Information processing device, program, and information processing method

Abstract

To provide a technique that makes it easier to recognize the correlation between dimensional data of a measurement point measured from a plurality of image data and parameters of a process condition.SOLUTION: An information processing device for processing a plurality of image data captured by an electron microscope includes a binarization processing unit for binarizing the image data into a region to be measured and other regions, a length measurement processing unit for measuring dimensional data of a plurality of measurement points in the region to be measured by using contour data of the region to be measured obtained from the binarized image data, and an output processing unit that uses a process condition including a plurality of parameters associated with the image data to output an image that visually shows the correlation between the dimensional data of the plurality measurement points and the plurality parameters.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus, a program, and an information processing method.

Background Art

[0002] A method of calculating a dimensional measurement value from a contour line of a pattern extracted from a captured image captured by an electron microscope has been conventionally known (see, for example, Patent Document 1).

[0003] For example, dimensional data of a length-measured portion measured from a captured image was expressed in a table or graph format by a person's hand and used for analysis.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] The present disclosure provides a technique for more easily recognizing a correlation between dimensional data of a length-measured portion measured from a plurality of image data and parameters of process conditions.

Means for Solving the Problems

[0006] One aspect of the present disclosure is an information processing apparatus that processes a plurality of image data captured by an electron microscope, the information processing apparatus including: a binarization processing unit that binarizes the image data into a region to be length-measured and a region other than the region; a length measurement processing unit that measures dimensional data of a plurality of length-measured portions of the region to be length-measured using contour data of the region to be length-measured obtained from the binarized image data; and an output processing unit that outputs an image visually showing a correlation between the dimensional data of the plurality of length-measured portions and the plurality of parameters using process conditions including a plurality of parameters associated with the image data.

Advantages of the Invention

[0007] According to the present disclosure, it is possible to provide a technique that makes it easier to recognize the correlation between the dimensional data of the measurement points measured from a plurality of image data and the parameters of the process conditions.

Brief Description of the Drawings

[0008]

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Embodiments for Carrying Out the Invention

[0009] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In this embodiment, an example of the correlation between the film thickness dimension and parameters (process parameters) included in the process conditions will be described, but it is not limited to the film thickness dimension, and may be a pattern dimension or the like.

[0010] <System Configuration> FIG. 1 is a configuration diagram of an example of a substrate processing system 1 according to this embodiment. The substrate processing system 1 shown in FIG. 1 includes a substrate processing apparatus 10, an apparatus control controller 20, an information processing apparatus 22, an electron microscope 24, and an information storage apparatus 26.

[0011] The substrate processing apparatus 10, the apparatus control controller 20, the information processing apparatus 22, the electron microscope 24, and the information storage apparatus 26 shown in FIG. 1 are communicably connected via a network 40 such as the Internet or a LAN (Local Area Network).

[0012] The substrate processing apparatus 10 is an apparatus that performs processes such as film formation processing, etching processing, or ashing processing, and processes a substrate such as a semiconductor wafer, for example. The substrate processing apparatus 10 is, for example, a semiconductor manufacturing apparatus, a heat treatment apparatus, or a film formation apparatus.

[0013] The substrate processing apparatus 10 receives, for example, a control command (process parameter) according to a recipe (process condition) from the apparatus control controller 20 and executes the process. The substrate processing apparatus 10 is provided with a plurality of sensors such as a temperature sensor for measuring temperature and a pressure sensor for measuring pressure in order to monitor the process state.

[0014] The apparatus control controller 20 is a controller having a computer configuration for controlling the substrate processing apparatus 10. The apparatus control controller 20 has a function of a man-machine interface that receives instructions for the substrate processing apparatus 10 from an operator and provides information regarding the substrate processing apparatus 10 to the operator. The apparatus control controller 20 receives sensor values output from a plurality of sensors installed in the substrate processing apparatus 10, etc.

[0015] The apparatus control controller 20 may be provided for each substrate processing apparatus 10, or may be provided for a plurality of substrate processing apparatuses 10. The apparatus control controller 20 may be provided inside the housing of the substrate processing apparatus 10.

[0016] The electron microscope 24 is an example of an apparatus that images the processing result of the substrate processing apparatus 10 executing a process according to process conditions and outputs image data. For example, the electron microscope 24 images, as an example of the processing result, the state of the film (film thickness) on the substrate processed by the substrate processing apparatus 10 according to process conditions and outputs image data. The substrate is an example of an object to be imaged.

[0017] The information storage device 26 receives and stores a plurality of image data of the object to be imaged imaged by the electron microscope 24. Further, the information storage device 26 may store the process conditions when the substrate processing apparatus 10 processes the object to be imaged in association with the image data of the object to be imaged. Further, the information storage device 26 may receive sensor values output from a plurality of sensors installed in the substrate processing apparatus 10 and store them as a process log.

[0018] The information processing device 22 is a computer that analyzes a plurality of image data of the object to be imaged imaged by the electron microscope 24. The information processing device 22 has a function of a man-machine interface that receives instructions such as analysis from an operator and displays the analysis result, etc. and provides it to the operator.

[0019] The information processing apparatus 22 receives image data of the measurement target from the electron microscope 24 or the information storage device 26. Further, the information processing apparatus 22 receives process conditions associated with the image data of the object to be imaged from the information storage device 26. Note that the information processing apparatus 22 may associate the process conditions input by the operator with the image data of the measurement target received from the electron microscope 24 or the information storage device 26. The image data of the measurement target or the process conditions may be input to the information processing apparatus 22 using a portable recording medium.

[0020] The information processing apparatus 22 measures the dimensional data of the measurement target, such as the film thickness on the substrate, for each measurement location by processing a plurality of image data of the object to be imaged captured by the electron microscope 24 as described later. Further, the information processing apparatus 22 outputs an image visually showing the correlation between the dimensional data of a plurality of measurement locations and the process parameters included in the process conditions by processing as described later.

[0021] Note that the substrate processing system 1 shown in FIG. 1 is an example, and it goes without saying that there are various system configuration examples depending on the application and purpose. The division of the devices of the apparatus control controller 20, the information processing apparatus 22, the electron microscope 24, and the information storage device 26 shown in FIG. 1 is an example. The substrate processing system 1 can have various configurations, such as a configuration in which at least two of the apparatus control controller 20, the information processing apparatus 22, the electron microscope 24, and the information storage device 26 are integrated, or a further divided configuration.

[0022] <Hardware Configuration> The apparatus control controller 20, the information processing apparatus 22, and the information storage device 26 of the substrate processing system 1 shown in FIG. 1 are realized by a computer having a hardware configuration as shown in FIG. 2, for example. FIG. 2 is a hardware configuration diagram of an example of a computer 500.

[0023] The computer 500 in FIG. 2 includes an input device 501, an output device 502, an external I / F (interface) 503, a RAM (Random Access Memory) 504, a ROM (Read Only Memory) 505, a CPU (Central Processing Unit) 506, a communication I / F 507, and an HDD (Hard Disk Drive) 508, etc., and they are all interconnected by a bus B. The input device 501 and the output device 502 may be in a form that can be connected and used when necessary.

[0024] The input device 501 is a keyboard, a mouse, a touch panel, etc., and is used for an operator or the like to input an operation signal. The output device 502 is a display or the like, and displays the processing result by the computer 500. The communication I / F 507 is an interface for connecting the computer 500 to the network 40 shown in FIG. 1. The HDD 508 is an example of a non-volatile storage device that stores programs and data.

[0025] The external I / F 503 is an interface with an external device. The computer 500 can read a recording medium 503a such as an SD (Secure Digital) memory card via the external I / F 503. The external I / F 503 may also be able to write to a recording medium 503a such as an SD memory card via the external I / F 503.

[0026] The ROM 505 is an example of a non-volatile semiconductor memory (storage device) in which programs and data are stored. The RAM 504 is an example of a volatile semiconductor memory (storage device) that temporarily holds programs and data. The CPU 506 is an arithmetic unit that realizes the control and functions of the entire computer 500 by reading programs and data from a storage device such as the ROM 505 or the HDD 508 onto the RAM 504 and executing the processing.

[0027] The apparatus controller 20, information processing apparatus 22, and information storage apparatus 26 of the substrate processing system 1 shown in FIG. 1 realize various functions by executing a program on the computer 500 shown in FIG. 2.

[0028] <Functional configuration> The information processing apparatus 22 of the substrate processing system 1 according to the present embodiment is realized, for example, with the functional configuration shown in FIG. 3. FIG. 3 is a configuration diagram showing an example of the functions of the information processing apparatus 22 according to the present embodiment. Note that FIG. 3 omits illustration of functions unnecessary for the description of the present embodiment.

[0029] The information processing apparatus 22 realizes an image data acquisition unit 50, an image data storage unit 52, a process condition acquisition unit 54, a process condition storage unit 56, an image data selection processing unit 58, a smoothing processing unit 60, a binarization processing unit 62, a contour detection processing unit 64, a length measurement processing unit 66, an operation reception unit 68, and an output processing unit 70 by executing a program.

[0030] The image data acquisition unit 50 acquires a plurality of pieces of image data captured by the electron microscope 24. The image data storage unit 52 stores the plurality of pieces of image data acquired by the image data acquisition unit 50.

[0031] The process condition acquisition unit 54 acquires the process conditions when the substrate processing apparatus 10 processes the object to be imaged imaged by the electron microscope 24. The process condition storage unit 56 stores the process conditions acquired by the process condition acquisition unit 54 in association with the plurality of pieces of image data stored in the image data storage unit 52.

[0032] The image data selection processing unit 58 selects the image data to be measured from the image data stored in the image data storage unit 52. The image data selection processing unit 58 may select the image data to be measured from the image data stored in the image data storage unit 52 according to the selection operation received from the operator by the operation reception unit 68. Further, the image data selection processing unit 58 may select the image data to be measured from the image data stored in the image data storage unit 52 according to the selection conditions (such as the designation of the substrate processing apparatus 10 that has processed the object to be imaged) received from the operator by the operation reception unit 68.

[0033] The smoothing processing unit 60 reduces the noise included in the image data of the measurement target selected by the image data selection processing unit 58. The binarization processing unit 62 determines the binarization threshold as described below based on the image histogram of the image data of the measurement target with reduced noise. The image histogram represents the pixels included in the image data as a graph with the horizontal axis being the pixel value of the pixel and the vertical axis being the number of pixels with the pixel value. The binarization processing unit 62 may determine the binarization threshold according to the setting operation received from the operator by the operation reception unit 68. The binarization processing unit 62 may automatically determine the binarization threshold based on the image histogram of the image data of the measurement target. The binarization processing unit 62 uses the determined binarization threshold to binarize the image data of the measurement target into a measurement target area (for example, an area where the film is imaged) and other areas.

[0034] The contour detection processing unit 64 detects the boundary of the measurement target area from the binarized image data of the measurement target. The contour detection processing unit 64 acquires the coordinates of the boundary pixels to obtain the contour data of the measurement target area.

[0035] The dimension measurement processing unit 66 measures the dimension data of a plurality of measurement points in the measurement target area using the contour data of the measurement target area obtained from the binarized image data of the measurement target. For example, the dimension measurement processing unit 66 can measure the actual dimension of the measurement point from the distance (number of pixels) between the contour data of the measurement target area.

[0036] The operation reception unit 68 receives various operations from the operator and notifies the content of the operation to a function corresponding to the operation received from the operator. The output processing unit 70 uses process conditions including a plurality of process parameters associated with the image data of the measurement target to output an image (for example, a mapping image described later) that visually shows the correlation between the dimensional data of a plurality of measurement locations and the plurality of process parameters.

[0037] <Process> FIG. 4 is a flowchart of an example of the processing of the information processing apparatus 22 according to the present embodiment.

[0038] In step S10, the image data selection processing unit 58 of the information processing apparatus 22 selects, for example, the image data 1000 of the measurement target shown in FIG. 5 from the image data stored in the image data storage unit 52.

[0039] FIG. 5 is an image diagram of an example of the image data 1000 of the measurement target. The image data 1000 is a microscope image (SEM image) obtained by imaging a film on a substrate processed by the substrate processing apparatus 10 with the electron microscope 24.

[0040] In step S12, the smoothing processing unit 60 of the information processing apparatus 22 smooths the image data 1000 of the measurement target shown in FIG. 5, for example, blurs the image to reduce the influence of noise included in the image data 1000. The smoothing processing unit 60 may perform smoothing of the image data 1000 using Bilateral Blur, which is an example of an edge-preserving smoothing filter. Bilateral Blur is based on a Gaussian filter.

[0041] The smoothing processing unit 60 smooths the image data 1000 of the measurement target shown in FIG. 5, and blurs the image like the image data 1010 of the measurement target shown in FIG. 6 while leaving (emphasizing) the edge portions. FIG. 6 is an image diagram of an example of the image data 1010 of the measurement target with reduced noise.

[0042] Note that the information processing apparatus 22 may perform Gaussian fitting processing before the processing of the binarization processing unit 62. The Gaussian fitting processing is a process of performing fitting on the image histogram of the image data to be measured and obtaining an approximate expression.

[0043] Before the processing of the binarization processing unit 62, by performing Gaussian fitting processing and determining a binarization threshold from the obtained approximate expression, the information processing apparatus 22 can obtain, by the processing of the binarization processing unit 62, the binarized image data 1030 of the measurement target as shown in, for example, FIG. 7, in which the boundary of the region to be measured is clear.

[0044] FIG. 7 is an image diagram of an example of the image data 1020 and 1030 of the measurement target. The image data 1020 of the measurement target is an example of the binarized image data of the measurement target when Gaussian fitting processing is not performed before the processing of the binarization processing unit 62. Further, the image data 1030 of the measurement target is an example of the binarized image data of the measurement target when Gaussian fitting processing is performed before the processing of the binarization processing unit 62.

[0045] In step S14, the binarization processing unit 62 determines a binarization threshold for detecting pixels having the color of the region to be measured based on the image histogram of the image data to be measured as shown in, for example, FIGS. 8 and 9. FIG. 8 is a diagram showing an example of the image histogram of the image data to be measured. FIG. 9 is a diagram showing an example of the relationship between the image histogram of the image data to be measured and the region to be measured. The image histograms shown in FIGS. 8 and 9 represent the pixels included in the image data as a graph with the horizontal axis being the pixel value of the pixel (black: 0 to white: 255) and the vertical axis being the number of pixel values.

[0046] The image histogram of the image data of the measurement target shown in FIG. 9 indicates the range of pixel values of the pixels representing the film region in the image data of the measurement target by the position and width of the highest middle peak. Also, the image histogram of the image data of the measurement target shown in FIG. 9 indicates the range of pixel values of the pixels close to white other than the film region in the image data of the measurement target by the position and width of the second highest right peak.

[0047] If the region to be measured is the film region, the binarization processing unit 62 determines the binarization threshold value for detecting the pixels in the region to be measured in the image data of the measurement target based on the position and width of the highest middle peak of the image histogram in FIG. 8. For example, the binarization processing unit 62 uses the two pixel values at the position of the peak width (the position corresponding to the valley between the peaks) of the image histogram in FIG. 8 as the binarization threshold values.

[0048] In step S16, the binarization processing unit 62 uses the binarization threshold value determined in step S14 to convert the image data 1040 of the measurement target shown in FIG. 10, for example, into two colors, white and black, like the image data 1050 of the measurement target shown in FIG. 10. FIG. 10 is an image diagram of an example of the image data 1040 of the measurement target and the binarized image data 1050 of the measurement target.

[0049] In the binarized image data 1050 of the measurement target in FIG. 10, the region to be measured (for example, the region representing the film) is represented in white, and the region other than the region to be measured (for example, the region representing other than the film) is represented in black. The binarization processing unit 62 converts the color of the pixels detected by the binarization threshold value determined in step S14 and the color of the pixels not detected by the binarization threshold value into different colors, white or black, to binarize the image data 1040 of the measurement target into the region to be measured and the other region like the image data 1050 of the measurement target.

[0050] In step S18, the contour detection processing unit 64 detects the boundary of the region to be measured from the binarized image data 1050 of the measurement target. The contour detection processing unit 64 acquires the coordinates of the boundary pixels and detects the contour data of the region to be measured.

[0051] In step S20, the length measurement processing unit 66 measures the dimensional data of a plurality of length measurement points of the region to be measured using the contour data of the region to be measured detected in step S18, as shown in FIG. 11 for example. FIG. 11 is an image diagram showing an example of a plurality of length measurement points 1052 to 1058 of the binarized image data 1050 of the region to be measured. In FIG. 11, as an example of a plurality of length measurement points, the top length measurement point 1052, the top-side length measurement point 1054, the middle-side length measurement point 1056, and the btm-side length measurement point 1058 are shown. Note that the length measurement points 1052 to 1058 in FIG. 11 are examples, and it is desirable to provide more detailed length measurement points.

[0052] The length measurement processing unit 66 can measure the actual dimensions of the length measurement points 1052 to 1058 using the distance (number of pixels) between the contour data of the regions of the length measurement points 1052 to 1058 indicated by arrows in FIG. 11 for example and the magnification at the time of imaging.

[0053] In step S22, the output processing unit 70 acquires the process conditions associated with the binarized image data 1050 of the region to be measured from the process condition storage unit 56. In step S24, the output processing unit 70 outputs a mapping image visually showing the correlation between the dimensional data of the plurality of length measurement points 1052 to 1058 and the plurality of process parameters using the plurality of process parameters included in the process conditions associated with the image data of the region to be measured.

[0054] FIG. 12 is a graph diagram showing an example of the correlation between the dimensional data of the plurality of length measurement points 1052 to 1058 and the process parameters. The graph diagram in FIG. 12 shows that the horizontal axis represents the gas flow rate which is an example of the process parameters, and the vertical axis represents the dimensional data of the length measurement points 1052 to 1058.

[0055] In FIG. 12, the dimensional data of a plurality of measurement locations 1052 to 1058 of the image data of the measurement target processed under the process conditions where the process parameter of the gas flow rate is “500”, “1000”, “1500”, and “2000” are plotted. In FIG. 12, the correlation coefficient is calculated for each measurement location using the plots of the dimensional data of the same measurement location with different values of the process parameter of the gas flow rate. For example, in FIG. 12, the change in the dimensional data of the top measurement location 1052 is larger than the changes in the dimensional data of the measurement locations 1054 to 1058 other than the top, and it can be seen that the process parameter of the gas flow rate is effective for the film thickness control of the top measurement location 1052. Also, in FIG. 12, the correlation coefficient between the gas flow rate, which is an example of the process parameter, and the dimensional data of the plurality of measurement locations 1052 to 1058 can be obtained from the plot of the dimensional data of the top measurement location 1052.

[0056] In step S24, the output processing unit 70 outputs a mapping image that visually shows the correlation between the dimensional data of a plurality of measurement locations of the image data 1000 of the measurement target and a plurality of process parameters for each process parameter.

[0057] FIG. 13 is an image diagram of an example of a mapping image showing the correlation between the dimensional data of a plurality of measurement locations of the image data 1000 of the measurement target and a plurality of process parameters for each process parameter. The image diagram shown in FIG. 13 shows, as an example, the mapping image of the gas flow rate, which is an example of the process parameter, and the mapping image of the stage temperature.

[0058] The mapping image in FIG. 13 superimposes the correlation coefficient with the process parameter calculated for each dimensional data of the plurality of measurement locations on the plurality of measurement locations of the image data 1000 of the measurement target and displays it, for example, by a change in color.

[0059] For example, by referring to the mapping image of the gas flow rate in FIG. 13, the operator can recognize that the gas flow rate is effective for the film thickness control at the top measurement location and not very effective for the film thickness control at measurement locations other than the top. Also, by referring to the mapping image of the stage temperature in FIG. 13, the operator can recognize that the stage temperature is effective for the film thickness control at the measurement locations on the middle - side and btm - side and not very effective for the film thickness control at the measurement locations on the top and top - side.

[0060] In the process of step S10, the mapping image in FIG. 13 can be output by selecting, as the image data to be measured, the image data associated with the central process conditions and a plurality of image data in which the process parameters included in the central process conditions are changed.

[0061] The mapping image in FIG. 13 is an example in which the measurement locations are provided more finely than the plurality of measurement locations 1052 - 1058 of the binarized image data 1050 to be measured. By providing the measurement locations finely, the mapping image can also represent the correlation between the dimensional data of the measurement locations of the image data 1000 to be measured and the process parameters in the form of a color gradation.

[0062] Note that for the output of the mapping image in step S24, a list of a plurality of mapping images may be displayed, or the mapping image of the process parameters selected by the operator may be displayed. Also, for the output of the mapping image in step S24, the mapping images may be classified and displayed. For example, for the output of the mapping image in step S24, the mapping images may be classified and output, such as the process parameters effective for the film thickness control at the top measurement location.

[0063] When the analysis of the mapping image by the operator is completed (YES in S26), the information processing device 22 ends the processing of the flowchart in FIG. 4.

[0064] <Summary> For example, when attempting to analyze the dimensional data of the length-measured locations measured from the captured image captured by an electron microscope by expressing it in the form of a table or graph by the operator's hand, subjective evaluation of the operator is involved and it cannot be said to be objective evaluation. Also, in the analysis by the operator's hand, as the number of length-measured locations increases, the amount of data becomes enormous, so it is difficult to increase the number of length-measured locations due to time problems.

[0065] In the present embodiment, using process conditions including a plurality of process parameters associated with the image data of the length measurement target, an image that visually shows the correlation between the dimensional data of a plurality of length measurement locations and the plurality of process parameters is automatically output.

[0066] Therefore, according to the present embodiment, an objective analysis result can be obtained instead of the subjective analysis result of the operator, so the reliability of the analysis result is increased. Also, according to the present embodiment, significant time reduction can be achieved by automating the process that was analyzed manually by the operator.

[0067] Also, according to the present embodiment, from the image that visually shows the correlation between the dimensional data of a plurality of length measurement locations and the plurality of process parameters, the operator can more easily recognize the process parameters that are effective or not effective for controlling the dimensional data of the plurality of length measurement locations.

[0068] Therefore, the operator can easily grasp the process parameters (knobs) that are effective or not effective for shape control even for, for example, a complex pattern shape.

[0069] According to the substrate processing system 1 according to the present embodiment, a technique can be provided that makes it easier to recognize the correlation between the dimensional data of the length measurement locations measured from a plurality of image data and the parameters of the process conditions.

[0070] As described above, the preferred embodiments of the present invention have been described in detail, but the present invention is not limited to the above-described embodiments, and various modifications and substitutions can be made to the above-described embodiments without departing from the scope of the present invention.

Description of Reference Numerals

[0071] 1 Substrate processing system 10 Substrate processing apparatus 20 Equipment control controller 22 Information processing apparatus 24 Electron microscope 26 Information storage device 40 Network 62 Binarization processing unit 66 Length measurement processing unit 70 Output processing unit

Claims

1. An information processing apparatus for processing a plurality of image data captured by an electron microscope, comprising: a binarization processing unit that binarizes the image data into a region to be measured and a region other than the region to be measured; a length measurement processing unit that measures dimension data of a plurality of length measurement points in the region to be measured using contour data of the region to be measured obtained from the binarized image data; an output processing unit that outputs an image visually showing a correlation relationship between the dimension data of the plurality of length measurement points and the plurality of parameters using a process condition including the plurality of parameters associated with the image data; An information processing apparatus having the above.

2. The output processing unit outputs, for each parameter of the process condition, an image visually showing a correlation relationship between the dimension data of the plurality of length measurement points and the plurality of parameters. The information processing apparatus according to Claim 1.

3. The output processing unit superimposes and displays a correlation coefficient with the plurality of parameters calculated for each dimension data of the plurality of length measurement points on the plurality of length measurement points of the image data. The information processing apparatus according to Claim 1 or 2.

4. The plurality of parameters associated with the image data are the plurality of parameters included in the process condition when processing the object to be imaged, and the output processing unit calculates the correlation coefficient for each of the plurality of length measurement points using the dimension data of the same length measurement points of the plurality of image data associated with different values of the parameters. The information processing apparatus according to Claim 3.

5. The output processing unit superimposes and displays, on the plurality of length measurement points of the image data, a color indicating the correlation coefficient with one of the parameters. The information processing apparatus according to Claim 3.

6. A program for causing an information processing apparatus for processing a plurality of image data captured by an electron microscope to execute a binarization processing step of binarizing the image data into a region to be measured and a region other than the region to be measured, a length measurement processing step of measuring dimension data of a plurality of length measurement points in the region to be measured using contour data of the region to be measured obtained from the binarized image data, an output processing step of outputting an image visually showing a correlation relationship between the dimension data of the plurality of length measurement points and the plurality of parameters using a process condition including the plurality of parameters associated with the image data.

7. An information processing method for an information processing apparatus that processes a plurality of image data captured by an electron microscope, comprising: Binarize the image data into a region to be measured and other regions; Measure the dimensional data of a plurality of measurement points in the region to be measured using the contour data of the region to be measured obtained from the binarized image data; Output an image visually showing the correlation between the dimensional data of the plurality of measurement points and the plurality of parameters using process conditions including a plurality of parameters associated with the image data; An information processing method having the above.

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