Contour extraction method, contour extraction system, and contour extraction program

Abstract

To extract a contour of a resin composition containing inorganic filler, in a crosse-sectional image.SOLUTION: A contour extraction method includes: acquiring, by a computer, a cross-sectional image of a resin composition pattern containing inorganic filler on a substrate, the image being captured by a microscope; performing predetermined filtering processing on the cross-sectional image so as to smooth the image while maintaining the contour of a region of the resin composition pattern containing inorganic filler in the cross-sectional image, to generate a first filter-processed image; perform binarization on the first processed image to generate a binarized second processed image; perform morphological processing on the second processed image to generate a binarized third processed image; and extract a contour of a predetermined region on the substrate on the basis of the third processed image.SELECTED DRAWING: Figure 6

Description

Technical Field

[0001] The present invention relates to a contour extraction method, a contour extraction system, and a contour extraction program.

Background Art

[0002] Conventionally, image processing techniques for cross-sectional images of semiconductor resists have been known.

[0003] For example, the pattern image measurement method described in Patent Document 1 is a method for measuring the sidewall angle of a pattern cross-section from an image obtained by imaging a pattern cross-section obtained with a scanning electron microscope. The method includes a step of acquiring an imaged SEM image, a step of performing image processing on the acquired image to extract contour line coordinate data of the pattern cross-section, a step of extracting coordinate values of the upper and lower parts of the pattern from the contour line coordinate data, a step of calculating the height of the pattern from the coordinate values, a step of extracting coordinate values of two points in a range for measuring the sidewall angle and calculating the height of the measurement range, a step of performing image processing on the SEM image to generate a luminance distribution signal corresponding to the coordinate values of the two points, a step of removing some signal components of the luminance distribution signal, a step of applying a cross-correlation method to the two signals after removal to calculate the peak-to-peak distance between the two signals, and a step of calculating the sidewall angle from the height of the measurement range and the signal peak-to-peak distance.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] However, in conventional image processing techniques, since the contour is extracted based on brightness, when the brightness difference in the area other than the contour part is large, the contour of a predetermined area cannot be accurately extracted. For example, in the case of a cross-sectional image of a resin composition pattern containing an inorganic filler, the inorganic filler within a predetermined area appears white while the other parts appear black, resulting in a large brightness difference within the predetermined area. In this case, the boundary between the inorganic filler with a large brightness difference and the other parts is extracted as the contour, and the contour of the predetermined area cannot be accurately extracted.

[0006] In the pattern image measurement method described in Patent Document 1, in order to solve the problem that the contour line extraction of the edge is not appropriately performed due to the influence of secondary electrons emitted from the sample surface in the depth direction of the observed cross-section, a predetermined image processing for mitigating the influence of the secondary electrons is performed. Therefore, when there is a problem that cannot be mitigated by the predetermined image processing for mitigating the influence of the secondary electrons, appropriate contour extraction cannot be performed. As described above, when an inorganic filler is included, the inorganic filler appears white in the cross-sectional image of the electron microscope image. In this case, in the cross-sectional image, since the contour part and the inorganic filler appear white, it is impossible to distinguish between the contour part and the inorganic filler in the image processing. Therefore, in the pattern image measurement method described in Patent Document 1, the contour of a predetermined area on the base material in the cross-sectional image cannot be extracted.

[0007] Therefore, an embodiment of the present invention aims to extract the contour in the cross-sectional image of a resin composition containing an inorganic filler.

Means for Solving the Problem

[0008] A contour extraction method according to an aspect of the present invention includes a computer acquiring a cross-sectional image of a resin composition pattern including an inorganic filler formed on a substrate, which is taken by a microscope, performing a predetermined filtering process on the cross-sectional image to smooth the image while maintaining the contour of the resin composition pattern including the inorganic filler in the cross-sectional image, generating a first processed image that has been filtered, performing a binarization process according to a predetermined threshold value on the first processed image, generating a second processed image that has been binarized, performing a morphology process including a predetermined number of dilation processes and a predetermined number of erosion processes on the second processed image, generating a third processed image that has been binarized, and extracting the contour of a predetermined region on the substrate based on the third processed image.

Effect of the Invention

[0009] According to an embodiment of the present invention, the contour in the cross-sectional image of the resin composition including the inorganic filler can be extracted.

Brief Description of the Drawings

[0010]

Figure 1

Figure 2A

Figure 2B

Figure 2C

Figure 2D

Figure 3A

Figure 3B

Figure 4

Figure 5A

Figure 5B

Figure 6

Figure 7

Mode for Carrying Out the Invention

[0011] With reference to the accompanying drawings, preferred embodiments of the present invention will be described. FIG. 1 is a diagram showing the configuration of a contour extraction system 100 which is an embodiment of the present invention. The contour extraction system 100 is communicably connected via a network such as the Internet to the user device 200.

[0012] The contour extraction system 100 is an information processing system realized by a contour extraction program. The contour extraction system 100 is an information processing system that extracts the contour of a predetermined region on a base material in a cross-sectional image of a resin composition pattern (hereinafter, also simply referred to as "resin composition pattern") containing an inorganic filler on the base material, which is photographed with a microscope.

[0013] First, the contour extraction system 100 acquires a cross-sectional image. Subsequently, the contour extraction system 100 performs predetermined image processing (for example, filtering processing, binarization processing, and morphological processing described later) on the cross-sectional image to generate a third processed image. Then, the contour extraction system 100 extracts the contour of a predetermined region based on the third processed image. Note that the predetermined region is an arbitrary region specified by the user in the cross-sectional image or extracted by the contour extraction system 100, and for example, is a region of the resin composition pattern described later or a region of a via portion sandwiched by the resin composition pattern. Details of the contour extraction system 100 will be described later.

[0014] The user device 200 is an information processing device used by the user of the contour extraction system 100, and is, for example, a computer, a smartphone, a tablet terminal, a personal computer, or the like.

[0015] The user can access the contour extraction system 100 using the user device 200 and provide a cross-sectional image to the contour extraction system 100. Also, the user can access the contour extraction system 100 using the user device 200 and refer to the display of the contour extracted in association with the cross-sectional image.

[0016] Note that the user device 200 may be an information processing device dedicated to the user, or may be an information processing device shared among multiple users in an organization (e.g., a company or department) to which the user belongs.

[0017] Also, in FIG. 1, one user device 200 is shown, but there may be multiple user devices 200.

[0018] Subsequently, the details of the contour extraction system 100 will be described. The contour extraction system 100 includes a storage unit 110, an acquisition unit 115, a parameter reception unit 120, a filtering processing unit 125, a binarization processing unit 130, a morphology processing unit 135, a contour extraction unit 140, a division unit 145, a rectangle setting unit 150, a measurement unit 155, and a display output unit 160. Each unit shown in FIG. 1 can be realized, for example, by using a storage area or by the processor executing a program stored in the storage area.

[0019] The storage unit 110 stores information processed in the contour extraction system 100. The storage unit 110 can store, for example, a cross-sectional image, parameter information, a first processed image, a second processed image, a third processed image, display information, and measurement result information, which will be described later.

[0020] The acquisition unit 115 acquires a cross-sectional image of the resin composition pattern on the substrate taken with a microscope and stores the acquired cross-sectional image in the storage unit 110. The cross-sectional image may be, for example, an image taken with an electron microscope (particularly, for example, a scanning electron microscope). Further, the cross-sectional image may be an image taken with an optical microscope. Even when taken with an optical microscope, a problem may occur in that the brightness difference becomes large between the inorganic filler and other parts as described later, but the contour extraction system 100 can accurately extract the contour of the resin composition pattern even in the cross-sectional image taken with an optical microscope.

[0021] Further, the cross-sectional image is a cross-sectional image of the resin composition pattern including the inorganic filler. The contour extraction system 100 can accurately extract the contour of the resin composition pattern in the cross-sectional image of the resin composition pattern including the inorganic filler.

[0022] In the conventional image processing technology, the contour of a predetermined region in the image was extracted by adjusting the brightness threshold of the image. However, in the case of a cross-sectional image of a resin composition pattern including an inorganic filler, since the inorganic filler appears white in the cross-sectional image while other parts appear black, the brightness difference may become large within the region for which the contour is to be extracted. In such a cross-sectional image, in the conventional image processing technology, the boundary between the inorganic filler and other parts was recognized as the contour, so the contour of a predetermined region in the image could not be accurately extracted. Therefore, the contour extraction system 100 can appropriately extract the contour of a predetermined region in the image by image processing using the filtering processing unit 125, the binarization processing unit 130, and the morphology processing unit 135, which will be described later, even in the case of a cross-sectional image including an inorganic filler.

[0023] The cross-sectional image may be a cross-sectional image of the resin composition pattern on a metal substrate or a resin substrate, and particularly may be a cross-sectional image of the resin composition pattern on a copper substrate, for example. The contour extraction system 100 can also clearly extract the contour of the copper part in the substrate.

[0024] The cross-sectional image may also be a cross-sectional image of a via portion sandwiched between resin composition patterns on a substrate. The contour extraction system 100 can also extract the contour of a via portion (hereinafter, also simply referred to as "via portion") sandwiched between resin composition patterns on a substrate.

[0025] In the conventional image processing technology, the contour of a region was extracted by setting a rectangle corresponding to the entire region to be subjected to contour extraction. However, since the contour shapes of the resin composition pattern, copper portion, and via portion on the substrate are indefinite, when setting a rectangle, the deviation between the actual region and the region where the rectangle is set becomes large, and the contour cannot be extracted appropriately. Therefore, the contour extraction system 100 divides a predetermined region into a plurality of rectangles and associates them by the processes of a division unit 145, a rectangle setting unit 150, and a measurement unit 155, which will be described later. For example, the widths of the resin composition pattern, copper portion, and via portion can be measured appropriately.

[0026] The cross-sectional image may also be a cross-sectional image of a resin-sealed substrate. Here, in the cross-sectional image of the resin-sealed substrate, since it is less affected by the depth direction of the cross-section, only the cross-section can be clearly photographed. Thereby, the contour extraction system 100 can extract the contour of a predetermined region on the substrate with high accuracy. As the resin used for resin sealing, for example, a commercially available epoxy resin or the like may be used.

[0027] The cross-sectional image may also be a cross-sectional image of a solder resist pattern on a substrate. The contour extraction system 100 can extract the contour of a predetermined region in the solder resist pattern with high accuracy.

[0028] The parameter reception unit 120 receives parameter information regarding parameters necessary for executing at least any one of filtering processing, binarization processing, and morphological processing (hereinafter, referred to as "image processing in the present embodiment") from the user through the user device 200, and stores the received parameter information in the storage unit 110.

[0029] The parameter reception unit 120 may receive parameter information before at least any one of the image processing operations in the present embodiment for the cross-sectional image, or may receive parameter information after at least any one of the image processing operations in the present embodiment.

[0030] When the parameter reception unit 120 receives parameter information after at least any one of the image processing operations in the present embodiment, the user may provide the parameter information to the contour extraction system 100 by referring to the contour extraction result displayed by the display information through, for example, the user device 200 on which the display information described later is displayed. Thereby, the user can provide appropriate parameter information with reference to the contour extraction result.

[0031] Also, at this time, the parameter reception unit may receive parameter information (first parameter information), and after at least any one of the image processing operations in the present embodiment described later, may receive second parameter information different from the first parameter information again. Thereby, the user can provide the second parameter information after referring to the result of the image processing in the present embodiment based on the first parameter information or the subsequent contour extraction processing, and can obtain the image processing in the present embodiment and the subsequent contour extraction result.

[0032] The filtering processing unit 125 performs a predetermined filtering process for smoothing the image while maintaining the contour of a predetermined region in the cross-sectional image on the cross-sectional image, generates a first processed image that has been filtered, and stores the generated first processed image in the storage unit 110. Here, the predetermined region in which the predetermined filtering process by the filtering processing unit 125 is performed may be, for example, a region of a resin composition pattern including an inorganic filler in the cross-sectional image.

[0033] The predetermined filtering process performed by the filtering processing unit 125 includes, for example, a Gaussian filter, an averaging filter, a median filter, a bilateral filter, etc., and may particularly be a filtering process using a bilateral filter.

[0034] Prior to the filtering process performed by the filtering processing unit 125, contrast correction may be performed. That is, the filtering processing unit 125 may perform a predetermined filtering process on the cross-sectional image subjected to contrast correction. Examples of the contrast correction include histogram equalization processing. When contrast correction is performed, when performing filtering processing on a plurality of different cross-sectional images, the contour can be accurately extracted using common parameter information.

[0035] The filtering processing unit 125 may perform a predetermined filtering process based on the parameter information. At this time, in response to the reception of the parameter information by the parameter reception unit 120, the filtering processing unit 125 may perform a predetermined filtering process, particularly in real time for example, and display the processing result to the user (for example, the user device 200). Thereby, the user can easily search for appropriate parameters while referring to the processing result.

[0036] By the filtering process, the second processed image after the binarization process described later can be smoothed, and noise existing outside a predetermined region can be removed.

[0037] The binarization processing unit 130 performs a binarization process on the first processed image according to a predetermined threshold value, generates a binarized second processed image, and stores the generated second processed image in the storage unit 110.

[0038] The binarization process performed by the binarization processing unit 130 may be, for example, a process of setting pixels with a pixel value equal to or greater than a predetermined threshold to white and pixels with a pixel value less than the predetermined threshold to black. Further, the binarization process performed by the binarization processing unit 130 may be, for example, a process of specifying the upper and lower limits of brightness and setting pixels within the range of the upper and lower limits to white and pixels outside the range of the upper and lower limits to black.

[0039] The binarization processing unit 130 may perform a binarization process based on parameter information. That is, the predetermined threshold used in the binarization process may be the value indicated by the parameter information. At this time, the binarization processing unit 130 may perform the binarization process, particularly in real time for example, in response to the reception of parameter information by the parameter reception unit 120, and display the processing result to the user (for example, the user device 200). Thereby, the user can easily search for appropriate parameters while referring to the processing result.

[0040] The morphology processing unit 135 performs a morphology process including a predetermined number of dilation processes and a predetermined number of erosion processes on the second processed image, and generates a binarized third processed image.

[0041] Here, the dilation process is, for example, a process of expanding the white pixel region in a binarized image. The erosion process is, for example, a process of shrinking the white pixel region in a binarized image. The dilation process and the erosion process may be performed using a rectangular kernel, an elliptical kernel, or a cross-shaped kernel.

[0042] Note that the morphology process executed by the morphology processing unit 135 by the dilation process and the erosion process includes, for example, an opening process of performing a dilation process after an erosion process and a closing process of performing an erosion process after a dilation process. In the morphology process, the number and order of the opening process and the closing process are not limited.

[0043] The morphological processing unit 135 may perform morphological processing based on the parameter information. That is, the morphological processing unit 135 may execute at least one of the opening processing and the closing processing in the number and order indicated by the parameter information based on the parameter information. At this time, the binarization processing unit 130 may perform morphological processing, for example, in real time, in response to the reception of the parameter information by the parameter reception unit 120, and display the processing result to the user (for example, the user device 200). Thereby, the user can easily search for appropriate parameters while referring to the processing result.

[0044] By performing morphological processing, it is possible to fill in portions that may be recognized as black and missing within a predetermined region of the cross-sectional image, and to remove portions that may be recognized as white and noise in regions outside the predetermined region. Thereby, the contour of the resin composition pattern containing the inorganic filler can be accurately extracted.

[0045] Figs. 2A to 2D are diagrams showing examples of image processing in the present embodiment.

[0046] Fig. 2A is a diagram showing an example of a cross-sectional image acquired by the acquisition unit 115. The cross-sectional image shown in Fig. 2A is, for example, an image taken with a scanning electron microscope, and includes a region 203 showing a copper portion of the base material, a region 202 showing a resin portion used for sealing, and a region 201 showing a resin composition pattern containing an inorganic filler.

[0047] As shown in Fig. 2A, the cross-sectional image may include an amorphous copper portion and also includes an inorganic filler that appears white. Therefore, with conventional image processing techniques, it has not been possible to appropriately extract the contour of a predetermined region on the base material included in the cross-sectional image.

[0048] FIG. 2B is a diagram showing an example of a first processed image. By performing a predetermined filtering process by the filtering unit 125 on the cross-sectional image subjected to the histogram equalization process, the image is smoothed while maintaining the contour of the region 201 showing the resin composition pattern in the image shown in FIG. 2A.

[0049] FIG. 2C is a diagram showing an example of a second processed image. The image shown in FIG. 2B is binarized by the binarization process by the binarization unit 130.

[0050] FIG. 2D is a diagram showing an example of a third processed image. The third processed image shown in FIG. 2D shows the result of the morphology processing unit 135 first performing three degrees of opening processing on the second processed image shown in FIG. 2C using a 5-pixel by 5-pixel cross-shaped kernel, and then performing three degrees of closing processing. By the morphology processing, some of the holes, protrusions, and isolated points seen in the second processed image are removed.

[0051] Based on the third processed image, the contour extraction unit 140 extracts the contour of a predetermined region on the substrate and stores the extraction result information indicating the extraction result in the storage unit 110.

[0052] The contour extraction unit 140 extracts the contour of a predetermined region on the substrate from the third processed image using, for example, an existing program that extracts the contour from a binarized image. At this time, the contour extraction unit 140 may extract the contour of a region having a predetermined area, or may extract the contour of a region selected based on a predetermined position. More specifically, the contour extraction unit 140 can, for example, extract the contour of a region having an area equal to or greater than a predetermined value and located at the uppermost position in the image. Thereby, the contour extraction unit 140 can extract the contour of the resin composition pattern in the cross-sectional image.

[0053] The contour extraction unit 140 can, for example, extract the contour of the copper portion region of the substrate. Also, the contour extraction unit 140 can, for example, extract the contour of the via portion region on the substrate.

[0054] FIG. 3A and FIG. 3B are diagrams showing examples of display information displayed on the user device 200.

[0055] FIG. 3A is a diagram showing an example of display information when the contour extraction unit 140 extracts the contour of the region of the resin composition pattern on the substrate. Using the line 301, the contour of the region of the resin composition pattern is shown in a color different from the cross-sectional image. Thereby, the user can easily grasp the contour of the region of the resin composition pattern.

[0056] FIG. 3B is a diagram showing an example of display information when the contour extraction unit 140 extracts the contour of the region of the via portion on the substrate. Using the line 302, the contour of the region of the via portion is shown in a color different from the cross-sectional image. Thereby, the user can easily grasp the contour of the region of the via portion.

[0057] Note that the method of displaying the contour shown in FIGS. 3A and 3B is only an example, and the method of displaying the contour is not limited to this.

[0058] The dividing unit 145 divides the region inside the contour into a plurality of sub-regions at predetermined intervals with lines parallel to the first axis direction in the cross-sectional image.

[0059] Here, the first axis may be an axis parallel to the surface of the substrate. That is, the dividing unit 145 can divide the region inside the contour into a plurality of sub-regions with, for example, a line parallel to the surface of the substrate. Thereby, the measuring unit 155 described later can measure the width of the resin composition pattern or the via portion on the substrate.

[0060] Note that the number of divisions by the dividing unit 145 is not particularly limited, but the dividing unit 145 may divide the region inside the contour, for example, for each number of pixels corresponding to 2 micrometers of the actual object.

[0061] The rectangle setting unit 150 sets a plurality of rectangles corresponding to each of the plurality of sub-regions for each of the plurality of sub-regions.

[0062] Regarding the rectangular setting process by the rectangular setting unit 150, taking the case where the dividing unit 145 provides sub-regions with lines parallel to the horizontal direction (i.e., parallel to the surface of the base material, for example) in the cross-sectional image as an example, it will be specifically described with reference to FIG. 4.

[0063] FIG. 4 is a diagram schematically showing an example of the rectangular setting process by the rectangular setting unit 150. The contour line 401 indicates, for example, the contour extracted by the contour extraction unit 140. The lines 402 (line 402a, line 402b, line 402c, line 402d, line 402e) indicate, for example, the lines provided by the dividing unit 145 for dividing the area within the contour into sub-regions. The dividing unit 145 divides the extracted contour into sub-regions a, b, c, d, for example. The sub-region is an area surrounded by the contour line 401 and the two upper and lower lines 402. Specifically, the sub-region a is an area surrounded by the contour line 401, line 402a, and line 402b, and the same applies to the other sub-regions.

[0064] First, the rectangular setting unit 150 sets the two lines 402 that form the outer periphery of each sub-region provided by the dividing unit 145 as the upper side and the lower side of the rectangle corresponding to that sub-region. When the sub-region is at the uppermost or lowermost part of the contour, a line passing through the topmost or bottommost part of the extracted contour and parallel to the surface of the base material (the first axis) is set as the upper side or the lower side of each rectangle, respectively.

[0065] That is, the rectangular setting unit 150 sets line 402a and line 402b that form the outer periphery of sub-region a as the upper side and the lower side of the rectangle corresponding to sub-region a, respectively, and sets line 402b and line 402c that form the outer periphery of sub-region b as the upper side and the lower side of the rectangle corresponding to sub-region b, respectively. The same applies to the other sub-regions.

[0066] Subsequently, the rectangular setting unit 150 sets the left side and the right side of the rectangle corresponding to each sub-region.

[0067] At this time, the rectangle setting unit 150 can set rectangles circumscribing each sub-region. That is, in this case, for the rectangle corresponding to the sub-region b, the left side can be set as line 403a.

[0068] Also, the rectangle setting unit 150 can set rectangles inscribed in each sub-region. That is, in this case, for the rectangle corresponding to the sub-region b, the left side can be set as line 403b.

[0069] Also, for the rectangle corresponding to the sub-region b, the rectangle setting unit 150 can set the left side as line 403c. Here, line 403c is, for example, a line located between line 403a and line 403b. Line 403b may be a line located in the middle of line 403a and line 403b, or line 403c may be such that the intersection with the contour line 401 is located in the middle of line 403c. Thereby, the rectangle setting unit 150 can set a rectangle with a small difference from the area of the sub-region b.

[0070] Also, similarly for the right side, the rectangle setting unit 150 can set any one of line 404a, line 404b, and line 404c.

[0071] Also, the rectangle setting unit 150 can set the left side and the right side at corresponding positions. That is, when the rectangle setting unit 150 sets line 403a as the left side, it may set the corresponding line 404a as the right side. Thereby, the rectangle setting unit 150 can set a rectangle symmetric with respect to the center of the sub-region.

[0072] Also, the rectangle setting unit 150 may set the left side and the right side at non-corresponding positions. That is, when the rectangle setting unit 150 sets line 403a as the left side, it may set line 404b or line 404c that does not correspond to line 403a as the right side. Thereby, the rectangle setting unit 150 can set an appropriate rectangle according to the shape of the contour line 401.

[0073] The measurement unit 155 measures the distance between opposite sides in each of the plurality of rectangles, and stores measurement result information regarding the measurement results in the storage unit 110.

[0074] The measurement unit 155 can measure, for example, the distance between opposite sides of a side orthogonal to the surface of the substrate. Specifically, the measurement unit 155 can measure, for example, the distance between the line 403a and the line 404a in FIG. 4. Thereby, the contour extraction system 100 can measure, for example, the width of the resin composition pattern on the substrate and the width of the via portion.

[0075] Further, when the same process is performed with the first axis as the axis perpendicular to the surface of the substrate in the division process, the rectangle corresponding to the sub-region a is a rectangle having the line 402a and the line 402b as the left and right sides, and the line 403 and the line 404 as the upper and lower sides. In this case, the measurement unit 155 can measure the distance between the line 403 and the line 404. Thereby, the contour extraction system 100 can measure, for example, the thickness (film thickness) of the resin composition pattern on the substrate and the depth of the via portion. Further, at this time, the measurement unit 155 may calculate the average value of the plurality of distances between sides. That is, the average value of the distances between sides such as the distance between sides measured from the rectangle corresponding to the sub-region a and the distance between sides measured from the rectangle corresponding to the sub-region b may be calculated and used as the thickness (film thickness) of the resin composition pattern on the substrate and the depth of the via portion.

[0076] The display output unit 160 generates and outputs display information for displaying the extracted contour in association with the cross-sectional image. The display output unit 160 can output the display information to, for example, the user device 200. At this time, the display output unit 160 can generate the display information based on the extraction result information stored in the storage unit 110.

[0077] Further, the display output unit 160 can generate and output display information for displaying the results of the processes of the division unit 145, the rectangle setting unit 150, and the measurement unit 155, which will be described later.

[0078] FIG. 5A and FIG. 5B are diagrams showing examples of screens displayed on the user device 200. The screens shown in FIGS. 5A and 5B are displayed on the user device 200 based on, for example, display information generated and output by the display output unit 160.

[0079] FIG. 5A shows an example in which, for the resin composition pattern on the substrate, the dividing unit 145 divides the area within the contour into a plurality of sub-areas by a line parallel to the surface of the substrate, and the measuring unit 155 calculates the distance between the sides (width of the resin composition pattern) of the side perpendicular to the surface of the rectangular substrate corresponding to each sub-area. Further, an example is shown in which the dividing unit 145 divides the area within the contour into a plurality of sub-areas by a line perpendicular to the surface of the substrate, and calculates the average value of the distances between the sides parallel to the surface of the rectangular substrate corresponding to each sub-area (thickness of the resin composition pattern). FIG. 5A shows a plurality of sub-areas divided by a line parallel to the surface of the substrate and one of the sub-areas divided by a line perpendicular to the surface of the substrate.

[0080] The dividing unit 145 divides the area within the contour into a plurality of sub-areas parallel to the surface of the substrate, and the rectangle setting unit 150 sets, for example, rectangle 501a.

[0081] Then, the measuring unit 155 measures, for example, the distance between side 502a and side 502b perpendicular to the surface of the substrate in rectangle 501a.

[0082] The display output unit 160 generates and outputs, for example, display information for displaying the distance between the sides in area 503.

[0083] Also, the measuring unit 155 measures a plurality of distances between sides parallel to the surface of the printed substrate, and calculates the average value of the plurality of distances between the sides as the thickness of the resin composition pattern. The display output unit 160 generates and outputs, for example, display information for displaying the thickness in area 504.

[0084] FIG. 5B shows an example in which, for the via portion in the substrate, when the dividing portion 145 divides the area within the contour into a plurality of sub-areas by a line parallel to the surface of the substrate. The rectangular setting unit 150 and the measuring unit 155 can measure the distance between the sides of the side orthogonal to the surface of the substrate and the distance between the sides parallel to the surface of the substrate in the via portion, in the same manner as in the case of FIG. 5A.

[0085] Note that the screens shown in FIGS. 5A and 5B are merely examples of displays, and the displays based on the display information are not limited to these.

[0086] FIG. 6 is a flowchart showing an example of processing in the contour extraction system 100.

[0087] The acquisition unit 115 acquires a cross-sectional image of the resin composition pattern on the substrate (S601). The parameter reception unit 120 receives parameter information (S602). The filtering processing unit 125 performs a predetermined filtering process on the cross-sectional image to generate a first processed image (S603). The binarization processing unit 130 performs a binarization process on the first processed image to generate a second processed image (S604). The morphology processing unit 135 performs a morphology process on the second processed image to generate a third processed image (S605). The contour extraction unit 140 extracts the contour of a predetermined area on the substrate based on the third processed image (S606).

[0088] Subsequently, the dividing unit 145 divides the area within the contour into a plurality of sub-areas at predetermined intervals (S607). The rectangular setting unit 150 sets a plurality of rectangles corresponding to each sub-area, respectively (S608). The measuring unit 155 measures the distance between the opposing sides in each rectangle (S609).

[0089] Then, the display output unit 160 generates and outputs display information for displaying the extracted contour in association with the cross-sectional image. Further, the display output unit 160 generates and outputs display information for displaying the results of the processing by the dividing unit 145, the rectangular setting unit 150, and the measuring unit 155.

[0090] Note that the contour extraction system 100 may be a system that operates in conjunction with other systems and continuously performs processing by a plurality of systems as a whole. For example, by operating in conjunction with a microscope image acquisition system, it may be a system that continuously performs operations from photographing a cross-sectional image to contour extraction. Further, for example, by operating in conjunction with a simulation system of a resin composition pattern, it may be a system that compares the contour of the simulated resin composition pattern with the contour of the actual resin composition pattern extracted by the contour extraction system 100 to verify the simulation accuracy.

[0091] Next, with reference to FIG. 7, an example of the hardware configuration when the contour extraction system 100 is realized by a computer 700 will be described. FIG. 7 is a diagram showing an example of the hardware configuration of the computer 700.

[0092] As shown in FIG. 7, the computer 700 includes, for example, a processor 701, a memory 702, a storage device 703, an input I / F unit 704, a data I / F unit 705, a communication I / F unit 706, and a display device 707.

[0093] The computer 700 may be, for example, a server computer, a personal computer (e.g., desktop, laptop, tablet, etc.), a media computer platform (e.g., cable, satellite set-top box, digital video recorder, etc.), a handheld computer device (e.g., PDA, email client, etc.), or another type of computer or communication platform.

[0094] The processor 701 is a control unit that controls various processes in the computer 700 by executing programs stored in the memory 702.

[0095] The memory 702 is a storage medium such as a RAM (Random Access Memory). The memory 702 temporarily stores the program code of a program executed by the processor 701 and the data required during the execution of the program.

[0096] The storage device 703 is a non-volatile storage medium such as a hard disk drive (HDD) or a flash memory. The storage device 703 stores an operating system and various programs for realizing the above-described respective configurations.

[0097] The input I / F unit 704 is a device for receiving an input from a user. The input I / F unit 704 is, for example, a keyboard, a mouse, a touch panel, various sensors, a wearable device, or the like. The input I / F unit 704 may be connected to the computer 700 via an interface such as a USB (Universal Serial Bus).

[0098] The data I / F unit 705 is a device for inputting data from outside the computer 700. The data I / F unit 705 is, for example, a drive device for reading data stored in various storage media. The data I / F unit 705 may be provided outside the computer 700. When the data I / F unit 705 is provided outside the computer 700, the data I / F unit 705 is connected to the computer 700 via an interface such as a USB.

[0099] The communication I / F unit 706 is a device for performing data communication with a device outside the computer 700 via a network such as the Internet, either wired or wirelessly. The communication I / F unit 706 may be provided outside the computer 700. When the communication I / F unit 706 is provided outside the computer 700, the communication I / F unit 706 is connected to the computer 700 via an interface such as a USB.

[0100] The display device 707 is a device for displaying various information. The display device 707 is, for example, a liquid crystal display, an organic EL (Electro-Luminescence) display, a display of a wearable device, etc. The display device 707 may be provided outside the computer 700. When the display device 707 is provided outside the computer 700, the display device 707 is connected to the computer 700 via, for example, a display cable or the like. Also, when a touch panel is adopted as the input I / F unit 704, the display device 707 may be configured integrally with the input I / F unit 704.

[0101] As described above, an embodiment of the present invention has been explained. The contour extraction system 100 acquires a cross-sectional image of a resin composition pattern including an inorganic filler on a substrate, performs a predetermined filtering process, binarization process, and morphological process on the cross-sectional image to generate a third processed image, and can extract the contour of a predetermined region on the substrate based on the third processed image. Thereby, the contour extraction system 100 can extract the contour in the cross-sectional image of the resin composition containing the inorganic filler.

[0102] Also, the contour extraction system 100 divides the region inside the contour into a plurality of sub-regions at predetermined intervals with lines parallel to the first axial direction in the cross-sectional image, sets a plurality of rectangles corresponding to each sub-region respectively, and can measure the distance between opposite sides in each rectangle. Thereby, the contour extraction system 100 can grasp the size of the extracted contour more precisely.

[0103] Also, the contour extraction system 100 can set rectangles circumscribing each sub-region respectively and measure the distance between opposite sides of the circumscribing rectangle. Thereby, the contour extraction system 100 can grasp the size of the extracted contour more precisely.

[0104] In addition, the contour extraction system 100 can acquire at least one of a cross-sectional image of a resin-sealed substrate and a cross-sectional image of a solder resist pattern on the substrate. Thereby, the contour extraction system 100 can extract contours in various cross-sectional images.

[0105] Also, the contour extraction system 100 can receive parameter information from a user through the user device 200 and execute at least one of filtering processing, binarization processing, and morphological processing based on the parameter information. Thereby, the contour extraction system 100 can perform appropriate image processing based on the parameters received from the user.

[0106] In addition, the contour extraction system 100 can receive second parameter information different from the parameter information from the user through the user device 200 that displays the display information, and further execute at least one of filtering processing, binarization processing, and morphological processing based on the second parameter information. Thereby, the user can adjust the parameters with reference to the results of the image processing.

[0107] Note that this embodiment is for facilitating the understanding of the present invention and is not for limiting and interpreting the present invention. The present invention can be changed / improved without departing from its gist, and equivalents thereof are also included in the present invention.

[0108] In the present invention, the "part" does not simply mean a physical means, and also includes a case where the function of the "part" is realized by software. Also, even if the function of one "part" or device is realized by two or more physical means, devices, or software, or the functions of two or more "parts" or devices are realized by one physical means, device, or software, it is also acceptable.

Explanation of Reference Numerals

[0109] 100 Contour extraction system, 110 Memory unit, 115 Acquisition unit, 120 Parameter reception unit, 125 Filtering processing unit, 130 Binarization processing unit, 135 Morphology processing unit, 140 Contour extraction unit, 145 Division unit, 150 Rectangle setting unit, 155 Measurement unit, 160 Display output unit, 200 User device

Claims

1. A computer obtains a cross-sectional image of a resin composition pattern containing an inorganic filler on a substrate, which is taken by a microscope, performs a predetermined filtering process on the cross-sectional image to smooth the image while maintaining the contour of the region of the resin composition pattern containing the inorganic filler in the cross-sectional image, and generates a first processed image that has been filtered, performs a binarization process on the first processed image according to a predetermined threshold value, and generates a second processed image that has been binarized, performs a morphological process including a predetermined number of dilation processes and a predetermined number of erosion processes on the second processed image, and generates a third processed image that has been binarized, extracts the contour of a predetermined region on the substrate based on the third processed image, and includes a contour extraction method.

2. divides the region within the contour into a plurality of sub-regions at predetermined intervals with lines parallel to the first axial direction in the cross-sectional image, sets a plurality of rectangles corresponding to each of the sub-regions respectively, measures the distance between opposite sides of each of the rectangles, and further includes the contour extraction method according to Claim 1.

3. The setting of each of the rectangles includes setting a rectangle circumscribing each of the sub-regions, The measuring includes measuring the distance between opposite sides of each of the circumscribing rectangles that are perpendicular to the first axial direction, and is the contour extraction method according to Claim 2.

4. The cross-sectional image includes a cross-sectional image of a resin composition pattern on the substrate encapsulated with resin, and is the contour extraction method according to any one of Claims 1 to 3.

5. The resin composition pattern includes a solder resist pattern, and is the contour extraction method according to any one of Claims 1 to 3.

6. further includes receiving, from a user, parameter information regarding parameters necessary for executing at least any one of the filtering process, the binarization process, and the morphological process, through a user device used by the user, and based on the parameter information, at least any one of the filtering process, the binarization process, and the morphological process is executed, and is the contour extraction method according to any one of Claims 1 to 3.

7. An acquisition unit that acquires a cross-sectional image of a resin composition pattern containing an inorganic filler on a substrate, taken with a microscope; A filtering processing unit that performs a predetermined filtering process for smoothing the image while maintaining the contour of the region of the resin composition pattern containing the inorganic filler in the cross-sectional image, and generates a first processed image that has been filtered; A binarization processing unit that performs a binarization process according to a predetermined threshold value on the first processed image, and generates a second processed image that has been binarized; A morphological processing unit that performs a morphological process including a predetermined number of dilation processes and a predetermined number of erosion processes on the second processed image, and generates a third processed image that has been binarized; A contour extraction unit that extracts the contour of a predetermined region on the substrate based on the third processed image; A display output unit that outputs display information for displaying the extracted contour in association with the cross-sectional image; A contour extraction system comprising the above.

8. A program for causing a computer to: An acquisition unit that acquires a cross-sectional image of a resin composition pattern containing an inorganic filler on a substrate, taken with a microscope; A filtering processing unit that performs a predetermined filtering process for smoothing the image while maintaining the contour of the region of the resin composition pattern containing the inorganic filler in the cross-sectional image, and generates a first processed image that has been filtered; A binarization processing unit that performs a binarization process according to a predetermined threshold value on the first processed image, and generates a second processed image that has been binarized; A morphological processing unit that performs a morphological process including a predetermined number of dilation processes and a predetermined number of erosion processes on the second processed image, and generates a third processed image that has been binarized; A contour extraction unit that extracts the contour of a predetermined region on the substrate based on the third processed image; A display output unit that outputs display information for displaying the extracted contour in association with the cross-sectional image; A contour extraction program for realizing the above.

Images