Mask Template Detection Method, Device, Equipment and Storage Medium

Abstract

The present application discloses a method, apparatus, device, and storage medium for mask detection. The present application relates to the field of semiconductor manufacturing technology. The mask detection method includes: dividing a detection area of the mask according to a preset area division strategy to obtain a mask detection energy distribution map; determining a detection mode of a detection device according to the mask detection energy distribution map, and detecting the mask according to the detection mode. The present application can improve the accuracy and efficiency of mask detection.

Description

Technical Field

[0001] This application relates to the field of semiconductor manufacturing technology, and in particular, to a method, device, equipment, and storage medium for mask inspection. Background Art

[0002] To ensure the quality and accuracy of masks, lasers are usually used for mask inspection. By using the method of imaging with a transmission light source, the actual image on the mask is photographed through a certain optical path and imaging equipment and then compared with the designed mask pattern. The area where the two do not match is the defective area of the mask.

[0003] In the existing mask inspection process, lasers with the same energy are usually used to inspect the entire mask. The inspection mode is fixed and inflexible, which cannot ensure the balanced detection of different defects and is prone to missing defects. If different inspection modes are used for the mask on different machines, the inspection workload is increased and the production efficiency is reduced.

[0004] Therefore, how to improve the accuracy and efficiency of mask inspection is an urgent problem to be solved at present. Summary of the Invention

[0005] The main purpose of this application is to provide a method, device, equipment, and storage medium for mask inspection, aiming to solve the technical problem of how to improve the accuracy and efficiency of mask inspection.

[0006] To achieve the above object, this application provides a method for mask inspection, and the method for mask inspection includes:

[0007] Dividing the inspection area of the mask according to a preset area division strategy to obtain a mask inspection energy distribution map;

[0008] Determining the inspection mode of the inspection device according to the mask inspection energy distribution map, and inspecting the mask according to the inspection mode.

[0009] In an embodiment, the step of dividing the inspection area of the mask according to a preset area division strategy to obtain a mask inspection energy distribution map includes:

[0010] Performing grayscale value detection on the mask to obtain the mask grayscale value;

[0011] Dividing the inspection area of the mask according to the mask grayscale value and a preset grayscale threshold to obtain a plurality of inspection energy regions;

[0012] Obtaining the mask inspection energy distribution map according to the plurality of inspection energy regions.

[0013] In one embodiment, the detection energy region includes a standard region, and the step of dividing the detection region of the mask according to the mask gray value and a preset gray threshold includes:

[0014] Determine the numerical size relationship between the mask gray value and the gray threshold;

[0015] If the mask gray value is equal to the gray threshold, then divide the region corresponding to the mask gray value into the standard region.

[0016] In one embodiment, the detection energy region includes a low-energy region and a high-energy region, and the step of dividing the detection region of the mask according to the mask gray value and a preset gray threshold includes:

[0017] Determine the numerical size relationship between the mask gray value and the gray threshold;

[0018] If the mask gray value is not equal to the gray threshold, then determine whether the mask gray value belongs to the numerical range formed by the gray threshold and the gray error range;

[0019] If the mask gray value belongs to the numerical range formed by the gray threshold and the gray error range, then divide the region corresponding to the mask gray value into the low-energy region;

[0020] If the mask gray value does not belong to the numerical range formed by the gray threshold and the gray error range, then divide the region corresponding to the mask gray value into the high-energy region.

[0021] In one embodiment, the detection device parameter includes the energy rise and fall time of the detection device, and the step of obtaining the mask detection energy distribution map according to the multiple detection energy regions includes:

[0022] Determine whether adjacent detection energy regions on the mask are the same;

[0023] If the adjacent detection energy regions are not the same, then determine a buffer area according to the energy rise and fall time of the detection device and the adjacent detection energy regions;

[0024] Obtain the mask detection energy distribution map according to the standard region, the low-energy region, the high-energy region and the buffer area.

[0025] In one embodiment, the step of determining the detection mode of the detection device according to the mask detection energy distribution map includes:

[0026] When the detection energy region of the mask detection energy distribution map is the standard region, determine the detection mode as the standard detection mode;

[0027] When the detection energy region of the reticle detection energy distribution map is the low - energy region, determine that the detection mode is the low - energy detection mode;

[0028] When the detection energy region of the reticle detection energy distribution map is the high - energy region, determine that the detection mode is the high - energy detection mode.

[0029] In one embodiment, the step of determining the detection mode of the detection device according to the reticle detection energy distribution map includes:

[0030] When the detection energy region of the reticle detection energy distribution map is the buffer region, perform strip division of the detection region on the adjacent detection energy regions to obtain a plurality of detection strip regions;

[0031] Determine the width threshold for detection mode switching according to the detection device moving speed of the detection device parameters;

[0032] Compare the width of the detection strip region with the width threshold. If the width of the detection strip region is less than the width threshold, maintain the current detection mode.

[0033] In addition, to achieve the above - mentioned purpose, the present application also provides a reticle detection device, and the reticle detection device includes:

[0034] A region division module, configured to perform detection region division on the reticle according to a preset region division strategy to obtain a reticle detection energy distribution map;

[0035] A detection module, configured to determine the detection mode of the detection device according to the reticle detection energy distribution map and perform detection on the reticle according to the detection mode.

[0036] In addition, to achieve the above - mentioned purpose, the present application also proposes a reticle detection device, and the device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the reticle detection method as described above.

[0037] In addition, to achieve the above - mentioned purpose, the present application also provides a storage medium, the storage medium is a computer - readable storage medium, and a program for implementing the reticle detection method is stored on the computer - readable storage medium, and the program for implementing the reticle detection method is executed by a processor to implement the steps of the reticle detection method as described above.

[0038] The present application provides a mask detection method. By dividing the detection energy region of the mask, a mask detection energy distribution map is generated. Based on the energy distribution map, the detection mode is automatically determined, and different detection strategies are adopted for different regions on the mask, improving the accuracy and efficiency of mask detection.

[0039] In summary, by determining the detection mode according to the energy distribution map, the present application can ensure that the detection device adapts to the detection requirements of different energy level regions on the mask, ensuring that the detection process is more accurate and reliable, reducing the possibility of false detection and missed detection, overcoming the problem that the mask detection mode is inflexible and easy to cause missed detection defects, and improving the accuracy and efficiency of mask detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings herein are incorporated into the specification and form a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application.

[0041] To more clearly illustrate the technical solutions in the embodiments of the present application or in the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0042] Figure 1 It is a schematic flowchart provided for Embodiment 1 of the mask detection method of the present application;

[0043] Figure 2 It is a detection effect diagram for detecting the entire mask with a laser of the same energy;

[0044] Figure 3 It is a detection effect diagram for detecting the entire mask with a laser of the same energy;

[0045] Figure 4 It is a physical diagram of the mask and a mask detection energy distribution map for the mask detection method of the present application;

[0046] Figure 5 It is a detection effect diagram for detecting different regions of the mask with lasers of different energies for the mask detection method of the present application;

[0047] Figure 6 It is a detection effect diagram for detecting different regions of the mask with lasers of different energies for the mask detection method of the present application;

[0048] Figure 7 It is a buffer detection schematic diagram for the mask detection method of the present application;

[0049] Figure 8Schematic diagram of buffer strip division for the mask inspection method of this application;

[0050] Figure 9 Schematic diagram of the module structure of the mask inspection device according to an embodiment of this application;

[0051] Figure 10 Schematic diagram of the device structure of the hardware operating environment involved in the mask inspection method according to an embodiment of this application.

[0052] The realization of the purpose, functional characteristics and advantages of this application will be further described with reference to the accompanying drawings in combination with the embodiments. Detailed implementation manners

[0053] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of this application and are not used to limit this application.

[0054] In order to better understand the technical solutions of this application, the following will be described in detail in combination with the accompanying drawings of the specification and specific implementation manners.

[0055] The main solution of this application is: dividing the detection area of the mask according to a preset area division strategy to obtain the mask inspection energy distribution map; determining the detection mode of the detection device according to the mask inspection energy distribution map, and detecting the mask according to the detection mode.

[0056] In the existing mask inspection process, lasers with the same energy are usually used to inspect the entire mask. However, when the same laser energy faces patterns of different shapes and sizes on the mask, the inspection effects shown are completely inconsistent. For example, when inspecting small holes or slits on the mask, if the laser energy is too low, the actual image of the mask captured will be blurred, forming semi-transparent pinholes. For the possible semi-transparent pinholes, it is necessary to perform transmission light imaging and comparison with the standard image through the DB mode (DieBase, each pattern on the mask is a Die, and the inspection mode based on each pattern), and then perform comparison between the transmission light image and the reflection light image through the SL mode (Starlight, starlight inspection mode) to detect the defects in the semi-transparent pinhole area. If different machines are used to perform different mode inspections on the mask, the inspection workload is increased and the production efficiency is reduced. Therefore, how to improve the accuracy and efficiency of mask inspection is an urgent problem to be solved at present.

[0057] By adjusting the detection mode according to the energy distribution map in this application, it can ensure that the detection device adapts to the detection requirements of different energy level areas on the mask, ensure that the detection process is more accurate and reliable, reduce the possibility of false detection and missed detection, overcome the problem that the mask detection mode is fixed and inflexible, which easily leads to missed detection of defects, and improve the accuracy and efficiency of mask inspection.

[0058] It should be noted that the execution entity of this embodiment can be a mask inspection system, or a computing service device with data processing, network communication, and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or a mask inspection device capable of implementing the above functions. This embodiment does not make specific limitations in this regard. Taking the mask inspection system as the execution entity as an example, this embodiment and the following embodiments will be described.

[0059] Based on this, the present application proposes a mask inspection method for the first embodiment. Please refer to Figure 1 , and the mask inspection method includes steps S10 to S20:

[0060] Step S10, divide the detection area of the mask according to a preset area division strategy to obtain a mask detection energy distribution map;

[0061] It should be noted that the defects that are likely to exist in the graphic area of the mask include black defects and white defects. A black defect means that there is an extra metal residue layer in the area where there should be only the glass substrate, which will cause the risk of product wire breakage; a white defect means that only the glass substrate remains in the graphic area and the surface metal layer is missing. Using a mask with white defects for production will cause component short circuits. In order to balance the detection of black and white defects in the graphic area, the laser used for detection cannot have too high energy. Too high laser energy will cause serious optical diffraction, affecting the imaging effect of the graphic edge. Small black defects in the white area may also not be captured by the camera due to excessive optical diffraction. Similarly, too low laser energy cannot be used, which will cause blurred edges at the black and white junction and missed detection of white defects. Refer to Figure 2 and Figure 3 , which are the detection effect diagrams of using the same energy laser to detect the entire mask. If the detection energy is not adjusted for the corresponding area, it is difficult to detect this corresponding type of defect.

[0062] Therefore, it is necessary to divide the detection area of the mask. The detection area division involves steps such as gray-scale scanning, image processing, and analysis of the mask to identify the areas on the mask that require different detection energy levels and generate a mask detection energy distribution map. Refer to Figure 4 , according to the mask detection energy distribution map, different detection strategies can be adopted for different areas in the follow-up, so as to improve the accuracy and reliability of detection.

[0063] Step S20, determine the detection mode of the detection device according to the mask detection energy distribution map, and detect the mask according to the detection mode.

[0064] It should be noted that according to factors such as the required detection energy level, area size, and area position in different regions of the energy distribution map, the detection mode corresponding to the region is determined. The detection mode includes parameters such as the detection speed, detection accuracy, and detection light source energy suitable for the current detection region, and the reticle is detected according to the determined detection mode. Refer to Figure 5 and Figure 6 , which are the detection effect diagrams for detecting the reticle with lasers of different energies in different regions of the reticle.

[0065] This embodiment provides a method for detecting a reticle. In this embodiment, first, the detection energy regions of the reticle are divided to generate a detection energy distribution map of the reticle. Based on the energy distribution map, the detection mode is automatically determined, and different detection strategies are adopted for different regions on the reticle, improving the accuracy and efficiency of reticle detection.

[0066] In summary, it can be seen that by determining the detection mode according to the energy distribution map in this application, it can ensure that the detection device adapts to the detection requirements of different energy level regions on the reticle, ensure that the detection process is more accurate and reliable, reduce the possibility of false detection and missed detection, overcome the problem that the reticle detection mode is fixed and inflexible, which is likely to cause missed detection defects, and improve the accuracy and efficiency of reticle detection.

[0067] In a feasible implementation manner, step S10 may include steps S101 to S103:

[0068] Step S101, perform a grayscale value detection on the reticle to obtain the grayscale value of the reticle;

[0069] Step S102, divide the detection regions of the reticle according to the grayscale value of the reticle and a preset grayscale threshold to obtain multiple detection energy regions;

[0070] Step S103, obtain the detection energy distribution map of the reticle according to the multiple detection energy regions.

[0071] It should be noted that an image acquisition device (such as a camera) is used to take pictures or scan the reticle to obtain its image data. For each pixel point in the grayscale image data, its grayscale value is calculated. Since there are fully transparent or fully opaque areas on the reticle, and the image line seam sizes of each reticle are different, energy calibration needs to be performed for each reticle to obtain a preset grayscale threshold. Since the determination of the defective area of the reticle is obtained by comparing the actual image of the reticle formed by the transmitted light source with the designed reticle pattern, the preset grayscale threshold can also be set according to the designed reticle pattern. Each pixel point on the reticle is traversed, and according to the comparison between its grayscale value and the preset grayscale threshold, each pixel point is divided into the corresponding energy area. The energy area can include a standard area, a low-energy area, a high-energy area, and a buffer area, and different energy areas can be set according to actual detection requirements. The information of multiple energy areas is sorted out, including information such as the grayscale value range, position, and size of each area, so as to detect different areas separately in subsequent steps.

[0072] In this embodiment, by detecting the grayscale value, the light transmittance of the reticle is converted into specific numerical values, making the quality evaluation of the reticle more quantitative and accurate. By setting the grayscale threshold, the reticle can be divided into multiple areas with different energy characteristics, so as to adopt different detection strategies for different energy areas, improving the detection accuracy and efficiency.

[0073] In a feasible embodiment, step S102 may include steps S1021 to S1022:

[0074] Step S1021, determining the numerical size relationship between the grayscale value of the reticle and the grayscale threshold;

[0075] Step S1022, if the grayscale value of the reticle is equal to the grayscale threshold, then the area corresponding to the grayscale value of the reticle is divided into the standard area.

[0076] It should be noted that referring to Figure 4 , the standard area is the area covered by the main pattern of the reticle. The preset grayscale threshold is set according to the designed reticle pattern. If the grayscale value of the white area in the design drawing is defined as a fixed value K, at this time, the average grayscale value of the white area in the standard pattern area of the actual image of the reticle obtained by imaging with the transmitted light source is adjusted to be exactly the same as the fixed value K, and the corresponding area is divided into the standard area.

[0077] In this embodiment, by comparing the grayscale value of the reticle with the preset grayscale threshold, different areas on the reticle can be accurately classified according to the size of their grayscale values. For the areas divided into the standard area, corresponding detection strategies are adopted for the standard area subsequently, improving the detection accuracy and efficiency.

[0078] In a feasible implementation, step S102 may include steps S1023 to S1026:

[0079] Step S1023, determine the numerical magnitude relationship between the gray value of the mask and the gray threshold;

[0080] Step S1024, if the gray value of the mask is not equal to the gray threshold, then determine whether the gray value of the mask belongs to the numerical range formed by the gray threshold and the gray error range;

[0081] Step S1025, if the gray value of the mask belongs to the numerical range formed by the gray threshold and the gray error range, then divide the area corresponding to the gray value of the mask into a low-energy area;

[0082] Step S1026, if the gray value of the mask does not belong to the numerical range formed by the gray threshold and the gray error range, then divide the area corresponding to the gray value of the mask into a high-energy area.

[0083] It should be noted that, referring to Figure 4 , lower energy and lower exposure are used in the fully transparent area to ensure the detection of black defects. This area is initially calibrated according to different sheet thicknesses and materials and will not be changed after calibration. The low-energy area is the ideal fully transparent area, and the energy is lower than that of the standard area, but it cannot be too low, otherwise the camera will not be able to receive images with high contrast and naturally cannot determine the defects. For example, when the gray value of the white area of the design drawing is defined as a fixed value K, the safe gray value range of the white area is K±G (G is the maximum gray difference caused by uneven light source in the standard graphic area, that is, the gray error range, which can be set according to the actual situation), the area corresponding to the gray value of the mask within the numerical range of K±G is divided into the low-energy area, and the area corresponding to the gray value of the mask outside the numerical range of K±G is divided into the high-energy area.

[0084] In this implementation, by dividing the area with gray values within the threshold and error range into the low-energy area, and dividing the area with gray values outside the threshold and error range into the high-energy area, corresponding detection strategies are adopted for the low-energy area and the high-energy area subsequently, improving the detection accuracy and efficiency.

[0085] In a feasible implementation, step S1031 may include steps S1031 to S1033:

[0086] Step S1031, determine whether the adjacent detection energy areas on the mask are the same;

[0087] Step S1032, if the adjacent detection energy areas are not the same, then determine the buffer area according to the energy rise and fall time of the detection device and the adjacent detection energy areas;

[0088] Step S1033: Obtain the detection energy distribution map of the mask template according to the standard region, the low-energy region, the high-energy region, and the buffer region.

[0089] It should be noted that, referring to Figure 4 , it is impossible to instantaneously adjust the detection energy when switching from the standard region, the low-energy region, or the high-energy region to another mode. Usually, the movement of the detection control platform cannot be directly paused due to the need to adjust the detection energy mode, resulting in the suspension of the detection process and thus reducing the overall detection efficiency. Therefore, a buffer region needs to be set in the transition area between each mode. According to the standard region, the low-energy region, and the high-energy region obtained in the above steps S1021 to S1026, determine whether adjacent regions are the same. When adjacent regions are different, determine the relevant region as the buffer region. The energy rise and fall time of the detection device is related to the energy switching speed of the laser and the movement speed of the mask template carrying platform. The detection device requires a certain amount of time during the process of adjusting the energy rise and fall for different detection energy regions. Therefore, the size of the buffer region needs to be set according to the energy rise and fall time of the detection device. Referring to Figure 7 , reasonably allocate the size of the buffer region according to the platform movement speed and the energy switching speed. For example, when switching from the low-energy region to the high-energy region, keep the energy in the standard mode when the detection lens moves to the region junction. At this time, the buffer region is the largest. When transitioning from the high-energy region to the standard region, the buffer region is halved compared to this situation.

[0090] In this embodiment, by setting the buffer region, the influence of detection defects caused by sudden changes in detection energy requirements can be reduced. The standard region, the low-energy region, the high-energy region, and the buffer region can more accurately reflect the detection energy corresponding to different regions on the mask template, which helps to improve the accuracy and efficiency of subsequent detections.

[0091] In a feasible embodiment, step S20 may include steps S201 to S203:

[0092] Step S201: When the detection energy region of the mask template detection energy distribution map is the standard region, determine the detection mode as the standard detection mode;

[0093] Step S202: When the detection energy region of the mask template detection energy distribution map is the low-energy region, determine the detection mode as the low-energy detection mode;

[0094] Step S203: When the detection energy region of the mask template detection energy distribution map is the high-energy region, determine the detection mode as the high-energy detection mode.

[0095] It should be noted that the standard area, i.e., the area covered by the main image of the mask, has no completely transparent or completely opaque areas. The image line seam sizes of each plate are different. Therefore, energy calibration needs to be performed for the main image of each mask. Neither too high energy should be used, which may cause overexposure at the edge and affect the detection of black defects, nor too low energy should be used, which may affect the detection of white defects. The detection energy in the standard detection mode needs to find an energy that takes into account the detection rates of both types of defects through energy calibration. The detection energy for the standard area is calibrated according to the different plate thicknesses and materials of the mask and will not be changed after calibration.

[0096] The low-energy area is an ideal completely transparent area. The detection energy setting in the low-energy detection mode should be lower than the detection energy in the standard area, but it should not be too low, otherwise the camera will not be able to receive images with high contrast and cannot judge the defects.

[0097] The high-energy area is a completely opaque area. In the high-energy detection mode, relatively high energy can be used for detection. There is no need to consider image overexposure. It is only necessary to ensure that the camera can obtain sufficient light brightness transmitted through the pinhole defects at a relatively high energy. When detecting in this area, there is no need to consider false defects caused by too large deviation of gray values. The detection energy setting should use relatively high energy as much as possible under the condition of ensuring the safe use of the detection equipment and the service life of the light source of the detection equipment.

[0098] In addition, corresponding detection speed settings can be made for different detection modes. When setting the detection speed, factors such as the field of view width of the line array camera for image acquisition, the matching of the moving speed of the mask carrying platform and the image acquisition speed of the camera, and the time required for the laser energy to rise and fall need to be considered. The detection speeds in different detection energy areas can be the same or can be set separately according to actual detection requirements.

[0099] In this embodiment, by determining the detection mode of the detection equipment according to different areas of the energy distribution map of the mask, the refinement of the detection process is realized, the problem that the detection mode of the mask is fixed and inflexible, which is easy to cause missed detection of defects, is overcome, and the detection accuracy and efficiency are improved.

[0100] In a feasible embodiment, step S20 may include steps S204 to S206:

[0101] Step S204, when the detection energy area of the energy distribution map of the mask detection energy is the buffer area, perform strip division of the detection area for the adjacent detection energy areas to obtain a plurality of detection strip areas;

[0102] Step S205, determine the width threshold for detection mode switching according to the moving speed of the detection equipment in the detection equipment parameters;

[0103] Step S206: Compare the width of the detected strip area with the width threshold. If the width of the detected strip area is less than the width threshold, maintain the current detection mode.

[0104] It should be noted that with reference to Figure 8 , the different detected energy areas in the buffer are divided into strips, and the junctions between the strips are all allocated to the junctions of different areas. The high-energy detection mode is used in the high-energy area (black area), the low-energy detection mode is used in the low-energy area (white area), and the standard detection mode is used in the standard area (the standard area of the main pattern of the mask). With reference to Figure 7 , the moving speed of the detection device determines the width threshold for switching the detection mode based on the moving speed of the detection laser and the moving speed of the mask carrier platform. When the width of the detected strip area is less than the width threshold, the current detection mode is maintained. For example, when there is a part of the high-energy area or low-energy area between two standard areas, if the width of the detected strip area divided by the high-energy area or low-energy area at this time is less than the width threshold, the detection mode is not switched, and the standard mode is maintained to detect the high-energy area or low-energy area existing in this standard interval. In addition, when the width of the detected strip area is less than the width threshold, if it is necessary to improve the detection accuracy, the mask carrier moving platform can also be stopped before switching the detection mode, and then the detection modes of the corresponding areas are used for detection.

[0105] In this embodiment, when the energy area of the mask energy distribution map is the buffer area, by dividing the adjacent energy areas into strips, the system can perform more refined detection on the energy characteristics of each small area, which helps to improve the accuracy of detection. Since the energy characteristics of each strip area are relatively single, the appropriate detection parameters can be determined faster, and the efficiency of mode detection can be improved. By comparing the width of the detected strip area with the width threshold, it is possible to automatically determine whether to adjust the detection mode of the detection device, and more accurately detect the different detection energy areas in the buffer area, which helps to improve the accuracy and efficiency of mask detection.

[0106] This application embodiment also provides a mask detection device. Please refer to Figure 9 , the mask detection device includes:

[0107] An area division module 10 for dividing the detection area of the mask according to a preset area division strategy to obtain a mask detection energy distribution map;

[0108] A detection module 20 for determining the detection mode of the detection device according to the mask detection energy distribution map and detecting the mask according to the detection mode.

[0109] Optionally, the area division module 10 further includes:

[0110] Detect the gray value of the mask to obtain the mask gray value;

[0111] Divide the detection area of the mask according to the mask gray value and a preset gray threshold to obtain multiple detection energy regions;

[0112] Obtain the mask detection energy distribution map according to the multiple detection energy regions.

[0113] Optionally, the area division module 10 further includes:

[0114] Judge the numerical size relationship between the mask gray value and the gray threshold;

[0115] If the mask gray value is equal to the gray threshold, divide the area corresponding to the mask gray value into a standard area.

[0116] Optionally, the area division module 10 further includes:

[0117] Judge the numerical size relationship between the mask gray value and the gray threshold;

[0118] If the mask gray value is not equal to the gray threshold, judge whether the mask gray value belongs to the numerical range formed by the gray threshold and the gray error range;

[0119] If the mask gray value belongs to the numerical range formed by the gray threshold and the gray error range, divide the area corresponding to the mask gray value into a low-energy area;

[0120] If the mask gray value does not belong to the numerical range formed by the gray threshold and the gray error range, divide the area corresponding to the mask gray value into a high-energy area.

[0121] Optionally, the area division module 10 further includes:

[0122] Judge whether adjacent detection energy regions on the mask are the same;

[0123] If the adjacent detection energy regions are not the same, determine a buffer area according to the energy rise and fall time of the detection device and the adjacent detection energy regions;

[0124] Obtain the mask detection energy distribution map according to the standard area, the low-energy area, the high-energy area and the buffer area.

[0125] Optionally, the detection module 20 further includes:

[0126] When the detection energy region of the mask detection energy distribution map is a standard area, determine the detection mode as the standard detection mode;

[0127] When the detection energy region of the mask detection energy distribution map is a low-energy region, determine that the detection mode is a low-energy detection mode;

[0128] When the detection energy region of the mask detection energy distribution map is a high-energy region, determine that the detection mode is a high-energy detection mode.

[0129] Optionally, the detection module 20 further includes:

[0130] When the detection energy region of the mask detection energy distribution map is a buffer zone, perform strip division on the detection regions of the adjacent detection energy regions to obtain a plurality of detection strip regions;

[0131] Determine the width threshold for detection mode switching according to the detection device moving speed of the detection device parameters;

[0132] Compare the width of the detection strip region with the width threshold. If the width of the detection strip region is less than the width threshold, maintain the current detection mode.

[0133] The mask detection device provided by the embodiment of the present application adopts the mask detection method in the above embodiment, and can solve the problem of how to improve the accuracy and efficiency of mask detection. Compared with the prior art, the beneficial effects of the mask detection device provided by the embodiment of the present application are the same as those of the mask detection method provided by the above embodiment, and other technical features in the mask detection device are the same as those disclosed in the method of the above embodiment, and will not be elaborated here.

[0134] The present application provides a mask detection device, and the mask detection device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the mask detection method in the first embodiment above.

[0135] Next, refer to Figure 10 , which shows a schematic structural diagram of a mask detection device suitable for implementing the embodiment of the present application. The mask detection device in the embodiment of the present application may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions: tablet computers), PMPs (Portable Media Players), in-vehicle terminals (such as in-vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc.Figure 10 The shown reticle inspection device is merely an example and should not impose any limitations on the functions and scope of use of the embodiments of the present application.

[0136] As Figure 10 shown, the reticle inspection device may include a processing device 1001 (such as a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM: Random Access Memory) 1004. In the RAM 1004, various programs and data required for the operation of the reticle inspection device are also stored. The processing device 1001, the ROM 1002, and the RAM 1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems may be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the reticle inspection device to communicate with other devices wirelessly or wiredly to exchange data. Although the figure shows a reticle inspection device having various systems, it should be understood that it is not required to implement or have all the shown systems. More or fewer systems may be alternatively implemented or had.

[0137] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for performing the methods shown in the flowcharts. In such an embodiment, the computer program can be downloaded and installed from a network through the communication device, or installed from the storage device 1003, or installed from the ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the methods of the embodiments disclosed in the present application are executed.

[0138] The mask inspection device provided by this application adopts the mask inspection method in the above-mentioned embodiment and can solve the technical problems of mask inspection. Compared with the prior art, the beneficial effects of the mask inspection device provided by this application are the same as those of the mask inspection method provided by the above-mentioned embodiment, and other technical features in this mask inspection device are the same as those disclosed in the method of the previous embodiment, which will not be elaborated here.

[0139] It should be understood that each part disclosed in this application can be implemented by hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in a suitable manner in any one or more embodiments or examples.

[0140] As mentioned above, it is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art within the technical scope disclosed in this application can easily think of changes or substitutions, which should all be covered within the protection scope of this application. Therefore, the protection scope of this application should be subject to the protection scope of the claims.

[0141] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., computer programs) stored thereon, and the computer-readable program instructions are used to execute the mask inspection method in the above-mentioned embodiment.

[0142] The computer-readable storage medium provided by this application can be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this embodiment, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or combined with an instruction execution system, device, or device. The program code contained on the computer-readable storage medium can be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0143] The above computer-readable storage medium may be included in a reticle inspection device, or may exist independently without being assembled into the reticle inspection device.

[0144] The above computer-readable storage medium stores one or more programs which, when executed by the reticle inspection device, cause the reticle inspection device to: obtain inspection device parameters; perform division of inspection energy regions on a reticle to obtain a reticle inspection energy distribution map; adjust a detection mode of the inspection device parameters according to the reticle inspection energy distribution map, and perform inspection on the reticle according to the detection mode.

[0145] Computer program code for performing the operations of the present application may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, execute as a stand-alone software package, execute partly on the user's computer and partly on a remote computer, or execute entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., by connecting through an Internet service provider using the Internet).

[0146] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0147] The modules involved in the embodiments of the present application can be implemented in software or in hardware. Among them, the name of the module does not constitute a limitation on the unit itself in some cases.

[0148] The readable storage medium provided by the present application is a computer-readable storage medium, and the computer-readable storage medium stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned mask detection method, which can solve the technical problem of how to improve the accuracy and efficiency of mask detection. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided by the present application are the same as those of the mask detection method provided by the above embodiments, and will not be elaborated here.

[0149] The above are only the preferred embodiments of the present application, and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be included in the patent scope of the present application by the same token.

Claims

1. A mask detection method, characterized in that, The mask detection method includes: Dividing the detection area of the mask according to a preset area division strategy to obtain a mask detection energy distribution map, specifically including: Detecting the gray value of the mask to obtain the mask gray value; Dividing the detection area of the mask according to the mask gray value and a preset gray threshold to obtain a plurality of detection energy areas; Obtaining the mask detection energy distribution map according to the plurality of detection energy areas; The detection energy areas include a standard area, a low-energy area, and a high-energy area. The step of dividing the detection area of the mask according to the mask gray value and a preset gray threshold includes: Judging the numerical size relationship between the mask gray value and the gray threshold; If the mask gray value is equal to the gray threshold, dividing the area corresponding to the mask gray value into the standard area; If the mask gray value is not equal to the gray threshold, judging whether the mask gray value belongs to the numerical range formed by the gray threshold and the gray error range; If the mask gray value belongs to the numerical range formed by the gray threshold and the gray error range, dividing the area corresponding to the mask gray value into the low-energy area; If the mask gray value does not belong to the numerical range formed by the gray threshold and the gray error range, dividing the area corresponding to the mask gray value into the high-energy area; Determining the detection mode of the detection device according to the mask detection energy distribution map, and detecting the mask according to the detection mode.

2. The method according to claim 1, characterized in that, The detection device parameters include the energy rise and fall time of the detection device. The step of obtaining the mask detection energy distribution map according to the plurality of detection energy areas includes: Judging whether adjacent detection energy areas on the mask are the same; If the adjacent detection energy areas are different, determining a buffer area according to the energy rise and fall time of the detection device and the adjacent detection energy areas; Obtaining the mask detection energy distribution map according to the standard area, the low-energy area, the high-energy area, and the buffer area.

3. The method according to claim 1, characterized in that The step of determining the detection mode of the detection device according to the mask detection energy distribution map includes: When the detection energy area of the mask detection energy distribution map is the standard area, determining the detection mode as the standard detection mode; When the detection energy area of the mask detection energy distribution map is the low-energy area, determining the detection mode as the low-energy detection mode; When the detection energy area of the mask detection energy distribution map is the high-energy area, determining the detection mode as the high-energy detection mode.

4. The method according to claim 2, wherein The step of determining the detection mode of the detection device according to the mask detection energy distribution map includes: When the detection energy area of the mask detection energy distribution map is the buffer area, performing strip division on the detection area of the adjacent detection energy area to obtain a plurality of detection strip areas; Determining a width threshold for detection mode switching according to the moving speed of the detection device in the detection device parameters; Comparing the width of the detection strip area with the width threshold. If the width of the detection strip area is less than the width threshold, maintaining the current detection mode.

5. A mask inspection device, characterized in that, The reticle detection device includes: A region division module, configured to divide the detection regions of the reticle according to a preset region division strategy to obtain a reticle detection energy distribution map; The region division module is further configured to perform a grayscale value detection on the reticle to obtain a reticle grayscale value; divide the detection regions of the reticle according to the reticle grayscale value and a preset grayscale threshold to obtain a plurality of detection energy regions; obtain the reticle detection energy distribution map according to the plurality of detection energy regions; the detection energy regions include a standard region, a low energy region, and a high energy region, and the step of dividing the detection regions of the reticle according to the reticle grayscale value and the preset grayscale threshold includes: determining the numerical magnitude relationship between the reticle grayscale value and the grayscale threshold; if the reticle grayscale value is equal to the grayscale threshold, then divide the region corresponding to the reticle grayscale value into the standard region; if the reticle grayscale value is not equal to the grayscale threshold, then determine whether the reticle grayscale value belongs to the numerical range formed by the grayscale threshold and the grayscale error range; if the reticle grayscale value belongs to the numerical range formed by the grayscale threshold and the grayscale error range, then divide the region corresponding to the reticle grayscale value into the low energy region; if the reticle grayscale value does not belong to the numerical range formed by the grayscale threshold and the grayscale error range, then divide the region corresponding to the reticle grayscale value into the high energy region; A detection module, configured to determine the detection mode of the detection device according to the reticle detection energy distribution map, and detect the reticle according to the detection mode.

6. A mask inspection device, characterized in that, The reticle detection device includes: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the computer program is configured to implement the steps of the reticle detection method according to any one of claims 1 to 4.

7. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the computer-readable storage medium, and when the computer program is executed by the processor, the steps of the reticle detection method according to any one of claims 1 to 4 are implemented.

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