Defect measurement method of semiconductor image and related product

Abstract

The invention provides a defect measurement method of a semiconductor image and a related product. The method comprises the following steps: acquiring a semiconductor image with a defect to be measured, and identifying the defect type of the defect to be measured on the semiconductor image; calling a processing template corresponding to the defect type; and measuring the defect to be measured on the semiconductor image according to an image processing step specified by the processing template. According to the defect measurement method for the semiconductor image, the defect measurement method on the semiconductor image of one semiconductor image can be used as a template or a reference and is used for processing other semiconductor images of the same type, so that automatic batch processing, such as automatic batch measurement, is realized.

Description

Technical Field

[0001] The present invention relates to the field of semiconductor technology, and in particular to a semiconductor image defect measurement method and related products. Background Art

[0002] In the manufacturing process of semiconductor integrated circuits, semiconductor devices, such as wafers, will inevitably introduce defects such as surface contamination, scratches, and foreign particles after a series of manufacturing processes. These defects will cause incomplete patterns and affect the electrical characteristics of the chip, thereby affecting the yield of chip production. Therefore, defect detection and analysis of target defect data have become important.

[0003] There are two main methods for defect measurement. One is to obtain information such as defect size from the defect detection result file; the other is manual measurement, which uses a ruler to correspond to the measurement tool of the semiconductor image to manually calculate the defect size.

[0004] For the first method, the defect size information usually output in the defect detection result file includes: XSIZE, YSIZE, DEFECTAREA, DSIZE. XSIZE is the length of the defect in the X direction; YSIZE is the length of the defect in the Y direction; DEFECTAREA is the area of ​​the defect, usually using XSIZE*YSIZE; DSIZE is the maximum size of the defect, using the larger value of XSIZE and YSIZE.

[0005] For the second method, the user views the image of the defect detection result, manually uses a ruler to match the measurement tool of the semiconductor image, and then calculates the defect size; if angle information needs to be measured, it is measured with the help of a protractor.

[0006] The inventors have found that whether obtaining the defect size from the defect detection result file or measuring the defect size manually, there are certain limitations, such as: (1) the defect measurement information in the defect detection result file is not accurate enough and deviates from the actual defect size. Figure 1 As shown in the figure, the maximum size of the defect is not the larger value of XSIZE and YSIZE; and the output information is single, and the defect cannot be measured from other dimensions, such as angle information. Therefore, there will be certain deviations in the analysis of the production process and the location of the problem. (2) Although manual measurement has improved the accuracy compared with the first method, it can only measure a single semiconductor image in actual application, and cannot achieve batch automatic measurement, which is inefficient and has high labor costs. In addition, this method also limits the method of combining the target defect data with other production data for analysis, resulting in the problem analysis being too single and lacking in systematicness and integrity. Summary of the invention

[0007] In view of the above problems, the present invention is proposed to provide a method for measuring defects in semiconductor images that overcomes the above problems or at least partially solves the above problems.

[0008] An object of the present invention is to improve the processing speed of semiconductor images and achieve automated and batch processing of semiconductor images.

[0009] A further object of the present invention is to improve the accuracy and / or comprehensiveness of measuring defects in semiconductor images.

[0010] In particular, the present invention provides a method for measuring defects in semiconductor images, including:

[0011] Obtain a semiconductor image with defects to be measured, and identify the defect type of the defects to be measured on the semiconductor image;

[0012] Retrieve a processing template corresponding to the defect type;

[0013] Measure the defects to be measured on the semiconductor image according to the image processing steps specified in the processing template.

[0014] Optionally, the image processing steps include:

[0015] Obtain the defect contour of the defects to be measured on the semiconductor image;

[0016] Obtain the measured part of the defect contour and the measuring tool used for measurement, and measure the measured part of the defect contour using the measuring tool.

[0017] Optionally, the image processing steps include:

[0018] Obtain the defect contour of the defects to be measured on the semiconductor image;

[0019] Obtain a measurement item, and the measurement item is configured to reflect a dimension of the defects to be measured;

[0020] Measure the defect contour based on the measurement item.

[0021] Optionally, the generation steps of the processing template include:

[0022] Obtain a sample image, and the sample image is a semiconductor image used to generate the processing template;

[0023] Record the image processing steps used when the sample image is processed;

[0024] Generate the processing template according to the image processing steps.

[0025] Optionally, the step of generating the processing template further includes:

[0026] Recording the relationship value between the measurement data of the measurement tool used in the measurement and the actual size, so as to generate measurement data equal to the actual size of the defect to be measured according to the relationship value during or after the execution of the image processing step.

[0027] Optionally, the step of generating the relationship value includes:

[0028] Obtaining the defect contour of the defect to be measured on the sample image;

[0029] Obtaining the measurement data generated by the measurement tool after measuring the defect contour;

[0030] Obtaining the actual size of the corresponding part of the defect contour measured by the measurement tool input by the input module, and calculating the relationship value based on the actual size and the measurement data; or, obtaining the relationship value input by the input module.

[0031] Optionally, the step of generating the relationship value includes:

[0032] Displaying the measurement tool;

[0033] Obtaining the tool data displayed by the measurement tool itself;

[0034] Obtaining the actual size of the measurement tool based on the display input by the input module, and calculating the relationship value based on the actual size and the tool data; or, obtaining the relationship value input by the input module.

[0035] Optionally, the method for measuring defects in a semiconductor image further includes:

[0036] Processing the measurement data generated during or after the execution of the image processing step to obtain a heat map.

[0037] Optionally, the processing the measurement data generated during or after the execution of the image processing step to obtain a heat map includes:

[0038] Obtaining the position of the defect to be measured on the semiconductor image on the surface of the semiconductor;

[0039] Generating the heat map based on the shape of the surface of the semiconductor, the position, and the measurement data.

[0040] Optionally, the method for measuring defects in a semiconductor image further includes:

[0041] Lasso a hot zone on the heat map to obtain target defect data, where the target defect data includes the measurement data corresponding to the lassoed hot zone and the position corresponding to the selected measurement data;

[0042] Obtain production data of a semiconductor during the production process;

[0043] Perform cross-module processing on the production data and the target defect data to combine and analyze the production data and the target defect data, and obtain and output an analysis result.

[0044] According to another aspect of the present invention, there is also provided a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of any one of the above semiconductor image defect measurement methods are implemented.

[0045] According to still another aspect of the present invention, there is also provided a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of any one of the above semiconductor image defect measurement methods are implemented.

[0046] According to yet another aspect of the present invention, there is also provided a computer device, which includes a memory, a processor, and a computer program stored on the memory, and the processor executes the computer program to implement the steps of any one of the semiconductor image defect measurement methods.

[0047] In the semiconductor image defect measurement method of the present invention, since there is a processing template corresponding to the defect type, the semiconductor image can be automatically processed based on the image processing steps specified in the processing template, and the target measurement data desired by the user can be obtained without user operation. Therefore, automated and batch semiconductor image processing is realized.

[0048] Furthermore, in the semiconductor image defect measurement method of the present invention, a processing template can be generated according to each step of processing the exemplary semiconductor image, that is, the subsequent semiconductor images can be automatically processed based on the processing steps of the exemplary image. That is to say, the semiconductor image defect measurement method can use the defect measurement method on one semiconductor image as a template or reference for processing other semiconductor images of the same type to achieve batch automatic processing, such as batch automatic measurement.

[0049] Furthermore, in the semiconductor image defect measurement method of the present invention, each semiconductor image needs to be measured, rather than relying on the existing defect detection result file. The defect measurement information is accurate, and it can also measure the measurement data not included in the existing defect detection result file, and can measure the defects to be measured from other dimensions, such as angle information. Obviously, the accuracy and comprehensiveness of defect measurement in semiconductor images are improved.

[0050] From the following detailed description of specific embodiments of the present invention in conjunction with the accompanying drawings, those skilled in the art will become more clearly aware of the above and other objects, advantages, and features of the present invention. Description of the Drawings

[0051] Some specific embodiments of the present invention will be described in detail hereinafter with reference to the accompanying drawings in an exemplary but non-limiting manner. The same reference numerals in the drawings denote the same or similar components or parts. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the drawings:

[0052] Figure 1 is a schematic diagram of a semiconductor image in the prior art; the two arrows in the figure are respectively the indication arrows in the X direction and the Y direction;

[0053] Figure 2 is a schematic flowchart of a method for measuring defects in a semiconductor image according to an embodiment of the present invention;

[0054] Figure 3 is a schematic flowchart of a step for generating a processing template in a method for measuring defects in a semiconductor image according to an embodiment of the present invention;

[0055] Figure 4 is a schematic flowchart of a step for generating a relationship value in a method for measuring defects in a semiconductor image according to an embodiment of the present invention;

[0056] Figure 5 is a schematic flowchart of a method for measuring defects in a semiconductor image according to an embodiment of the present invention;

[0057] Figure 6 is a schematic diagram of a semiconductor image in a method for measuring defects in a semiconductor image according to an embodiment of the present invention;

[0058] Figure 7 is a schematic diagram of defect contour detection in a method for measuring defects in a semiconductor image according to an embodiment of the present invention;

[0059] Figure 8 is a schematic diagram of defect contour detection in a method for measuring defects in a semiconductor image according to an embodiment of the present invention;

[0060] Figure 9 is a heat map in a method for measuring defects in a semiconductor image according to an embodiment of the present invention;

[0061] Figure 10 is a schematic diagram of a computer program product according to an embodiment of the present invention;

[0062] Figure 11Schematic diagram of a computer-readable storage medium according to an embodiment of the present invention; and

[0063] Figure 12 Schematic diagram of a computer device according to an embodiment of the present invention. Detailed implementation manners

[0064] This embodiment provides a solution for a method of measuring defects in semiconductor images. Figure 2 Schematic flowchart of a method of measuring defects in semiconductor images according to an embodiment of the present invention. Generally, the method may include:

[0065] Step S100: Obtain a semiconductor image with a defect to be measured, and identify the defect type of the defect to be measured on the semiconductor image. The semiconductor image is an SEM image, that is, a scanning electron microscope image, which is a microscopic structure image of the surface of a sample observed by a scanning electron microscope. Defects in semiconductor images usually include optically patterned defects and optically non-patterned defects. Optically patterned defects include broken lines, line edge defects, bridges, and line shape changes (such as bending, twisting, etc.). Optically non-patterned defects include particles, residues, and scratches. Scratches are usually scratches or damages that appear on the semiconductor image. The defect to be measured may be a broken line, a line edge defect, a bridge, a line shape change, a particle, a residue, or a scratch, etc.

[0066] Step S200: Retrieve a processing template corresponding to the defect type.

[0067] Step S300: Measure the defect to be measured on the semiconductor image according to the image processing steps specified in the processing template.

[0068] When processing a semiconductor image with a defect to be measured, especially when batch processing semiconductor images, directly process according to the defect type of the defect to be measured on the semiconductor image to be detected and the corresponding processing template, without the user having to operate step by step for each picture. That is, in the method of measuring defects in semiconductor images according to the embodiment of the present invention, due to having a processing template corresponding to the defect type, the semiconductor image can be automatically processed based on the image processing steps specified in the processing template, and the target measurement data desired by the user can be obtained without user operation. Therefore, automated and batch processing of semiconductor images is achieved.

[0069] Moreover, when the image processing steps specified in the processing template are executed, measurement data required by the user can be generated. For example, the measurement data required by the user is the data corresponding to the measurement items required by the user. The measurement items required by the user may be the size of the defect. That is to say, the measurement item is configured to reflect a dimension of the defect to be measured, including but not limited to: the length of the defect, the width of the defect, the angle of the defect, the area of the defect, the perimeter of the defect, etc.

[0070] In this embodiment, the image processing step can measure each semiconductor image, rather than relying on the existing defect detection result file. The defect measurement information is accurate, and it can also measure the measurement data that is not in the existing defect detection result file, and can measure defects from other dimensions, such as angle information. Obviously, it improves the accuracy and comprehensiveness of the measurement of defects in semiconductor images. The image processing step can be repeatedly measured to achieve batch measurement of defects in semiconductor images. Collecting, analyzing, processing, and deeply mining the target defect data can timely discover the problems in the semiconductor manufacturing process, and then the key points to improve the yield can be found. Because the data obtained from the defect detection in the embodiment of the present invention is accurate, it is more conducive to accurately discovering the problems in the semiconductor manufacturing process, and then more conducive to improving the yield of semiconductor products.

[0071] In some embodiments of the present invention, as Figure 3 shown, the steps for generating the processing template include:

[0072] Step S210, obtaining a sample image, where the sample image is a semiconductor image used to generate the processing template. That is to say, according to the processing steps of a semiconductor image, the above-mentioned processing template can be generated.

[0073] Step S220, recording the image processing steps used when the sample image is processed.

[0074] Step S230, generating a processing template according to the image processing steps.

[0075] In the embodiment of the present invention, when the computer device processes the sample image, it can record each processing step to form an image processing step for the semiconductor image, that is, form a template for the processing of the semiconductor image. That is to say, the defect measurement method for the semiconductor image can use the defect measurement method on a semiconductor image as a template or reference for the processing of other semiconductor images of the same type to achieve batch automatic processing, such as batch automatic measurement.

[0076] In some embodiments of the present invention, during specific operations, a user can store multiple semiconductor images of the same type in a computer device or the like, so that the computer device or the like can obtain multiple semiconductor images. Then, the user uses the computer device to process one semiconductor image, and the computer device generates a processing template according to the steps of processing the semiconductor image. After processing one semiconductor image, the computer device continues to call another semiconductor image and the processing template to perform processing according to the above-mentioned image processing steps until all semiconductor images are processed. For multiple semiconductor images, the same type of semiconductor images can be selected manually, which is convenient for improving the defect type recognition speed of semiconductor images, facilitating the processing of the same type of semiconductor images, improving the processing speed, and making the correlation of the measured data stronger. Of course, in some other embodiments of the present invention, the user does not need to select the same type of semiconductor images manually, and only needs to analyze the measurement results of the same type of semiconductor images together.

[0077] In some embodiments of the present invention, the steps of generating the processing template further include: recording the relationship value between the measurement data of the measurement tool used for measurement and the actual size, so that during or after the execution of the image processing steps, measurement data equal to the actual size of the defect to be measured can be generated according to the relationship value. By setting the relationship value, the measurement data measured by the computer device or the like corresponds to the actual size. Usually, the measurement data is reflected by pixel values. Through the relationship value, the pixel values and the actual size can be corresponded, ensuring the accuracy of the measurement, without the user having to convert it manually, reducing the labor cost, and improving the efficiency. The measurement tool usually includes a scale.

[0078] In some embodiments of the present invention, the steps of generating the relationship value include:

[0079] Obtain the defect contour 40 of the defect to be measured on the sample image. By using a computer device or the like to extract the defect contour on the sample image, the defect contour 40 can be obtained. The defect contour 40 can also be identified and extracted by using AI (Artificial Intelligence).

[0080] Obtain the measurement data generated by the measurement tool after measuring the defect contour. Specifically, when using the measurement tool to measure a certain part of the defect contour, the measurement data corresponding to this part will be formed, or when using the measurement tool to measure the distance between two parts of the defect contour, the measurement data of the defect to be measured, such as length, width, etc., can be obtained.

[0081] Obtain the actual size of the corresponding part measured by the measuring tool on the defect contour input by the input module. Specifically, an interface for inputting the actual size can be generated first to wait for the actual size input by the input module. After receiving the input actual size, it is considered that the actual size has been obtained. The actual size is obtained by the user through actual measurement based on the semiconductor image.

[0082] Calculate the relationship value based on the actual size and the measurement data.

[0083] In some alternative embodiments of the present invention, after obtaining the measurement data generated by the measuring tool after measuring the defect contour, the relationship value input by the input module can be directly obtained. Specifically, an interface for inputting the relationship value can be generated first to wait for the relationship value input by the input module. After receiving the input relationship value, it is considered that the relationship value has been obtained. The relationship value can be calculated by the user based on the measurement data and the actual size and then input through the input module.

[0084] In some embodiments of the present invention, as Figure 4 shown, during the processing of the example image, a relationship value is generated; and the steps for generating the relationship value include:

[0085] Step S223, display the measuring tool. Specifically, the display interface of the computer device can display the measuring tool.

[0086] Step S224, obtain the tool data displayed by the measuring tool itself. The tool data can be the measuring range of the measuring tool, or the distance between two scale values, etc.

[0087] Step S225, obtain the actual size based on the displayed measuring tool input by the input module, and calculate the relationship value based on the actual size and the tool data; or, obtain the relationship value input by the input module. In this embodiment, the actual size can be obtained by the user using an actual measuring tool to measure the corresponding position on the measuring tool based on the display interface of the computer device. That is, "measuring tool measurement pixel value" = "user input actual size corresponding to the measuring tool", such as 78pix = 1u, and the corresponding relationship value can be 1 / 78, that is, the actual size is 1 / 78 of the measurement data.

[0088] In some embodiments of the present invention, during the processing of the example image, a relationship value is generated. That is to say, a relationship value needs to be generated when the example image is processed, and the example image is fully utilized for more operations to improve the processing speed. That is, obtain the relationship value between the measurement data of the measuring tool used to measure the defect and the actual size, which can be performed simultaneously during the processing of the semiconductor image to form a processing template. This process can be recorded or not recorded.

[0089] In some embodiments of the present invention, as Figure 4 、Figure 5 As shown, the image processing steps specified by the processing template include:

[0090] Step S221, obtaining the defect contour 40 of the defect to be measured on the semiconductor image. As Figures 6 to 8 shown.

[0091] Step S222, obtaining the part of the defect contour to be measured and the measuring tool used for measurement, and using the measuring tool to measure the part of the defect contour to be measured.

[0092] When forming the measurement template by processing the sample image, computer devices, etc., obtain the measuring tool (such as a length measuring tool, an angle measuring device, etc.) according to the user's input, such as mouse input, at the part of the defect contour to be measured. Then, the computer device uses the measuring tool to measure the part of the defect contour to be measured and generates the measurement data of the measurement item. The measurement item can be the defect length (i.e., the distance between two parts on the defect contour), the angle at a certain part of the defect contour, etc. For the semiconductor image processed according to the processing template, after the computer device extracts the defect contour 40 on the semiconductor image, it performs measurement based on the same strategy (i.e., the above image processing steps) without obtaining the user's input based on the input module. For example Figure 7 , Figure 8 shown, the image processing steps measure the length L of the defect, the angle θ of the defect, the perimeter of the defect, etc.

[0093] In some other embodiments of the present invention, the image processing steps specified by the processing template include:

[0094] Obtaining the defect contour 40 of the defect to be measured on the semiconductor image. By using computer devices, etc., to extract the defect contour on the sample image, the defect contour 40 can be obtained. It is also possible to use AI (Artificial Intelligence) for defect recognition and extract the defect contour 40.

[0095] Obtaining the measurement item and measuring the defect contour based on the measurement item. In the defect measurement method of the semiconductor image, computer devices, etc., are configured to be able to perform measurement independently. Just by obtaining the user's requirement input by the input device, that is, the measurement item, the computer device will perform independent measurement on this measurement item. This can be implemented in many image processing software.

[0096] In some embodiments of the present invention, as Figure 5 shown, in step S300, according to the image processing steps specified by the processing template, measure the defect to be measured on the semiconductor image. After that, the defect measurement method of the semiconductor image further includes:

[0097] Step S226: Determine whether there is a next semiconductor image;

[0098] If so, return to the above steps of obtaining the semiconductor image with the defect to be measured, identifying the defect type of the defect to be measured on the semiconductor image, and batch-processing the image autonomously.

[0099] In some embodiments of the present invention, as Figure 5 shown, the defect measurement method for semiconductor images further includes:

[0100] Step S400: Process the measurement data generated during or after the execution of the image processing step to obtain a heat map, as Figure 9 shown. The heat map can more clearly express the situation of the defects, remind the user of the defects that need attention, significantly improve the presentation ability of the measurement data, and make the prominent defects be focused on.

[0101] Through the heat map, the distribution of the defect sizes can be visually seen. This method can generate different heat maps according to different attribute information of the defects, such as the XSIZE, YSIZE, maximum length, area, or perimeter of the defects. The larger the measurement data corresponding to the defect in the heat map, the deeper or warmer the color represents.

[0102] In some embodiments of the present invention, Step S400: Process the measurement data generated during or after the execution of the image processing step to obtain a heat map, including:

[0103] Obtain the position of the defect to be measured on the surface of the semiconductor in the semiconductor image. Usually, the description information of the semiconductor image has the position where the defect to be measured is located.

[0104] Generate a heat map based on the shape, position, and measurement data of the surface of the semiconductor. Each point on the heat map can reflect the position of the defect to be measured on the surface of the semiconductor, and the color on the heat map reflects the measurement data corresponding to the defect to be measured.

[0105] In some embodiments of the present invention, as Figure 5 shown, the defect measurement method for semiconductor images further includes:

[0106] Step S500: Lasso a hot zone on the heat map to obtain target defect data, where the target defect data includes the measurement data corresponding to the lassoed hot zone and the position corresponding to the selected measurement data. As Figure 9 shown, Figure 9 the area circled by the line 50 in

[0107] Step S600: Obtain production data during the production process of semiconductors (i.e., WIP data, data in Work In Progress).

[0108] Step S700: Perform cross-module processing (Cross Module) on the production data and the target defect data to combine and analyze the production data and the target defect data, and obtain and output the analysis result.

[0109] Specifically, through the cross-module processing of the production data and the target defect data, the drawbacks of single production data analysis are solved. It can analyze semiconductors with large-size defects, such as wafers, to determine which production tools (Process Tools) they pass through during the actual production process, assist engineers in further analysis, analyze the impact of production tools on the manufacturing process, identify production tools with potential problems, quickly locate anomalies in production tools, and identify quality anomaly problems, etc., which is very helpful for improving the yield, that is, effectively improving the yield of semiconductor products.

[0110] The defect measurement method for semiconductor images in the embodiments of the present invention makes up for the deficiency of inaccurate defect size in the defect detection result file output for the defect measurement method of a single semiconductor image, providing a basis closer to objective facts for subsequent problem analysis. The batch automatic measurement method for semiconductor images improves work efficiency; the heat map generated according to the defect measurement results visualizes and compares data by means of color changes, quickly locates the data in the hot zone, and specifically obtains the corresponding WIP data, reducing the analysis of redundant data, quickly locating which Process Tools may cause these large defect anomalies, and taking timely measures to stop losses, thereby further improving the yield of the production process and then increasing the yield of semiconductor products.

[0111] The flowchart provided in this embodiment is not intended to indicate that the operations of the method will be executed in any specific order, or that all operations of the method are included in every case. In addition, the method may include additional operations. Within the scope of the technical idea provided by the method in this embodiment, additional changes can be made to the above method.

[0112] It should be understood that in some embodiments, each part can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system.

[0113] This embodiment also provides a computer program product 10, a computer-readable storage medium 20, and a computer device 30. Figure 10 It is a schematic diagram of a computer program product 10 according to an embodiment of the present invention. Figure 11Schematic diagram of a computer-readable storage medium 20 according to an embodiment of the present invention. Figure 12 Schematic diagram of a computer device 30 according to an embodiment of the present invention. The computer program product 10 includes a computer program 11. When the computer program 11 is executed by a processor 32, it implements the steps of the defect measurement method for semiconductor images in any of the above. The computer-readable storage medium 20 stores the above computer program 11. When the computer program 11 is executed by a processor 32, it implements the steps of the defect measurement method for semiconductor images in any of the above embodiments. The computer device 30 may include a memory 31, a processor 32, and a computer program 11 stored on the memory 31 and running on the processor 32.

[0114] The computer program 11 for performing the operations of the present invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, status setting data, configuration data of an integrated circuit, or source code or object code written in any combination of one or more programming languages and procedural programming languages. The computer program 11 may be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, 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. In some embodiments, to perform various aspects of the present invention, an electronic circuit, including, for example, a programmable logic circuit, a field-programmable gate array (FPGA), or a programmable logic array (PLA), may execute computer-readable program instructions by utilizing the status information of the computer-readable program instructions to personalize the electronic circuit.

[0115] For the description of this embodiment, the computer program product 10 is a related product that includes the computer program 11.

[0116] For the description of this embodiment, the computer-readable storage medium 20 is a tangible device capable of retaining and storing the computer program 11, which can be any device that can contain, store, communicate, propagate, or transmit the computer program 11 for use by or in connection with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of the computer-readable storage medium 20 include the following: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD), memory stick, floppy disk, mechanically encoded device, and any suitable combination of the above.

[0117] The computer device 30 can be, for example, a server, a desktop computer, a laptop computer, a tablet computer, or a smart phone. In some examples, the computer device 30 can be a cloud computing node. The computer device 30 can be described in the general context of computer system-executable instructions, such as program modules, executed by a computer system. Generally, program modules can include routines, programs, object programs, components, logic, data structures, etc. that perform specific tasks or implement specific abstract data types. The computer device 30 can be implemented in a distributed cloud computing environment where tasks are performed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media including storage devices.

[0118] The computer device 30 can include a processor 32 suitable for executing stored instructions and a memory 31 that provides temporary storage space for the operation of the instructions during operation. The processor 32 can be a single-core processor, a multi-core processor, a computing cluster, or any other number of other configurations. The memory 31 can include random access memory (RAM), read-only memory, flash memory, or any other suitable storage system.

[0119] The computer device 30 can also include a network adapter / interface and an input / output (I / O) interface. The I / O interface allows data to be input and output with external devices that can be connected to the computer device. The network adapter / interface can provide communication between the computer device and a network, which is usually shown as a communication network.

[0120] At this point, those skilled in the art should recognize that although multiple exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications that conform to the principles of the present invention can still be directly determined or derived from the content disclosed in the present invention without departing from the spirit and scope of the present invention. Therefore, the scope of the present invention should be understood and determined to cover all these other variations or modifications.

Claims

1. A method for measuring defects in semiconductor images, characterized in that: include: Acquire a semiconductor image having a defect to be measured, and identify a defect type of the defect to be measured on the semiconductor image; Retrieving a processing template corresponding to the defect type; The defect to be measured on the semiconductor image is measured according to the image processing steps specified by the processing template.

2. The semiconductor image defect measurement method according to claim 1, characterized in that: The image processing step comprises: Acquiring a defect profile of the defect to be measured on the semiconductor image; The measured portion of the defect profile and the measuring tool used for the measurement are obtained, and the measured portion of the defect profile is measured using the measuring tool.

3. The semiconductor image defect measurement method according to claim 1, characterized in that: The image processing step comprises: Acquiring a defect profile of the defect to be measured on the semiconductor image; A measurement item is acquired, and the defect profile is measured based on the measurement item; the measurement item is configured to reflect a dimension of the defect to be measured.

4. The semiconductor image defect measurement method according to claim 1, characterized in that: The step of generating the processing template includes: Acquire an example image, wherein the example image is a semiconductor image used to generate the processing template; recording the image processing steps used when the example image is processed; The processing template is generated according to the image processing steps.

5. The semiconductor image defect measurement method according to claim 4, characterized in that: The step of generating the processing template further includes: The relationship value between the measurement data of the measuring tool used for measurement and the actual size is recorded, so as to generate measurement data equal to the actual size of the defect to be measured according to the relationship value during or after the image processing step is performed.

6. The semiconductor image defect measurement method according to claim 5, characterized in that: The step of generating the relationship value comprises: Acquire a defect contour of a defect to be measured on the sample image; Acquiring the measurement data generated by the measuring tool after measuring the defect profile; The actual size of the corresponding part measured by the measuring tool on the defect contour input by the input module is obtained, and the relationship value is calculated based on the actual size and the measurement data; or, the relationship value is obtained by the input module.

7. The semiconductor image defect measurement method according to claim 5, characterized in that: The step of generating the relationship value comprises: demonstrating the measuring tool; Obtaining tool data displayed by the measuring tool itself; The actual size of the measuring tool based on the display is obtained from the input module, and the relationship value is calculated based on the actual size and the tool data; or, the relationship value is obtained from the input module.

8. The semiconductor image defect measurement method according to claim 1, characterized in that: Also includes: Acquire the position of the defect to be measured on the surface of the semiconductor on the semiconductor image; generating a thermal map based on the shape of the surface of the semiconductor, the position, and measurement data generated during or after the image processing step; lassoing a hot zone on the thermal map to obtain target defect data, the target defect data including the measurement data corresponding to the lassoed hot zone and the position corresponding to the selected measurement data; Acquiring production data about semiconductors in the production process; The production data and the target defect data are processed across modules to combine and analyze the production data and the target defect data to obtain and output analysis results.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the semiconductor image defect measurement method according to any one of claims 1 to 8 are implemented.

10. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the semiconductor image defect measurement method according to any one of claims 1 to 8.

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