Measurement system

Abstract

The purpose of the present invention is to provide a technology that allows for brightness / contrast adjustment suitable for measurement, even in the case of a structure, such as a semiconductor cross-section, the shape of which varies depending on the type of material, and in which a plurality of regions having different luminance values exist. This measurement system: creates a luminance histogram of an image which is in a boundary region of a sample; creates an integrated histogram by integrating the histogram; and adjusts at least either the brightness or the contrast of the image so as to flatten the integrated histogram, thereby sharpening the boundary region.

Description

Measurement system

[0001] The present invention relates to a technique for measuring a sample using a sample image generated by irradiating a sample with a charged particle beam by a charged particle beam apparatus.

[0002] There is a technique for detecting secondary charged particles generated from a sample by irradiating the sample with a charged particle beam, and generating an observation image of the sample by detecting the intensity of the secondary charged particles. In order to evaluate the quality of an etching process or the like using this observation image, the height of a structure formed on the surface of the sample may be measured on the image. It is necessary to detect the edge of the measurement location during length measurement. At this time, the brightness and contrast of the observation image are adjusted as necessary. If the brightness and contrast difference around the edge is small, the edge cannot be sufficiently sharpened on the observation image, and the length measurement may fail.

[0003] The following Patent Document 1 describes a technique for optimally adjusting the brightness and contrast of an observation image of a sample obtained by a charged particle beam apparatus. In this document, as shown in FIG. 10, the observation image is divided into a region A1205 and a region B1206 (paragraph 0042), and a luminance histogram is generated for each divided region (step 1405). FIG. 13(a) of this document shows the luminance distribution 1501 of the region A1205, and FIG. 13(b) shows the luminance distribution 1502 of the region B1206 (paragraph 0043). FIG. 13(c) is a composite histogram of these (paragraph 0049).

[0004] WO2018 / 138875

[0005] Patent Document 1 divides the region of the image, generates histograms in each region, and then performs brightness and contrast adjustment using the composite histogram of these histograms. Since this technique requires region division of the image, its application target is limited to an image of a structure that can be divided into regions by straight lines, such as a semiconductor wiring pattern.

[0006] This invention has been made in view of the above-mentioned problems, and aims to provide a technology that can perform brightness and contrast adjustment suitable for measurement, even in structures where the shape differs depending on the type of material, such as a semiconductor cross-section, and where there are multiple regions with different luminance values.

[0007] The measurement system according to the present invention creates a brightness histogram of the image in the boundary region of the sample, creates an integrated histogram by integrating the histograms, and sharpens the boundary region by adjusting at least one of the brightness or contrast of the image so that the integrated histogram is flattened.

[0008] According to the measurement system of the present invention, even in the case of structures such as semiconductor cross-sections, where the shape differs depending on the type of material and there are multiple regions with different luminance values, it is possible to perform brightness and contrast adjustments suitable for measurement. Other issues, configurations, effects, etc. will be clarified by the following description of embodiments.

[0009] This is a side cross-sectional view of a semiconductor sample. This is a block diagram of the measurement system 200 according to Embodiment 1. This is a block diagram of the charged particle beam apparatus 201. This is a flowchart explaining the operation of the charged particle beam apparatus 201 and the measurement system 200. This is a flowchart explaining the operation of the charged particle beam apparatus 201 and the measurement system 200. This is a flowchart explaining the operation of the charged particle beam apparatus 201 and the measurement system 200. This shows an example of the boundary region 502. This is a diagram showing another procedure in which the brightness / contrast adjustment unit 205 calculates the histogram of the boundary region 502.

[0010] <Embodiment 1> Figure 1 is a side cross-sectional view of a semiconductor sample. This image was acquired by a charged particle beam apparatus. The upper right of Figure 1 is an enlarged view of the upper left of Figure 1. The bottom of Figure 1 is an example of the upper left of Figure 1 sharpened. The measurement system detects the interface 103 between material 101 and material 102, and the coordinates of the vertex 104 of material 101, on the observation image of the sample. The measurement system measures the distance 105 between the interface 103 and the vertex 104, etc. The interface 103 is the boundary between different materials. The vertex 104 is located at the boundary between the material and the background. The measurement system detects the boundary region 106 including the interface 103 and the vertex 104 by image processing such as template matching or an object detection AI model. The measurement system performs edge detection on the boundary region 106 by image processing.

[0011] Figure 2 is a block diagram of a measurement system 200 according to Embodiment 1 of the present invention. The measurement system 200 detects measurement locations in a semiconductor cross-sectional image using a measurement location detection model that has learned measurement data, generates a histogram for each measurement location, and performs measurement after adjusting the brightness and contrast of the image using a histogram obtained by integrating these histograms. The measurement system 200 comprises a measurement location detection unit 202, a brightness / contrast adjustment unit 205, and a measurement unit 209.

[0012] The charged particle beam apparatus 201 is a device that captures observation images of the sample illustrated in Figure 1. The measurement system 200 receives the images captured by the charged particle beam apparatus 201 as input and measures the length of patterns on the sample, such as the distance 105 in Figure 1.

[0013] The measurement location detection unit 202 includes a measurement location detector 203 and a measurement data storage unit 204. The measurement location detection unit 202 receives images captured by the charged particle beam device 201 as input and automatically detects boundary regions 106 including the interface 103 and vertices 104 as exemplified in Figure 1. The measurement location detector 203 is a detector that automatically detects boundary regions 106 by learning the data stored in the measurement data storage unit 204. The measurement data storage unit 204 stores the height of the interface 103, the coordinates of the vertices 104, the distance 105, etc. The measurement data storage unit 204 may store different datasets for each object being measured.

[0014] The brightness / contrast adjustment unit 205 comprises a histogram generator 206, a histogram integrator 207, and a brightness / contrast adjuster 208. The brightness / contrast adjustment unit 205 adjusts the brightness and contrast of the sample image. The histogram generator 206 generates a histogram for each measurement location detected by the measurement location detection unit 202. The horizontal axis of the histogram represents the brightness level of the pixels, and the vertical axis represents the number of pixels with the same brightness level. The histogram integrator 207 integrates the histograms generated by the histogram generator 206. The brightness / contrast adjuster 208 uses the histograms integrated by the histogram integrator 207 to adjust the brightness and contrast of the image captured by the charged particle beam apparatus 201 based on algorithms such as histogram flattening. An example of an image with adjusted brightness and contrast is shown in the lower part of Figure 1.

[0015] Histogram flattening means dispersing the frequency distribution of the histogram over a wider range than before the flattening process (increasing the variance of the histogram). This allows for a higher contrast in the image from which the histogram was obtained. The sharpening process itself, achieved by flattening the histogram, is a well-known technique and will not be described in detail here.

[0016] The measurement unit 209 includes a measuring instrument 210 and a display 211. The measuring instrument 210 detects measurement points such as interfaces 103 and vertices 104 in all boundary regions 106 detected by the measurement location detection unit 202, using image processing such as edge detection, on the image processed by the brightness / contrast adjustment unit 205 (the image with adjusted brightness and contrast). The measuring instrument 210 performs a predetermined measurement (e.g., distance 105 between measurement points) from the detected measurement points. The measurement results are stored in the measurement data storage unit 204. The display 211 displays the measurement results and images, etc.

[0017] <Embodiment 1: Summary> The measurement system 200 according to Embodiment 1 detects the measurement location in the sample image acquired by the charged particle beam apparatus 201, and adjusts at least one of the brightness or contrast of the entire image so that the integrated histogram of the measurement location is flattened. As a result, the measurement location is sharpened by adjusting the brightness or contrast of the entire image. Therefore, accurate measurements can be performed using the image of the measurement location.

[0018] <Embodiment 2> In Embodiment 1, the measurement system 200 sharpens the measurement area by applying a brightness or contrast adjustment process to the image acquired by the charged particle beam device 201. Similar processing can also be performed by adjusting the shooting parameters so that the integrated histogram of the measurement area is sharpened, instead of adjusting the image itself acquired by the charged particle beam device 201. Embodiment 2 of the present invention will describe an example of a configuration for this purpose.

[0019] Figure 3 is a block diagram of the charged particle beam apparatus 201. The charged particle beam apparatus 201 includes a SED (secondary electron detector) 303, a PMT (photomultiplier tube) 304, an amplifier 305, an ADC (analog-to-digital converter) 306, a digital signal processor 307, a histogram generator 308, and a control parameter setter 309. The operation of these components will be explained in the flowchart below. The measurement system 200 adjusts the irradiation parameters when the charged particle beam apparatus 201 irradiates with a charged particle beam (electron beam 301) by giving instructions to the control parameter setter 309.

[0020] Figures 4A to 4C are flowcharts illustrating the operation of the charged particle beam apparatus 201 and the measurement system 200. These flowcharts show how to perform optimal brightness and contrast adjustments to measure the pattern length on a sample using the sample image captured by the charged particle beam apparatus 201. The steps in Figure 4 are explained below.

[0021] Step 401: The charged particle beam apparatus 201 irradiates the sample material 302 with an electron beam 301.

[0022] Step 402: Secondary electrons generated from the material 302 by irradiating it with the electron beam 301 in step 401 are detected by the SED 303.

[0023] Step 403: SED303 converts the secondary electrons detected in step 402 into an image signal. Details of this step are explained in Figure 4B.

[0024] Step 404: The PMT 304 amplifies the secondary electrons detected in step 402.

[0025] Step 405: Amplifier 305 converts the electrons amplified in step 404 into a detection signal.

[0026] Step 406: The ADC 306 quantizes the detection signal converted in step 405.

[0027] Step 407: The digital signal processor 307 uses the quantized signal from step 406 to form an observation image of the material 302. The digital signal processing used in this step may include, for example, pixel integration or frame integration, but other signal processing methods may also be used.

[0028] Step 408: The histogram generator 308 generates a histogram of the image formed in step 407.

[0029] Step 409: The histogram generator 308 calculates the standard deviation and mean of the histogram generated in step 408. The histogram generator 308 compares these values ​​with the target values ​​set in advance by the user. If the standard deviation and mean are within the target range, the process proceeds to step 411. If they are outside the target range, the process proceeds to step 410, and steps 403, 408, 409, and 410 are repeated until the values ​​are within the target range. This step is intended to first ensure that the overall contrast of the image is sufficient before proceeding to the process of adjusting the contrast of the measurement points.

[0030] Step 410: The control parameter setter 309 sets the control parameters to adjust the brightness and contrast of the image formed in step 407. This is done by adjusting the voltage applied to the PMT 304 for contrast and the summing voltage of the amplifier 305 for brightness. This step is for adjusting the brightness and contrast using the histogram acquired for the entire sample image.

[0031] Step 411: The measurement location detection unit 202 detects boundary regions containing the measurement locations from the image formed in step 403. The histogram generator 206 generates histograms for each detected boundary region. The histogram integrater 207 integrates all the generated histograms. Details of this step are explained in Figure 4C.

[0032] Step 412: Once the target image is formed in step 403, the measurement location detection unit 202 detects the measurement locations. An example of a measurement location is the boundary region 502, which will be described later.

[0033] Step 413: The histogram generator 206 generates histograms 503 (specific examples will be described later) for all of the boundary regions 502 detected by the measurement location detection unit 202. The histogram generator 206 may not generate histograms for all of the boundary regions 502 detected by the measurement location detection unit 202, but rather divide the measurement points according to the type of measurement location and generate histograms for each of those divisions.

[0034] Step 414: The histogram integrator 207 integrates the histograms 503 generated in step 413 to generate a boundary region integrated histogram 504 (a specific example will be described later).

[0035] Step 415: The brightness / contrast adjuster 208 adjusts the brightness and contrast of the image using the boundary region integrated histogram 504. Specific parameter adjustments are performed by instructing the control parameter setter 309 to adjust the parameters. For example, for contrast, the voltage applied to the PMT 304 is adjusted, and for brightness, the summing voltage of the amplifier 305 is adjusted. After this step, the image signal is acquired again in the same manner as in step 403, and the boundary region integrated histogram 504 is generated again in the same manner as in step 411.

[0036] Step 416: The brightness / contrast adjustment unit 205 calculates the standard deviation and mean of the boundary region integrated histogram 504. The brightness / contrast adjustment unit 205 compares these values ​​with the target values ​​that the user has set in advance. If the values ​​are within the target range, the unit proceeds to step 417. If the values ​​are outside the target range, the unit proceeds to step 415 and repeats steps 415, (403, 411,) 416 until the values ​​are within the target range. In step 409, the brightness and contrast were adjusted using the histogram acquired for the entire image, but in step 416, the brightness and contrast are adjusted using a histogram created by integrating the histograms of the measurement points (boundary regions).

[0037] Step 417: The measuring instrument 210 measures the image processed by the previous steps. Specifically, it detects measurement points in all boundary regions detected by the measurement location detection unit 202, performs measurements from the detected measurement points, and stores the measurement results in the measurement data storage unit 204. The measuring instrument 210 may divide the measurement points according to the type of measurement location, rather than measuring all boundary regions 502, and measure the measurement points in each of those divisions.

[0038] Step 418: Display 211 displays the measurement results.

[0039] Figure 5 shows an example of a boundary region 502. In the observed image 501, areas including the boundaries between materials and the boundaries between materials and the background are detected as boundary regions 502. A histogram 503 is created for each boundary region. By integrating all the histograms 503, a boundary region integrated histogram 504 is created. Integration here means summing up the number of pixels for each brightness level described in each histogram 503. The same applies in Embodiment 1.

[0040] Examples of boundary regions 502 include the interface 103 and vertex 104 described in Embodiment 1. The interface 103 is a boundary region between different materials. The vertex 104 is a region that includes the boundary between the sample structure and the background. When creating a boundary region integrated histogram 504, it is meaningful to sum the histograms of each measurement location that have the same structure. This is because summing histograms of different structures does not have a sharpening effect. It should be noted that "same structure" here means that the image features are common enough that the same type of measurement region can be sharpened by creating a boundary region integrated histogram 504, and it is not necessary for them to have strictly identical shapes or brightness values.

[0041] <Embodiment 3> Figure 6 is a diagram showing another procedure for the brightness / contrast adjustment unit 205 to calculate the histogram of the boundary region 502. For example, for the image 601 in which the boundary region 502 of the measurement location is detected in Figure 6, it is conceivable to mask the regions other than the detected boundary region as in the image 602 and then obtain the histogram of the entire image. Thereby, substantially the histogram of the measurement location (boundary region 502) can be created. The histogram of the boundary region 502 may also be created by other appropriate methods. Other configurations are the same as those in Embodiments 1 to 2.

[0042] <Regarding Modifications of the Present Invention> The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail for easy understanding of the present invention, and it is not necessarily required to include all the configurations described. Also, a part of one embodiment can be replaced with the configuration of another embodiment. Also, the configuration of another embodiment can be added to the configuration of one embodiment. Also, for a part of the configuration of each embodiment, a part of the configuration of another embodiment can be added, deleted, or replaced.

[0043] In the above embodiments, it has been described that the measurement location detection unit 202 specifies the measurement location using a learning device that has previously learned the feature amount of the measurement location. Other methods may be used as the method for specifying the measurement location. For example, parameters describing the geometric features of the measurement location are previously stored in the measurement data storage device 204, and the measurement location may be specified by searching for locations in the image that match the parameters. The method of previously learning the feature amount of the measurement location can also be said to be one type thereof in a broad sense.

[0044] In the above embodiments, as a method for the brightness / contrast adjustment unit 205 to adjust the brightness and contrast of the boundary region 502, it has been described that the boundary region integrated histogram 504 is flattened. The method for adjusting the brightness and contrast of the boundary region 502 is not limited to this, and other image processing methods may be used.

[0045] In the embodiments described above, each functional unit of the measurement system 200 (measurement location detection unit 202, brightness / contrast adjustment unit 205, measurement unit 209) can be configured by hardware such as circuit devices that implement these functions, or, for functions that do not contradict the nature of software, they can be configured by having a processing unit such as a CPU (Central Processing Unit) execute software that implements these functions. The same applies to the digital signal processor 307, histogram generator 308, and control parameter setter 309.

[0046] 200: Measurement system 201: Charged particle beam device 202: Measurement location detection unit 205: Brightness / contrast adjustment unit 209: Measurement unit

Claims

1. A measurement system for measuring a sample using an image of the sample generated by irradiating the sample with a charged particle beam device, comprising: a measurement location detection unit that detects boundary regions of the structure of the sample as measurement locations within the image; a brightness / contrast adjustment unit that sharpens the measurement locations; and a measurement unit that measures the sample using the image of the measurement locations sharpened by the brightness / contrast adjustment unit, wherein the brightness / contrast adjustment unit creates a histogram of the brightness levels of the image for the boundary regions having the same structure; the brightness / contrast adjustment unit creates a boundary region integrated histogram by integrating the histograms; and the brightness / contrast adjustment unit sharpens the measurement locations by adjusting at least one of the brightness or contrast of the image so that the boundary region integrated histogram is flattened.

2. The measurement system further comprises a measurement data storage device that stores parameters describing the geometric features of the boundary region, and the measurement location detection unit detects a region within the image that matches the parameters stored in the measurement data storage device as the measurement location, characterized in that the measurement system according to claim 1.

3. The measurement system according to claim 2, characterized in that the parameter is at least one of the following: the height of the interface included in the boundary region, the coordinates of the vertices included in the boundary region, and the distance between the interface and the vertices in the image.

4. The measurement system according to claim 1, characterized in that the boundary region is at least one of the following: a region including the boundary between different materials of the sample, or a region including the boundary between the structure of the sample and the background image.

5. The measurement system according to claim 1, characterized in that the brightness / contrast adjustment unit adjusts at least one of the brightness or contrast of the measurement location by adjusting at least one of the brightness or contrast of the entire image.

6. The measurement system according to claim 1, characterized in that the brightness / contrast adjustment unit obtains the image with the boundary region integrated histogram flattened by applying a process to adjust the brightness or contrast of the image.

7. The measurement system according to claim 1, characterized in that the brightness and contrast adjustment unit sharpens the measurement location in the image by changing the irradiation parameters of the charged particle beam.

8. The measurement system according to claim 7, characterized in that the brightness / contrast adjustment unit sharpens the measurement area by repeatedly changing the irradiation parameters so that the boundary region integrated histogram is flattened, and then performing the sharpening again on the image acquired using the changed irradiation parameters.

9. The measurement system according to claim 1, characterized in that the brightness / contrast adjustment unit masks the portion of the image excluding the measurement location, and the brightness / contrast adjustment unit creates a histogram of the luminance level of the masked image, thereby creating a histogram of the boundary region.

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