Surface texture measuring device and surface texture measuring method

Abstract

To provide a surface property measurement device and a surface property measurement method that can convert surface properties such as irregularities and waviness, so-called orange peel into numbers.SOLUTION: A surface property measurement device 10 is provided which has: an irradiation unit 2 that irradiates a surface to be measured 1 with illumination light L1 having a bright area and a dark area; a light detection unit 5 that focuses on the surface to be measured 1 to receive reflected light L2 that is reflected on the surface to be measured 1 and has a bright area and a dark area corresponding to the bright area and the dark area of the illumination light L1, and detects a light intensity distribution of the reflected light L2 on the surface to be measured 1; a first processing unit 6 that, in the light intensity distribution of the reflected light L2 on the surface to be measured 1, determines a peak value of light intensity of the bright area or the light intensity of a position separated by a predetermined value from a position indicating the peak value of the light intensity of the bright area; and a second processing unit 7 that converts a variation of the light intensity determined by the first processing unit 6 into numbers.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a surface texture measuring device and a surface texture measuring method. [Background technology]

[0002] Since the surface condition of an object contributes to its appearance, design, etc., it is important to examine the surface condition of the object. One example of the surface condition of an object is surface texture such as unevenness and waviness, known as the "orange peel" effect. For example, Patent Document 1 discloses a flatness measuring device that measures the flatness of the surface of an object to be measured, such as the orange peel effect, by projecting a lattice image onto the surface of the sample to be measured, detecting the pitch of the lattice image, and determining the average value of the standard deviation of the pitch of the lattice image as the flatness. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 2521729 Summary of the Invention [Problem to be solved by the invention]

[0004] However, existing devices are unable to adequately quantify the orange peel, and visual evaluation is generally required.

[0005] The present disclosure has been made in consideration of the above-described circumstances, and aims to provide a surface texture measuring device and a surface texture measuring method that are capable of quantifying surface textures such as unevenness and waviness, or so-called orange peel texture. [Means for solving the problem]

[0006] One embodiment of the present disclosure provides a surface texture measuring device having an irradiation unit that irradiates a surface to be measured with illumination light having bright and dark regions; a light detection unit that focuses the illumination light on the surface to be measured, receives reflected light that is reflected by the surface to be measured and has bright and dark regions that correspond to the bright and dark regions of the illumination light, and detects the light intensity distribution of the reflected light on the surface to be measured; a first processing unit that determines the peak value of the light intensity of the bright region or the light intensity at a position a predetermined distance from a position showing the peak value of the light intensity of the bright region in the light intensity distribution of the reflected light on the surface to be measured; and a second processing unit that quantifies the variation in the light intensity determined by the first processing unit.

[0007] In the surface texture measuring device of the present disclosure, the light detecting section is preferably an imaging device.

[0008] In the surface texture measuring device of the present disclosure, it is preferable that the illumination light has a linear bright region as the bright region, and that the reflected light has a linear bright region as the bright region that corresponds to the linear bright region of the illumination light.

[0009] In the above case, it is preferable that the first processing unit divides the light intensity distribution of the reflected light on the measurement surface into N divided regions in the longitudinal direction of the linear bright region of the reflected light, and calculates the light intensity for each divided region.

[0010] Furthermore, in the surface texture measuring device of the present disclosure, when the first processing unit determines the light intensity at a position in the light intensity distribution of the reflected light on the measured surface that is a predetermined distance away from the position showing the peak value of the light intensity of the bright region, it is preferable that the arithmetic mean value of the light intensity when the peak value of the light intensity of the bright region is determined in the light intensity distribution of the reflected light on the measured surface is used as a reference value, and the light intensity is determined at a position from the position showing the peak value of the light intensity of the bright region where the light intensity is 30% to 80% of the reference value.

[0011] Another embodiment of the present disclosure provides a surface texture measurement method including: an irradiation step of irradiating a surface to be measured with illumination light having bright and dark regions; a light detection step of focusing the illumination light on the surface to be measured, receiving reflected light having bright and dark regions that correspond to the bright and dark regions of the illumination light, and detecting the light intensity distribution of the reflected light on the surface to be measured; a first processing step of determining, in the light intensity distribution of the reflected light on the surface to be measured, the peak value of the light intensity of the bright region or the light intensity at a position that is a predetermined distance away from the position showing the peak value of the light intensity of the bright region; and a second processing step of quantifying the variation in the light intensity determined in the first processing step.

[0012] In the surface texture measuring method of the present disclosure, it is preferable to use an imaging device in the light detection step.

[0013] In the surface texture measuring device of the present disclosure, it is preferable that the illumination light has a linear bright region as the bright region, and that the reflected light has a linear bright region as the bright region that corresponds to the linear bright region of the illumination light.

[0014] In the above case, in the first processing step, it is preferable to divide the light intensity distribution of the reflected light on the measurement surface into N divided regions in the longitudinal direction of the linear bright region of the reflected light, and to obtain the light intensity for each divided region.

[0015] Furthermore, in the surface texture measurement method of the present disclosure, when determining the light intensity at a position in the light intensity distribution of the reflected light on the measured surface that is a predetermined distance away from the position showing the peak value of the light intensity of the bright region, it is preferable that the arithmetic mean value of the light intensity when determining the peak value of the light intensity of the bright region in the light intensity distribution of the reflected light on the measured surface is used as a reference value, and the light intensity is determined at a position from the position showing the peak value of the light intensity of the bright region where the light intensity is 30% to 80% of the reference value. [Effects of the Invention]

[0016] The present disclosure has the effect of enabling the quantification of surface characteristics such as unevenness and undulations, so-called orange peel. [Brief explanation of the drawings]

[0017] [Figure 1] FIG. 1 is a diagram illustrating a surface texture measuring device according to the present disclosure. [Figure 2] 10 is a schematic plan view illustrating an example of a mask that configures an illumination unit in the surface texture measuring device of the present disclosure. FIG. [Figure 3] 10A and 10B are diagrams illustrating examples of images captured by a light detection unit in the surface texture measuring device of the present disclosure. [Figure 4] 10 is a graph illustrating the light intensity distribution of reflected light on a surface to be measured. [Figure 5] 10 is a graph illustrating the light intensity distribution of reflected light on a surface to be measured. [Figure 6] 10 is a schematic plan view illustrating an example of a mask that configures an illumination unit in the surface texture measuring device of the present disclosure. FIG. [Figure 7] 10A and 10B are diagrams illustrating examples of images captured by a light detection unit in the surface texture measuring device of the present disclosure. [Figure 8] 10A and 10B are diagrams illustrating examples of images captured by a light detection unit in the surface texture measuring device of the present disclosure. [Figure 9] 10A and 10B are diagrams illustrating examples of images captured by a light detection unit in the surface texture measuring device of the present disclosure. [Figure 10] 10 is a graph illustrating the light intensity distribution of reflected light on a surface to be measured. [Figure 11] 1A to 1C are process diagrams illustrating a surface texture measuring method according to the present disclosure. [Figure 12] FIG. 10 is a schematic plan view illustrating a mask used in a comparative example. DETAILED DESCRIPTION OF THE INVENTION

[0018] Embodiments of the present disclosure will be described below with reference to the drawings and the like. However, the present disclosure can be implemented in many different forms, and should not be construed as being limited to the description of the embodiments exemplified below. Furthermore, to clarify the explanation, the drawings may schematically depict the width, thickness, shape, etc. of each part compared to the actual form, but these are merely examples and are not intended to limit the interpretation of the present disclosure. Furthermore, in this specification and each drawing, elements similar to those previously described with reference to the preceding drawings will be designated by the same reference numerals, and detailed descriptions may be omitted as appropriate.

[0019] The surface texture measuring device and the surface texture measuring method according to the present disclosure will be described in detail below.

[0020] A.Surface texture measuring device The surface texture measuring device of the present disclosure includes an irradiation unit that irradiates a measurement surface with illumination light having bright and dark regions; a light detection unit that focuses on the measurement surface, receives reflected light that is reflected by the measurement surface and has bright and dark regions corresponding to the bright and dark regions of the illumination light, and detects the light intensity distribution of the reflected light on the measurement surface; a first processing unit that determines, in the light intensity distribution of the reflected light on the measurement surface, the peak value of the light intensity of the bright region or the light intensity at a position a predetermined distance away from the position showing the peak value of the light intensity of the bright region; and a second processing unit that quantifies the variation in the light intensity determined by the first processing unit.

[0021] The surface texture measuring device of the present disclosure will be described with reference to the drawings. FIG. 1 is a diagram illustrating an example of the surface texture measuring device of the present disclosure. As shown in FIG. 1, the surface texture measuring device 10 includes an irradiation unit 2 that irradiates a measurement surface 1 with illumination light L1 having bright and dark regions; a light detection unit 5 that focuses on the measurement surface 1, receives reflected light L2 that is reflected by the measurement surface 1 and has bright and dark regions corresponding to the bright and dark regions of the illumination light L1, and detects the light intensity distribution of the reflected light L2 on the measurement surface 1; a first processing unit 6 that determines the peak value of the light intensity in the bright region or the light intensity at a position a predetermined distance from the position showing the peak value of the light intensity in the bright region in the light intensity distribution of the reflected light L2 on the measurement surface 1; and a second processing unit 7 that quantifies the variation in light intensity determined by the first processing unit 6.

[0022] The illumination unit 2 has a light source 3 and a mask 4. For example, as shown in Fig. 2, the mask 4 has a rectangular transmission area 11 and a light-shielding area 12. In the illumination unit 2, light from the light source 3 passes through the mask 4, and illumination light L1 having linear bright and dark areas is irradiated onto the measurement surface 1.

[0023] When illumination light L1 is irradiated onto the measurement surface 1, the illumination light L1 is reflected by the measurement surface 1. As shown in Fig. 3, this reflected light L2 has linear bright regions 21 (21a to 21d) and dark regions 22 that correspond to the linear bright regions and dark regions of the illumination light L1.

[0024] For example, in Fig. 1, if the light detection unit 5 is an imaging device, the light detection unit 5 focuses on the surface 1 to be measured and captures the reflected light L2. This results in an image of the reflected light on the surface 1 to be measured, as shown in Fig. 3. The imaging device (light detection unit 5) also detects the light intensity of the reflected light L2 for each pixel, and detects the light intensity distribution of the reflected light L2 on the surface 1 to be measured.

[0025] For example, in Fig. 3, if the image of reflected light from the surface to be measured has N pixels in the longitudinal direction D1 of the linear bright region of the reflected light and M pixels in the lateral direction D2 of the linear bright region of the reflected light, the image of reflected light from the surface to be measured is divided into N divided regions A1 to An in the longitudinal direction D1 of the linear bright region of the reflected light. The light intensity distribution of the reflected light in each divided region A1 to An is, for example, as shown in Fig. 4. In the light intensity distribution graph shown in Fig. 4, the horizontal axis represents the position in the lateral direction D2 of the linear bright region of the reflected light.

[0026] The first processing unit 6 determines, for each divided region A1 to An, the peak value of the light intensity of the linear bright region 21 (21a to 21d) in the light intensity distribution of the reflected light, or the light intensity at a position a predetermined distance away from the position showing the peak value of the light intensity of the linear bright region 21 (21a to 21d).

[0027] 5(a) is a graph showing the light intensity distribution of the reflected light in each divided region A1 to An, and is an example of determining the peak value of the light intensity of the bright region. As shown in FIG. 3, the reflected light L2 has four linear bright regions 21 (21a to 21d), so in the light intensity distribution of the reflected light shown in FIG. 5(a), the peak value P1 of the light intensity is determined for each of the linear bright regions 21a to 21d. j ~P4 j Then, for each of the divided regions A1 to An and for each of the linear bright regions 21a to 21d, the peak value P1 of the light intensity is calculated. j ~P4 j (j=1~n).

[0028] 5(b) is a graph showing the light intensity distribution of the reflected light in each divided region A1 to An, and is an example of determining the light intensity at a position a predetermined distance away from the position showing the peak value of the light intensity of the bright region. As shown in FIG. 3, the reflected light L2 has four linear bright regions 21 (21a to 21d), so in the light intensity distribution of the reflected light shown in FIG. 5(b), first, the peak value P1 of the light intensity is determined for each of the linear bright regions 21a to 21d. j ~P4 j The positions q0, r0, s0, and t0 that indicate the peak values ​​P1 of the light intensity distribution of each of the linear bright regions 21a to 21d are calculated. j ~P4j The left light intensity distribution 23 and the right light intensity distribution 24 are divided into a left light intensity distribution 23 and a right light intensity distribution 24. Next, in the left light intensity distribution 23 of the linear bright region 21a, the peak value P1 j The light intensity value Q1 at a position a predetermined distance q1 from the position q0 k Similarly, in the right-side light intensity distribution 24 of the linear bright region 21a, the peak value P1 of the light intensity is calculated. j The light intensity value Q2 at a position a predetermined value q2 away from the position q0 k Then, for each of the linear bright regions 21a to 21d and for each of the left light intensity distribution 23 and the right light intensity distribution 24, the peak value P1 of the light intensity is calculated. j ~P4 j The light intensity value Q1 at positions q1 to q2, r1 to r2, s1 to s2, t1 to t2 away from the positions q0, r0, s0, t0 indicating k ~Q2 k , R1 k ~R2 k , S1 k ~S2 k , T1 k ~T2 k Furthermore, for each of the divided regions A1 to An, for each of the linear bright regions 21a to 21d, and for each of the left light intensity distribution 23 and the right light intensity distribution 24, the light intensity value Q1 k ~Q2 k , R1 k ~R2 k , S1 k ~S2 k , T1 k ~T2 k (k=1~n).

[0029] In the second processing unit 7, the variations in light intensity obtained in the first processing unit 6 are quantified.

[0030] In the first processing unit 6, when the peak value of the light intensity is calculated for each divided region A1 to An and for each linear bright region 21 (21a to 21d) in the light intensity distribution of the reflected light, as shown in FIG. 5(a), the variation in the light intensity can be quantified as follows: First, for one linear bright region 21a, the peak value P1 of the light intensity in each divided region A1 to An is calculated. jThe arithmetic mean value and standard deviation of (j=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate the coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the linear bright region 21a. Similarly, for the other linear bright regions 21b, the peak values ​​P2 of the light intensity in each of the divided regions A1 to An are calculated. j The arithmetic mean value and standard deviation of (j=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate the coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the linear bright region 21b. In addition, for the other linear bright regions 21c, the peak value P3 of the light intensity in each of the divided regions A1 to An is calculated. j The arithmetic mean value and standard deviation of (j=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate the coefficient of variation, which is set as the coefficient of variation of the light intensity of the linear bright region 21c. Furthermore, for the other linear bright regions 21d, the peak value P4 of the light intensity in each of the divided regions A1 to An is calculated. j The arithmetic mean and standard deviation of (j=1 to n) are found, and the standard deviation is divided by the arithmetic mean to calculate a coefficient of variation, which is set as the coefficient of variation of the light intensity of linear bright region 21d. Next, the arithmetic mean of the coefficients of variation of the light intensity of each linear bright region 21a to 21d is calculated. This arithmetic mean of the coefficients of variation of the light intensity of each linear bright region 21a to 21d is set as the variation in light intensity.

[0031] 5(b), when the first processing unit 6 determines the light intensity at a position that is a predetermined distance from the position showing the peak value of the light intensity for each divided region A1 to An, for each linear bright region 21 (21a to 21d), for each left light intensity distribution 23, and for each right light intensity distribution 24 in the light intensity distribution of the reflected light, the variation in the light intensity can be quantified as follows: First, for the left light intensity distribution 23 of one linear bright region 21a, the light intensity value Q1 in each divided region A1 to An is calculated. k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the left light intensity distribution 23 of the linear bright region 21a. In addition, for the right light intensity distribution 24 of one linear bright region 21a, the light intensity value Q2 in each divided region A1 to An is kThe arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the right-side light intensity distribution 24 of the linear bright region 21a. Similarly, for the left-side light intensity distribution 23 of the other linear bright region 21b, the light intensity value R1 in each divided region A1 to An is set as the coefficient of variation of the light intensity of the right-side light intensity distribution 24 of the linear bright region 21a. k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the left light intensity distribution 23 of the linear bright region 21b. In addition, for the right light intensity distribution 24 of the linear bright region 21b, the light intensity value R2 in each divided region A1 to An is k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the right-side light intensity distribution 24 of the linear bright region 21b. In addition, for the left-side light intensity distribution 23 of the other linear bright region 21c, the light intensity values ​​S1 in each of the divided regions A1 to An are calculated. k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the left light intensity distribution 23 of the linear bright region 21c. In addition, for the right light intensity distribution 24 of the linear bright region 21c, the light intensity values ​​S2 in each of the divided regions A1 to An are k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the right-side light intensity distribution 24 of the linear bright region 21c. Furthermore, for the left-side light intensity distribution 23 of the other linear bright region 21d, the light intensity value T1 in each divided region A1 to An is calculated. k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the left light intensity distribution 23 of the linear bright region 21d. In addition, for the right light intensity distribution 24 of the linear bright region 21d, the light intensity value T2 in each divided region A1 to An is set as the coefficient of variation of the light intensity of the left light intensity distribution 23 of the linear bright region 21d. kThe arithmetic mean value and standard deviation of (k=1 to n) are found, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation, which is set as the coefficient of variation of the light intensity of right-side light intensity distribution 24 of linear bright region 21d. Next, the arithmetic mean value of the coefficients of variation of the light intensity of left-side light intensity distribution 23 and right-side light intensity distribution 24 of each linear bright region 21a to 21d is calculated. This arithmetic mean value of the coefficients of variation of the light intensity of left-side light intensity distribution 23 and right-side light intensity distribution 24 of each linear bright region 21a to 21d can be used as the variation in light intensity.

[0032] The surface texture measuring device of the present disclosure can quantitatively evaluate surface texture such as unevenness and waviness on the surface of an object, i.e., the so-called orange peel, for example, as the coefficient of variation of the light intensity. Therefore, it is possible to quantify the orange peel.

[0033] In addition, conventional devices generally focus on the light source and capture the reflected light. In contrast, in the present disclosure, instead of focusing on the light source, the device focuses on the surface to be measured, receives the reflected light, and detects the light intensity distribution of the reflected light. By focusing on the surface to be measured in this way, the orange peel effect can be emphasized.

[0034] Furthermore, when determining the pitch of bright regions as with conventional devices, the relative distortion between bright regions due to the pitch is quantified. In this case, for example, if the distortion of the bright regions is relatively small, the variation in the pitch of the bright regions tends to be small, making it impossible to adequately evaluate orange peel. In contrast, the present disclosure determines the peak value of the light intensity of a bright region or the light intensity at a position a predetermined distance away from the position showing the peak value of the light intensity of the bright region, thereby making it possible to quantify the absolute distortion of a single bright region. Therefore, even if the distortion of the bright region is relatively small, orange peel can be quantitatively evaluated.

[0035] The configuration of the surface texture measuring device of the present disclosure will be described below.

[0036] 1. Lighting section The illumination unit in the present disclosure irradiates the surface to be measured with illumination light having a bright region and a dark region.

[0037] The illumination light emitted by the illumination unit may have one or more bright regions and one or more dark regions. It is preferable that the illumination light have multiple bright regions. By irradiating the surface to be measured with such illumination light, the number of data points (sample size) can be increased, enabling accurate measurement of the surface texture of the surface to be measured.

[0038] The shape of the bright region is not particularly limited, and examples thereof include a line, a dot, and a plane.

[0039] When the bright region is linear, the shape of the linear bright region is not particularly limited as long as it is linear, and may be, for example, a straight line or a curved line.

[0040] When the bright regions are dot-like, the shape of the dot-like bright regions is not particularly limited as long as they are dot-like, and examples thereof include square, rectangular, circular, and elliptical shapes.

[0041] When the bright region is planar, the shape of the planar bright region is not particularly limited as long as it is planar, and examples thereof include a square, a rectangular, a circular, an elliptical, and the like.

[0042] In particular, the illumination light preferably has a linear bright region, and more preferably has multiple linear bright regions. In particular, when the illumination light has multiple linear bright regions, it preferably has stripe-shaped bright and dark regions. By irradiating the surface to be measured with such illumination light, the number of data points (sample size) can be increased, and the surface texture of the surface to be measured can be accurately measured.

[0043] Furthermore, when the illumination light has a plurality of point-like bright regions, the bright regions may be arranged in a grid pattern.

[0044] The illumination unit is not particularly limited as long as it can emit illumination light having a bright region and a dark region, and examples thereof include an illumination unit having a light source and a mask having a transmissive region and a light-blocking region, and a light source. In particular, the illumination unit preferably has a light source and a mask having a transmissive region and a light-blocking region. By using the mask, the shape of the bright region can be easily controlled.

[0045] When the illumination unit has a light source and a mask, the light source is not particularly limited, and examples thereof include LEDs (light-emitting diodes), OLEDs (organic light-emitting diodes), halogen lamps, and tungsten lamps. Among these, OLEDs are preferred. OLED light sources have high uniformity of light intensity.

[0046] The mask has a transmissive region and a light-shielding region, and the number of transmissive regions and light-shielding regions in the mask may be one or more.

[0047] The shape of the transmission region is not particularly limited, and examples thereof include a line, a dot, and a plane.

[0048] When the transmission region is linear, the shape of the linear transmission region is not particularly limited as long as it is linear, and may be, for example, straight or curved.

[0049] Furthermore, when the transmission region is dot-like, the shape of the dot-like bright region is not particularly limited as long as it is dot-like, and examples thereof include a square, a rectangle, a circle, and an ellipse.

[0050] Furthermore, when the transmission region is planar, the shape of the planar transmission region is not particularly limited as long as it is planar, and examples thereof include a square, a rectangular, a circular, an elliptical, and the like.

[0051] In particular, the mask preferably has a linear transmission region, and more preferably has multiple linear transmission regions. In particular, when the mask has multiple linear transmission regions, the transmission regions are preferably arranged in a stripe pattern. By using such a mask, the number of data points (sample size) can be increased, allowing for accurate measurement of the surface texture of the measurement surface.

[0052] Furthermore, when the mask has a plurality of point-like transmitting regions, the transmitting regions may be arranged in the form of lattice points.

[0053] For example, Fig. 2 shows an example in which the transmissive regions 11 are linear and straight, and are arranged in a stripe pattern, in which case the shape of the transmissive regions 11 in a planar view is rectangular. Also, for example, Fig. 6(a) shows an example in which the transmissive regions 11 are linear and curved, and in this case the shape of the transmissive regions 11 in a planar view can be an arc shape. Also, for example, Fig. 6(b) shows an example in which the transmissive regions 11 are dot-like, are arranged in a lattice pattern, and are square-shaped in a planar view. Also, for example, Fig. 6(c) shows an example in which the transmissive regions 11 are planar, and are rectangular in a planar view.

[0054] When the mask has a plurality of linear transmissive regions arranged in a stripe pattern, the linear transmissive regions may have the same or different line widths, lengths, and pitches, but are preferably equal to each other. The line widths, lengths, and pitches of the linear transmissive regions are not particularly limited and may be set appropriately.

[0055] Furthermore, when the mask has a plurality of dot-like transmission regions arranged in a grid pattern, the size and pitch of the dot-like transmission regions may be equal or different, but are preferably equal. The size and pitch of the dot-like transmission regions are not particularly limited and are set as appropriate.

[0056] Furthermore, when the mask has a planar transmitting region, the size of the planar transmitting region is not particularly limited and may be set appropriately.

[0057] The mask may have a transparent region and a light-shielding region, and may have, for example, a transparent substrate and a patterned light-shielding layer disposed on one side of the transparent substrate, or may have a light-shielding substrate and an opening that penetrates the light-shielding substrate.

[0058] When the illumination unit is a light source, examples of the light source include a linear light source, a point light source, and a surface light source. Among these, a linear light source is preferable. A linear light source can emit illumination light having a linear bright region.

[0059] Examples of the linear light source include a fluorescent lamp, a linear LED light source, and a linear OLED light source.

[0060] Examples of the surface light source include a surface LED light source and a surface OLED light source.

[0061] Alternatively, a display may be used as the illumination unit, in which case the display displays a pattern having light and dark areas.

[0062] The angle of incidence of the illumination light on the surface to be measured is not particularly limited as long as the light detection unit can receive the reflected light from the surface to be measured, and is usually less than 90°. The variation in light intensity may be quantified for each angle of incidence of the illumination light. The angle of incidence of the illumination light on the surface to be measured is the angle between the direction of incidence of the illumination light on the surface to be measured and the normal direction of the surface to be measured.

[0063] The distance between the surface to be measured and the illumination unit is not particularly limited as long as the illumination light emitted from the illumination unit can be reflected by the surface to be measured and the reflected light having bright and dark areas can be received by the light detection unit, and can be set appropriately.

[0064] 2. Light detection unit The light detection unit in the present disclosure focuses on the surface to be measured, receives reflected light that is reflected by the surface to be measured and has bright and dark regions corresponding to the bright and dark regions of the illumination light, and detects the light intensity distribution of the reflected light on the surface to be measured.

[0065] The light detection unit is not particularly limited as long as it can focus on the surface to be measured, receive reflected light from the surface to be measured, and detect the light intensity distribution of the reflected light on the surface to be measured, and examples thereof include a photoelectric conversion device that converts light into an electrical signal. Examples of photoelectric conversion devices include an imaging device and a photodiode array. The photoelectric conversion device may also be a device that scans a single photodiode using a driving device such as a stepping motor. Among these, a photoelectric conversion device is preferred, and an imaging device is more preferred.

[0066] The imaging device focuses on the surface to be measured and captures the reflected light having bright and dark regions corresponding to the bright and dark regions of the illumination light. From the captured image, the light intensity distribution of the reflected light on the surface to be measured is obtained.

[0067] The imaging device has an imaging element. Examples of the imaging element include a CCD image sensor and a CMOS image sensor. Examples of the imaging device include a digital camera. The imaging device can be, for example, an area camera or a line camera. In the case of a line camera, if the reflected light has a linear bright area, it is preferable to scan in the longitudinal direction of the linear bright area of ​​the reflected light. In the case of a line camera, if the reflected light has a lattice-point-shaped bright area, it is preferable to scan in the x direction or y direction of the lattice points of the bright area of ​​the reflected light.

[0068] The light detection unit receives specularly reflected light of the illumination light. Therefore, the reception angle of the reflected light is equal to the incident angle of the illumination light. The reception angle of the reflected light is the angle relative to the normal direction of the surface to be measured. Furthermore, the reception angle θ2 of the reflected light being equal to the incident angle θ1 of the illumination light means that the reception angle θ2 is within θ1±10°, preferably within θ1±5°, and more preferably within θ1±3°.

[0069] The distance between the measurement surface and the light detection unit is not particularly limited as long as the light detection unit can receive reflected light having bright and dark regions, and may be set appropriately. The distance between the measurement surface and the light detection unit may be the same as or different from the distance between the measurement surface and the illumination unit.

[0070] When the light detection unit is an imaging device, the number of pixels of the imaging element can be set appropriately.

[0071] In particular, it is preferable to set the distance between the surface to be measured and the light detection unit and the number of pixels of the imaging element so that the size of one pixel is, for example, 1 μm or more and 1000 μm or less, more preferably 10 μm or more and 100 μm or less, and particularly 10 μm or more and 30 μm or less. The resolution of the human eye, although subject to individual differences, is, for example, about 100 μm at a distance of 30 cm. Therefore, it is considered sufficient for the size of one pixel to be small, as long as it slightly exceeds the resolution of the human eye. If the size of one pixel is within the above range, the surface texture of the surface to be measured can be adequately measured.

[0072] The light detection unit focuses on the surface to be measured. The focus may be slightly off. Methods for focusing on the surface to be measured include, for example, placing an alignment mark on the surface to be measured and focusing on this alignment mark, or placing a mark at a position a predetermined distance away from the surface to be measured in the normal direction and focusing on this mark. When the mark is placed at a position a predetermined distance away from the surface to be measured in the normal direction, the distance between the surface to be measured and the mark is, for example, 3 cm or less.

[0073] The light reflected from the surface to be measured has light and dark regions that correspond to the light and dark regions of the illumination light. The light and dark regions in the reflected light are the same as the light and dark regions in the illumination light.

[0074] 3. First processing section In the first processing unit of the present disclosure, the peak value of the light intensity of the bright region or the light intensity at a position a predetermined distance away from the position showing the peak value of the light intensity of the bright region is determined in the light intensity distribution of the reflected light on the surface to be measured.

[0075] When the reflected light has a linear bright region, it is preferable that the first processing unit divides the light intensity distribution of the reflected light on the surface to be measured into N divided regions in the longitudinal direction of the linear bright region of the reflected light, and calculates the light intensity for each divided region. Also, when the reflected light has multiple linear bright regions, it is preferable that the first processing unit divides the light intensity distribution of the reflected light on the surface to be measured into N divided regions in the longitudinal direction of the linear bright region of the reflected light, and calculates the light intensity for each divided region and for each linear bright region. This allows for a large number of data (sample size) and enables accurate measurement of the surface texture of the surface to be measured.

[0076] In the above case, the number of divided regions (N) is not particularly limited. For example, if the light detection unit is an imaging device, the number of divided regions (N) can be the number of pixels in the longitudinal direction of the linear bright region of the reflected light in the image of the reflected light obtained by the imaging device. The greater the number of divided regions (N), the greater the number of data (sample size) can be, and the more accurately the surface texture of the surface to be measured can be measured. Furthermore, for example, if the light detection unit is an imaging device, the light intensity of the reflected light is detected for each pixel, so the upper limit of the number of divided regions (N) is set to be equal to or less than the number of pixels in the longitudinal direction of the linear bright region of the reflected light.

[0077] Here, the longitudinal direction of the linear bright region of the reflected light refers to the direction in which the linear bright region of the reflected light extends. For example, if the linear bright region of the reflected light has a linear shape, the longitudinal direction of the linear bright region of the reflected light is the direction in which the linear linear bright region extends. Also, for example, if the linear bright region of the reflected light has a curved shape, the longitudinal direction of the linear bright region of the reflected light is the direction in which the curved linear bright region extends.

[0078] For example, if the shape of the linear bright region of the reflected light is linear, the longitudinal direction of the linear bright region of the reflected light is the direction in which the linear linear bright region extends, as indicated by the symbol D1 in Fig. 3. For example, if the shape of the linear bright region of the reflected light is curved, the longitudinal direction of the linear bright region of the reflected light is the direction in which the curved linear bright region extends, as indicated by the symbol D1 in Fig. 7.

[0079] When the reflected light has a planar bright region, the first processing unit can divide the light intensity distribution of the reflected light on the surface to be measured into N divided regions in any direction and determine the light intensity for each divided region. This can increase the number of data (sample size). The direction in which the light intensity distribution of the reflected light on the surface to be measured is divided into N divided regions is not particularly limited and can be set appropriately depending on the shape of the planar bright region.

[0080] For example, as shown in FIG. 8(a), if the planar shape of planar bright region 21 is rectangular, first, the image of reflected light on the surface to be measured can be cut out along frame line 31 so that dark region 22, bright region 21, and dark region 22 are arranged in this order in the short direction D4 of rectangular bright region 21 in the image of reflected light on the surface to be measured. In this case, an image of reflected light such as that shown in FIG. 8(b) can be obtained. Next, as shown in FIG. 8(b), the image of reflected light can be divided into N divided regions A1 to An in the long direction D3 of the original rectangular bright region 21 shown in FIG. 8(a), and the light intensity can be calculated for each divided region and for each left-side light intensity distribution and right-side light intensity distribution.

[0081] Alternatively, for example, as shown in FIG. 8(a), if the planar shape of planar bright region 21 is rectangular, the image of reflected light on the surface to be measured can be cut out along frame line 32 so that dark regions 22, bright regions 21, and dark regions 22 are arranged in this order in the longitudinal direction D3 of rectangular bright region 21 in the image of reflected light on the surface to be measured. In this case, an image of reflected light such as that shown in FIG. 8(c) can be obtained. Next, as shown in FIG. 8(c), the image of reflected light can be divided into N divided regions A1 to An in the lateral direction D4 of the original rectangular bright region 21 shown in FIG. 8(a), and the light intensity can be calculated for each divided region and for each of the left-side light intensity distribution and the right-side light intensity distribution.

[0082] In the above case, the number of divided regions (N) is not particularly limited. For example, if the light detection unit is an imaging device, the number of pixels in any of the above directions in the image of reflected light obtained by the imaging device can be the number of divided regions (N).

[0083] Furthermore, if the reflected light has bright regions in the form of lattice points, the light intensity can be determined for each bright region. In this case, the light intensity distribution of the reflected light on the surface to be measured may be divided in the x direction of the lattice points of the bright regions of the reflected light to determine the light intensity for each bright region. Alternatively, the light intensity distribution of the reflected light on the surface to be measured may be divided in the y direction of the lattice points of the bright regions of the reflected light to determine the light intensity for each bright region.

[0084] For example, in an image of reflected light on a measurement surface as shown in FIG. 9, the x direction of the grid points of the bright areas of the reflected light is indicated by D5, and the y direction of the grid points of the bright areas of the reflected light is indicated by D6.

[0085] Furthermore, for example, as shown in FIG. 9, if an image of reflected light from the surface to be measured has four bright regions in the x-direction D5 of the grid points of the bright regions of the reflected light and nine bright regions in the y-direction D6 of the grid points of the bright regions of the reflected light, and if the image of reflected light from the surface to be measured is divided into the x-direction D5 of the grid points of the bright regions of the reflected light and the light intensity is calculated for each bright region, a light intensity distribution such as that shown in FIG. 10(a) can be obtained. In the light intensity distribution graph shown in FIG. 10(a), the horizontal axis represents the position in the x-direction D5 of the grid points of the bright regions of the reflected light. In the above case, if the image of reflected light from the surface to be measured is divided into the y-direction D6 of the grid points of the bright regions of the reflected light and the light intensity is calculated for each bright region, a light intensity distribution such as that shown in FIG. 10(b) can be obtained. In the light intensity distribution graph shown in FIG. 10(b), the horizontal axis represents the position in the y-direction D6 of the grid points of the bright regions of the reflected light.

[0086] For example, when the light detection unit is an imaging device and the reflected light has a linear bright region, and the light intensity distribution of the reflected light on the measurement surface is divided into N divided regions in the longitudinal direction of the linear bright region of the reflected light, the image of the reflected light obtained by the imaging device may be divided into N divided regions in the longitudinal direction of the linear bright region of the reflected light. In this case, if the reflected light has a linear linear bright region, an angle adjustment process may be performed to adjust the angle of the image so that the longitudinal direction of the linear bright region is horizontal or vertical.

[0087] Specifically, first, to remove noise, a smoothing process and a binarization process are performed on the image of reflected light obtained by the imaging device. Examples of smoothing methods include a moving average method and a Gaussian filter. Next, a linear approximation is performed on one linear bright region. In this case, the linear approximation can be performed using data from one end of the longitudinal direction of the binarized linear bright region. Examples of linear approximation methods include the least squares method. Next, the image is rotated so that the slope of the approximated line is zero. This makes it possible to make the longitudinal direction of the linear bright region of reflected light vertical. Furthermore, by rotating the image by an additional 90°, it is possible to make the longitudinal direction of the linear bright region of reflected light horizontal.

[0088] The first processing unit may determine the peak value of the light intensity of the bright region in the light intensity distribution of the reflected light from the surface to be measured, or may determine the light intensity at a position a predetermined distance from the position showing the peak value of the light intensity of the bright region. It is particularly preferable to determine the light intensity at a position a predetermined distance from the position showing the peak value of the light intensity of the bright region in the light intensity distribution of the reflected light from the surface to be measured. Because orange peel is easily visible near the boundary between the bright and dark regions, it is preferable to determine the light intensity at such a position.

[0089] 5(a) is an example of determining the peak value of the light intensity of a bright region in the light intensity distribution of reflected light on the measurement surface, where the reflected light has linear bright regions 21a to 21d. In the light intensity distribution of the reflected light shown in FIG. 5(a), the peak value P1 of the light intensity is obtained for each of the linear bright regions 21a to 21d. j ~P4 j Furthermore, when the reflected light has a linear bright region, and the light intensity distribution of the reflected light on the measurement surface is divided into N divided regions in the longitudinal direction of the linear bright region of the reflected light, the peak value P1 of the light intensity is calculated for each of the divided regions A1 to An and for each of the linear bright regions 21a to 21d. j ~P4 j (j=1~n).

[0090] 5(b) shows an example of determining the light intensity at a position a predetermined distance from the position showing the peak value of the light intensity of the bright region in the light intensity distribution of the reflected light on the measurement surface, where the reflected light has linear bright regions 21a to 21d. In the light intensity distribution of the reflected light shown in FIG. 5(b), first, the peak value P1 of the light intensity is calculated for each of the linear bright regions 21a to 21d. j ~P4 j The positions q0, r0, s0, and t0 that indicate the peak values ​​P1 of the light intensity distribution of each of the linear bright regions 21a to 21d are calculated. j ~P4 j The left light intensity distribution 23 and the right light intensity distribution 24 are divided into a left light intensity distribution 23 and a right light intensity distribution 24. Next, in the left light intensity distribution 23 of the linear bright region 21a, the peak value P1 j The light intensity value Q1 at a position a predetermined distance q1 from the position q0 kSimilarly, in the right-side light intensity distribution 24 of the linear bright region 21a, the peak value P1 of the light intensity is calculated. j The light intensity value Q2 at a position a predetermined value q2 away from the position q0 k Then, for each of the linear bright regions 21a to 21d and for each of the left light intensity distribution 23 and the right light intensity distribution 24, the peak value P1 of the light intensity is calculated. j ~P4 j The light intensity value Q1 at positions q1 to q2, r1 to r2, s1 to s2, t1 to t2 away from the positions q0, r0, s0, t0 indicating k ~Q2 k , R1 k ~R2 k , S1 k ~S2 k , T1 k ~T2 k Furthermore, for each of the divided regions A1 to An, for each of the linear bright regions 21a to 21d, and for each of the left light intensity distribution 23 and the right light intensity distribution 24, the light intensity value Q1 k ~Q2 k , R1 k ~R2 k , S1 k ~S2 k , T1 k ~T2 k (k=1~n).

[0091] When determining the light intensity at a position that is a predetermined distance away from the position showing the peak value of the light intensity of the bright region in the light intensity distribution of reflected light on the surface to be measured, the distance between the position showing the peak value of the light intensity of the bright region and the predetermined position is not particularly limited.

[0092] For example, the arithmetic mean value of the light intensity when the peak value of the light intensity in the bright region is determined in the light intensity distribution of the reflected light on the surface to be measured can be used as a reference value, and the light intensity at a position where the light intensity is 10% to 100% of the reference value from the position where the peak value of the light intensity in the bright region is shown can be determined. In particular, it is preferable to use the arithmetic mean value of the light intensity when the peak value of the light intensity in the bright region is determined in the light intensity distribution of the reflected light on the surface to be measured as a reference value, and to determine the light intensity at a position where the light intensity is 30% to 80%, particularly 40% to 60%, of the reference value from the position where the peak value of the light intensity in the bright region is shown. Because orange peel is easily visible near the boundary between the bright and dark regions, it is preferable to determine the light intensity at such a position.

[0093] In the above case, for example, first, the peak value of the light intensity of the bright region is obtained in the light intensity distribution of the reflected light on the measurement surface. Specifically, in the light intensity distribution of the reflected light shown in FIG. 5(a), the peak value of the light intensity P1 for each of the linear bright regions 21a to 21d is obtained. j ~P4 j Furthermore, when the light intensity distribution of the reflected light on the measurement surface is divided into N divided regions in the longitudinal direction of the linear bright regions of the reflected light, the peak value P1 of the light intensity is calculated for each of the divided regions A1 to An and for each of the linear bright regions 21a to 21b. j ~P4 j (j=1 to n) and calculate the peak value P1 j ~P4 j The arithmetic mean value of (j=1 to n) is calculated and used as the reference value. Next, the light intensity of the bright region is calculated from the position showing the peak value of the light intensity to the position where the light intensity is within a predetermined range of the reference value.

[0094] The distance between the position showing the peak value of the light intensity in the bright region and the predetermined position can be constant, i.e., for example, in Fig. 5(b), the predetermined values ​​q1 to q2, r1 to r2, s1 to s2, and t1 to t2 can be constant.

[0095] The first processing unit may perform a smoothing process in advance on the light intensity distribution of the reflected light on the measurement surface detected by the light detection unit, in order to determine the position of the peak value of the light intensity of the bright region. When it is difficult to determine the position of the peak value of the light intensity of the bright region due to small fluctuations in the light intensity distribution of the reflected light, it is preferable to perform the smoothing process. By performing the smoothing process, the position of the peak value of the light intensity of the bright region can be easily determined. Furthermore, when the fluctuations in light intensity are small, simply taking the maximum value of the light intensity of the bright region as the peak value of the light intensity of the bright region may make it difficult to accurately evaluate the variation in light intensity.

[0096] Examples of the smoothing method include a moving average method, etc. Alternatively, the smoothing method may involve performing a Fourier transform, removing components with higher frequencies than the pitch of the peaks that become noise, and then performing an inverse Fourier transform.

[0097] When smoothing is performed, the position of the peak value of light intensity in the bright region is determined in the light intensity distribution after the smoothing process. Then, when determining the peak value of light intensity in the bright region or the light intensity at a position a predetermined distance away from the position indicating the peak value of light intensity in the bright region, the light intensity is determined from the light intensity distribution before the smoothing process, not from the light intensity distribution after the smoothing process. In other words, the position of the peak value of light intensity in the bright region is determined from the light intensity distribution after the smoothing process, and the light intensity value is determined from the light intensity distribution before the smoothing process.

[0098] 4. Second processing section In the second processing section of the present disclosure, the variations in light intensity obtained in the first processing section are quantified.

[0099] The variation in light intensity can be measured using, for example, standard deviation, coefficient of variation, variance, deviation value, mean absolute deviation, etc. The coefficient of variation is the value obtained by dividing the standard deviation by the arithmetic mean value. Among these, the coefficient of variation is preferable. Here, when the reflectance of the surface to be measured is relatively low or when the amount of illumination light is relatively low, the variation in light intensity tends to be small. Therefore, in such cases, the variation in light intensity can be adequately evaluated by using the coefficient of variation.

[0100] For example, if the reflected light has a plurality of linear bright regions, and the first processing unit divides the light intensity distribution of the reflected light on the measurement surface into N divided regions in the longitudinal direction of the linear bright regions of the reflected light, and obtains the peak value of light intensity for each divided region and for each linear bright region, the variation in light intensity for each linear bright region can be calculated, and the arithmetic mean value of the variation in light intensity for each linear bright region can be calculated and used as the variation in light intensity. Specifically, if the variation in light intensity for each linear bright region is to be used as the standard deviation, the standard deviation of light intensity for each linear bright region can be calculated, and the arithmetic mean value of the standard deviation of light intensity for each linear bright region can be calculated, and this arithmetic mean value of the standard deviation of light intensity for each linear bright region can be used as the variation in light intensity. Specifically, when the variation in light intensity of each linear bright region is used as the coefficient of variation, the coefficient of variation in light intensity is calculated for each linear bright region, and the arithmetic mean value of the coefficients of variation in light intensity of each linear bright region is calculated, and the arithmetic mean value of the coefficients of variation in light intensity of each linear bright region can be used as the variation in light intensity.

[0101] 5(a), for example, in the case where the first processing unit 6 determines the peak value of the light intensity for each divided region A1 to An and for each linear bright region 21 a to 21 d in the light intensity distribution of the reflected light, and the variation in the light intensity of each linear bright region 21 a to 21 d is used as the coefficient of variation, the variation in the light intensity can be quantified specifically as follows. First, for one linear bright region 21 a, the peak value P1 of the light intensity in each divided region A1 to An is calculated. jThe arithmetic mean value and standard deviation of (j=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate the coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the linear bright region 21a. Similarly, for the other linear bright regions 21b, the peak values ​​P2 of the light intensity in each of the divided regions A1 to An are calculated. j The arithmetic mean value and standard deviation of (j=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate the coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the linear bright region 21b. In addition, for the other linear bright regions 21c, the peak value P3 of the light intensity in each of the divided regions A1 to An is calculated. j The arithmetic mean value and standard deviation of (j=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate the coefficient of variation, which is set as the coefficient of variation of the light intensity of the linear bright region 21c. Furthermore, for the other linear bright regions 21d, the peak value P4 of the light intensity in each of the divided regions A1 to An is calculated. j The arithmetic mean and standard deviation of (j=1 to n) are found, and the standard deviation is divided by the arithmetic mean to calculate a coefficient of variation, which is set as the coefficient of variation of the light intensity of linear bright region 21d. Next, the arithmetic mean of the coefficients of variation of the light intensity of each linear bright region 21a to 21d is calculated. This arithmetic mean of the coefficients of variation of the light intensity of each linear bright region 21a to 21d is set as the variation in light intensity.

[0102] Furthermore, for example, when the reflected light has a plurality of linear bright regions, the first processing unit divides the light intensity distribution of the reflected light on the surface to be measured into N divided regions in the longitudinal direction of the linear bright regions of the reflected light, and determines the light intensity at a position a predetermined distance from the position showing the peak value of the light intensity for each divided region, for each linear bright region, and for each left-side light intensity distribution and right-side light intensity distribution, the variation in light intensity for each linear bright region, for each left-side light intensity distribution, and for each right-side light intensity distribution is calculated, and the arithmetic mean value of the variation in light intensity for each linear bright region, for each left-side light intensity distribution, and for each right-side light intensity distribution is calculated, and this can be used as the variation in light intensity. Specifically, when the variation in light intensity for each linear bright region and for each left-side light intensity distribution and right-side light intensity distribution is used as the standard deviation, the standard deviation of light intensity is calculated for each linear bright region and for each left-side light intensity distribution and right-side light intensity distribution, and the arithmetic mean value of the standard deviation of light intensity for each linear bright region and for each left-side light intensity distribution and right-side light intensity distribution is calculated, and the arithmetic mean value of the standard deviation of light intensity for each linear bright region and for each left-side light intensity distribution and right-side light intensity distribution can be used as the variation in light intensity. Specifically, when the variation in light intensity for each linear bright region and for each left-side light intensity distribution and for each right-side light intensity distribution is used as the coefficient of variation, the coefficient of variation in light intensity is calculated for each linear bright region and for each left-side light intensity distribution and for each right-side light intensity distribution, and the arithmetic mean value of the coefficients of variation in light intensity for each linear bright region and for each left-side light intensity distribution and for each right-side light intensity distribution is calculated, and the arithmetic mean value of the coefficients of variation in light intensity for each linear bright region and for each left-side light intensity distribution and for each right-side light intensity distribution can be used as the variation in light intensity.

[0103] 5(b), when determining the light intensity at a position that is a predetermined distance from the position showing the peak value of the light intensity for each divided region A1 to An, for each linear bright region 21 (21a to 21d), for each left light intensity distribution 23, and for each right light intensity distribution 24 in the light intensity distribution of the reflected light, the first processing unit 6 can specifically quantify the variation in light intensity as follows. First, for the left light intensity distribution 23 of one linear bright region 21a, the light intensity value Q1 in each divided region A1 to An is calculated. kThe arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the left light intensity distribution 23 of the linear bright region 21a. In addition, for the right light intensity distribution 24 of one linear bright region 21a, the light intensity value Q2 in each divided region A1 to An is k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the right-side light intensity distribution 24 of the linear bright region 21a. Similarly, for the left-side light intensity distribution 23 of the other linear bright region 21b, the light intensity value R1 in each divided region A1 to An is set as the coefficient of variation of the light intensity of the right-side light intensity distribution 24 of the linear bright region 21a. k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the left light intensity distribution 23 of the linear bright region 21b. In addition, for the right light intensity distribution 24 of the linear bright region 21b, the light intensity value R2 in each divided region A1 to An is k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the right-side light intensity distribution 24 of the linear bright region 21b. In addition, for the left-side light intensity distribution 23 of the other linear bright region 21c, the light intensity values ​​S1 in each of the divided regions A1 to An are calculated. k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the left light intensity distribution 23 of the linear bright region 21c. In addition, for the right light intensity distribution 24 of the linear bright region 21c, the light intensity values ​​S2 in each of the divided regions A1 to An are k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the right-side light intensity distribution 24 of the linear bright region 21c. Furthermore, for the left-side light intensity distribution 23 of the other linear bright region 21d, the light intensity value T1 in each divided region A1 to An is calculated. k The arithmetic mean value and standard deviation of (k=1 to n) are calculated, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation. This coefficient of variation is set as the coefficient of variation of the light intensity of the left light intensity distribution 23 of the linear bright region 21d. In addition, for the right light intensity distribution 24 of the linear bright region 21d, the light intensity value T2 in each divided region A1 to An is set as the coefficient of variation of the light intensity of the left light intensity distribution 23 of the linear bright region 21d.k The arithmetic mean value and standard deviation of (k=1 to n) are found, and the standard deviation is divided by the arithmetic mean value to calculate a coefficient of variation, which is set as the coefficient of variation of the light intensity of right-side light intensity distribution 24 of linear bright region 21d. Next, the arithmetic mean value of the coefficients of variation of the light intensity of left-side light intensity distribution 23 and right-side light intensity distribution 24 of each linear bright region 21a to 21d is calculated. This arithmetic mean value of the coefficients of variation of the light intensity of left-side light intensity distribution 23 and right-side light intensity distribution 24 of each linear bright region 21a to 21d can be used as the variation in light intensity.

[0104] 5.Display section The surface texture measuring device of the present disclosure may have a display unit that displays the numerical value of the variation in light intensity.

[0105] 6.Applications The use of the surface texture measuring device of the present disclosure is not particularly limited. The surface texture measuring device of the present disclosure can be used, for example, to measure the orange peel of coatings, films, sheets, painted surfaces, processed surfaces, etc. In particular, the surface texture measuring device of the present disclosure is preferably used to measure the surface texture of optical films, and more preferably used to measure the surface texture of surface members of display devices.

[0106] B. Surface texture measurement method The surface texture measurement method disclosed herein includes an irradiation step of irradiating a surface to be measured with illumination light having bright and dark regions; a light detection step of focusing the light on the surface to be measured, receiving reflected light having bright and dark regions that correspond to the bright and dark regions of the illumination light, and detecting the light intensity distribution of the reflected light on the surface to be measured; a first processing step of determining, in the light intensity distribution of the reflected light on the surface to be measured, the peak value of the light intensity of the bright region or the light intensity at a position a predetermined distance away from the position showing the peak value of the light intensity of the bright region; and a second processing step of quantifying the variation in the light intensity determined in the first processing step.

[0107] FIG. 11 is a process diagram illustrating a surface texture measurement method according to the present disclosure, for example, a process diagram illustrating a surface texture measurement method performed by the surface texture measurement apparatus 10 shown in FIG. 1 . As shown in FIGS. 1 and 11 , first, in an irradiation step S11, the irradiation unit 2 irradiates the measurement surface 1 with illumination light L1 having bright and dark regions. Next, in a light detection step S12, the light detection unit 5 focuses on the measurement surface 1 and receives reflected light L2 having bright and dark regions corresponding to the bright and dark regions of the illumination light L1, thereby detecting the light intensity distribution of the reflected light L2 on the measurement surface 1. Next, in a first processing step S13, the first processing unit 5 determines the peak value of the light intensity in the bright region or the light intensity at a position a predetermined distance away from the position showing the peak value of the light intensity in the bright region in the light intensity distribution of the reflected light L2 on the measurement surface 1. Then, in the second processing step S14, the second processing unit 6 quantifies the variations in light intensity obtained in the first processing step S13.

[0108] In the surface texture measuring method of the present disclosure, similar to the above-described surface texture measuring device, surface textures such as unevenness and waviness on the surface of an object, so-called orange peel, can be quantitatively evaluated. Therefore, it is possible to quantify the orange peel.

[0109] Each step in the surface texture measuring method of the present disclosure will be described below.

[0110] 1.Lighting process In the light detection step of the present disclosure, illumination light having a bright region and a dark region is irradiated onto the surface to be measured.

[0111] The illumination step can be the same as that described in the section on the illumination unit in the surface texture measuring device.

[0112] In an object to be measured having a surface to be measured, a light-shielding layer may be disposed on the surface of the object to be measured opposite the surface to be measured. The light-shielding layer can suppress backside reflection. The light-shielding layer is not particularly limited, and for example, a black resin film or a blackboard can be used. Alternatively, a black resin composition may be applied to the surface of the object to be measured opposite the surface to be measured to form a light-shielding layer.

[0113] 2. Optical detection process In the light detection process of the present disclosure, the light is focused on the surface to be measured, reflected by the surface to be measured and has bright and dark regions corresponding to the bright and dark regions of the illumination light, and the light intensity distribution of the reflected light on the surface to be measured is detected.

[0114] The light detection step can be the same as that described in the section on the light detection unit in the surface texture measuring device.

[0115] 3. First processing step In the first processing step of the present disclosure, the peak value of the light intensity of the bright region or the light intensity at a position a predetermined distance away from the position showing the peak value of the light intensity of the bright region is determined in the light intensity distribution of the reflected light on the surface to be measured.

[0116] The first processing step can be the same as that described in the section on the first processing section of the surface texture measuring device.

[0117] 4. Second processing step In the second processing step of the present disclosure, the variations in light intensity obtained in the first processing step are quantified.

[0118] The second processing step can be the same as that described in the section on the second processing section of the surface texture measuring device.

[0119] 5.Applications The surface texture measuring method of the present disclosure has the same applications as the surface texture measuring device described above.

[0120] The present disclosure is not limited to the above-described embodiments. The above-described embodiments are merely examples, and any configuration that is substantially identical to the technical idea described in the claims of the present disclosure and that provides similar effects is included within the technical scope of the present disclosure. [Example]

[0121] The present disclosure will be specifically described below with reference to examples and comparative examples.

[0122] [Manufacturing Example 1] Corning Gorilla Glass 3 was used as the glass substrate. A black PET film was placed on the backside of the glass substrate. This was designated Sample 1. The surface to be measured of Sample 1 was the front side of the glass substrate.

[0123] [Manufacturing Example 2] The glass substrate used was Gorilla Glass 3 manufactured by Corning Incorporated. An acrylic film (CAT40 manufactured by Nitto Denko Corporation) was placed on one side of the glass substrate via an optically transparent adhesive sheet (OCA, PD-S1 manufactured by Panac Corporation, thickness 25 μm). A black PET film was placed on the other side of the glass substrate. This was designated Sample 2. The surface to be measured of Sample 2 was the surface of the acrylic film.

[0124] [Manufacturing Example 3] The glass substrate used was Corning Gorilla Glass 3. An optically transparent adhesive sheet (OCA, PD-S1 manufactured by Panac Corporation, thickness 25 μm) was placed on one side of the glass substrate. A black PET film was placed on the other side of the glass substrate. This was designated Sample 3. The surface to be measured of Sample 3 was the surface of the optically transparent adhesive sheet.

[0125] [Manufacturing Example 4] The glass substrate used was Gorilla Glass 3 manufactured by Corning Incorporated. An optically transparent adhesive sheet (OCA, Z6264 manufactured by Big Technos Corporation) was placed on one side of the glass substrate. A black PET film was placed on the other side of the glass substrate. This was designated Sample 4. The surface to be measured of Sample 4 was the surface of the optically transparent adhesive sheet.

[0126] [Example 1] (1) Configuration of surface texture measuring device The OLED light source used was an EELM-SKY-300-W manufactured by Ecorica. The mask used was a metal plate with rectangular openings penetrating the metal plate. The mask had a transmission area consisting of four rectangular openings. The rectangular transmission area had a length of 65 mm, a line width of 2.0 mm, and a pitch of 4.0 mm. The mask was directly attached to the OLED light source.

[0127] The camera used was a Nikon D5600 digital SLR camera, with a Nikon AF-P DX NIKKOR 18-55mm f / 3.5-5.6G VR lens. The camera settings were aperture f / 22, exposure time 1 / 8 second, ISO 100, and focal length 55mm.

[0128] The distance between the light source and the surface to be measured was 33 cm, the incident angle of the illumination light emitted from the lighting unit was 60°, the distance between the camera and the surface to be measured was 33 cm, and the receiving angle of the reflected light of the imaging device was 60°.

[0129] (2) Illumination and Light Detection A mark was placed 1 cm in front of the surface to be measured, and the camera was autofocused to focus on the mark. Light was irradiated onto the surface from the light source through a mask, and an image of the light reflected from the surface was taken with the camera.

[0130] (3) Processing The moving average of the image captured by the camera was taken over a 50-pixel scale, and the maximum value / 1.3 was used as the threshold value to binarize and remove noise. A straight line was approximated using the least squares method for the leftmost cell of each row, and the image was rotated so that the slope of the approximated line was 0. This corrected the position of the image.

[0131] In addition, 1100 pixels were cut from the center of the image captured by the camera in the longitudinal direction of the linear bright area of ​​the reflected light, and 500 pixels were cut in the lateral direction of the linear bright area of ​​the reflected light. The linear bright area of ​​the reflected light was divided into 1100 divided areas in the longitudinal direction, and the light intensity was calculated for each divided area and each linear bright area at a position 20 pixels away from the position showing the peak light intensity value. In this case, for example, as shown in Figure 5(b), two light intensities were calculated for each linear bright area in one divided area.

[0132] In this case, a moving average of 50 pixels was taken for the light intensity distribution in each divided region, and the position of the maximum light intensity of the linear bright region in the light intensity distribution after moving average processing was taken as the position of the peak light intensity of the linear bright region.

[0133] Furthermore, the position 20 pixels away from the position showing the peak light intensity value was the position where the light intensity was approximately 50% of the reference value. The reference value was calculated as follows. First, the peak light intensity value was calculated for each divided region and each linear bright region in the reflected light image. Next, the arithmetic mean value of the peak light intensity values ​​was calculated. This arithmetic mean value of the peak light intensity values ​​was used as the reference value.

[0134] Next, the arithmetic mean value and standard deviation of the obtained light intensity were calculated for each linear bright region and for each left-side light intensity distribution and right-side light intensity distribution, and the coefficient of variation (%) was calculated by dividing the standard deviation by the arithmetic mean value and multiplying the result by 100. Then, the arithmetic mean value of the coefficient of variation of the light intensity for each linear bright region and for each left-side light intensity distribution and right-side light intensity distribution was calculated.

[0135] [Example 2] (1) Configuration of the surface texture measuring device The surface texture measuring device had the same configuration as in Example 1.

[0136] (2) Illumination and Light Detection A mark was placed 1 cm in front of the surface to be measured, and the camera was autofocused to focus on the mark. Light was irradiated onto the surface from the light source through a mask, and an image of the light reflected from the surface was taken with the camera.

[0137] (3) Processing The moving average of the image captured by the camera was taken over a 50-pixel scale, and the maximum value / 1.3 was used as the threshold value to binarize and remove noise. A straight line was approximated using the least squares method for the leftmost cell of each row, and the image was rotated so that the slope of the approximated line was 0. This corrected the position of the image.

[0138] In addition, 1100 pixels were cut out from the center of the image taken by the camera in the longitudinal direction of the linear bright area of ​​the reflected light, and 500 pixels were cut out in the lateral direction of the linear bright area of ​​the reflected light. The linear bright area of ​​the reflected light was divided into 1100 divided areas in the longitudinal direction, and the peak value of the light intensity was calculated for each divided area and each linear bright area.

[0139] In this case, a moving average of 50 pixels was taken for the light intensity distribution in each divided region, and the position of the maximum light intensity of the linear bright region in the light intensity distribution after moving average processing was taken as the position of the peak light intensity of the linear bright region.

[0140] Next, the arithmetic mean and standard deviation of the light intensity were calculated for each linear bright region, and the coefficient of variation (%) was calculated by dividing the standard deviation by the arithmetic mean and multiplying the result by 100. Then, the arithmetic mean of the coefficient of variation of the light intensity of each bright region was calculated.

[0141] [Comparative Example] (1) Configuration of the surface texture measuring device The surface texture measuring device was configured in the same manner as in Example 1, except that the following mask was used.

[0142] The mask used was a metal plate with rectangular and cross-shaped openings penetrating the metal plate. As shown in Fig. 12, the mask had two transmissive regions: transmissive region 11a consisting of four rectangular openings and transmissive region 11b consisting of three cross-shaped openings. The rectangular transmissive regions had a length of 70 mm, a line width of 0.5 mm, and a pitch of 1.0 mm.

[0143] (2) Illumination and Light Detection The light source was focused by using the autofocus of the camera on the cross section of the reflected image of the surface to be measured. Light was irradiated onto the surface to be measured from the light source through a mask, and an image of the reflected light from the surface to be measured was taken with the camera.

[0144] (3) Processing From the center of the image captured by the camera, 1100 pixels were cut out in the longitudinal direction of the linear bright area of ​​the reflected light, and 500 pixels were cut out in the lateral direction of the linear bright area of ​​the reflected light. The linear bright area of ​​the reflected light was divided into 1100 divided areas in the longitudinal direction, and the pitch of the linear bright area was calculated for each divided area. In this case, the peak value of the light intensity of the linear bright area was calculated, and the distance between the peak values ​​of the light intensity of adjacent linear bright areas was defined as the pitch of the linear bright area. For one divided area, the standard deviation δ of the three pitches was calculated. Similarly, the standard deviation δ of the three pitches was calculated for each of the 1100 divided areas. The arithmetic mean value of the standard deviation δ of the pitch for each divided area was then calculated.

[0145] Comparative Example 1 imitates the method using the flatness measuring device described in Patent Document 1.

[0146] [Reference example] Instead of using a camera, the reflected light from the surface to be measured was observed visually and evaluated according to the following criteria. A: No yuzu skin B: Yuzuhada small C: Yuzu skin medium D: Yuzu skin size

[0147] [Table 1]

[0148] In the comparative example, the evaluations of Samples 2 and 3 were the same as the evaluation of Sample 1, and the orange peel was not sufficiently evaluated numerically. On the other hand, in Example 1, similar to the reference example, the evaluations of Samples 2 to 4 were all different from the evaluation of Sample 1, and the orange peel was evaluated numerically. Furthermore, in Example 2, similar to the reference example, the evaluations of Samples 3 and 4 were different from the evaluation of Sample 1, and the orange peel was evaluated numerically. Furthermore, for Sample 2, a comparison with Examples 1 and 2 confirmed that it is preferable to determine the light intensity at a position that is a predetermined value away from the position showing the peak value of the light intensity in the bright region in the light intensity distribution of the reflected light on the measurement surface. [Explanation of symbols]

[0149] 1 … Surface to be measured 2. Lighting section 3 … light source 4. Mask 5... Light detection section 6 ... First processing section 7 ... Second processing section 10…Surface texture measuring device

Claims

1. an illumination unit that irradiates the measurement surface with illumination light having a bright region and a dark region; a light detection unit that focuses on the measurement surface, receives reflected light that is reflected by the measurement surface and has bright and dark regions corresponding to the bright and dark regions of the illumination light, and detects a light intensity distribution of the reflected light on the measurement surface; a first processing unit that determines, in a light intensity distribution of the reflected light on the measurement surface, a peak value of the light intensity of the bright region or a light intensity at a position that is a predetermined distance away from a position showing the peak value of the light intensity of the bright region; a second processing unit that quantifies the variation in light intensity obtained by the first processing unit; A surface texture measuring device having the above structure.

2. The surface texture measuring device according to claim 1 , wherein the light detecting unit is an imaging device.

3. 3. The surface texture measuring device according to claim 1, wherein the illumination light has a linear bright region as the bright region, and the reflected light has a linear bright region as the bright region corresponding to the linear bright region of the illumination light.

4. 4. The surface texture measuring device according to claim 3, wherein the first processing unit divides the light intensity distribution of the reflected light on the measurement surface into N divided regions in a longitudinal direction of the linear bright region of the reflected light, and calculates the light intensity for each divided region.

5. 5. The surface texture measuring device according to claim 1, wherein, when determining the light intensity at a position in the light intensity distribution of the reflected light on the measured surface that is a predetermined distance away from a position showing the peak value of the light intensity of the bright region, the first processing unit uses an arithmetic mean value of the light intensity when determining the peak value of the light intensity of the bright region in the light intensity distribution of the reflected light on the measured surface as a reference value, and determines the light intensity at a position where the light intensity is 30% to 80% of the reference value from the position showing the peak value of the light intensity of the bright region.

6. an illumination step of irradiating the surface to be measured with illumination light having a bright region and a dark region; a light detection step of focusing on the measurement surface, receiving reflected light that is reflected by the measurement surface and has bright and dark regions corresponding to the bright and dark regions of the illumination light, and detecting a light intensity distribution of the reflected light on the measurement surface; a first processing step of determining, in the light intensity distribution of the reflected light on the measurement surface, a peak value of the light intensity of the bright region or a light intensity at a position a predetermined distance away from a position showing the peak value of the light intensity of the bright region; a second processing step of quantifying the variation in light intensity obtained in the first processing step; A surface texture measuring method comprising the steps of:

7. The surface texture measuring method according to claim 6 , wherein the light detecting step uses an imaging device.

8. 8. The surface texture measuring method according to claim 6, wherein the illumination light has a linear bright region as the bright region, and the reflected light has a linear bright region as the bright region corresponding to the linear bright region of the illumination light.

9. 9. The surface texture measuring method according to claim 8, wherein in the first processing step, the light intensity distribution of the reflected light on the measurement surface is divided into N divided regions in a longitudinal direction of the linear bright region of the reflected light, and the light intensity is determined for each of the divided regions.

10. 10. The surface texture measuring method according to claim 6, wherein, in the first processing step, when determining the light intensity at a position in the light intensity distribution of the reflected light on the measurement surface that is a predetermined distance away from a position showing the peak value of the light intensity of the bright region, the arithmetic mean value of the light intensity when the peak value of the light intensity of the bright region is determined in the light intensity distribution of the reflected light on the measurement surface is used as a reference value, and the light intensity is determined at a position from the position showing the peak value of the light intensity of the bright region where the light intensity is 30% to 80% of the reference value.

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