and the second direction parallel to the Y-axis direction.

[0126] In this embodiment, during the process of obtaining the alignment error of the first mark 110 and the second mark 120 using the positions of the first mark 110 in multiple first images 210 and the positions of the second mark 120 in multiple second images 220, the position is the center position. In other embodiments, the position can also be a corner position or an intersection position.

[0127] Accordingly, in this embodiment, the alignment error of the first mark 110 and the second mark 120 is obtained by using the center S1 position of the first mark 110 in multiple first images 210 and the center S2 position of the second mark 120 in multiple second images 220. Correspondingly, based on the same coordinate system, the positional error Δx of the center S1 of the first mark 110 and the center S2 of the second mark 120 in the first direction and the positional error Δy in the second direction are obtained.

[0128] As an example, the processing module 20 includes: a first processing unit, used to calculate the positional deviation of the first mark 110 and the second mark 120 as a sampling alignment error using the first image 210 and the second image 220 acquired at adjacent times or at a preset number of times intervals, to obtain an alignment error set containing multiple sampling alignment errors, wherein the preset number is less than or equal to 5; and a second processing unit, used to perform median processing on the multiple sampling alignment errors in the alignment error set to obtain the alignment error of the first mark 110 and the second mark 120.

[0129] It should be noted that the preset number is less than or equal to 5, so that the time interval between the first image 210 and the second image 220 acquired at preset intervals will not be too long. This is beneficial for the mutual compensation of errors caused by the shaking of the detection equipment, and correspondingly helps to reduce the impact of the shaking of the detection equipment on the detection results of the alignment error of the first mark 110 and the second mark 120.

[0130] For example: in the first image acquisition, the first marker 110 is captured at time t1 and the second marker 120 is captured at time t2; in the second image acquisition, the second marker 120 is captured at time t3 and the first marker 110 is captured at time t4; in the third image acquisition, the first marker 110 is captured at time t5 and the second marker 120 is captured at time t6; in the fourth image acquisition, the second marker 120 is captured at time t7 and the first marker 110 is captured at time t8, and so on.

[0131] Accordingly, taking the first image 210 and the second image 220 acquired at adjacent times as an example, the first processing unit uses the first image 210 acquired at time t1 and the second image 220 acquired at time t2 to calculate the positional deviation of the first mark 110 and the second mark 120 as the sampling alignment error, and obtains the first sampling alignment error.

[0132] Similarly, the first processing unit obtains a second sampling alignment error using the second image 220 captured at time t3 and the first image 210 captured at time t4; it obtains a third sampling alignment error using the first image 210 captured at time t5 and the second image 220 captured at time t6; it obtains a fourth sampling alignment error using the second image 220 captured at time t7 and the first image 210 captured at time t8, and so on.

[0133] Therefore, by using the first image 210 and the second image 220 acquired at adjacent times, multiple sampling alignment errors are obtained, and then the median of the multiple sampling alignment errors is processed to obtain the final alignment error.

[0134] In this embodiment, the median processing method is to calculate the average value. Averaging the sampling alignment errors obtained from the first image 210 and the second image 220 acquired at adjacent time points allows the errors caused by jitter (e.g., low-frequency jitter) generated by the detection device to compensate for each other, thereby reducing the error caused by the jitter of the detection device. In other embodiments, the median processing method may also be to calculate the median value or the maximum value.

[0135] It should be noted that each of the sampling alignment errors includes a sampling alignment error in the first direction and a sampling alignment error in the second direction. Accordingly, the sampling alignment errors in the first direction and the sampling alignment errors in the second direction are respectively processed by median value.

[0136] In other embodiments, when the first image acquisition and the second image acquisition are performed alternately during the multiple image acquisitions, the first image and the second image acquired at adjacent times can be randomly selected for data statistics.

[0137] For example, in the first image acquisition, the first marker is photographed at time t1 and the second marker is photographed at time t2; in the second image acquisition, the first marker is photographed at time t3 and the second marker is photographed at time t4; in the third image acquisition, the first marker is photographed at time t5 and the second marker is photographed at time t6; in the fourth image acquisition, the first marker is photographed at time t7 and the second marker is photographed at time t8, and so on. Correspondingly, when the first processing unit performs data statistics, it can also obtain a sampling alignment error based on the second image photographed at time t2 and the first image photographed at time t3, and obtain another sampling alignment error based on the second image photographed at time t4 and the first image photographed at time t5, and so on, thus obtaining multiple sampling alignment errors.

[0138] In other embodiments, the processing module includes: a first processing unit, configured to perform median processing on the positions of a plurality of first images to obtain the position of the first mark; a second processing unit, configured to perform median processing on the positions of a plurality of second images to obtain the position of the second mark, wherein the second images subjected to median processing correspond one-to-one with the first images subjected to median processing, and the first and second images satisfying the one-to-one correspondence are obtained in the same image acquisition step; and a third processing unit, configured to calculate the positional deviation between the first mark and the second mark to obtain the alignment error between the first mark and the second mark.

[0139] Performing median processing on the positions of the first image and the second image separately can help compensate for the errors caused by the shaking of the detection equipment, thus reducing the impact of the shaking of the detection equipment on the detection results of the alignment error of the first and second marks.

[0140] Specifically, the median processing method includes calculating the average or the median value.

[0141] This invention also provides a device that can implement the detection method provided in this invention by loading a program in the form of the above-described detection method.

[0142] refer to Figure 6 The diagram illustrates the hardware structure of a device according to an embodiment of the present invention. The device in this embodiment includes: at least one processor 01, at least one communication interface 02, at least one memory 03, and at least one communication bus 04.

[0143] In this embodiment, the number of processor 01, communication interface 02, memory 03 and communication bus 04 is at least one, and the processor 01, communication interface 02 and memory 03 communicate with each other through the communication bus 04.

[0144] The communication interface 02 can be an interface of a communication module used for network communication, such as the interface of a GSM module.

[0145] The processor 01 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the detection method described in this embodiment.

[0146] The memory 03 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0147] The memory 03 stores one or more computer instructions, which are executed by the processor 01 to implement the detection method provided in the foregoing embodiments.

[0148] It should be noted that the aforementioned terminal device may also include other devices (not shown) that may not be essential to understanding the content disclosed in the embodiments of the present invention; given that these other devices may not be essential for understanding the content disclosed in the embodiments of the present invention, the embodiments of the present invention will not describe them one by one.

[0149] This invention also provides a storage medium storing one or more computer instructions for implementing the detection method provided in the foregoing embodiments.

[0150] In the detection method provided by the embodiments of the present invention, the number of samples is increased by acquiring the first image and the second image at adjacent time points multiple times. Since the first image and the second image are acquired at adjacent time points, compared with the scheme of acquiring only one image, increasing the number of samples is beneficial to make the errors caused by the shaking of the detection equipment compensate for each other, that is, it is beneficial to reduce the impact of the shaking of the detection equipment on the detection results of the alignment error of the first mark and the second mark, thereby improving the detection accuracy of the alignment error.

[0151] The embodiments of the present invention described above are combinations of elements and features of the present invention. Unless otherwise stated, the elements or features described are optional. Individual elements or features may be practiced without combination with other elements or features. Furthermore, embodiments of the present invention may be constructed by combining some elements and / or features. The order of operations described in the embodiments of the present invention may be rearranged. Some constructions of any embodiment may be included in another embodiment and may be replaced by corresponding constructions of another embodiment. It will be apparent to those skilled in the art that claims in the appended claims that are not expressly referenced to each other may be combined to form embodiments of the present invention, or may be included as new claims in amendments made after the filing of this application.

[0152] Embodiments of the present invention can be implemented by various means, such as hardware, firmware, software, or combinations thereof. In a hardware configuration, the method according to an exemplary embodiment of the present invention can be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, etc.

[0153] In firmware or software configuration, embodiments of the present invention can be implemented in the form of modules, processes, functions, etc. Software code can be stored in a memory unit and executed by a processor. The memory unit is located inside or outside the processor and can send data to and receive data from the processor via various known means.

[0154] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is accorded the widest scope consistent with the principles and novel features disclosed herein.

[0155] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. A detection method, characterized in that, The detection method is used to detect overprinted marks on a test object, the overprinted marks including a first mark and a second mark, and the detection method includes: Multiple image acquisitions are performed sequentially. Each image acquisition consists of a first image acquisition and a second image acquisition performed at adjacent time points. The first image acquisition includes acquiring a first image containing the first marker, and the second image acquisition includes acquiring a second image containing the second marker. The time interval between the first image acquisition and the second image acquisition performed at adjacent time points is less than the period of the low-frequency jitter between the image acquisition component and the motion platform. The alignment error between the first mark and the second mark is obtained by using the positions of the first mark in multiple first images and the positions of the second mark in multiple second images.

2. The detection method as described in claim 1, characterized in that, The alignment error between the first mark and the second mark is obtained by using the positions of the first mark in multiple first images and the positions of the second mark in multiple second images, including: The alignment error of the first mark and the second mark in the first direction and the alignment error of the first mark and the second mark in the second direction are obtained respectively, wherein the first direction and the second direction are perpendicular to each other.

3. The detection method as described in claim 1, characterized in that, During the multiple image acquisition processes, the first image acquisition and the second image acquisition are performed alternately. or, In two consecutive image acquisitions, the order of the first and second image acquisitions in the first acquisition is different from the order of the first and second image acquisitions in the second acquisition.

4. The detection method as described in claim 1, characterized in that, The alignment error between the first mark and the second mark is obtained by using the positions of the first mark in multiple first images and the positions of the second mark in multiple second images, including: Using a first image and a second image acquired at adjacent times or at a preset number of times, the positional deviation between the first mark and the second mark is calculated as a sampling alignment error to obtain an alignment error set containing multiple sampling alignment errors, wherein the preset number is less than or equal to 5. The median value of multiple sampled alignment errors in the alignment error set is processed to obtain the alignment errors of the first mark and the second mark.

5. The detection method as described in claim 1, characterized in that, The alignment error between the first mark and the second mark is obtained by using the positions of the first mark in multiple first images and the positions of the second mark in multiple second images, including: The position of the first marker is obtained by performing median processing on the positions of multiple first images; Median processing is performed on the positions of multiple second images to obtain the positions of the second markers. The second images that have undergone median processing correspond one-to-one with the first images that have undergone median processing, and the first and second images that satisfy the one-to-one correspondence are obtained in the same image acquisition step. After performing median processing on the positions of multiple first images and multiple second images, the positional deviation between the first mark and the second mark is calculated to obtain the alignment error between the first mark and the second mark.

6. The detection method as described in claim 1, characterized in that, The first image acquisition includes: acquiring multiple frames of images at the same time, wherein the first image includes multiple first sub-images; The second image acquisition includes: acquiring multiple frames of images at the same time, wherein the second image includes multiple second sub-images; before obtaining the alignment error of the first mark and the second mark using the positions of the first mark in the multiple first images and the positions of the second mark in the multiple second images, the acquisition further includes: performing median processing on the position of the first sub-image corresponding to each first image to obtain the position of each first image; and performing median processing on the position of the second sub-image corresponding to each second image to obtain the position of each second image.

7. The detection method as described in claim 6, characterized in that, During the simultaneous acquisition of multiple frames of images, the time interval between acquisitions of adjacent first sub-images is less than 15 milliseconds; During the acquisition of multiple frames of images at the same time, the acquisition time interval between adjacent second sub-images is less than 15 milliseconds.

8. The detection method as described in claim 6, characterized in that, In each of the first image acquisitions, the number of the first sub-images is 2 to 10, and in each of the second image acquisitions, the number of the second sub-images is 2 to 10.

9. The detection method according to any one of claims 4 to 6, characterized in that, The median processing methods include calculating the average or the median.

10. The detection method as described in claim 1, characterized in that, The detection method is performed using a detection device, which includes an image acquisition component for acquiring images of the overlay marks. A motion platform is used to move the image acquisition component and the object under test relative to each other. In the multiple image acquisitions, the time interval between the first and second image acquisitions performed at adjacent moments is less than the period of the low-frequency jitter between the image acquisition component and the motion platform. The low-frequency jitter refers to a jitter frequency of less than 100 Hz.

11. The detection method as described in claim 1 or 10, characterized in that, In the multiple image acquisitions, the time interval between the first and second image acquisitions performed at adjacent moments is 50 milliseconds to 100 milliseconds.

12. The detection method as described in claim 1, characterized in that, The number of image acquisitions is 2 to 5.

13. The detection method as described in claim 1 or 5, characterized in that, The location includes the center location, corner location, or intersection location.

14. The detection method as described in claim 1, characterized in that, The overprinted marks are located on the object to be tested. The first mark and the second mark are located at different height positions on the object to be tested, or the first mark and the second mark are formed in different processes.

15. A detection system, characterized in that, The detection system is used to detect overlay marks on the object to be tested, the overlay marks including a first mark and a second mark, and the detection system includes: The image acquisition module is used to perform multiple image acquisitions sequentially. Each image acquisition consists of a first image acquisition and a second image acquisition performed at adjacent time points. The first image acquisition includes acquiring a first image containing the first mark, and the second image acquisition includes acquiring a second image containing the second mark. The time interval between the first image acquisition and the second image acquisition performed at adjacent time points is less than the period of the low-frequency jitter between the image acquisition component and the motion platform. The processing module is used to obtain the alignment error of the first mark and the second mark by using the position of the first mark in multiple first images and the position of the second mark in multiple second images.

16. A device, characterized in that, It includes at least one memory and at least one processor, the memory storing one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the detection method as described in any one of claims 1 to 14.

17. A storage medium, characterized in that, The storage medium stores one or more computer instructions, which are used to implement the detection method as described in any one of claims 1 to 14.

Images