Image contrast metric for deriving and improving imaging conditions

Abstract

Inter-wafer and intra-wafer image contrast variations can be identified and mitigated by extracting image frames at the same location during recipe setup and then during run time. Image contrast of the two image frames is determined. Contrast ratio of the two image frames can be used to determine contrast variation and focus variation.

Description

[0001] Cross-reference of related applications

[0002] This application claims priority to provisional patent application filed on June 17, 2021, and to the assigned U.S. Application No. 63 / 211,556, the disclosure of which is incorporated herein by reference. Technical Field

[0003] This disclosure relates to imaging of semiconductor wafers. Background Technology

[0004] The evolution of the semiconductor manufacturing industry places higher demands on yield management (and specifically, measurement and inspection systems). Critical dimensions continue to shrink, but the industry needs to reduce the time required to achieve high-yield, high-value production. Minimizing the total time from detecting yield problems to resolving them maximizes the return on investment for semiconductor manufacturers.

[0005] Manufacturing semiconductor devices (such as logic and memory devices) typically involves processing semiconductor wafers using a wide range of manufacturing processes to form the various features and multiple layers of the semiconductor device. For example, photolithography is a semiconductor manufacturing process that involves transferring a pattern from a photomask to a photoresist disposed on a semiconductor wafer. Additional examples of semiconductor manufacturing processes include (but are not limited to) chemical mechanical polishing (CMP), etching, deposition, and ion implantation. The arrangement of multiple semiconductor devices manufactured on a single semiconductor wafer can be classified as individual semiconductor devices.

[0006] Inspection processes are used at various stages of semiconductor manufacturing to detect defects on wafers, thereby promoting higher yields and, consequently, higher profits. Inspection has always been a crucial part of manufacturing semiconductor devices, such as integrated circuits (ICs). However, as the size of semiconductor devices shrinks, inspection becomes even more critical for successfully manufacturing acceptable semiconductor devices, as even smaller defects can cause device failure. For example, as the size of semiconductor devices decreases, the detection of defects in smaller sizes has become necessary, because even relatively small defects can introduce unwanted aberrations into the semiconductor device.

[0007] The inspection system does not effectively and directly inspect the focus on the bare semiconductor wafer. The autofocus system is not sensitive enough to detect changes in image focus. The runtime focus calibration system is also not sensitive enough. Furthermore, these prior techniques do not compare image contrast with the bare wafer. Manual calibration is time-consuming and can be limited in duration or application to avoid negatively impacting the semiconductor manufacturer's production volume.

[0008] The technology and systems need to be improved. Summary of the Invention

[0009] A method is provided in the first embodiment. The method includes: extracting a setup image frame using a processor during recipe setting; determining a first image contrast of the setup image frame using the processor; extracting a runtime setup image frame at the same location as the setup image frame using the processor during runtime; aligning the setup image frame with the runtime image frame using the processor; determining a second image contrast of the runtime image frame using the processor; and determining a ratio between the first image contrast and the second image contrast using the processor.

[0010] The method may include adjusting the position of a stage configured to hold a semiconductor wafer based on the ratio.

[0011] The method may include normalizing the ratio by using the processor to divide the first image contrast by the maximum contrast of the set image frame and to divide the second image contrast by the maximum contrast of the runtime image frame.

[0012] The method may include using the processor to determine focus shifts caused by the position of a stage configured to hold a semiconductor wafer using the contrast ratio.

[0013] The method may include using the processor to adjust the runtime image frame and the setting image frame based on the contrast ratio.

[0014] In the example, the method includes: using the processor to determine a first offset between the setup and runtime of a plurality of inspection frames; using the processor to determine a second offset between the setup and runtime of the plurality of inspection frames; and using the processor to determine the placement of one or more regions of interest based on an offset correction including the first offset and the second offset.

[0015] The method may include using the processor to determine the offset by the sum of the squared differences between the set image frame and the runtime image frame.

[0016] A non-transitory computer-readable medium storing a process that can be configured to instruct a processor to perform the method of the first embodiment.

[0017] A second embodiment provides a system. The system includes: a stage configured to hold a semiconductor wafer; an energy source configured to direct a beam to the semiconductor wafer on the stage; a detector configured to receive the beam reflected from the semiconductor wafer on the stage; and a processor electronically communicating with the detector. The energy source may be a light source. The beam may be a light beam. The processor is configured to: extract a setup image frame during recipe setting; determine a first image contrast of the setup image frame; extract a runtime setup image frame at the same location as the setup image frame during runtime; align the setup image frame with the runtime image frame; determine a second image contrast of the runtime image frame; and determine a ratio between the first image contrast and the second image contrast.

[0018] The processor can be further configured to adjust a position of the stage according to the ratio.

[0019] The processor may be further configured to normalize the ratio by dividing the first image contrast by the maximum contrast of the set image frame and by dividing the second image contrast by the maximum contrast in the runtime image frame.

[0020] The processor can be further configured to use the contrast ratio to determine focus shifts caused by the position of the stage.

[0021] The processor can be further configured to adjust the runtime image frames and the setting image frames based on the contrast ratio.

[0022] In the example, the processor is further configured to: determine a first offset between the setup and runtime of a plurality of inspection frames; determine a second offset between the setup and runtime of the plurality of inspection frames; and determine the placement of one or more regions of interest based on an offset correction that includes the first offset and the second offset.

[0023] The processor can be further configured to determine the offset using the sum of the squared differences between the set image frames and the runtime image frames. Attached Figure Description

[0024] For a more complete understanding of the nature and purpose of this disclosure, reference should be made to the following detailed description taken in conjunction with the accompanying drawings, wherein:

[0025] Figure 1 This is a flowchart illustrating an embodiment of the method according to the present disclosure;

[0026] Figure 2 This is an exemplary comparison of the contrast between settings and runtime;

[0027] Figure 3 This is an exemplary flowchart of image data collection using Patch-to-Design Alignment (PDA);

[0028] Figure 4 This demonstrates how to determine the Tenengrad variance using exemplary image frames; and

[0029] Figure 5 This is an embodiment of the system according to the present disclosure. Detailed Implementation

[0030] While the claimed objectives will be described with reference to certain embodiments, other embodiments (including those not providing all the advantages and features set forth herein) are also within the scope of this disclosure. Various structural, logical, procedural, and electronic changes may be made without departing from the scope of this disclosure. Therefore, the scope of this disclosure is defined solely by reference to the appended claims.

[0031] The embodiments disclosed herein can identify and mitigate wafer-to-wafer and in-wafer image contrast variations. Image frames can be extracted and their image contrast can be determined. Focusing conditions can be checked at high temporal resolution during runtime. The focusing conditions of the inspection system can also be checked directly on the inspection image in the active investigation area of ​​the die. Defocusing conditions, inspection system focus variations, and correct stage position (e.g., in the Z direction) can be determined.

[0032] Figure 1 This is an embodiment of method 100. Figure 2 Additional embodiments of method 100 are shown below. Some or all of the steps of method 100 can be performed using a processor.

[0033] exist Figure 1 In method 100, a setup image frame is extracted at 101. This occurs during recipe setup. For example, a gold image can be extracted from a selected die during setup. The gold image can be generated from a gold die. The image frame can be, for example, a die on a semiconductor wafer or a portion of a die on a semiconductor wafer.

[0034] At 102, the first image contrast (C) of the set image frame is determined. This can be determined using the following equation (1) to determine some or all pixels with grayscale intensity I.

[0035]

[0036] In Equation 1, Δ is the Laplacian operator. If known differences already exist within the frame, then the first image contrast can be determined for only some pixels. It's possible to perform this for other reasons, using only some pixels for the first image contrast. If no known differences exist within the frame, then the first image contrast can be determined for all pixels in the frame.

[0037] At 103, the runtime setup image frame is extracted. This occurs during runtime at the same location as the setup image frame. At 104, the setup image frame is aligned with the runtime image frame. For example, the sum of squared differences can be determined when shifting the images relative to each other to determine the optimal alignment position. The setup image frame and the runtime image frame can be different dies or different wafers. If different dies or different wafers are used, then the same location is the same location on the wafer or die as the selected die used in the gold image.

[0038] At 105, the second image contrast of the runtime image frame is determined. This can also be done using equation (1).

[0039] At step 106, the ratio between the contrast of the first image and the contrast of the second image is determined. If the ratio is close to 1.0, then the contrast has not changed significantly between the setup and runtime. This can be helpful during image alignment. A deviation from 1.0 may indicate that corrective action should be taken. Out-of-control situations or focus changes can be reported based on the contrast ratio. Wafer-to-wafer or in-wafer image contrast changes can be monitored. For example, if the image contrast is blurry, then the inspection system or the wafer may be out of control. These effects will be reflected in the ratio.

[0040] Although a single runtime image frame description method 100 is used, more than one runtime image frame can be extracted. A second image contrast and resulting ratio can be determined for each of these runtime image frames. In this example, this operation is repeated for each or multiple dies during runtime.

[0041] In this example, the position of the stage configured to hold the semiconductor wafer is adjusted based on the ratio. For example, the stage can be adjusted in the Z direction. A calibration curve is generated by collecting images at focal points (e.g., with a known Z position) and calculating the image contrast at each focal point. The curve is fitted to these data points and used to predict the current Z position based on the image contrast (e.g., ...). Figure 5 (As shown in the image). This can improve the focus and ratio results. The stage can be adjusted in the Z direction using the calibration curve.

[0042] In another example, a contrast-based defect attribute is determined. This contrast-based defect attribute can be used to perform obstruction filtering or other troubleshooting. The contrast-based defect attribute can be, for example, image contrast or normalized image contrast.

[0043] In another example, a contrast ratio can be used to normalize defect attribute values. Since image contrast values ​​can range from a wide number, dividing the number by the maximum contrast value can be helpful.

[0044] In another example, a contrast ratio can be used to determine focus variation. This can be achieved using the stage's calibration curve in the Z direction. Each image contrast value can be mapped to a specific focus point. Focus variation can then be determined based on this mapping.

[0045] In another example, the candidate image and reference image can be adjusted based on the contrast ratio. The candidate image can be a runtime image. The reference image can be a setup image or another gold image.

[0046] In another example, a first offset between setup and runtime, and a second offset between setup and runtime, can be determined for multiple test frames. For example, multiple frames on a setup wafer (e.g., a gold wafer) and a runtime wafer can be used. The placement of one or more regions of interest can be determined based on offset corrections that include the first and second offsets. In this example, the offset is determined by the sum of the squared differences between the setup and runtime images. If both the setup and runtime images are located at the same focal point, the x / y offset can be corrected with higher accuracy because the images look as similar as possible.

[0047] Figure 2 Here's another example. The image frame during recipe setup can be a gold foil frame. The image frame size can be, for example, 196 x 196 pixels, but other sizes are also possible.

[0048] Image frame data during setup and runtime can be collected while the optical PDA is in operation. This image frame data during setup and runtime data can be used to collect data for image contrast comparison. Figure 3 The PDA workflow is demonstrated. Highlighted items with hash outlines indicate the locations from which image data can be extracted. Unique 2D targets are uniformly distributed across the wafer. Image color targets can be learned from instance targets. Design image offsets from targets can be determined for each inspection frame. Saved targets and offsets in the database can be used for runtime inspection. The offset between the setup and the runtime image, or the offset between the design and the runtime image, can be determined for each inspection frame.

[0049] Figure 3 This data extraction can be added to the current processing flow and can be used for image contrast calculation. Note that... Figure 3 This is just one example of image data collection. Other techniques for collecting this data (such as using a completely separate process) are also feasible.

[0050] Contrast calculations are not limited to Laplace-based contrast; they can also be performed using other metrics, such as Tenangler variance. Figure 4 This demonstrates the calculation process using Tenangler variance. Tenangler variance (TEN) is calculated by convolving the image with the Sobel operator and summing the squares of all values ​​greater than a threshold.

[0051] Using embodiments of method 100, semiconductor manufacturers can immediately determine whether the focus of an inspection system is out of control and / or needs adjustment. This avoids manual calibration or additional run-time focus calibration steps that impact production volume. Focus changes can be measured directly based on the image being inspected rather than a virtual structure. The stage position can be adjusted based on the results. Because the focus conditions of the inspection system can be monitored in real time, lower variability in defect inspection results can be provided. Variations in defect attribute values ​​can be smaller, leading to more stable inspection results and higher defect capture rates. Tool-to-tool matching (i.e., matching between inspection systems) can be improved. More stable results can be provided for applications using images or defect attributes, such as decision trees (e.g., random forest-based decision trees) or other obstruction event filters.

[0052] Figure 5 An embodiment of system 200 is shown. System 200 includes an optically based subsystem 201. Typically, the optically based subsystem 201 is configured to generate an optically based output for sample 202 by directing light onto sample 202 (or scanning light on sample 202) and detecting the light from sample 202. In one embodiment, sample 202 includes a wafer. The wafer may include any wafer known in the art. In another embodiment, sample 202 includes a photomask. The photomask may include any photomask known in the art.

[0053] exist Figure 5 In the embodiment of system 200 shown, the optical-based subsystem 201 includes an illumination subsystem configured to direct light to sample 202. The illumination subsystem includes at least one light source. For example, such as... Figure 5 As shown, the illumination subsystem includes a light source 203. In one embodiment, the illumination subsystem is configured to direct light to the sample 202 at one or more incident angles, which may include one or more tilt angles and / or one or more normal angles. For example, as... Figure 5 As shown, light from light source 203 is guided at an oblique angle of incidence through optical element 204 and then through lens 205 to reach sample 202. The oblique angle of incidence may include any suitable oblique angle of incidence, which may vary depending on, for example, the characteristics of sample 202.

[0054] The optical-based subsystem 201 can be configured to guide light to the sample 202 at different times and different incident angles. For example, the optical-based subsystem 201 can be configured to change one or more characteristics of one or more elements of the illumination subsystem so that the light can be different. Figure 5The incident angle shown in the figure is guided to the sample 202. In one example, the optical-based subsystem 201 can be configured to move the light source 203, optical element 204 and lens 205 so that light is guided to the sample 202 at different tilted incident angles or normal (or near normal) incident angles.

[0055] In some examples, the optical-based subsystem 201 can be configured to simultaneously guide light to the sample 202 at more than one incident angle. For example, the illumination subsystem may include more than one illumination channel, one of which may include, for example, Figure 5 The light source 203, optical element 204, and lens 205 shown herein, and another element in the illumination channel (not shown), may contain similar elements, which may be configured differently or identically, or may contain at least one light source and possibly one or more other components, such as those further described herein. If this light is directed to the sample simultaneously with other light, then one or more characteristics (e.g., wavelength, polarization, etc.) of the light directed to the sample 202 at different incident angles may be different such that light originating from illuminating the sample 202 at different incident angles can be distinguished from each other at the detector.

[0056] In another example, the lighting subsystem may contain only one light source (e.g. Figure 5 The light source 203 shown in the figure can be split into different optical paths (e.g., based on wavelength, polarization, etc.) by one or more optical elements (not shown) of the illumination subsystem. The light from each of the different optical paths can then be directed to the sample 202. Multiple illumination channels can be configured to direct light to the sample 202 at the same time or at different times (e.g., when different illumination channels are used to sequentially illuminate the sample). In another example, the same illumination channel can be configured to direct light with different characteristics to the sample 202 at different times. For example, in some examples, optical element 204 can be configured as a spectral filter, and the properties of the spectral filter can be changed in a variety of different ways (e.g., by replacing the spectral filter) so that light of different wavelengths can be directed to the sample 202 at different times. The illumination subsystem can have any other suitable configuration known in the art for sequentially or simultaneously directing light with different or the same characteristics to the sample 202 at different or the same incident angles.

[0057] In one embodiment, light source 203 may comprise a broadband plasma (BBP) source. In this way, the light generated by light source 203 and directed to sample 202 may comprise broadband light. However, the light source may comprise any other suitable light source, such as a laser. The laser may comprise any suitable laser known in the art and may be configured to produce light having any suitable wavelength known in the art. Additionally, the laser may be configured to produce monochromatic or nearly monochromatic light. In this way, the laser may be a narrow-band laser. Light source 203 may also comprise a multicolor light source that produces light having multiple discrete wavelengths or bands.

[0058] Light from optical element 204 can be focused onto sample 202 by lens 205. Although lens 205... Figure 5 While shown as a single refractive optical element, it should be understood that in practice, lens 205 may comprise a combination of several refractive and / or reflective optical elements to focus light from the optical element onto the sample. Figure 5 The illumination subsystem shown and described herein may include any other suitable optical elements (not shown in the figures). Examples of such optical elements include (but are not limited to) polarization components, spectral filters, spatial filters, reflective optics, apodizers, beam splitters (e.g., beam splitter 213), apertures, and the like, which may include any such suitable optical elements known in the art. Additionally, the optical-based subsystem 201 may be configured to modify one or more of the elements of the illumination subsystem based on the type of illumination used to produce the optical-based output.

[0059] The optical-based subsystem 201 may also include a scanning subsystem configured to cause light to scan across the sample 202. For example, the optical-based subsystem 201 may include a stage 206 on which the sample 202 is positioned during optical-based output generation. The scanning subsystem may include (including the stage 206) any suitable mechanical and / or robotic assembly configured to move the sample 202 such that light can be scanned across the sample 202. Alternatively or additionally, the optical-based subsystem 201 may be configured such that one or more optical elements of the optical-based subsystem 201 perform some optical scanning across the sample 202. Light can be scanned across the sample 202 in any suitable manner (e.g., in a serpentine or helical path).

[0060] The optical-based subsystem 201 further includes one or more detection channels. At least one of the detection channels includes a detector configured to detect light from the sample 202 due to illumination of the sample 202 by the subsystem and to generate an output in response to the detected light. For example, Figure 5 The optical-based subsystem 201 shown includes two detection channels, one formed by a light collector 207, element 208, and detector 209, and the other formed by a light collector 210, element 211, and detector 212. Figure 5 As shown, the two detection channels are configured to collect and detect light at different collection angles. In some examples, the two detection channels are configured to detect scattered light, and the detection channels are configured to detect light scattered from sample 202 at different angles. However, one or more of the detection channels may be configured to detect another type of light (e.g., reflected light) from sample 202.

[0061] like Figure 5The diagram further illustrates that the two detection channels are positioned within the plane of the paper, and the illumination subsystem is also positioned within the plane of the paper. Therefore, in this embodiment, the two detection channels are positioned within the incident plane (e.g., centered within the incident plane). However, one or more of the detection channels can be positioned outside the incident plane. For example, the detection channel formed by the light collector 210, element 211, and detector 212 can be configured to collect and detect light scattered outside the incident plane. Therefore, this detection channel is often referred to as a "side" channel, and this side channel can be centered in a plane substantially perpendicular to the incident plane.

[0062] although Figure 5 An embodiment of an optically based subsystem 201 comprising two detection channels is shown, but the optically based subsystem 201 may comprise a different number of detection channels (e.g., only one detection channel or two or more detection channels). In one example, the detection channel formed by the light collector 210, element 211, and detector 212 may form a side channel as described above, and the optically based subsystem 201 may include an additional detection channel (not shown) formed as another side channel positioned on the opposite side of the incident plane. Thus, the optically based subsystem 201 may include a detection channel comprising a light collector 207, element 208, and detector 209, centered in the incident plane and configured to collect and detect light at a scattering angle perpendicular or nearly perpendicular to the surface of sample 202. Therefore, this detection channel is often referred to as the "top" channel, and the optically based subsystem 201 may also include two or more side channels configured as described above. Therefore, the optical-based subsystem 201 may include at least three channels (i.e., one top channel and two side channels), and each of the at least three channels has its own light collector, each of the light collectors being configured to collect light at a different scattering angle than each of the other light collectors.

[0063] As further described above, each of the detection channels included in the optical-based subsystem 201 can be configured to detect scattered light. Therefore, Figure 5 The optical-based subsystem 201 shown herein can be configured for generating dark-field (DF) output from sample 202. However, the optical-based subsystem 201 may also, or alternatively, include a detection channel configured for generating bright-field (BF) output from sample 202. In other words, the optical-based subsystem 201 may include at least one detection channel configured to detect light reflected from the specular surface of sample 202. Therefore, the optical-based subsystem 201 described herein can be configured for DF only, BF only, or both DF and BF imaging simultaneously. Although each of the light collectors is... Figure 5The image is shown as a single refractive optical element, but it should be understood that each of the light collectors may contain one or more refractive optical blanks and / or one or more reflective optical elements.

[0064] One or more detection channels may contain any suitable detector known in the art. For example, the detector may include a photomultiplier tube (PMT), a charge-coupled device (CCD), a time-delay integration (TDI) camera, and any other suitable detector known in the art. The detector may also include a non-imaging detector or an imaging detector. In this way, if the detector is a non-imaging detector, each of the detectors may be configured to detect certain characteristics (e.g., intensity) of the scattered light but not to detect characteristics, for example, based on position within the imaging plane. Therefore, the output generated by each of the detectors in each of the detection channels of the optical-based subsystem may be a signal or data, rather than an image signal or image data. In such examples, a processor (e.g., processor 214) may be configured to generate an image of sample 202 from the non-imaging output of the detector. However, in other examples, the detector may be configured as an imaging detector configured to generate an imaging signal or image data. Therefore, the optical-based subsystem may be configured to generate the optical images or other optical-based outputs described herein in several ways.

[0065] Note that this article provides Figure 5 The following describes the configuration of an optically based subsystem 201 that may be included in or produce optically based output used by the system embodiments described herein. The configuration of the optically based subsystem 201 described herein can be modified to optimize its performance, as is typically done when designing commercial output acquisition systems. Additionally, the system described herein can be implemented using existing systems (e.g., by adding the functionality described herein to an existing system). For some such systems, the methods described herein may be provided as optional functionality of the system (e.g., in addition to other system functionalities). Alternatively, the system described herein may be designed as a completely new system.

[0066] Processor 214 may be coupled to components of system 200 in any suitable manner (e.g., via one or more transmission media, which may include wired and / or wireless transmission media) so that processor 214 can receive output. Processor 214 may be configured to perform certain functions using the output. System 200 may receive instructions or other information from processor 214. Processor 214 and / or electronic data storage unit 215 may, as appropriate, communicate electronically with wafer inspection tools, wafer measurement tools, or wafer re-inspection tools (not shown) to receive additional information or send instructions. For example, processor 214 and / or electronic data storage unit 215 may communicate electronically with a scanning electron microscope.

[0067] The processor 214, other systems, or other subsystems described herein may be part of a variety of systems, including personal computer systems, graphics computers, mainframe computer systems, workstations, network devices, Internet devices, or other devices. The subsystem or system may also include any suitable processor known in the art, such as a parallel processor. Additionally, the subsystem or system may include a platform with high-speed processing and software as a standalone or network tool.

[0068] The processor 214 and electronic data storage unit 215 may be housed in or be part of the system 200 or another device. In an example, the processor 214 and electronic data storage unit 215 may be part of a separate control unit or located in a centralized quality control unit. Multiple processors 214 or electronic data storage units 215 may be used.

[0069] Processor 214 can be implemented in any combination of hardware, software, and firmware. Furthermore, its functions as described herein can be performed by a single unit or divided among different components, each of which can be implemented in any combination of hardware, software, and firmware. Program code or instructions for processor 214 to implement various methods and functions can be stored in a readable storage medium, such as the memory in electronic data storage unit 215 or other memory.

[0070] If system 200 includes more than one processor 214, then different subsystems can be coupled to each other so that images, data, information, instructions, etc., can be sent between the subsystems. For example, a subsystem can be coupled to an additional subsystem via any suitable transmission medium (which may include any suitable wired and / or wireless transmission medium known in the art). Two or more such subsystems can also be effectively coupled via a shared computer-readable storage medium (not shown in the figure).

[0071] Processor 214 may be configured to perform certain functions using the output of system 200 or other outputs. For example, processor 214 may be configured to send output to electronic data storage unit 215 or another storage medium. Processor 214 may be configured according to any of the embodiments described herein. Processor 214 may also be configured to perform other functions or additional steps using the output of system 200 or using images or data from other sources.

[0072] The various steps, functions, and / or operations of the system 200 and methods disclosed herein are performed by one or more of the following: electronic circuits, logic gates, multiplexers, programmable logic devices, ASICs, analog or digital controls / switches, microcontrollers, or computing systems. Program instructions for implementing the methods (such as those described herein) may be transmitted via or stored on a carrier medium. The carrier medium may include storage media, such as read-only memory, random access memory, magnetic disks or optical disks, non-volatile memory, solid-state memory, magnetic tape, and the like. The carrier medium may include transmission media, such as wires, cables, or wireless transmission links. For example, the various steps described in this disclosure may be performed by a single processor 214 or alternatively by multiple processors 214. Furthermore, different subsystems of system 200 may include one or more computing or logic systems. Therefore, the above description should not be construed as limiting the scope of this disclosure but is merely illustrative.

[0073] In this example, processor 214 communicates with system 200. Processor 214 is configured to perform an embodiment of method 100. Processor 214 may extract a setup image frame during recipe setting and determine a first image contrast of the setup image frame. Processor 214 may also extract a runtime setup image frame at the same location as the setup image frame during runtime, align the setup image frame and the runtime image frame, and determine a second image contrast of the runtime image frame. Then, processor 214 may determine the ratio between the first image contrast and the second image contrast.

[0074] Although disclosed as using the same system 200, the setup image frame can be extracted by a system different from the runtime setup image frame.

[0075] Additional embodiments relate to a non-transitory computer-readable medium storing program instructions executable on a controller for performing a computer-implemented method for classifying wafer patterns, as disclosed herein. Specifically, as... Figure 5 As shown herein, electronic data storage unit 215 or other storage media may contain non-transitory computer-readable media containing program instructions executable on processor 214. The computer-implemented method may include any step of any method described herein (including method 100).

[0076] Program instructions can be implemented in any of a variety of ways, including procedural, component-based, and / or object-oriented technologies. For example, ActiveX controls, C++ objects, JavaBeans, Microsoft Foundation Classes (MFC), Streaming SIMD Extensions (SSE), or other technologies or methods may be used as needed to implement program instructions.

[0077] When system 200 uses light, different semiconductor inspection systems can be used to perform method 100. For example, results from systems using electron beams (e.g., scanning electron microscopes or ion beams) can be used to perform method 100. Therefore, the system can have an electron beam source or an ion beam source as an energy source rather than a light source.

[0078] Although this disclosure has been described with respect to one or more specific embodiments, it should be understood that other embodiments of this disclosure may be made without departing from the scope of this disclosure. Therefore, this disclosure is considered to be limited only by the appended claims and their reasonable interpretation.

Claims

1. A method for processing image data, comprising: During setup, use the processor to extract setup image frames; The processor is used to determine the first image contrast of the set image frame; During runtime, the processor extracts runtime setup image frames at the same location as the setup image frames. The processor is used to align the setup image frame with the runtime image frame; The processor is used to determine the second image contrast of the runtime image frame; and The processor is used to determine the ratio between the contrast of the first image and the contrast of the second image. wherein the first image contrast and the second image contrast are determined using the formula wherein I is the gray scale intensity and Δ is the Laplacian operator, and x, y are the two-dimensional coordinates of the image pixels.

2. The method of claim 1, further comprising adjusting the position of the stage configured to hold the semiconductor wafer based on the ratio.

3. The method of claim 1, further comprising normalizing the ratio by using the processor to divide the first image contrast by the maximum contrast of the set image frame and to divide the second image contrast by the maximum contrast in the runtime image frame.

4. The method of claim 1, further comprising using the processor to use the contrast ratio to determine focus shifts caused by the position of the stage configured to hold the semiconductor wafer.

5. The method of claim 1, further comprising using the processor to adjust the runtime image frame and the setting image frame based on the contrast ratio.

6. The method of claim 1, further comprising: The processor is used to determine a first offset between the settings of multiple verification frames and the runtime; The processor is used to determine a second offset between the design and runtime of the plurality of check frames; and The processor is used to determine the placement of one or more regions for inspection based on an offset correction that includes the first offset and the second offset.

7. The method of claim 1, further comprising using the processor to determine the offset using the sum of the squared differences between the set image frame and the runtime image frame.

8. A non-transitory computer-readable medium storing a program that can be configured to instruct a processor to execute the method of claim 1.

9. A system for processing image data, comprising: A stage configured to hold a semiconductor wafer; A light source configured to direct a light beam toward the semiconductor wafer on the stage; A detector configured to receive the light beam reflected from the semiconductor wafer on the stage; and A processor that communicates electronically with the detector, wherein the processor is configured to: Extract the setup image frame during setup; Determine the first image contrast of the set image frame; During runtime, a runtime setting image frame is extracted at the same location as the set image frame; Align the setting image frame with the runtime image frame; Determine the second image contrast of the runtime image frame; and Determine the ratio between the contrast of the first image and the contrast of the second image. The first image contrast and the second image contrast are calculated using the formula And determined, where I is the grayscale intensity and ∆ is the Laplacian operator, and x and y are the two-dimensional coordinates of the image pixels.

10. The system of claim 9, wherein the processor is further configured to adjust the position of the stage according to the ratio.

11. The system of claim 9, wherein the processor is further configured to normalize the ratio by dividing the first image contrast by the maximum contrast of the set image frame and dividing the second image contrast by the maximum contrast in the runtime image frame.

12. The system of claim 9, wherein the processor is further configured to use the contrast ratio to determine focus variations caused by the position of the stage.

13. The system of claim 9, wherein the processor is further configured to adjust the runtime image frame and the setting image frame based on the contrast ratio.

14. The system of claim 9, wherein the processor is further configured to: Determine the first offset between the settings of multiple inspection frames and the runtime; Determine a second offset between the design and runtime of the plurality of inspection frames; and The placement of one or more regions for inspection is determined based on the offset correction that includes the first offset and the second offset.

15. The system of claim 9, wherein the processor is further configured to determine the offset using the sum of the squared differences between the setup image frame and the runtime image frame.

Images