Data processing method, program, image processing device, and scanning probe microscope

Abstract

A computer (132): acquires image data (step S10); extracts, as edge pixels, pixels that satisfy a condition in which a comparison result with adjacent pixels from the image data is an edge (step S12); and generates first data by executing extension processing that extends the edge composed of the corresponding edge pixels (step S14). In addition, the computer (132) generates second data that specifies an area corresponding to a substrate in a specimen by using the first data (step S22).

Description

[Technical Field]

[0001] The present invention relates to the processing of images obtained by scanning probe microscopes. [Background technology]

[0002] A scanning probe microscope (SPM) observes the topography of a sample surface with high resolution by bringing a sharpened probe close enough to the sample to be observed and scanning the sample surface horizontally with the probe while raising or lowering the probe height so that the physical quantities acting on the tip of the probe and the sample surface remain constant. SPM is a general term for microscopes that observe the topography of a sample surface using the above operating principle. Representative SPMs include the scanning tunneling microscope (STM), which detects the current flowing between the probe and sample as an interaction, and the atomic force microscope (AFM), which detects the atomic force acting between the probe and sample as an interaction.

[0003] Scanning probe microscopes have high resolution in the surface height direction, and it is difficult to set the sample surface horizontally at that resolution level. Therefore, height correction is generally performed on the height image acquired by the scanning probe microscope (hereinafter referred to as SPM image) to correct the inclined surface so that it is horizontal. By providing the corrected image instead of the SPM image, the user can more accurately recognize the surface condition of the sample.

[0004] As an example of processing images obtained by such a scanning probe microscope, Japanese Patent Application Laid-Open No. 2019-164090 (Patent Document 1) discloses height correction of measurement data. More specifically, Patent Document 1 discloses a technique for extracting at least a portion of the area other than the edge in the image data as a reference plane area and correcting the height of the measurement data based on height information of three points belonging to the reference plane area. According to this technique, when a sample is composed of a substrate including a structure, if the edge of the structure is accurately detected, the three points used in image processing belong to the area corresponding to the substrate. In other words, three points selected from the area corresponding to the substrate are used in image processing. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2019-164090 Summary of the Invention [Problem to be solved by the invention]

[0006] In the above-mentioned techniques, there are cases where the edges of structures are not detected accurately, and in such cases, the SPM image cannot be accurately corrected, and as a result, an accurate image of the sample's surface condition cannot be provided to the user.

[0007] The present invention has been devised in view of the above circumstances, and its purpose is to provide a technique for providing a user with an accurate surface condition of a sample. [Means for solving the problem]

[0008] A data processing method according to one aspect of the present disclosure is a method for processing image data of a sample including a substrate and a structure on the substrate, generated based on measurements by a scanning probe microscope, and includes the steps of acquiring the image data, extracting pixels from the image data as edge pixels that satisfy the condition that they are edges when compared with adjacent pixels, generating first data by performing an expansion process on the image data to expand edges formed by the edge pixels, and using the first data to generate second data that identifies an area on the sample corresponding to the substrate.

[0009] A program according to an aspect of the present disclosure causes a computer to perform the above-described data processing method.

[0010] An image processing device according to an aspect of the present disclosure implements the above-described data processing method. A scanning probe microscope according to an aspect of the present disclosure includes the image processing device described above. [Effects of the Invention]

[0011] According to one aspect of the present disclosure, techniques are provided for providing a user with accurate surface conditions for a sample. [Brief explanation of the drawings]

[0012] [Figure 1] 1 is a schematic configuration diagram of a scanning probe microscope according to a first embodiment. [Figure 2] FIG. 1 is a diagram showing an example of the shape of a sample observed with a scanning probe microscope. [Figure 3] 3 is a graph showing the height along the Y1-Y1 line in FIG. 2. [Figure 4] 10A and 10B are diagrams showing other examples of the shape of a sample observed with a scanning probe microscope. [Figure 5] 5 is a graph showing the height along the Y2-Y2 line in FIG. 4. [Figure 6]FIG. 10 is a diagram schematically showing the results of edge extraction for an image obtained as an observation result using a scanning probe microscope. [Figure 7] FIG. 10 is a diagram illustrating the results of a process of expanding extracted edges. [Figure 8] FIG. 10 is a diagram schematically illustrating the results of binarization processing. [Figure 9] FIG. 10 is a diagram schematically illustrating the results of filling processing. [Figure 10] FIG. 2 is a diagram for schematically explaining the data configuration of a board area. [Figure 11] 3A to 3C are diagrams showing a part of the process of tilt correction in the scanning probe microscope 1. [Figure 12] 3A to 3C are diagrams showing a part of the process of tilt correction in the scanning probe microscope 1. [Figure 13] 10 is a flowchart of an example of processing carried out for image processing in the scanning probe microscope 1. [Figure 14] 10 is a flowchart of an example of processing performed in the scanning probe microscope 1 of the second embodiment. [Figure 15] 11 is a flowchart of an example of processing performed in the scanning probe microscope 1 of the third embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0013] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail with reference to the accompanying drawings, in which the same or corresponding parts are designated by the same reference numerals and will not be described repeatedly.

[0014] [Embodiment 1] <Schematic configuration of a scanning probe microscope> 1 is a schematic diagram of a scanning probe microscope according to embodiment 1. An example of a scanning probe microscope is an atomic force microscope. However, the scanning probe microscope may be another type of scanning probe microscope (for example, a scanning tunneling microscope).

[0015] 1, the scanning probe microscope 1 includes a sample stage 112 on which a sample 110 is placed, a piezoelectric scanner 111 that displaces the sample stage, a cantilever 113 having a probe 114 formed at the tip thereof, a displacement detection mechanism 120 that detects the displacement of the cantilever 113, a feedback signal generator 131, a computer 132, a scanning signal generator 133, a storage device 134, and a display device 135. In one implementation example, the computer 132 includes at least one processor, and the storage device 134 non-temporarily (non-volatilely) stores a program executed by the processor.

[0016] The piezo scanner 111 includes a Z scanner 111z that generates a displacement in the Z direction based on a voltage value Vz, and an XY scanner 111xy that generates a displacement in the X and Y directions based on voltage values ​​Vx and Vy.

[0017] Displacement detection mechanism 120 includes laser diode 115 and photodetector 119. In scanning probe microscope 1, when the tip of probe 114 is brought close to sample 110 to observe the surface, laser light emitted from laser diode 115 is reflected by the back surface of cantilever 113, and the reflected light is received by photodetector 119. As probe 114 is brought closer to the surface of sample 110, cantilever 113 bends like a leaf spring, and the amount of bending is observed at the light receiving position of photodetector 119.

[0018] The feedback signal generating unit 131 receives a detection signal from the photodetector 119. The feedback signal generating unit 131 calculates the amount of deflection of the cantilever 113 based on the detection signal. The feedback signal generating unit 131 controls the Z-direction position of the sample so that the atomic force between the probe 114 and the surface of the sample 110 is always constant. The feedback signal generating 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 the voltage value Vz to the Z scanner 111z.

[0019] The scanning signal generating unit 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 outputs them to the XY scanner 111xy.

[0020] A signal reflecting the feedback amount in the Z-axis direction (the voltage Vz applied to the scanner and the deviation signal Sd) is also sent to the computer 132 and stored in the storage device 134. The computer 132 calculates the amount of surface displacement due to the unevenness of the sample 110 from the voltage Vz based on correlation information previously stored in the storage device 134, which indicates the relationship between the voltage Vz and the corresponding amount of surface displacement due to the unevenness of the sample 110. The computer 132 reconstructs 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 displays 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 those coordinates. The computer 132 can read out the three-dimensional image data stored in the storage device 134 at any time and display it on the display unit 135.

[0021] The computer 132 can correct the height of the three-dimensional image data as needed and display it on the display unit 135 .

[0022] <Ideal observation example> FIG. 2 is a diagram showing an example of the shape of a sample observed with a scanning probe microscope. In sample 110 corresponding to image IM01 shown in FIG. 2, 16 structures are arranged on a substrate. The 16 structures are arranged in four rows in the X-axis direction and four rows in the Y-axis direction, i.e., a 4x4 configuration. An example of a substrate is a mica plate. An example of a structure is nanoparticles or nanofibers of a biological sample. Note that these are merely examples, and the samples (substrates, structures) that the scanning probe microscope 1 targets are not limited to these.

[0023] The shade of the pixels in image IM01 represents the height along the Z axis. Darker pixels represent higher positions in the sample along the Z axis. Lighter pixels represent lower positions in the sample along the Z axis.

[0024] Fig. 3 is a graph showing height along the Y1-Y1 line in Fig. 2. In the graph of Fig. 3, line L30 represents 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.

[0025] In image IM01 in Figure 2, the planar boundary (the boundary between the substrate and the structure) is shown by a line, but in Figure 3, to make it easier to understand the correction process, the planar boundary is tapered to resemble the actual sample shape. The horizontal axis indicates the position in the X direction, and the Z axis indicates the height at each X position. When the probe is scanned along the X direction, the X axis also corresponds to the time axis.

[0026] <Example of observation with a tilted sample> FIG. 4 shows another example of the shape of a sample observed with a scanning probe microscope. Image IM10 shown in FIG. 4 corresponds to the same sample as sample 110 corresponding to image IM01 shown in FIG. 2. Image IM10 shows shading variations on the same plane. In particular, image IM10 shows large shading variations in the areas other than the areas corresponding to the 16 structures (the areas corresponding to the substrate). One of the reasons for this shading variation is that sample 110 was placed at an angle on sample stage 112.

[0027] Fig. 5 is a graph showing the height along the Y2-Y2 line in Fig. 4. In Fig. 5, line L10 represents the height of the sample 110 estimated from the Y2-Y2 line in image IM10. Line L10 indicates that the surface of the sample 110 is inclined such that the surface of the sample 110 becomes higher as the X coordinate increases.

[0028] In the scanning probe microscope 1, corrections are made to an image generated based on observation results such as image IM10, and a corrected image is provided. This allows the surface state of the sample 110 to be recognized more accurately from the corrected image. The details of the corrections made to the image are explained below.

[0029] <Edge extraction> Fig. 6 is a diagram showing the result of edge extraction for an image obtained as an observation result with a scanning probe microscope. In one implementation example, image IM11 shown in Fig. 6 is obtained by performing a known process for edge extraction (such as Process / Find Edges in the open source ImageJ (https: / / imagej.nih.gov / ij / )) on image IM10.

[0030] The process of extracting edges to obtain image IM11 typically involves differential processing of the height image. Alternatively, the process of extracting edges may use a contour extraction method commonly used in photo processing techniques. For example, the part where the absolute value of the difference between adjacent pixel data exceeds a certain threshold may be extracted.

[0031] In image IM11, the pixels that form the boundaries between each of the 16 structures and the substrate are detected as edges and are shown as black pixels. Each of the pixels detected as an edge is an example of an edge pixel.

[0032] <Edge expansion> 7 is a diagram showing the result of the process of dilating the extracted edges. In one implementation, the image IM12 shown in FIG. 7 is obtained by performing maximum value processing on the image IM11 of FIG.

[0033] In image IM11 of Fig. 6, edge pixels are shown as black pixels (pixels having relatively high pixel values). Therefore, by performing maximum value processing on image IM11, edges formed by edge pixels are expanded in image IM12 shown in Fig. 7. Data for displaying image IM12 is an example of "first data."

[0034] The process for edge expansion is not limited to maximum value processing. The type of process for edge expansion can be changed as appropriate depending on the representation of edge pixels, etc. For example, if edge pixels are represented as white pixels (pixels having relatively low pixel values), minimum value processing may be adopted as the process for edge expansion.

[0035] <Binarization> Fig. 8 is a diagram schematically illustrating the result of a binarization process. In one implementation example, image IM13 shown in Fig. 8 is obtained by performing a known binarization process (such as Process / Binary / Make Binary in the open source ImageJ (https: / / imagej.nih.gov / ij / )) on image IM12 of Fig. 7. The threshold for binarization may be adjusted as appropriate by the user and / or the computer 132.

[0036] In the image IM13 shown in FIG. 8, portions of the sample 110 corresponding to the ends of the 16 structures are represented by black pixels, and the other portions are represented by white pixels.

[0037] <Line connection> The computer 132 may perform a line-connecting process on the binarized image IM13, so that the edge pixels detected in the image IM10 more accurately represent the outer edges of the structures. The line-connecting process can be realized, for example, by a known technique (such as Process / Binary / Close in the open source ImageJ (https: / / imagej.nih.gov / ij / )).

[0038] <Filling process> The computer 132 may perform a hole filling process on the binarized image IM13 (or an image obtained by performing a line connection process on the image IM13).

[0039] 9 is a diagram schematically illustrating the results of the hole filling process. The hole filling process can be realized by, for example, a known technique (such as Process / Binary / Fill Holes in the open source ImageJ (https: / / imagej.nih.gov / ij / )).

[0040] In the image IM14 shown in FIG. 9, the areas of the sample 110 corresponding to each of the 16 structures are represented by being filled with black pixels, and the other areas are represented by being filled with white pixels.

[0041] <Substrate area> The computer 132 can extract the region of white pixels from the image IM14 shown in Fig. 9 as a region of the sample corresponding to the substrate (a region on which no structure is placed). Data specifying the region corresponding to the substrate (substrate region) is also referred to as "second data."

[0042] Fig. 10 is a diagram for schematically explaining the data configuration of the board area, and includes lines L11, L12, L13, L14, and L15 that indicate the height of the board area along the Y3-Y3 line in Fig. 9.

[0043] 10 further shows the line L10 shown in FIG. 5 for comparison. The ends of each of the lines L11 to L15 are located a length D1 inward from the portion of the line L10 that corresponds to the substrate. This corresponds to the substrate region being identified as a region other than the region identified by the expanded edge after the detected edge of the structure is expanded. That is, in the scanning probe microscope 1, by expanding the edge of the structure, the region of the structure is broadly identified, thereby reliably avoiding the structure from being included in the substrate region.

[0044] <Tilt correction> Fig. 11 is a diagram schematically showing part of the process of tilt correction in the scanning probe microscope 1. In Fig. 11, the data that has been filled in (interpolated) to combine lines L11 to L15 shown in Fig. 10 into a single line is shown by a dashed line. The line formed by data interpolation is shown as line A10.

[0045] In one implementation example, the computer 132 generates a straight line (line A10) inferred from the points that make up lines L11 to L15 during data interpolation. The generation of the straight line is an example of generating data for filling. The computer 132 then performs data interpolation by filling the parts other than the five lines L11 to L15 with data from the corresponding parts of the generated straight line.

[0046] The computer 132 performs data interpolation (generation of data to be filled and filling of the data) similar to that shown in FIG. 11 on the entire data of the substrate area (not only the Y3-Y3 line in FIG. 9 but also other areas). This generates data corresponding to the entire area of ​​the sample, i.e., data representing the surface of the substrate corresponding to the entire area of ​​the sample. The data generated here virtually represents the substrate in a state where the structure has been removed from the sample, and is an example of "third data." The tilt of the surface generated here is expected to represent the tilt of the sample 110 on the sample stage 112.

[0047] Fig. 12 is a diagram schematically illustrating a part of the process of tilt correction in the scanning probe microscope 1. Computer 132 calculates the tilt of the data plane generated in the process described with reference to Fig. 11 relative to an ideal plane, and corrects image IM10 so as to correct the calculated tilt.

[0048] In FIG. 12, the surface orientation of the data generated in the process described with reference to FIG. 11 is shown as line A10. The ideal surface orientation is shown as line A20. The computer 132 calculates the inclination of line A10 relative to line A20. This inclination corresponds to the inclination of the sample 110. The computer 132 then corrects image IM10 ( FIG. 4 ) to offset the calculated inclination. This correction generates line L20 from line L10, as shown in FIG. 12 . Similarly, the entire area of ​​image IM10 is corrected to generate a corrected image. This correction is expected to bring image IM10 closer to image IM01 ( FIG. 2 ). In this specification, the corrected image is also referred to as “fourth data.”

[0049] <Processing flow> Fig. 13 is a flowchart of an example of a process performed for image processing in the scanning probe microscope 1. In one implementation example, the process of Fig. 13 is performed by the processor of the computer 132 executing a given program. In this sense, the computer 132 is an example of an image processing device.

[0050] In step S10, the scanning probe microscope 1 acquires image data that is the observation result. An example of the image data acquired here corresponds to the image IM10 in FIG.

[0051] In step S12, the scanning probe microscope 1 extracts edges from the image acquired in step S10. The edge extraction is realized by, for example, the method described with reference to FIG.

[0052] In step S14, the scanning probe microscope 1 dilates the edges extracted in step S12. The dilation of the edges is achieved by, for example, the method described with reference to FIG.

[0053] In step S16, the scanning probe microscope 1 binarizes the image whose edges have been dilated in step S14. The binarization is achieved by, for example, the method described with reference to FIG.

[0054] In step S18, the scanning probe microscope 1 performs line connection processing on the image binarized in step S16. The line connection processing is realized by, for example, the method described with reference to FIG.

[0055] In step S20, the scanning probe microscope 1 performs hole filling processing on the image that has been subjected to line connection processing in step S18. The hole filling processing is realized by, for example, the method described with reference to FIG.

[0056] In step S22, the scanning probe microscope 1 generates substrate area data using the image that has been subjected to the hole filling process in step S20. The substrate area data is data that identifies the substrate area, and is the above-mentioned "second data."

[0057] In step S24, the scanning probe microscope 1 uses the second data to correct (correct height) the image data acquired in step S10. The image data correction is realized, for example, by the method described with reference to FIGS.

[0058] 11 and 12, data specifying the substrate region was filled into the region corresponding to the structure, as shown by the dashed line (line A10) in FIG. 11. Note that such data filling may be omitted when correcting the image data. The scanning probe microscope 1 may calculate the tilt of the sample 110 (with respect to the ideal plane) from only the substrate region.

[0059] In step S26, the scanning probe microscope 1 displays the processing results on the display unit 135. The displayed results may include an image generated by the correction in step S24. Thereafter, the scanning probe microscope 1 ends the processing of FIG.

[0060] In the first embodiment described above, first data is generated by performing a dilation process on the edge of a structure, and the first data is used to generate second data that identifies a region of the sample corresponding to the substrate (a region on the substrate where no structure exists). This reliably prevents an image of the structure from being included in the region corresponding to the substrate identified by the second data. Furthermore, the region other than the region is reliably identified as a region including the entire structure.

[0061] When the area specified by the second data is used to correct the tilt in the original image data caused by the tilt of the sample, more points (or lines or areas) can be used for the correction. This allows the tilt to be corrected more accurately. Therefore, the surface condition of the sample can be accurately provided to the user.

[0062] [Embodiment 2] In the second embodiment, the scanning probe microscope 1 corrects the original image data using the substrate region data, and identifies the region corresponding to the structure again from the corrected image data.

[0063] FIG. 14 is a flowchart of an example of processing performed in the scanning probe microscope 1 according to the second embodiment.

[0064] The process of Fig. 14 includes the controls of steps S10 to S24, similar to the process of Fig. 13. After step S24, the process of Fig. 14 advances control to step S30.

[0065] In step S30, the scanning probe microscope 1 identifies an area corresponding to the structure in the corrected image data generated in step S24. The corrected image data generated in step S24 is an example of "fourth data."

[0066] Identifying 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 data, expands the extracted edges, binarizes the edge-expanded image, performs line connection processing on the binarized image, performs hole filling processing on the image that has been subjected to line connection processing, and generates substrate region data for the image that has been subjected to hole filling processing. Then, the scanning probe microscope 1 identifies a region other than the substrate region identified by the substrate region data as a region corresponding to the structure.

[0067] In step S32, the scanning probe microscope 1 generates "structure data" by extracting an area corresponding to the structure identified in step S30 from the image data corrected in step S24. The structure data includes an image corresponding to the structure.

[0068] In step S34, the scanning probe microscope 1 displays the results of the processing on the display unit 135. The displayed results may include an image of the structure data generated in step S30, i.e., an image corresponding to the structure. Thereafter, the scanning probe microscope 1 ends the processing of FIG. 14.

[0069] In the second embodiment described above, an area other than the area specified by the second data is extracted from the original image data and displayed as structure data. The second data is generated using the first data, and the first data is generated through an expansion process. This ensures that the area other than the area specified by the second data includes the entire structure. Therefore, the user can be provided with an accurate view of the structure's condition, which in turn can provide an accurate view of the surface condition of the sample.

[0070] [Embodiment 3] In the third embodiment, the scanning probe microscope 1 generates a pseudo image of the entire sample by combining the structure data of the second embodiment with background data that fills in the substrate area.

[0071] FIG. 15 is a flowchart of an example of processing performed in the scanning probe microscope 1 of the third embodiment.

[0072] The process of Fig. 15 includes the controls of steps S10 to S22, similar to the process of Fig. 13. After step S22, the process of Fig. 15 advances control to step S40.

[0073] In step S40, the scanning probe microscope 1 generates structure data using the image data acquired in step S10 and the substrate region data generated in step S22. The structure data generated in step S40 is generated by extracting, from the image data acquired in step S10, regions other than the region of the substrate identified by the substrate region data generated in step S22.

[0074] In step S42, the scanning probe microscope 1 generates viewing data by filling in the areas other than the areas specified by the structure data generated in step S40 with background data. The viewing data represents a pseudo image of the entire sample. This image combines the structure in the image data acquired in step S10 with the background image.

[0075] In step S44, the scanning probe microscope 1 displays the results of the processing on the display unit 135. The displayed results may include an image of the viewing data generated in step S42, i.e., a pseudo image of the entire sample. Thereafter, the scanning probe microscope 1 ends the processing of FIG. 14.

[0076] In the image of the viewing data of the third embodiment (a pseudo image of the entire sample), the area corresponding to the substrate region has appropriate brightness, which eliminates the need for contrast adjustment when displaying the image of the viewing data. Therefore, the user can visually confirm the results of processing without the need for tedious tasks such as adjusting contrast. Furthermore, in conventional techniques, contrast adjustment can sometimes result in fluctuations in pixel density in the background. In the third embodiment, contrast adjustment can be omitted, thereby preventing the occurrence of such fluctuations in pixel density in the image displayed to the user. The viewing data may be generated by combining the structure data (S30) and background data (S42) generated in the second embodiment.

[0077] The pseudo-image of the entire sample includes an image of an area other than the area specified by the second data from the original image data. The second data is generated using the first data, and the first data is generated through an expansion process. This ensures that the area other than the area specified by the second data includes the entire structure. Therefore, by providing a pseudo-image of the entire sample, the user can be provided with an accurate representation of the structure's condition, which in turn can provide an accurate representation of the sample's surface condition.

[0078] [Aspect] It will be appreciated by those skilled in the art that the exemplary embodiments described above are examples of the following aspects.

[0079] (Item 1) A data processing method according to one embodiment is a method for processing image data of a sample including a substrate and a structure on the substrate, generated based on measurements using a scanning probe microscope, and may include the steps of acquiring the image data, extracting pixels from the image data that satisfy the condition that they are edges as a result of comparison with adjacent pixels, generating first data by performing an expansion process on the image data to expand edges formed by the edge pixels, and using the first data to generate second data that identifies an area in the sample corresponding to the substrate.

[0080] According to the data processing method described in paragraph 1, a technique is provided for providing the user with an accurate surface condition of a sample.

[0081] (Item 2) In the data processing method described in Item 1, the expansion process may include maximum value processing.

[0082] According to the data processing method described in paragraph 2, the structure is reliably dilated by edge pixels in the dilation process.

[0083] (Clause 3) The data processing method described in clause 1 or 2 may further include a step of generating third data representing an image of only the substrate by filling areas of the image data other than the area specified by the second data with filling data.

[0084] According to the data processing method described in paragraph 3, the height of the original image data can be corrected more accurately.

[0085] (Clause 4) In the data processing method described in clause 3, the step of generating the third data may include generating the filling data using pixel values ​​of an area in the image data identified by the second data.

[0086] According to the data processing method described in Section 4, data for filling can be generated that is more compatible with the original image data.

[0087] (Clause 5) In the data processing method described in clause 3 or 4, the step of generating the third data may include generating fourth data by performing tilt correction on the image data using the third data.

[0088] According to the data processing method described in paragraph 5, image data whose tilt has been corrected more reliably can be generated as the fourth data.

[0089] (Clause 6) The data processing method described in clause 5 may further include a step of identifying an area in the image data corresponding to the structure in the fourth data, and a step of generating structure data by extracting the area corresponding to the identified structure from the image data.

[0090] According to the data processing method described in paragraph 6, data including the entire structure can be generated more reliably as structure data.

[0091] (Clause 7) The data processing method described in clause 1 or clause 2 may further include a step of generating structure data by extracting an area identified by the second data from the image data.

[0092] According to the data processing method described in paragraph 7, data including the entire structure can be generated more reliably as structure data.

[0093] (Clause 8) The data processing method described in clause 6 or clause 7 may further include a step of generating viewing data by combining the structure data with background data having background pixels in the area identified by the second data.

[0094] According to the data processing method described in paragraph 8, contrast adjustment is not required when displaying the viewing data.

[0095] (Clause 9) The data processing method described in any one of clauses 1 to 8 may further include a step of performing a binarization process on the first data or data derived from the first data in order to generate the second data.

[0096] According to the data processing method described in paragraph 9, edges can be more clearly expressed in the data.

[0097] (Item 10) The data processing method described in Item 9 may further include a step of performing a line connection process on the image that has been subjected to the binarization process in order to generate the second data.

[0098] According to the data processing method described in item 10, the area corresponding to the substrate in the data can be more reliably identified.

[0099] (Item 11) A program according to one aspect may cause a computer to execute the data processing method according to items 1 to 10.

[0100] According to the program described in paragraph 11, a technique is provided for providing a user with an accurate surface condition of a sample.

[0101] (Item 12) An image processing device according to one aspect implements the data processing method described in items 1 to 10.

[0102] According to the image processing device described in paragraph 12, a technique is provided for providing the user with an accurate image of the surface state of a sample.

[0103] (Item 13) A scanning probe microscope according to one aspect may include the image processing device according to item 12.

[0104] The scanning probe microscope described in paragraph 13 provides a technique for providing the user with an accurate surface state of a sample.

[0105] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present disclosure is defined by the claims, not by the description of the above-described embodiments, and is intended to include all modifications within the meaning and scope of the claims. Furthermore, it is intended that each technique in the embodiments can be implemented alone or, if necessary, in combination with other techniques in the embodiments to the extent possible. [Explanation of symbols]

[0106] 1 scanning probe microscope, 110 sample, 111 piezo scanner, 111xy XY scanner, 111z Z scanner, 112 sample stage, 113 cantilever, 114 needle, 115 laser diode, 119 photodetector, 120 displacement detection mechanism, 131 feedback signal generator, 132 computer, 133 scanning signal generator, 134 storage device, 135 display unit.

Claims

1. 1. A method for processing image data of a sample, including a substrate and structures on the substrate, generated based on scanning probe microscope measurements, comprising: acquiring the image data; extracting a first substrate region from the image data, the first substrate region being a region corresponding to the substrate; extracting a structure area corresponding to the structure from the image data; extracting, from the image data, pixels that satisfy a condition for being an edge as a result of comparison with adjacent pixels, as edge pixels; identifying an edge expansion region by performing an expansion process on the image data to expand an edge formed by the edge pixels; generating second data by removing the edge expansion region and the structure region from the first substrate region; and calculating a slope using the second data.

2. The data processing method according to claim 1 , wherein the expansion process includes a maximum value process.

3. 2. The data processing method according to claim 1, further comprising a step of generating third data representing an image of only the substrate from the image data by filling areas other than the area specified by the second data with filling data.

4. 4. The data processing method according to claim 3, wherein the step of generating the third data includes generating the filling data by using pixel values ​​of an area in the image data that is specified by the second data.

5. 4. The data processing method according to claim 3, wherein the step of generating the third data includes generating fourth data by performing tilt correction on the image data using the third data.

6. identifying, in the fourth data, an area corresponding to the structure in the image data; The data processing method according to claim 5 , further comprising the step of generating structure data by extracting an area corresponding to the identified structure from the image data.

7. The data processing method according to claim 1 , further comprising the step of generating structure data by extracting, from the image data, an area specified by the second data.

8. The data processing method according to claim 6, further comprising a step of generating viewing data by combining the structure data with background data having background pixels in the area specified by the second data.

9. 2. The data processing method according to claim 1, further comprising a step of performing a binarization process on data generated by performing the expansion process on the image data or on data resulting from the data, in order to generate the second data.

10. 10. The data processing method according to claim 9, further comprising the step of performing a line-connecting process on the image that has been subjected to the binarization process to generate the second data.

11. The method further comprises generating filler data that complements the data of the first substrate region; The data processing method according to claim 1 , wherein the step of calculating the gradient uses the filler data in addition to the second data.

12. A program that causes a computer to execute the data processing method according to claim 1.

13. An image processing device that performs the data processing method according to claim 1.

14. A scanning probe microscope comprising the image processing device according to claim 13.

Images