JP5681021B2 - Surface texture measuring device - Google Patents

Description

The present invention relates to a metal surface such as a stainless steel plate that is required to have a smooth surface close to a mirror surface, a product surface such as ceramics, film, plastic, ceramics, and glossy paper, a painted surface, a plated surface, a polished surface, and a product. It affects rolling roll surface texture of, regarding the surface texture measuring device for quantitatively measuring comprehensively evaluate the processing machine or surface properties of the surface of the work tool of the mold or the like.

  As a device for measuring the surface property of a smooth surface close to a mirror surface, a surface roughness meter (abbreviated as a roughness meter for short) that measures surface roughness (roughness of fine irregularities) with a stylus type. In addition, a specular gloss meter (also referred to as a gloss meter for short) that measures glossiness with the amount of light received by regular reflection (specular reflection) has been used.

  In addition, as a device that measures the surface roughness and glossiness by taking a reflected image instead of measuring only the amount of received light, for example, the light of a black and white pattern is projected obliquely with respect to the measurement target surface at a predetermined angle, and at the same angle. It is conventionally known to measure the surface properties in a non-contact manner by reflecting the image to the opposite side (regular reflection), capturing the pattern reflection image with a camera, and processing the image signal with a computer. (For example, refer to Patent Documents 1 and 2.)

  In addition, the applicant plots the luminance distribution of the captured pattern reflection image (graphs a part of the pattern), obtains the standard deviation of the luminance waveform (variation in luminance from the average luminance), and calculates the standard deviation based on the standard deviation. Developed a method and apparatus for measuring surface properties to measure roughness, surface reflectance, etc., and further compared the standard deviation of the brightness value of the pattern reflection image (virtual image) with the standard deviation (reference value) in the case of a mirror surface The value is defined as “specularity”, and the shoulder of the rectangular waveform of the luminance waveform is narrowed and the edge is seen in specularity, so that the image clarity of the sample surface (whether the pattern is accurately captured) Development of a specularity evaluation method and apparatus that quantitatively evaluates surface properties such as surface roughness and glossiness caused by minute surface irregularities by adding other information such as reflectance (For example, special References 3 and 4.).

  In the measurement of specularity, the focus of the camera is matched to the pattern reflection image. In this case, instead of looking at the surface to be measured (the surface of the object to be measured), treat the surface to be measured as a mirror, copy the pattern on the sample surface, and focus on the image of the captured pattern. Yes.

JP-A-61-75236 JP 2006-84452 A JP 2001-99632 A JP 2007-155709 A

  The specularity is an effective index for quantitatively evaluating the surface property of a smooth surface close to the specular surface from the same viewpoint as the visual inspection. However, even if the surface property is evaluated, for example, in the case of stainless steel, in the case of building materials, in the case of films, in the case of polymer materials, etc., the industry changes, and the type of product that is the object of measurement changes. The perspective changes slightly. In the visual inspection, the surface properties are evaluated from a viewpoint specific to each industry. In the case of visual observation, the viewpoint differs depending on the industry, and depending on the industry, for example, the evaluation for swell and the evaluation for sharpness are unconsciously in the head as the main viewpoint of the inspection, which greatly affects the evaluation. And in the case of visual inspection, for example, even if “surface is bad”, it is clear what is wrong, such as whether it felt bad because the surface is wavy, whether it felt bad because of dullness, etc. Not. In addition, the evaluation of the surface properties based on the specularity is a comprehensive evaluation, but the evaluation may not exactly match the evaluation from the specific point of view of the type of product that is the measurement object or the industry. is there. Moreover, even in the evaluation of the surface property based on the specularity, it is not always clear what exactly is good or bad.

The present invention relates to a metal surface such as a stainless steel plate that is required to have a smooth surface close to a mirror surface, a product surface such as ceramics, film, plastic, ceramics, and glossy paper, a painted surface, a plated surface, a polished surface, and a product. It is possible to quantitatively and comprehensively evaluate the surface properties of the surface of processing machines or processing tools such as rolling rolls and dies that influence the surface properties of products based on indices close to the sensibilities specific to each product or industry. An object of the present invention is to provide a surface texture measuring device that can be used.

The surface texture measuring device of the present invention includes a projection optical system that projects a check pattern indicating a two-dimensional distribution shape of optical brightness on a display such as a liquid crystal display by computer control, and projects it onto the surface of a measurement object. It consists of an imaging optical system that captures a virtual image of the check pattern reflected by the object surface with an image sensor. The surface properties of the surface of the measurement object are acquired by processing the image data of the check pattern captured by the image sensor in a computer and processing it. a surface texture measuring device for measuring the specular calculation means, specularity variation calculating means, gloss degree calculating means, sharpness calculating means comprise waviness and shape error calculating means, the contrast calculating means, and the opacity calculation means It is characterized by.

  The specularity calculating means calculates a standard deviation with respect to the amplitude of the luminance value data from the check pattern image obtained by projecting a check pattern for specularity measurement (for example, a black and white striped check pattern) onto the surface of the measurement object, Computation logic is incorporated in the computer so that the standard deviation is compared with a predetermined specularity evaluation reference value, and a relative value to the specularity evaluation reference value is calculated as the specularity of the surface of the measurement object. .

  The specularity variation calculating means divides the surface of the measurement object into a plurality of sections, calculates the specularity for each section, and calculates the standard deviation of the specularity for each section as the specularity variation of the measurement target surface. Calculation logic is built into a computer.

  The gloss level calculation means calculates the standard deviation and the brightness value data with respect to the amplitude of the brightness value data from the check pattern image obtained by projecting a check pattern for glossiness measurement (for example, a black and white striped check pattern) onto the surface of the measurement object. The calculation logic is incorporated in the computer so as to calculate the average value of the measurement object and to calculate the value obtained by adding the standard deviation and the average value as the glossiness of the surface of the measurement object.

  The sharpness calculating means projects a check pattern for sharpness measurement (for example, a check pattern in which a white background and a black background are arranged in half, or a black and white striped check pattern) on the surface of the measurement object, and obtains each check pattern image for each pixel. For example, a non-linear least square method using a sigmoid function is applied to the luminance waveform at the light / dark boundary portion, and the average value of the gain of the luminance waveform calculated by the fitting processing is calculated as the sharpness ( The calculation logic is incorporated in the computer so as to calculate as an index of image clarity).

  The undulation and shape error calculation means is a check obtained by projecting a check pattern for measuring undulation and shape error (for example, a check pattern in which a white background and a black background are arranged in half, or a check pattern of black and white stripes) onto the surface of the measurement object. For example, a non-linear least square method using a sigmoid function is applied to the luminance waveform at the light / dark boundary part of each pixel of the pattern image, and the inflection point position (center position) of the luminance waveform calculated by the fitting process is applied. The calculation logic is incorporated in the computer so as to calculate the standard deviation as a waviness or shape error of the surface of the measurement object.

The contrast calculating means calculates the maximum value (Imax) and the minimum value (Imin) of luminance value data from a check pattern image obtained by projecting a check pattern for contrast measurement (for example, a black and white striped check pattern) onto the surface of the measurement object. ) And calculation logic is incorporated in the computer so that the value of (Imax−Imin) / (Imax + Imin) is calculated as the contrast of the surface of the measurement object.

  The white turbidity calculating means calculates an average value of luminance value data from a check pattern image obtained by projecting a check pattern for measuring white turbidity (for example, a check pattern in which a black circle is arranged at the center of a white background) onto the surface of the measurement object. Calculation logic is incorporated in the computer so as to calculate and compare the average value with a predetermined turbidity evaluation reference value and calculate a relative value to the turbidity evaluation reference value as the turbidity of the surface of the measurement object. Is.

  This surface texture measuring device includes all of specularity calculating means, specularity variation calculating means, glossiness calculating means, sharpness calculating means, waviness and shape error calculating means, contrast calculating means, and white turbidity calculating means. Is preferred.

Furthermore, the surface texture measuring device, specularity, specularity dispersion, gloss, sharpness, waviness and shape error, contrast, and the opacity, automatically executes the sequentially calculated, the calculated data of all measurement items and It is preferable to provide list display means for displaying a list.

Then , using the surface texture measuring device having the above configuration, the specularity, the specularity variation, the glossiness, the sharpness, the waviness or the shape error, the contrast, and the turbidity are calculated. It is preferable to comprehensively evaluate the surface properties of the surface of the object to be measured by multi-index analysis based on the above.

The surface texture measuring device according to the present invention is as described above, whereby a plurality of measurement items related to the surface texture can be measured at a time with a single device on a smooth surface close to a mirror surface. The surface properties can be evaluated quantitatively and comprehensively from various viewpoints, using the measurement items as the index, and the surface properties can be selected by selecting an index close to the sensitivity of each product or industry related to the measurement object. Rolls and molds that affect the surface properties of metals, such as stainless steel plates, product surfaces such as ceramics, films, plastics, ceramics, and glossy paper, painted surfaces, plated surfaces, polished surfaces, etc. The evaluation of the surface texture of the surface of a processing machine or processing tool such as the above can be brought close to a visual inspection with sensitivity unique to each product or industry. Then, by automatically executing check pattern switching, projection, acquisition and calculation of image data, and displaying a list of calculated measurement item data, surface properties can be immediately evaluated at the measurement site.

  Since the surface texture measuring device of the present invention forms a check pattern on a display screen such as a liquid crystal under computer control, the check pattern can be easily switched. Only when a check pattern is formed on a display screen such as a liquid crystal display by computer control, a plurality of measurement items can be easily measured at one time with a single device.

  As is apparent from the above description, according to the present invention, a metal such as a stainless steel plate, which is required to be a smooth surface close to a mirror surface, a product surface such as a ceramic, film, plastic, ceramic, glossy paper, The surface properties of the surface of the processing surface or surface of the machine, such as rolling rolls, dies, etc., that affect the surface properties of the painted surface, plated surface, polished surface, and product, are based on indices close to the sensibility specific to each product or industry. And can be evaluated quantitatively and comprehensively.

1 is a system diagram of a surface texture measuring device according to an embodiment of the present invention. The example of the check pattern which concerns on embodiment of this invention is shown, (a) is a figure which shows the check pattern of a monochrome striped pattern, (b) is a figure which shows the check pattern which has arrange | positioned the black circle in the center part of a white background, ( c) is a diagram showing a check pattern in which a white background and a black background are arranged in half. 2A and 2B show an example of a luminance distribution of a check pattern image according to an embodiment of the present invention, in which FIG. 1A shows an example of a luminance distribution of a check pattern image projected on an evaluation reference plane, and FIG. It is a figure which shows the example of the luminance distribution of the check pattern image projected on. It is a flowchart which shows the operation | movement of the surface texture measuring apparatus which concerns on embodiment of this invention, and the procedure (an example) of the surface texture comprehensive evaluation method.

  FIG. 1 shows an example of a system configuration of a surface texture measuring apparatus according to an embodiment of the present invention. In the figure, reference numeral 1 denotes a spectroscope constituting the main body of the surface texture measuring device, 2 denotes a measurement object, and 3 denotes a computer.

  The spectroscope 1 includes a display 11 that displays and projects a check pattern that can be controlled by a computer 3, and an imaging device (imaging device) 12 that captures a reflected image of the check pattern. An arbitrary check pattern such as black and white stripes indicating the distribution shape is displayed on the display 11, and the check pattern is projected onto the measurement target surface (measurement target surface) 21, and is projected by the projection optical system. Thus, an imaging optical system for imaging the virtual image of the check pattern reflected by the measurement surface 21 by the imaging device 12 is configured.

  The display 11 is a liquid crystal display, for example. In addition, displays such as plasma and organic / inorganic EL may be used.

  The check pattern formed by the display 11 can be freely set by the operation of the computer 3. For example, a check pattern having a black and white stripe shape as shown in FIG. 2A or a white background as shown in FIG. A check pattern with a black circle (may be a shape other than a circle) at the center, a check pattern with a white background and a black background half as shown in FIG. Can be switched easily.

  The imaging device 12 includes an area image sensor such as a CCD, CMOS, or digital camera as an image sensor. The focus of the image sensor is adjusted to the position of the virtual image plane 4 where the check pattern reflected by the measurement target surface 21 connects the images. The focusing is performed by fixing the focal length of the image sensor and adjusting either or both of the position (height) of the spectroscope 1 and the height of the table on which the measurement object 2 is placed.

  The spectrophotometer 1 and the computer 3 constitute a surface texture measuring device. Using this surface texture measuring device, a check pattern showing a two-dimensional optical bright / dark distribution shape is displayed on the display 11 under computer control, and the check pattern is obliquely applied to the surface to be measured 21 with the display 11 itself serving as a light source. The check pattern projected onto the surface to be measured 21 is photographed by the photographing device 12 (a half mirror is used, the check pattern is reflected by the half mirror and projected onto the surface to be measured 21 substantially vertically, It is also possible to take a picture through a mirror.) The image data of the taken check pattern is acquired and processed by the computer 3 to measure the surface property of a smooth surface close to the mirror surface.

  The luminance distribution of the check pattern image when a black and white striped check pattern is projected onto an evaluation reference plane which is a mirror surface, for example, shows a rectangular wave shape as shown in FIG. On the other hand, the luminance distribution of the check pattern image when the same black and white striped check pattern is projected on the surface of a normal product or the like has a rectangular shape of rising and falling, as shown in FIG. As compared with the wave, it collapses and the amplitude is small.

  Measurement objects include, for example, metals such as stainless steel plates, product surfaces such as ceramics, films, plastics, ceramics, and glossy paper, painted surfaces, plated surfaces, polished surfaces, and products (for example, flat, cylindrical, and complex shaped products) It is a processing machine or a processing tool such as a rolling roll or a die that affects the surface properties of the steel sheet.

  In this embodiment, a surface texture measuring device comprising a spectrophotometer 1 and a computer 3 is used, and specularity, specularity variation, glossiness, sharpness, waviness or shape error, contrast, and turbidity are measured items. Measurement items are automatically and sequentially measured with a single device, and the surface properties are evaluated quantitatively and comprehensively using these measurement items as indicators. The computer 3 includes computer software 5 including processing procedures of specularity calculation logic, specularity variation calculation logic, glossiness calculation logic, sharpness calculation logic, waviness and shape error calculation logic, contrast calculation logic, and white turbidity calculation logic. And the control unit is configured to function as specularity calculating means, specularity variation calculating means, glossiness calculating means, sharpness calculating means, waviness and shape error calculating means, contrast calculating means, and white turbidity calculating means. ing.

  The procedure (flow) for measuring and evaluating the surface properties in this embodiment is as shown in FIG. 4, for example (it is an example and is not limited to this).

  First, as an initial setting, a check pattern used for measurement of each measurement item is set by a computer and stored in a memory built in the computer. For example, for the measurement of specularity, specularity variation, glossiness, and contrast (sometimes used for measuring sharpness, waviness or shape error), the black and white stripes shown in FIG. Set and store a check pattern, set and store a check pattern in which a black circle is placed at the center of the white background shown in FIG. 2 (b) for measuring white turbidity, and for measuring sharpness, swell, or shape error. A check pattern in which the white background and the black background shown in FIG. 2C are arranged in half is set and stored. The check pattern may be different for each measurement item.

  Then, each check pattern is projected onto the surface of the evaluation reference object as the reference surface (evaluation reference surface) for specularity and turbidity measurement, and a check pattern reflected on the reference surface (evaluation reference surface) for each check pattern. Shoot to acquire the image data of the check pattern.

  Further, each check pattern is projected onto the surface of the measurement object (surface to be measured), and for each check pattern, the check pattern reflected on the surface to be measured is photographed to obtain the image data of the check pattern.

  Then, each measurement item is sequentially calculated in the order of specularity, specularity variation, glossiness, sharpness, waviness or shape error, contrast, and white turbidity.

  In calculating the specularity, a standard deviation (for example, FIG. 3) with respect to the amplitude of the luminance value data is obtained from a check pattern image obtained by projecting a check pattern for specularity measurement (for example, a black and white striped check pattern) onto the surface of the measurement object. 3 (corresponding to the value of (HL) / 2 in (b)), and the standard deviation is the specularity evaluation reference value (standard deviation in the case of the evaluation reference surface, for example, in FIG. (Equivalent to a value of (HL) / 2), the relative value to the specularity evaluation reference value (for example, the relative value when the reference value is 1000) is the "specularity" of the surface of the measurement object. Calculate as

  In calculating the specularity variation, the surface of the measurement object is divided into a plurality of sections, and the specularity is calculated for each section according to the above procedure. Then, the standard deviation of the specularity for each section is calculated as “specularity variation” of the surface of the measurement object.

  In calculating glossiness, a standard deviation (for example, FIG. 3) with respect to the amplitude of luminance value data is obtained from a check pattern image obtained by projecting a check pattern for glossiness measurement (for example, a black and white striped check pattern) onto the surface of the measurement object. (Equivalent to the value of (HL) / 2 in (b)) and the average value of luminance values (for example, equivalent to the value of a in (b) of FIG. 3), and the standard deviation and the average value are added together. The calculated value is calculated as the “glossiness” of the surface of the measurement object.

  The glossiness in the present invention is close to the glossiness measured with a conventional glossometer (a specular glossometer that measures glossiness with the amount of light received by specular reflection), but the glossiness measured with a conventional glossometer. May not match. When it is necessary to distinguish from the glossiness according to the conventional definition, the “glossiness” in the present invention may be referred to as “glossiness”, for example.

  In the calculation of sharpness, a check pattern for sharpness measurement (for example, a check pattern in which a white background and a black background are arranged in half, or a check pattern in black and white stripes) is projected onto the surface of the measurement object and is obtained for each pixel of the check pattern image obtained. For example, a fitting process by a non-linear least square method using a sigmoid function expressed by the following formula 1 (a fitting process by another method) may be performed on the luminance waveform at the light / dark boundary portion. The average value of the gain a of the calculated luminance waveform is calculated as “sharpness” of the surface of the measurement object.

  When specular reflection (specular reflection) is performed, if there is a distribution of tilt angles due to unevenness on the surface, reflection does not become complete regular reflection but reflects in the direction of blur. Therefore, a rising edge that goes from a dark place to a bright place in the luminance waveform is dropped. Sharpness is an index that evaluates the sharpness of the edge, such as how sharply the rising edge of the luminance waveform from dark to bright and the falling edge from bright to dark change. It is. In the present invention, for example, a fitting process for approximating a sigmoid function to a waveform at the rising edge of a luminance waveform from a dark place to a bright place or a falling waveform from a bright place to a dark place is performed. The sharpness is defined by the average value of the gain a which is one parameter of the function.

  In the calculation of waviness or shape error, a check pattern for waviness and shape error measurement (for example, a check pattern in which a white background and a black background are arranged in half, or a black and white striped check pattern similar to sharpness) is applied to the surface of the measurement object. For the luminance waveform at the light / dark boundary portion of each pixel of the check pattern image obtained by projection, for example, a fitting process by a nonlinear least square method using a sigmoid function is performed, and the center position of the luminance waveform calculated by the fitting process The standard deviation of (inflection point position) is calculated as “swell or shape error” on the surface of the measurement object. In this case, the maximum waviness and the arithmetic average waviness can be calculated by using the data on the center position (inflection point position) of the luminance waveform.

  For example, when fitting a sigmoid function to the rising edge of a luminance waveform from a dark place to a bright place or the falling edge from a bright place to a dark place, the rising or falling edge of the waveform is applied. However, it can be determined whether the line connecting the center positions (inflection point positions) is a straight line or undulating in the image. A straight line means that the surface to be measured is flat, and that it is wavy is that the surface to be measured is not flat.

In the calculation of contrast, a maximum value (Imax) and a minimum value (Imin) of luminance value data are obtained from a check pattern image obtained by projecting a check pattern for contrast measurement (for example, a black and white striped check pattern) onto the surface of the measurement object. ) And “contrast” is calculated by the calculation formula shown in the following formula 2.

  Contrast is made dimensionless by dividing the difference between Imax and Imin (the amplitude of the luminance waveform) by the sum of Imax and Imin (twice the average brightness) and depends on whether the reflectivity is high or low Evaluation that is not possible is possible.

  In the calculation of white turbidity, the average value of luminance value data is obtained from a check pattern image obtained by projecting a check pattern for measuring white turbidity (for example, a check pattern in which a black circle is placed at the center of a white background) onto the surface of the measurement object. The average value is calculated and compared with the white turbidity evaluation reference value (average value in the case of the evaluation reference surface), and the relative value to the white turbidity evaluation reference value is calculated as “white turbidity” of the surface of the measurement object. .

  The turbidity is the degree of turbidity on the surface of the measurement object due to scratches such as processing marks. If there is a scratch on the surface, most of the reflected light will be regularly reflected and enter the image sensor, but depending on the angle of inclination of the scratched surface, light from the surroundings may enter the image sensor and the entire area where there is a scratch It becomes bright with Bo. That is white turbidity, and the degree of white turbidity is measured as white turbidity. For example, when a check pattern in which a black circle is arranged at the center portion of a white background is used, if there is a scratch that causes white turbidity on the measurement object surface 21, regular reflection is performed at a position where the black circle portion of the check pattern is projected. The luminance value measured at the center of the black circle located at the center of the image is higher than the luminance value for the evaluation reference plane (mirror surface). It becomes higher overall, and the difference appears prominently. By comparing the average values of the luminance values, the degree of white turbidity can be quantitatively evaluated.

  Note that the calculation order is not limited to this, and can be changed to any order. Further, it is not always necessary to measure all of specularity, specularity variation, glossiness, sharpness, waviness or shape error, contrast, and white turbidity. What is necessary is just to measure several measurement items including specularity as needed.

  The calculated data of a plurality of measurement items (preferably all of these measurement items) including the specularity among the specularity, specularity variation, glossiness, sharpness, waviness or shape error, contrast, and white turbidity. It is displayed on the display screen of the computer 3 and can be output by a printer (not shown) connected to the computer 3. The screen display and print output of the calculated data can be displayed for each item or a list display of all items.

  Based on this screen display or print output, the surface properties of the measurement object are comprehensively evaluated.

  As mentioned above, although an example of embodiment was demonstrated, this invention is not limited to this, Various embodiment is possible.

Measurement items, specularity, specularity dispersion, gloss, sharpness, waviness or the shape errors, contrast, besides opacity also Ru can be added as appropriate.

DESCRIPTION OF SYMBOLS 1 Mirror surface meter 11 Display 12 Image pick-up device 2 Measurement object 21 Measurement surface (measurement object surface)
3 Computer 4 Virtual image plane 5 Computer software

Claims (1)

It consists of a projection optical system that displays a check pattern on a display by computer control and projects it onto the surface of the measurement object, and an imaging optical system that captures a virtual image of the check pattern that is projected and reflected from the surface of the measurement object with an image sensor. A surface texture measuring device that measures the surface texture of the surface of a measurement object by acquiring image data of a check pattern captured by the image sensor and processing the data,
From the check pattern image obtained by projecting the check pattern for specularity measurement onto the surface of the measurement object, the standard deviation with respect to the amplitude of the luminance value data is calculated, and the standard deviation is compared with a predetermined specularity evaluation reference value. , A specularity calculating means for calculating a relative value to the specularity evaluation reference value as the specularity of the surface of the measurement object
The surface of the measurement object is divided into a plurality of sections, the specularity is calculated for each section, and the standard deviation of the specularity for each section is calculated as the specularity variation of the surface of the measurement object;
From the check pattern image obtained by projecting the check pattern for glossiness measurement onto the surface of the object to be measured, the standard deviation with respect to the amplitude of the luminance value data and the average value of the luminance value data are calculated, and the standard deviation and the average value are added. Glossiness calculating means for calculating the measured value as the glossiness of the surface of the measurement object,
The brightness waveform gain calculated by the fitting process is performed on the brightness waveform of the light / dark boundary part of each pixel of the check pattern image obtained by projecting the check pattern for sharpness measurement onto the surface of the measurement object. Sharpness calculation means for calculating the average value of the measurement object surface sharpness,
Luminance calculated by performing fitting processing on the luminance waveform of the light / dark boundary portion of each pixel of the check pattern image obtained by projecting the check pattern for measuring undulation and shape error onto the surface of the measurement object. Waviness and shape error calculating means for calculating the standard deviation of the inflection point position of the waveform as the undulation or shape error of the surface of the measurement object
From the check pattern image obtained by projecting the check pattern for contrast measurement onto the surface of the object to be measured, the maximum value (Imax) and the minimum value (Imin) of the luminance value data are obtained, and (Imax−Imin) / (Imax + Imin) Contrast calculation means for calculating the value as the contrast of the surface of the measurement object;
From the check pattern image obtained by projecting the check pattern for measuring turbidity on the surface of the object to be measured, the average value of the luminance value data is calculated, and the average value is compared with a predetermined turbidity evaluation reference value. the relative values for the turbidity evaluation reference value, the surface texture measuring device, characterized in that it comprises a clouding degree calculating means for calculating as a clouding of the measurement object surface.

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