WO2024014185A1 - 画像処理方法、画像処理装置、走査型プローブ顕微鏡、およびプログラム - Google Patents

画像処理方法、画像処理装置、走査型プローブ顕微鏡、およびプログラム Download PDF

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WO2024014185A1
WO2024014185A1 PCT/JP2023/021094 JP2023021094W WO2024014185A1 WO 2024014185 A1 WO2024014185 A1 WO 2024014185A1 JP 2023021094 W JP2023021094 W JP 2023021094W WO 2024014185 A1 WO2024014185 A1 WO 2024014185A1
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Prior art keywords
image
correction
substrate
data
image processing
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English (en)
French (fr)
Japanese (ja)
Inventor
雅人 平出
賢治 山▲崎▼
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Shimadzu Corp
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Shimadzu Corp
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Priority to CN202380052807.7A priority Critical patent/CN119522369A/zh
Priority to JP2024533572A priority patent/JP7810264B2/ja
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01Q—SCANNING-PROBE TECHNIQUES OR APPARATUS; APPLICATIONS OF SCANNING-PROBE TECHNIQUES, e.g. SCANNING PROBE MICROSCOPY [SPM]
    • G01Q30/00—Auxiliary means serving to assist or improve the scanning probe techniques or apparatus, e.g. display or data processing devices
    • G01Q30/04—Display or data processing devices
    • G01Q30/06—Display or data processing devices for error compensation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01Q—SCANNING-PROBE TECHNIQUES OR APPARATUS; APPLICATIONS OF SCANNING-PROBE TECHNIQUES, e.g. SCANNING PROBE MICROSCOPY [SPM]
    • G01Q60/00—Particular types of SPM [Scanning Probe Microscopy] or microscopes; Essential components thereof
    • G01Q60/10—STM [Scanning Tunnelling Microscopy] or apparatus therefor, e.g. STM probes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01Q—SCANNING-PROBE TECHNIQUES OR APPARATUS; APPLICATIONS OF SCANNING-PROBE TECHNIQUES, e.g. SCANNING PROBE MICROSCOPY [SPM]
    • G01Q60/00—Particular types of SPM [Scanning Probe Microscopy] or microscopes; Essential components thereof
    • G01Q60/24—AFM [Atomic Force Microscopy] or apparatus therefor, e.g. AFM probes

Definitions

  • the present invention relates to the processing of images obtained by a scanning probe microscope.
  • a scanning probe microscope uses a sufficiently sharpened probe brought close enough to the sample to be observed, and the height of the probe is adjusted so that the physical quantity acting on the tip of the probe and the surface of the sample remains constant. By scanning the sample surface in the horizontal direction with a probe while moving the probe up and down, the unevenness of the sample surface can be observed with high resolution.
  • SPM is a general term for microscopes that observe the unevenness of a sample surface using the above operating principle.
  • a typical SPM is a scanning tunneling microscope (STM) that detects the current flowing between the probe and the sample as an interaction.
  • Scanning Tunneling Microscope Scanning Tunneling Microscope
  • AFM Atomic Force Microscope
  • a scanning probe microscope has high resolution in the surface height direction, and it is difficult to set the sample surface horizontally at that level of resolution. Therefore, it is common to perform height correction on a height image (hereinafter referred to as an SPM image) acquired with a scanning probe microscope so that the inclined surface becomes horizontal.
  • an SPM image a height image acquired with a scanning probe microscope so that the inclined surface becomes horizontal.
  • Patent Document 1 discloses that at least a part of a region other than edges in image data is extracted as a reference plane region, A technique is disclosed for correcting the height of measurement data based on height information of three points belonging to the reference plane area.
  • the present invention was devised in view of the above-mentioned circumstances, and its purpose is to identify the type of correction to be made in accordance with the surface condition of the sample for images of the sample generated based on measurements with a scanning probe microscope.
  • the aim is to provide the technology to do so.
  • An image processing method is a method of processing a target image generated based on measurement of a sample with a scanning probe microscope, the method comprising: performing a first correction on the target image;
  • the first correction includes extracting a plurality of pixels on a straight line along a predetermined direction in a predetermined plane from the target image, and based on the brightness of each extracted pixel. correcting the height of the target image; generating a histogram of pixel values in the corrected image; and using the histogram, a second correction different from the first correction is required for the target image. and a step of determining whether or not.
  • An image processing device includes one or more processors and a storage device that stores a program that is executed by the one or more processors and causes the one or more processors to perform the above-described image processing method. Be prepared.
  • a scanning probe microscope includes the above-described image processing device.
  • a program according to an aspect of the present disclosure is executed by one or more processors, thereby causing the one or more processors to perform the above-described image processing method.
  • a corrected image is generated by performing a first correction on a target image, and a second correction is performed on the target image using a histogram of pixel values in the corrected image. It is determined whether correction is necessary.
  • the histogram of pixel values reflects the surface condition of the sample. Therefore, according to an aspect of the present disclosure, it is determined whether the second correction is necessary depending on the surface condition of the sample, and thereby the type of correction depending on the surface condition of the sample can be specified. .
  • FIG. 1 is a schematic configuration diagram of a scanning probe microscope according to an embodiment.
  • FIG. 3 is a diagram for explaining the contents of the first correction.
  • FIG. 2 is a diagram showing an example of the shape of a sample observed with a scanning probe microscope.
  • 4 is a graph showing the height along the Y1-Y1 line in FIG. 3.
  • FIG. 7 is a diagram showing another example of the shape of a sample observed with a scanning probe microscope. 6 is a graph showing the height along the Y2-Y2 line in FIG. 5.
  • FIG. FIG. 3 is a diagram schematically showing the result of edge extraction for an image obtained as an observation result using a scanning probe microscope.
  • FIG. 3 is a diagram schematically showing the result of processing to expand extracted edges.
  • FIG. 1 is a schematic configuration diagram of a scanning probe microscope according to an embodiment.
  • FIG. 3 is a diagram for explaining the contents of the first correction.
  • FIG. 2 is a diagram showing an example of the shape of a sample observed with a scanning
  • FIG. 3 is a diagram schematically showing the results of binarization processing.
  • FIG. 3 is a diagram schematically showing the result of hole-filling processing.
  • FIG. 3 is a diagram schematically illustrating a data structure of a substrate region.
  • 3 is a diagram schematically showing a part of a tilt correction process in the scanning probe microscope 1.
  • FIG. 3 is a diagram schematically showing a part of a tilt correction process in the scanning probe microscope 1.
  • FIG. 3 is a flowchart of an example of processing performed for image processing in the scanning probe microscope 1.
  • FIG. It is a figure which shows an example of the histogram produced
  • FIG. 7 is a diagram showing another example of a histogram generated in step SA3.
  • step SA5 is a flowchart of a subroutine regarding implementation of the second correction in step SA5. It is a flowchart of the 1st modification of the subroutine of step SA5 in modification (1). It is a flowchart of the 2nd modification of the subroutine of step SA5.
  • FIG. 1 is a schematic configuration diagram of a scanning probe microscope according to an embodiment.
  • An example of a scanning probe microscope is an atomic force microscope. Note that the scanning probe microscope may be another type of scanning probe microscope (for example, a scanning tunneling microscope).
  • a scanning probe microscope 1 includes a sample stage 112 on which a sample 110 is placed, a piezo scanner 111 that displaces the sample stage, a cantilever 113 having a probe 114 formed at its tip, and a cantilever. 113, a feedback signal generating section 131, a computer 132, a scanning signal generating section 133, a storage device 134, and a display section 135.
  • computer 132 includes at least one processor, and storage 134 non-volatilely stores programs executed by the processor.
  • the piezo scanner 111 includes a Z scanner 111z that generates displacement in the Z direction based on the voltage value Vz, and an XY scanner 111xy that generates displacement in the XY direction based on the voltage values Vx and Vy.
  • the displacement detection mechanism 120 includes a laser diode 115 and a photodetector 119.
  • the laser light emitted from the laser diode 115 is reflected by the back surface of the cantilever 113, and the reflected light is received by the photodetector 119. be done.
  • the cantilever 113 bends like a leaf spring, and the amount of bending is observed at the light receiving position of the photodetector 119.
  • the feedback signal generator 131 receives a detection signal from the photodetector 119. Feedback signal generator 131 calculates the amount of deflection of cantilever 113 based on the detection signal. The feedback signal generator 131 controls the position of the sample in the Z direction so that the atomic force between the probe 114 and the surface of the sample 110 is always constant. The feedback signal generation unit 131 calculates a voltage value Vz for displacing the piezo scanner 111 in the Z-axis direction based on the amount of deflection of the cantilever 113, and outputs it to the Z scanner 111z.
  • the scanning signal generator 133 calculates voltage values Vx and Vy in the X-axis and Y-axis directions so that the sample 110 moves relative to the probe 114 in the XY plane according to a predetermined scanning pattern. , and output to the XY scanner 111xy.
  • a signal reflecting the amount of feedback in the Z-axis direction (voltage Vz applied to the scanner and deviation signal Sd) is also sent to the computer 132 and stored in the storage device 134.
  • the computer 132 calculates the surface displacement due to the unevenness of the sample 110 from the voltage Vz based on the correlation information indicating the relationship between the voltage Vz and the corresponding amount of surface displacement due to the unevenness of the sample 110, which is stored in the storage device 134 in advance. Calculate the amount.
  • the computer 132 reproduces a three-dimensional image of the sample surface by calculating the amount of displacement at each position in the X-axis and Y-axis directions, and depicts this on the screen of the display unit 135.
  • This three-dimensional image data is also stored in the storage device 134.
  • the data includes coordinates indicating the position on the XY plane and the sample height at the coordinates.
  • the computer 132 can read the three-dimensional image data stored in the storage device 134 and display it on the display unit 135 at any time
  • the computer 132 can perform height correction on the three-dimensional image data as necessary and display the data on the display unit 135.
  • the computer 132 may perform at least two types of height corrections.
  • the two types of corrections may be referred to as “first correction” and “second correction,” respectively.
  • the computer 132 corrects the surface of the sample 110, which should originally be horizontal, along a predetermined direction in the image of the surface, as described in Japanese Patent No. 6,631,647.
  • the brightness of a plurality of pixels on a straight line is extracted, and the height is corrected based on the brightness of the extracted plurality of pixels.
  • FIG. 2 is a diagram for explaining the contents of the first correction.
  • FIG. 2 shows an image IM90 as an example of a surface image of the sample 110.
  • a specific example of the sample 110 corresponding to the image IM90 includes, for example, a pattern manufactured by a semiconductor process.
  • FIG. 2 also shows the same X and Y axes as in FIG.
  • a line L90 is a straight line along the Y axis, and represents the straight line from which the brightness of the image is extracted in the first correction.
  • the computer 132 As an example of the second correction, the computer 132 generates an image that specifies a region where the sample 110 corresponds to the substrate, and performs height correction on the image. The second correction will be explained below.
  • FIG. 3 is a diagram showing an example of the shape of a sample observed with a scanning probe microscope.
  • 16 structures are arranged on the substrate.
  • the 16 structures are arranged in four rows in the X-axis direction and four rows in the Y-axis direction, that is, in a 4x4 configuration.
  • An example of the substrate is a mica board.
  • An example of a structure is a nanoparticle or nanofiber of a biological sample. Note that these are just examples, and the sample (substrate, structure) targeted by the scanning probe microscope 1 is not limited to these.
  • the shading of pixels in image IM01 represents the height in the Z-axis direction. Darker pixels represent higher positions in the sample in the Z-axis direction. Thin pixels represent positions lower in the sample in the Z-axis direction.
  • FIG. 4 is a graph showing the height along the Y1-Y1 line in FIG. 3.
  • the line L30 represents the height generated based on ideal observation by the scanning probe microscope 1. More specifically, line L30 represents one line of image data observed in an ideal case where there is no tilt of the substrate in the sample.
  • the plane boundary (the boundary between the substrate and the structure) is shown as a line, but in FIG. 4, the actual sample shape is shown to facilitate understanding of the correction process.
  • a taper is provided at the plane boundary to make it closer.
  • the horizontal axis indicates the position in the X direction, and the Z axis indicates the height at each X position. Note that when the probe scans along the X direction, the X axis also corresponds to the time axis.
  • FIG. 5 is a diagram showing another example of the shape of a sample observed with a scanning probe microscope.
  • Image IM10 shown in FIG. 5 corresponds to the same sample as sample 110 that corresponds to image IM01 shown in FIG.
  • shading occurs on the same plane.
  • large shading occurs in areas other than the areas corresponding to the 16 structures (areas corresponding to the substrate).
  • One of the reasons why such shading occurs is that the sample 110 is installed at an angle on the sample stage 112.
  • FIG. 6 is a graph showing the height along the Y2-Y2 line in FIG. 5.
  • line L10 represents the height of sample 110 assumed from line Y2-Y2 of image IM10.
  • the line L10 indicates that the surface of the sample 110 is inclined such that the larger the X coordinate is, the higher the surface of the sample 110 is.
  • the scanning probe microscope 1 applies correction to an image generated based on observation results, such as the image IM10, and provides the corrected image. Thereby, the surface state of the sample 110 can be more accurately recognized from the corrected image. The details of the correction added to the image will be explained below.
  • FIG. 7 is a diagram schematically showing the result of edge extraction for an image obtained as an observation result using a scanning probe microscope.
  • the image IM11 shown in FIG. 7 is processed by a known process for edge extraction (Process/ Find Edges, etc.).
  • the process of extracting edges to obtain the image IM11 typically includes differential processing of the height image. Furthermore, the processing for extracting edges may use a general outline extraction method used in photo processing techniques and the like. In one example, a portion where the absolute value of the difference between adjacent pixel data exceeds a certain threshold value may be extracted.
  • pixels forming the boundaries between each of the 16 structures and the substrate are detected as edges and are shown as black pixels.
  • each pixel detected as an edge is an example of an edge pixel.
  • FIG. 8 is a diagram schematically showing the result of the process of expanding the extracted edges.
  • the image IM12 shown in FIG. 8 is obtained by subjecting the image IM11 of FIG. 7 to maximum value processing.
  • edge pixels are shown as black pixels (pixels with relatively high pixel values). Therefore, by performing the maximum value processing on the image IM11, in the image IM12 shown in FIG. 8, edges formed by edge pixels are expanded.
  • Image IM12 is an example of an "expanded image.”
  • processing for edge expansion is not limited to maximum value processing.
  • the type of processing for edge expansion can be changed as appropriate depending on the expression mode of edge pixels. For example, when an edge pixel is expressed as a white pixel (pixel having a relatively low pixel value), minimum value processing may be employed as the processing for edge expansion.
  • FIG. 9 is a diagram schematically showing the results of the binarization process.
  • the image IM13 shown in FIG. 9 is processed by a known binarization process (open source ImageJ (https://imagej.nih.gov/ij/)) with respect to the image IM12 of FIG. Process/Binary/Make Binary etc.).
  • the threshold value for binarization may be adjusted by the user and/or computer 132 as appropriate.
  • the computer 132 may perform line connection processing on the binarized image IM13. This allows the edge pixels detected in image IM10 to more accurately represent the outer edge of the structure.
  • the line connection process can be realized, for example, by a known technique (Process/Binary/Close in open source ImageJ (https://imagej.nih.gov/ij/), etc.).
  • the computer 132 may perform hole filling processing on the binarized image IM13 (or the image obtained by performing line connection processing on the image IM13).
  • FIG. 10 is a diagram schematically showing the results of the hole filling process.
  • the hole filling process can be realized, for example, by a known technique (Process/Binary/Fill Holes in open source ImageJ (https://imagej.nih.gov/ij/), etc.).
  • areas of the sample 110 corresponding to each of the 16 structures are represented filled with black pixels, and other areas are represented filled with white pixels. ing.
  • the computer 132 can extract a white pixel region from the image IM14 shown in FIG. 10 as a region of the sample corresponding to the substrate (a region where no structure is placed). Data specifying a region corresponding to a substrate (substrate region) is also referred to as "substrate region data.”
  • FIG. 11 is a diagram for schematically explaining the data structure of the substrate area.
  • FIG. 11 includes lines L11, L12, L13, L14, and L15 that indicate the height along the Y3-Y3 line in FIG. 10 in the substrate area.
  • each end of the lines L11 to L15 is located inside by a length D1.
  • FIG. 12 is a diagram schematically showing a part of the tilt correction process in the scanning probe microscope 1.
  • data filled (interpolated) to make the lines L11 to L15 shown in FIG. 11 into one line is shown by a broken line.
  • the line formed by data interpolation is shown as line A10.
  • computer 132 generates a straight line (line A10) inferred from the points making up lines L11-L15 during data interpolation.
  • Generation of a straight line is an example of generation of data for filling. Then, the computer 132 realizes data interpolation by filling the portions other than the five lines L11 to L15 with the data of the corresponding portions of the generated straight lines.
  • the computer 132 performs data interpolation similar to that shown in FIG. 12 (generation of filling data and filling). This generates data corresponding to the entire area of the sample, that is, data representing the surface of the substrate corresponding to the entire area of the sample.
  • the image represented by the data generated here virtually represents the substrate from which the structure has been removed from the sample, and is an example of a "substrate display image.”
  • the inclination of the surface generated here is expected to represent the inclination of the sample 110 on the sample stage 112.
  • FIG. 13 is a diagram schematically showing a part of the tilt correction process in the scanning probe microscope 1.
  • the computer 132 calculates the inclination of the plane of the data generated in the process described with reference to FIG. 12 with respect to the ideal plane, and corrects the image IM10 so as to correct the calculated inclination.
  • FIG. 13 the direction of the surface of the data generated in the process described with reference to FIG. 12 is shown as line A10.
  • the ideal surface orientation is shown as line A20.
  • Computer 132 calculates the slope of line A10 with respect to line A20. This slope corresponds to the slope of the sample 110. Then, the computer 132 corrects the image IM10 (FIG. 5) so as to offset the calculated tilt. Through this correction, a line L20 is generated from the line L10, as shown in FIG. 13. Similarly, by correcting the entire area of image IM10, a corrected image is generated. This correction is expected to bring image IM10 closer to image IM01 (FIG. 3). In this specification, the image subjected to the second correction is also referred to as a "corrected image.”
  • FIG. 14 is a flowchart of an example of processing performed for image processing in the scanning probe microscope 1.
  • the process of FIG. 14 is performed by the processor of computer 132 executing a given program.
  • the scanning probe microscope 1 is an example of an image processing device.
  • step SA1 the scanning probe microscope 1 acquires image data that is the observation result.
  • An example of the image acquired here corresponds to image IM10 in FIG. 5.
  • an image that is an observation result is an example of a "target image.”
  • step SA2 the scanning probe microscope 1 performs the above-mentioned "first correction" on the target image.
  • step SA3 the scanning probe microscope 1 generates a histogram of pixel values for the target image subjected to the first correction performed in step SA2.
  • FIG. 15 is a diagram showing an example of the histogram generated in step SA3. As shown in FIG. 15, the horizontal axis of the histogram represents pixel values, and the vertical axis of the histogram represents the number of pixels. In the example of FIG. 15, the number of each pixel value in the target image is represented by a line L91. Line L91 has a peak at pixel value V11.
  • step SA4 the scanning probe microscope 1 determines whether the number of peaks in the histogram generated in step SA3 is plural.
  • the number and position of peaks in the histogram are identified, for example, by performing a known peak detection process on the histogram. Note that the scanning probe microscope 1 may perform smoothing processing on the graph shown by line L91 before the peak detection processing.
  • the number and location of peaks in the histogram may be specified by the user. That is, the scanning probe microscope 1 may display the histogram generated in step SA3 on the display unit 135. The user may look at the histogram displayed on the display unit 135, specify the number (and position) of peaks, and input the number to the scanning probe microscope 1.
  • the scanning probe microscope 1 includes an input device such as a keyboard, and the user may input the number (and position) of peaks using the input device. The scanning probe microscope 1 may use the input number of peaks to make the determination in step SA4.
  • step SA4 determines that the number of peaks in the histogram is plural (YES in step SA4), the control proceeds to step SA6, and if it determines otherwise, that is, the number of peaks is singular. If it is determined (NO in step SA4), control proceeds to step SA6.
  • step SA6 an example of the expected correlation between the number of peaks in the histogram and the surface morphology of the sample 110 will be described.
  • FIG. 16 is a diagram showing another example of the histogram generated in step SA3.
  • the number of each pixel value in the target image is represented by a line L92.
  • Line L92 has peaks at pixel value V21 and pixel value V22. That is, line L92 has two peaks.
  • Whether there are multiple peaks in the histogram reflects whether the surface of the sample 110 has an uneven structure. More specifically, when the surface of the sample 110 has an uneven structure, it is assumed that the histogram of the image of the surface has multiple peaks. For example, when a structure is placed on a substrate in a sample as explained with reference to FIG. 3, the multiple peaks correspond to the height of the substrate and the height of the structure. peaks. On the other hand, if the surface of the sample 110 does not have an uneven structure (in a macro sense) as explained with reference to FIG. 2, it is assumed that the histogram of the image of the surface has a single peak. be done.
  • step SA5 the scanning probe microscope 1 performs a second correction on the target image. Implementation of the second correction will be described later with reference to FIG. 17.
  • the scanning probe microscope 1 displays the processing results on the display section 135.
  • the displayed results may include an image generated by the first correction or the second correction as the corrected image.
  • the image displayed as a corrected image is the image that has been subjected to the second correction when the second correction in step SA6 has been performed; If not, the image has been subjected to the first correction. After that, the scanning probe microscope 1 ends the process of FIG. 14.
  • FIG. 17 is a flowchart of a subroutine regarding implementation of the second correction in step SA5.
  • step S10 the scanning probe microscope 1 acquires a target image. If the target image acquired in step SA1 is stored in the storage device 134, the target image may be read from the storage device 134 in step S10.
  • step S12 the scanning probe microscope 1 extracts edges from the image acquired in step S10. Edge extraction is achieved, for example, by the method described with reference to FIG.
  • step S14 the scanning probe microscope 1 expands the edge extracted in step S12. Edge dilation is achieved, for example, by the technique described with reference to FIG.
  • step S16 the scanning probe microscope 1 binarizes the image whose edges have been expanded in step S14. Binarization is realized, for example, by the method described with reference to FIG.
  • step S18 the scanning probe microscope 1 performs line connection processing on the image binarized in step S16.
  • the line connection process is realized, for example, by the method described with reference to FIG.
  • step S20 the scanning probe microscope 1 performs hole-filling processing on the image subjected to the line connection processing in step S18.
  • the hole filling process is realized, for example, by the method described with reference to FIG.
  • step S22 the scanning probe microscope 1 generates substrate area data using the image subjected to the hole-filling process in step S20.
  • the substrate area data is data that specifies a substrate area.
  • step S24 the scanning probe microscope 1 uses the second data to correct the image data acquired in step S10 (height correction). Correction of image data is realized, for example, by the method described with reference to FIGS. 12 and 13. Through the control in step S24, an image in which the "second correction" is applied to the "target image” is generated. The scanning probe microscope 1 then returns control to FIG. 14.
  • data specifying a substrate region is filled with data in a region corresponding to a structure, as shown by a broken line (line A10) in FIG. It was done. Note that in the correction of image data, such data filling may be omitted.
  • the scanning probe microscope 1 may calculate the inclination of the sample 110 (with respect to an ideal plane) only from the substrate area.
  • the first correction is applied to the target image, and furthermore, a histogram of the image subjected to the first correction is generated. If the number of peaks in the histogram is plural, the second corrected image is displayed as the "corrected image” in step SA6. On the other hand, if the number of peaks in the histogram is not plural, the first corrected image is displayed as the "corrected image” in step SA6.
  • an "expanded image” is generated by performing dilation processing on the edge of the structure, and then, using the “expanded image", an area of the sample corresponding to the substrate (structures on the substrate) is used.
  • “Substrate area data” that specifies areas (areas where no objects exist) is generated. This reliably prevents the image of the structure from being included in the area specified by the "substrate area data.” Further, areas other than the area specified by the "substrate area data" are reliably specified as an area including the entire structure.
  • the region specified by the "substrate region data" is used to correct the tilt in the target image caused by the tilt of the sample, more points (or lines or regions) can be used for the correction. Thereby, the tilt can be corrected more accurately during correction. Therefore, the surface state of the sample can be accurately provided to the user.
  • Modification (1) In modified example (1), in the second correction, the scanning probe microscope 1 corrects the target image using the substrate area data, and again identifies the area corresponding to the structure from the corrected image data. .
  • FIG. 18 is a flowchart of a first modification of the subroutine of step SA5 in modification (1).
  • the process in FIG. 18 includes control in steps S10 to S24, similar to the process in FIG. In the process of FIG. 18, the scanning probe microscope 1 advances the control to step S30 after step S24.
  • step S30 the scanning probe microscope 1 identifies a region corresponding to the structure in the corrected image generated in step S24.
  • the corrected image generated in step S24 is an example of a "corrected image.”
  • the identification of the region corresponding to the structure in step S30 may include, for example, the same control as steps S12 to S22. That is, the scanning probe microscope 1 extracts edges from the corrected image, dilates the extracted edges, binarizes the edge-dilated image, and converts the binarized image to Line connection processing is performed, hole filling processing is performed on the image subjected to line connection processing, and board area data of the image subjected to hole filling processing is generated. Then, the scanning probe microscope 1 identifies a region other than the region specified by the substrate region data (that is, a region other than the substrate region) as a region corresponding to the structure.
  • step S32 the scanning probe microscope 1 generates a "structure image" by extracting a region corresponding to the structure identified in step S30 from the image data corrected in step S24.
  • the structure image includes an image corresponding to a structure.
  • the scanning probe microscope 1 returns control to FIG. 14.
  • the results displayed in step SA6 may include an image of the structure image generated in step S30, that is, an image corresponding to the structure.
  • a region other than the region specified by the substrate region data (that is, a region other than the substrate region) is extracted from the target image and displayed as a structure image.
  • the substrate area data is generated using an expanded image, and the expanded image is generated through expansion processing. This ensures that the entire area of the structure is included in the area other than the area specified by the substrate area data. Therefore, the state of the structure can be accurately provided to the user, and thereby the surface state of the sample can be accurately provided.
  • Modification (2) the scanning probe microscope 1 generates a pseudo image of the entire sample by combining the structure image of modification (1) with background data that fills the area of the substrate. .
  • the "pseudo-image of the whole sample" generated in this way is an image subjected to the second correction.
  • FIG. 19 is a flowchart of a second modification of the subroutine of step SA5.
  • the scanning probe microscope 1 advances the control to step S40 after step S22.
  • step S40 the scanning probe microscope 1 generates a structure image using the target image acquired in step S10 and the substrate area data generated in step S22.
  • the structure image generated in step S40 is generated by extracting an area other than the area of the substrate specified by the substrate area data generated in step S22 from the target image acquired in step S10.
  • step S42 the scanning probe microscope 1 generates viewing data by filling an area other than the area specified by the structure image generated in step S40 with background data.
  • the data for viewing represents a pseudo image of the entire sample. In the pseudo image of the whole sample, the structure in the target image acquired in step S10 and the background image are combined.
  • the scanning probe microscope 1 returns control to FIG. 14.
  • the results displayed in step SA6 may include an image of the viewing data generated in step S42, that is, a pseudo image of the entire sample.
  • the area corresponding to the substrate area has appropriate brightness, which makes it possible to improve the contrast when displaying the image of the data for viewing. No adjustment required. Therefore, the user can visually check the processing results without having to perform complicated operations such as contrast adjustment. Furthermore, in the conventional technology, a wave in pixel density may occur in the background during contrast adjustment. In modification (2), the contrast adjustment can be omitted, so that it is possible to avoid the above-mentioned wave of pixel density from occurring in the image displayed to the user.
  • the viewing data may be generated by combining the structure image (S30) generated in modification (1) and the background data (S42).
  • the image of the entire pseudo sample includes an image of a region other than the region specified by the substrate region data from the target image.
  • the substrate area data is generated using an expanded image, and the expanded image is generated through expansion processing. This ensures that the entire area of the structure is included in the area other than the area specified by the substrate area data. Therefore, by providing a pseudo image of the entire sample, the user can be provided with an accurate state of the structure, and thereby an accurate surface state of the sample.
  • An image processing method is a method of processing a target image generated based on measurement of a sample with a scanning probe microscope, the method comprising: performing a first correction on the target image;
  • the first correction includes extracting a plurality of pixels on a straight line along a predetermined direction in a predetermined plane from the target image, and correcting the height of the target image based on pixel brightness, and generating a histogram of pixel values in the corrected image; and using the histogram, and a step of determining whether a second correction different from the correction is necessary.
  • the type of correction depending on the surface condition of the sample can be specified.
  • the step of determining whether or not the second correction is necessary includes, if the histogram includes a plurality of peaks, the step of determining whether or not the second correction is necessary.
  • the method may include determining that correction is necessary, and determining that the second correction is unnecessary if the histogram does not include a plurality of peaks.
  • the sample includes a substrate and a structure on the substrate, and the second correction is performed on the substrate in the target image.
  • the method may include the steps of: generating substrate area data specifying an area corresponding to the substrate area data; and performing height correction based on pixels of the area specified by the substrate area data.
  • an accurate surface state of the sample can be provided by the second correction.
  • the second correction is a step of extracting, as an edge pixel, a pixel that satisfies a condition that a comparison result with an adjacent pixel is an edge from the target image. and generating an expanded image by performing expansion processing on the target image to expand an edge formed by the edge pixels, and the step of generating the substrate area data includes:
  • the method may include generating the substrate area data using the expanded image.
  • a more accurate surface state of the sample can be provided by the second correction.
  • the expansion process may include maximum value processing.
  • the configuration is reliably expanded by edge pixels in the expansion process.
  • the second correction may be performed on an area other than the area specified by the substrate area data in the target image.
  • the method may include generating a substrate display image representing an image of only the substrate by filling data for filling.
  • the height of the original image data can be corrected more accurately.
  • generating the substrate display image includes using the pixel values of the area specified by the substrate area data in the target image to It may include generating data.
  • data for filling can be generated as data that more closely matches the original image data.
  • generating the board display image includes correction by performing tilt correction on the target image using the board display image.
  • the method may also include generating a post-image.
  • an image whose tilt has been more reliably corrected can be generated as the corrected image.
  • the image processing method according to Item 8 includes the steps of: identifying, in the corrected image, an area corresponding to the structure in the target image; The method may further include a step of generating a structure image in which a region corresponding to the region is extracted.
  • data including the entire structure can be generated more reliably as a structure image.
  • the image processing method according to any one of Items 3 to 9 generates a structure image by extracting a region specified by the substrate region data from the target image.
  • the method may further include a step of doing so.
  • an image that includes the entire structure can be generated more reliably as a structure image.
  • the image processing method according to Paragraph 9 or 10 combines the structure data and background data having background pixels in the region specified by the substrate region data. , the method may further include the step of generating data for viewing.
  • contrast adjustment is not required when displaying data for viewing.
  • the image processing method according to Section 4 or 5 performs binarization processing on the expanded image or data resulting from the expanded image in order to generate the substrate area data. It may further include steps.
  • edges can be expressed more clearly in the data.
  • the image processing method according to Item 12 may further include the step of performing line connection processing on the image subjected to the binarization processing in order to generate the substrate area data. good.
  • the region corresponding to the substrate in the data can be specified more reliably.
  • the image processing device includes one or more processors, and the one or more processors, by being executed by the one or more processors, provides the one or more items of the items 1 to 13. and a storage device that stores a program for implementing the image processing method described in .
  • the type of correction depending on the surface condition of the sample can be specified.
  • a scanning probe microscope may include the image processing device described in Section 14.
  • the type of correction depending on the surface condition of the sample can be specified.
  • the program according to one aspect causes the one or more processors to perform the image processing method according to any one of Items 1 to 13 by being executed by one or more processors. You can.
  • the type of correction depending on the surface condition of the sample can be specified.
  • Scanning probe microscope 110. Sample, 111. Piezo scanner, 111.xy. 1 Feedback signal generation section, 132 Computer, 133 Scanning signal generation section, 134 Storage device, 135 Display section.

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PCT/JP2023/021094 2022-07-11 2023-06-07 画像処理方法、画像処理装置、走査型プローブ顕微鏡、およびプログラム Ceased WO2024014185A1 (ja)

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Citations (5)

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JPH1138019A (ja) * 1997-07-17 1999-02-12 Seiko Instr Inc 走査型プローブ顕微鏡
JPH11142416A (ja) * 1997-11-12 1999-05-28 Olympus Optical Co Ltd 走査型プローブ顕微鏡における測定データの補正方法
JP2010203999A (ja) * 2009-03-05 2010-09-16 Shimadzu Corp 特定部位検出方法、及び該方法を用いた試料分析装置
JP2019158387A (ja) * 2018-03-08 2019-09-19 株式会社島津製作所 走査型プローブ顕微鏡及び表面画像補正方法
JP2021043096A (ja) * 2019-09-12 2021-03-18 株式会社日立ハイテク パターン高さ情報補正システム及びパターン高さ情報の補正方法

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Publication number Priority date Publication date Assignee Title
JP4136157B2 (ja) * 1999-02-09 2008-08-20 オリンパス株式会社 分子測長方法

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH1138019A (ja) * 1997-07-17 1999-02-12 Seiko Instr Inc 走査型プローブ顕微鏡
JPH11142416A (ja) * 1997-11-12 1999-05-28 Olympus Optical Co Ltd 走査型プローブ顕微鏡における測定データの補正方法
JP2010203999A (ja) * 2009-03-05 2010-09-16 Shimadzu Corp 特定部位検出方法、及び該方法を用いた試料分析装置
JP2019158387A (ja) * 2018-03-08 2019-09-19 株式会社島津製作所 走査型プローブ顕微鏡及び表面画像補正方法
JP2021043096A (ja) * 2019-09-12 2021-03-18 株式会社日立ハイテク パターン高さ情報補正システム及びパターン高さ情報の補正方法

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