JP2015087389A - Visibility evaluation method of sample, dot pattern for visibility evaluation, and metal-clad laminate - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a method for numerically expressing visibility of a sample to evaluate it objectively.SOLUTION: A dot pattern 1 distributed in two dimensions is prepared and photographed via a sample 5. A photographed dot pattern image 3 is generated as an output image. The output image is divided into the same dot number as the dot pattern 1, which is an input image, and each dot is classified into two or more kinds. A frequency distribution is obtained by quantifying luminance of classified each kind of dot and a signal noise ratio is calculated from the average of luminance and a standard deviation. The signal noise ratio is compared with a signal noise ratio similarly calculated for an output image obtained when the dot pattern 1 is photographed via no sample and visibility of the sample is evaluated.

Description

  The present invention relates to a method for evaluating the visibility of a sample when observing an object through a sample made of a light transmissive material such as a synthetic resin, a dot pattern for visibility evaluation used in this method, and a metal The present invention relates to a tension laminate.

  In the photolithography process for CCL (copper-clad laminate) and the FPC (flexible printed circuit board) mounting process using CCL, various processes such as bonding, cutting, exposure, etching, etc. based on the alignment mark provided on CCL Is done. In order to maintain the processing accuracy in these steps, it is important to accurately recognize the alignment mark through the CCL synthetic resin layer.

  As an image visibility evaluation method, Patent Document 1 proposes a method for quantitatively evaluating the amount of blurring seen by human eyes. In Patent Document 1, an image using a finite element as a light source is formed, the image is projected onto an image capturing unit, and then the amount of blur of the image captured by the evaluation unit is evaluated. However, in the method of Patent Document 1, even when deformation distortion occurs in an image, if there is no change in the slope (blur) of the black-and-white boundary portion, the visibility is evaluated as good, and the visibility is properly evaluated. There was a disadvantage that it was not possible.

  Moreover, in patent document 2, the evaluation method of the anti-glare film for high definition displays by which the base film and the glare-proof layer were laminated | stacked is proposed. In this Patent Document 2, using an image sharpness measuring apparatus defined in JIS K7105-1981, four types of image sharpness obtained through an optical comb having a predetermined width and a 60-degree glossiness of an antiglare layer are used as indices. Yes. However, in the method of Patent Document 2, as in Patent Document 1, even when deformation distortion occurs in an image, if there is no change in the slope of the black and white boundary portion, the visibility is evaluated as good. , Visibility cannot be legitimately evaluated. Further, there is a drawback that only one direction perpendicular to the optical comb can be evaluated.

JP 2004-186789 A (Claims etc.) JP 2013-137554 A (Claims etc.)

  When the light transmittance of the CCL synthetic resin layer is small, when scattering, refraction, etc. are large, or when the thickness of the synthetic resin layer is non-uniform and strain is present, the visibility is greatly reduced. As a result, the alignment mark cannot be recognized accurately, and processing accuracy may be reduced. Therefore, it has been required to grasp the visibility of the synthetic resin layer as objective numerical data in advance.

  An object of the present invention is to provide a method for objectively evaluating the visibility of a sample by digitizing it.

The sample visibility evaluation method according to the present invention includes the following steps A to D;
A) preparing a two-dimensionally distributed dot pattern;
B) Photographing the dot pattern with an imaging device through the sample, and generating the photographed dot pattern image as an output image;
C) The output image is divided into the same number of dots as the dot pattern that is the input image, each dot is classified into two or more types, and the luminance is quantified for each classified type of dot to obtain a frequency distribution. Calculating the average value and standard deviation of the brightness for each type, and
D) calculating a signal-to-noise ratio from the average value and standard deviation of the luminance,
Is included.

The sample visibility evaluation method according to the present invention includes the following step E;
E) a step of comparing the signal-to-noise ratio with a signal-to-noise ratio calculated in the same manner for the output image of the dot pattern obtained when the image is taken without passing through the sample;
May further be included.

  In the sample visibility evaluation method according to the present invention, the sample may be a synthetic resin film.

  The sample visibility evaluation method according to the present invention may be configured such that the sample is placed at a position deviated from the imaging position of the input image and photographing is performed by the imaging device.

  In the sample visibility evaluation method according to the present invention, the dot pattern may be formed with nonuniform spatial frequencies.

  In the sample visibility evaluation method according to the present invention, the dot pattern may have a spatial frequency equal to or higher than that of the two-dimensional code.

  In the sample visibility evaluation method according to the present invention, the sample is the synthetic resin layer in a metal-clad laminate in which a metal layer and a synthetic resin layer are laminated, and the dot pattern is formed on the metal layer. Also good. In this case, the dot pattern may be formed by the metal layer and an opening carved in the metal layer, or the dot pattern may be printed on the metal layer. .

In the sample visibility evaluation method according to the present invention, the process C includes the following processes i) to vi):
i) a process of trimming the outline of the output image with a size including a margin of a predetermined range and assigning a plurality of pixels;
ii) the process of digitizing the brightness of each pixel;
iii) A process of dividing a trimmed output image into the same number of dots as the dot pattern as an input image, with a plurality of pixels as one dot,
iv) A process of selecting a pixel group to be processed by excluding pixels existing at the boundary of each dot,
v) a process of classifying each dot as either a white dot or a black dot, assuming that one dot is constituted by the selected pixel group;
vi) A process for calculating the frequency distribution by digitizing the luminance for each classified white dot or black dot, and calculating the average value and standard deviation of the luminance for each white dot or black dot;
May be included.

  In the sample visibility evaluation method according to the present invention, in the step C, the dots of the output image may be classified as either white dots or black dots.

  In the sample visibility evaluation method according to the present invention, in the step D, the signal-to-noise ratio may be calculated based on the following formula (1) or the following formula (2).

[In the formula, SNR represents the signal-to-noise ratio, μ ₀ is the average value of the luminance of the black dots, μ ₁ is the average value of the luminance of the white dots, σ ₀ is the standard deviation of the luminance of the black dots, and σ ₁ is the white dot This means the standard deviation of the brightness. ]

[In the formula, SNR ′ represents a signal-to-noise ratio, and σ _L represents the larger one of the standard deviation of luminance of black dots and the standard deviation of luminance of white dots. ]

  In the sample visibility evaluation method according to the present invention, the two-dimensionally distributed dot pattern includes a plurality of first dots and a plurality of second dots different from the first dots, The ratio of the first dot to the second dot (first dot: second dot) is in the range of 45:55 to 55:45, and the first dot or the second dot Any of the above may have a region that appears continuously in the range of 1 to 15 in the two-dimensional direction. In this case, the first dot and the second dot may form a quadrangle, and the entire dot pattern may have a quadrangular outline, which is out of the four corners of the quadrangular outline. The position may include an alignment area composed of a plurality of the second dots, and all four corner dots closest to the alignment area may be configured by the first dots. Further, the first dot may be a white dot and the second dot may be a black dot. Further, the sample may be the synthetic resin layer in a metal-clad laminate in which a metal layer and a synthetic resin layer are laminated, or the metal layer may be partially etched to form the dot pattern. The first dot may be constituted by the metal layer, and the second dot may be constituted by an opening carved in the metal layer.

  The dot pattern for visibility evaluation according to the present invention includes a plurality of first dots and a plurality of second dots different from the first dots, and the first dots and the second dots Are two-dimensionally distributed, and the ratio of the first dot to the second dot (first dot: second dot) is within a range of 45:55 to 55:45, and One of the dots or the second dot has a region that appears continuously in the range of 1 to 15 in the two-dimensional direction, and is used for evaluating the visibility of the sample.

  In the dot pattern for visibility evaluation according to the present invention, the first dot and the second dot may form a quadrangle, and the entire dot pattern may have a quadrangular outline. An alignment region composed of a plurality of the second dots may be provided at positions deviating from the four corners of the contour, and all the dots at the four corners closest to the alignment region are all the first dots. You may be comprised by the dot. Further, the first dot may be a white dot and the second dot may be a black dot. Furthermore, the sample may be the synthetic resin layer in a metal-clad laminate in which a metal layer and a synthetic resin layer are laminated, or the metal layer may be partially etched to form a dot pattern. The first dot may be constituted by the metal layer, and the second dot may be constituted by an opening carved in the metal layer.

  The metal-clad laminate according to the present invention is a metal-clad laminate in which a metal layer and a synthetic resin layer are laminated, and has any one of the above-described visibility evaluation dot patterns.

  According to the visibility evaluation method of the present invention, using a two-dimensionally distributed dot pattern, the luminance frequency distribution (histogram) is obtained from the output image of the dot pattern photographed through the sample, and the signal to noise ratio is calculated. By calculating, the visibility of the sample can be digitized and objectively evaluated. Therefore, according to the visibility evaluation method of the present invention, the visibility of, for example, a synthetic resin layer used for CCL or the like can be easily and quickly evaluated with an accuracy close to visual observation.

It is drawing which shows schematic structure of the dot pattern used for the visibility evaluation method which concerns on one embodiment of this invention. It is drawing which shows schematic structure of another aspect of a dot pattern. It is drawing explaining the principle of the visibility evaluation method which concerns on one embodiment of this invention. It is explanatory drawing which expands and shows a part of output image. It is explanatory drawing which shows another example of an output image. It is explanatory drawing which expands and shows a part of FIG. 3B. It is drawing which shows the histogram produced based on the brightness | luminance of each dot in an output image. It is a schematic block diagram of the visibility evaluation apparatus which concerns on the 1st Embodiment of this invention. It is a schematic block diagram of the visibility evaluation apparatus which concerns on the 2nd Embodiment of this invention. It is a schematic block diagram of the visibility evaluation apparatus which concerns on the 3rd Embodiment of this invention. It is a schematic block diagram of the visibility evaluation apparatus which concerns on the 4th Embodiment of this invention. It is drawing which shows the histogram of the brightness | luminance obtained about the sample A by the visibility evaluation apparatus shown in FIG. It is drawing which shows the output image obtained by the visibility evaluation apparatus shown in FIG. It is drawing which shows the histogram of the brightness | luminance obtained about the sample B by the visibility evaluation apparatus shown in FIG. It is drawing which shows the output image obtained by the visibility evaluation apparatus shown in FIG. It is drawing which shows the histogram of the brightness | luminance by the reference obtained by the visibility evaluation apparatus shown in FIG. It is drawing which shows the output image of the reference obtained by the visibility evaluation apparatus shown in FIG. It is drawing which shows the histogram of the brightness | luminance obtained about the sample A by the visibility evaluation apparatus shown in FIG. It is drawing which shows the output image obtained by the visibility evaluation apparatus shown in FIG. It is drawing which shows the histogram of the brightness | luminance obtained about the sample C by the visibility evaluation apparatus shown in FIG. It is drawing which shows the output image obtained by the visibility evaluation apparatus shown in FIG. It is drawing which shows the histogram of the brightness | luminance obtained about the sample D by the visibility evaluation apparatus shown in FIG. It is drawing which shows the output image obtained by the visibility evaluation apparatus shown in FIG. It is drawing which shows the histogram of the brightness | luminance by the reference obtained by the visibility evaluation apparatus shown in FIG. It is drawing which shows the output image of the reference obtained by the visibility evaluation apparatus shown in FIG. It is a graph which shows the result of having measured the angle profile of the scattered light about the samples A-E using the goniophotometer. It is a graph which shows the signal-noise ratio of the brightness | luminance totaled in the dot unit at the time of excluding a dot boundary from the process target by 2-pixel width about 3 types of CCL. It is a graph which shows the signal noise ratio of the brightness | luminance totaled in the pixel unit at the time of excluding a dot boundary from the process target in 2 steps C about three types of CCL. It is a graph which shows the signal noise ratio of the brightness | luminance totaled in the dot unit at the time of excluding a dot boundary from the process target by 1 pixel width in process C about three types of CCL. It is drawing which shows the signal-noise ratio of the brightness | luminance totaled in the pixel unit at the time of excluding a dot boundary from the process target by 1 pixel width about 3 types of CCL. It is drawing which shows the dot pattern image which image | photographed CCL-1 by LED light output 3mW / cm < ² >. It is drawing which shows the dot pattern image which image | photographed CCL-1 by LED light output 8mW / cm < ² >. It is drawing which shows the dot pattern image which image | photographed CCL-2 by LED light output 3mW / cm < ² >. It is drawing which shows the dot pattern image which image | photographed CCL-2 by LED light output 8mW / cm < ² >. It is drawing which shows the dot pattern image which image | photographed CCL-3 by LED light output 3mW / cm < ² >. It is drawing which shows the dot pattern image which image | photographed CCL-3 by LED light output 8mW / cm < ² >. It is drawing which shows the signal-noise ratio of the brightness | luminance totaled per dot about the case where a dot boundary is not excluded from a process target in process C about three types of CCL. It is drawing which shows the signal-noise ratio of the brightness | luminance totaled per pixel about the case where a dot boundary is not excluded from a process target in process C about three types of CCL. It is drawing which shows the histogram of the brightness | luminance totaled per dot when a dot boundary is excluded from the process target by 2 pixel width in the process C about CCL-1. It is drawing which shows the histogram of the brightness | luminance totaled in the pixel unit at the time of excluding a dot boundary from the process target by 2 pixel width in the process C about CCL-1. It is drawing which shows the histogram of the brightness | luminance tabulated in the dot unit at the time of excluding the dot boundary from the process target by 1 pixel width about the CCL-1. It is drawing which shows the histogram of the brightness | luminance tabulated for the pixel unit at the time of excluding a dot boundary from the process target by 1 pixel width about the CCL-1. It is a figure which shows the histogram of the brightness | luminance tabulated by the dot unit in the case of not excluding a dot boundary from the process target in the process C about CCL-1. It is drawing which shows the histogram of the brightness | luminance totaled per pixel in the case where a dot boundary is not excluded from a process target in the process C about CCL-1. It is a graph which shows the result of the reproducibility experiment of the signal noise ratio totaled in the dot unit at the time of excluding a dot boundary from the process target by 1 pixel width about 3 types of CCL.

  Next, embodiments of the present invention will be described with reference to the drawings as appropriate. A sample visibility evaluation method according to an embodiment of the present invention includes the following steps.

Step A) Preparing a two-dimensionally distributed dot pattern:
FIG. 1A is a drawing showing a schematic configuration of a dot pattern for visibility evaluation used in the visibility evaluation method according to the present embodiment. The dot pattern 1 illustrated in FIG. 1A is a pattern in which black and white dots are two-dimensionally distributed with an arbitrary number of dots (m × n; where m and n are positive integers).

  The dot pattern 1 preferably has a two-dimensional distribution in which the length and size of the continuous portion of black or white are not single. That is, it is preferable that the dot pattern 1 is not a single spatial frequency but a pattern in which a plurality of spatial frequencies are mixed and the spatial frequency is not uniform. Such a dot pattern 1 can be realized by randomly arranging black dots and white dots two-dimensionally. From this point of view, arbitrary digital information is used as the dot pattern 1 using, for example, a QR code (registered trademark), a CP code, a 2/4 modulation code, a 3/16 modulation code, a 5/9 modulation code, and the like. A two-dimensional coded version may be used. That is, it is preferable that the dot pattern 1 has a spatial frequency equivalent to or higher than that of the two-dimensional code. In FIG. 1A, a two-dimensional barcode consisting of 50 × 50 dots is used as the dot pattern 1 using a 2/4 modulation code.

  In addition, as the dot pattern 1, you may use the image which expressed the spatial frequency intricately, for example, animals and plants, a landscape, etc. by the fine dot.

  The dot pattern 1 is not limited to black and white binary, and may be a pattern of, for example, RGB three primary colors.

  Next, another aspect of the dot pattern for visibility evaluation will be described with reference to FIG. 1B. FIG. 1B is a plan view of the dot pattern 2. The dot pattern 2 has a plurality of first dots and a plurality of second dots different from the first dots. Here, the first dot may be a “black dot”, for example, and the second dot may be a “white dot”, for example. In the dot pattern 2, the first dots and the second dots are randomly distributed two-dimensionally. In the dot pattern 2, the first dot and the second dot each form a quadrangle, and the entire dot pattern 2 has a quadrilateral outline. In the example shown in FIG. 1B, the dot pattern 2 has a total of 2500 dots, 50 in the vertical direction and 50 in the horizontal direction.

  In the dot pattern 2, the ratio of the first dot to the second dot (first dot: second dot) is in the range of 45:55 to 55:45. When the ratio of the first dots is lower than 45, an unbalanced histogram in which the second number of dots is largely biased is obtained. When the ratio of the first dots is more than 55, an unbalanced histogram in which the number of first dots is biased is increased. In the dot pattern 2 shown in FIG. 1B, the ratio of the first dots to the second dots is close to 1: 1 compared to the dot pattern 1 using the 2/4 modulation code shown in FIG. Can be widened. For example, in the dot pattern 2, either the first dot or the second dot has a minimum value of 1 in the two-dimensional direction and a maximum value of 5 or more, preferably a maximum value so as to have an appropriate spatial frequency. It has the area | region which appears continuously as 10 or more. More specifically, it is preferable that either the first dot or the second dot has a region that appears continuously in a two-dimensional direction within a range of, for example, 1 to 15.

  Moreover, the dot pattern 2 has the marker part 2a which is an alignment area | region in the position which remove | deviated from the four corner | angular parts of a square outline, respectively. The marker portion 2a is a reference when performing trimming. In the example shown in FIG. 1B, the marker portion 2a shows only its outline, but is an area formed by 6 × 6 second dots (white dots). In addition, although the area | region around the marker part 2a becomes black originally, in FIG. 1B, it has shown in white for convenience of explanation. In FIG. 1B, the marker portions 2a are provided at four locations corresponding to the corner portions of the square dot pattern 2, but may be three locations.

  Further, in order to make it easy to detect the marker portion 2a formed by the second dots (white dots) on the image data, the dot pattern 2 has all the four corner dots closest to each marker portion 2a as the first. Dot (black dot). In the example shown in FIG. 1B, in each corner, not only the four corner dots but also the three dots adjacent to the four corner dots, each including a total of four dots, the first dot (black Dot).

  The dot pattern 2 can also be provided on a metal-clad laminate in which a metal layer and a synthetic resin layer are laminated. In that case, the dot pattern 2 can be formed by partially etching the metal layer. In this case, the first dot can be constituted by a metal layer, and the second dot can be constituted by a portion where the metal layer is removed by etching, that is, an opening carved in the metal layer. In this case, the synthetic resin layer is a sample that is subject to visibility evaluation.

Step B) Step of photographing the dot pattern 1 with the imaging device through the sample 5 and generating the photographed dot pattern image 3 as an output image:
FIG. 2 shows the principle of the process B in a simplified manner. In the visibility evaluation method of the present embodiment, the dot pattern 1 is photographed with the sample 5 interposed between the dot pattern 1 as an input image and the imaging device. In the following description, the dot pattern 1 is taken as an example, but the dot pattern 2 can be similarly used.

  Sample 5 is made of a light transmissive material, for example, synthetic resin film, glass, quartz, etc., transparent electrodes such as ITO (indium tin oxide) and zinc oxide, titanium oxide, aluminum oxide, iron oxide And light transmissive materials such as cobalt oxide, chromium oxide, zirconia, vanadium oxide, magnesium fluoride, silicon nitride, titanium nitride, and calcium carbonate. As the material of the synthetic resin film, polyimide, polyethylene, polyethylene oxide, polyethylene terephthalate, polyethylene naphthalate, polybutylene terephthalate, polybutylene naphthalate, polyurethane, nylon 6, nylon 66, triacetyl cellulose, triacetate, polystyrene, polyarylate, Polycarbonate, polyvinyl chloride, polymethylpentene, polyethersulfone, polymethyl methacrylate, polymethyl methacrylate (various acrylic resins), polytetrafluoroethylene, polyacrylonitrile, polyvinyl alcohol, diethylene glycol bisallyl carbonate, polycyclohexyl methacrylate, poly Benzyl methacrylate, polyphenylene methacrylate, polydialph Rate, polyvinyl naphthalene, polyvinyl carbazole, and various epoxy resins can be exemplified.

  The synthetic resin film may be a synthetic resin layer in a metal-clad laminate in which a metal layer and a synthetic resin layer are laminated, for example, represented by CCL (copper-clad laminate). When the sample 5 is a synthetic resin layer in a metal-clad laminate, the dot pattern 1 can be formed on the metal layer. In this case, the dot pattern 1 may be formed by, for example, a metal layer and an opening formed in the metal layer, or the dot pattern 1 may be printed on the metal layer using an appropriate ink. May be.

  The dot pattern image 3 photographed through the sample 5 differs from the original dot pattern 1 that is an input image due to the presence of the sample 5. In the visibility evaluation method of the present embodiment, this difference is quantified based on the luminance after step C, and the visibility of the sample 5 is evaluated. When the image is taken without passing through the sample 5 (reference), or when the light transmittance of the sample 5 is 100% and no refraction or scattering occurs, theoretically, the dot pattern image 3 that is an output image is The dot pattern 1 almost coincides with the original dot pattern 1. The dot pattern image 3 that is an output image can be subjected to, for example, marker detection, inclination correction, trimming, and the like as image processing.

Step C) The output image is divided into the same number of dots as the original dot pattern 1 that is the input image, and each dot is classified into two or more types, and the brightness is quantified for each classified type of dot. The process of calculating the distribution and calculating the average value and standard deviation of the brightness for each type
FIG. 3A shows an enlarged portion of a dot pattern image 3 that is an output image. The output image is divided into the same number of dots (50 × 50 dots) as the input image. Then, all the dots are classified into two or more types based on the dots of the input image. In the present embodiment, each dot of the output image is classified into two types of black dots or white dots based on the dots of the input image. Then, the luminance is digitized for each classified dot to obtain a frequency distribution.

  In addition, when the dot pattern 1 is a color, each dot can also be classified into, for example, three types of RGB.

FIG. 4 shows a histogram created based on the brightness of each dot. Here, a black dot is “0”, a white dot is “1”, and a luminance signal level (horizontal axis in FIG. 4) is divided into 256 scales to create a histogram. Based on this histogram, the average luminance values μ ₀ and μ ₁ and the standard deviations σ ₀ and σ ₁ are calculated for each of the black dot distribution and the white dot distribution.

Step D) Step of calculating a signal to noise ratio from the average value and standard deviation of luminance:
In step D, the signal-to-noise ratio can be calculated based on, for example, the following formula (1) or formula (2).

[Wherein μ ₀ is the average value of the brightness of the black dots, μ ₁ is the average value of the brightness of the white dots, σ ₀ is the standard deviation of the brightness of the black dots, and σ ₁ is the standard deviation of the brightness of the white dots . ]

[In the formula, σ _L means the larger one of the standard deviation σ ₀ of the luminance of black dots and the standard deviation σ ₁ of the luminance of white dots. ]

In order to obtain the signal noise ratio (SNR value or SNR ′ value; hereinafter, if they are not distinguished from each other, they may be simply referred to as “SNR value”), either equation (1) or equation (2) is used. However, in the formula (2), by using the larger value (σ _L ) of the standard deviation σ ₀ of the luminance of black dots and the standard deviation σ ₁ of the luminance of white dots, for example, the monochrome of the output image When the bias is large and the luminance standard deviation itself is small, the SNR value is corrected to be excessively high, and more accurate evaluation is possible.

In FIG. 4, the difference between the average value μ ₁ of the brightness of the white dots and the average value μ ₀ of the brightness of the black dots indicates the signal intensity S. Further, the difference between the standard deviation σ ₁ of the brightness of the white dots and the standard deviation σ ₀ of the brightness of the black dots indicates the noise intensity N. And the visibility of the sample 5 can be evaluated as objective numerical data by calculating a signal noise ratio (SNR value) based on the above formula (1) or formula (2).

Moreover, the visibility evaluation method according to the present embodiment includes the following step E:
E) For example, a step of photographing the dot pattern 1 without using the sample 5 and comparing the calculated SNR value with a reference SNR value obtained by performing the same processes as in Steps C and D can be included. By comparing with the SNR value of the reference, the visibility of the sample 5 can be objectively evaluated.

<Modification of process C>
Here, a modified example of the process in the process C will be described with reference to FIGS. 3B and 3C. FIG. 3B shows the entire dot pattern image 3 that is an output image when the dot pattern 2 (see FIG. 1B) is used. FIG. 3C shows an enlarged vicinity of one corner of the dot pattern image 3 of FIG. 3B. FIG. 3C also illustrates a boundary for trimming the dot pattern image 3 that is an output image and a position at which the dot pattern image 3 is divided.

Step C can include the following processes i) to vi).
i) Trimming the outline 3a of the dot pattern image 3 as an output image with a size including a margin within a predetermined range, and assigning a plurality of pixels.
ii) Digitize the brightness of each pixel.
iii) Using a plurality of pixels as one dot, the trimmed dot pattern image 3 is divided into the same number of dots as the dot pattern 1 as the input image.
iv) A pixel group to be processed is selected by excluding pixels existing at the boundary of each dot.
v) Assuming that one dot is constituted by the selected pixel group, each dot is classified as either a white dot or a black dot.
vi) The luminance is digitized for each classified white dot or black dot to obtain a frequency distribution, and the average value and standard deviation of the luminance are calculated for each white dot or black dot.

In the process i, for example, as shown in FIG. 3C, trimming is performed in a range surrounded by a trimming position 10 that is slightly larger than the original contour 3 a of the dot pattern image 3. This is because, in the subsequent process iii), when the trimmed dot pattern image 3 is divided into the same number of dots as the dot pattern 1 as the input image with reference to the trimming position 10, vertical division is performed. This is because the possibility that the boundary line 11 and the horizontal division boundary line 13 deviate from the actual dot boundary is considered.
That is, in process i, trimming is performed with reference to the marker portion 2a, and in process iii, division into a plurality of dots is performed with reference to the trimming position 10. Therefore, for example, when the marker portion 2a is not accurately imaged, or when there is distortion in the dot pattern image 3 itself that is the output image, the vertical division boundary line set in the dot pattern image 3 is used. 11 and the horizontal division boundary line 13 may not coincide with the dot boundary of the dot pattern image 3 in some cases. Such “deviation” in image data processing is a cause of misidentifying a “white dot” as a “black dot” or a “black dot” as a “white dot”. It becomes. Accordingly, in consideration of the occurrence of “deviation” in the image data processing, in the process i, the trimming position 10 is set in advance to a position that is enlarged outside the outline 3 a of the dot pattern image 3 by a predetermined range.

  For example, in the example shown in FIGS. 3B and 3C, 5 × 5 = 25 pixels are assigned to one dot, and the dot pattern image 3 is 50 × 50 = 2500 dots composed of square white dots and black dots. . In this case, for example, the trimming position 10 may be set to a square of 251 × 251 pixels by enlarging the upper and lower, left and right sides by 1/2 pixel width from the outline 3a. For example, when 500 × 500 pixels are allocated to the entire contour 3a, the trimming position 10 may be expanded to the outside of the top, bottom, left, and right by one pixel width from the contour 3a and set to a square of 502 × 502 pixels. Good. Preferably, the former can be processed with a smaller number of pixels, which is advantageous in terms of speeding up the processing and saving the amount of data.

  In process ii, the luminance of each pixel is digitized. For example, the luminance of each pixel is divided into a plurality of gradations and digitized. In the embodiment described later, the luminance of each pixel is digitized by dividing it into 256 gradations.

  In the process iii, the trimmed dot pattern image 3 is divided into the same number of dots as the dot pattern 1 that is the input image with reference to the trimming position 10. A plurality of pixels are assigned to each divided dot. For example, in the example shown in FIGS. 3B and 3C, a square of 251 × 251 pixels is divided into 50 × 50 = 2500 dots, and 5 × 5 = 25 pixels are assigned to one dot in the dot pattern image 3.

  In the process iv, a pixel group to be processed is selected by excluding pixels existing at the boundaries of the divided dots. For example, in FIG. 3C, for the outermost 16 pixels in one dot of 5 × 5 = 25 pixels, 4 pixels in the corner portion are each 1/4 pixel (1 pixel in total), and the other 14 pixels are The inner 4 × 4 = 16 pixels are extracted by excluding each half pixel (total 8 pixels). Then, the inner 4 × 4 = 16 pixels are selected as a pixel group to be processed. In this case, since the trimming position 10 is enlarged from the outline 3a of the dot pattern image 3 in the process i), the 1/2 pixel width located at the boundary of each dot when the trimming position 10 is divided as a reference is targeted. It becomes possible to exclude. The excluded 1/2 pixel width forms a boundary together with the outermost 1/2 pixel width of the adjacent dots. In this manner, by excluding the pixels existing at the boundaries between the divided dots from the processing target, it is possible to mitigate the influence of the blurring of the dot boundaries caused by the optical system. In addition, the influence of errors due to aberration caused by the optical system and “deviation” occurring in image processing can be reduced.

  In the process v, each dot of the dot pattern image 3 is classified as either a white dot or a black dot, assuming that one dot is constituted by the selected pixel group of 4 × 4 = 16 pixels.

  In the processing vi, in the same manner as described above, the luminance is digitized for each classified white dot and black dot to obtain a frequency distribution, and the average value and standard deviation of the luminance are calculated.

  As described above, in the modified example of the step C, the pixel located at the boundary portion of each dot in the dot pattern image 3 that is the output image is excluded from the processing target of the luminance frequency distribution, thereby causing the optical system. It is possible to mitigate the effects of blurring at the dot boundaries. In addition, the influence of errors due to aberration caused by the optical system and “deviation” occurring in image processing can be reduced.

  Next, the structure of the visibility evaluation apparatus for enforcing the visibility evaluation method of the sample 5 of this invention is demonstrated, referring FIGS.

[First Embodiment]
FIG. 5 is a schematic configuration diagram of the visibility evaluation apparatus according to the first embodiment of the present invention. The visibility evaluation apparatus 100 includes a light source 101, a spatial light modulator (SLM) 103 that displays the dot pattern 1, and an imaging device 105 that captures the dot pattern 1 displayed on the spatial light modulator (SLM) 103. It has.

  As the light source 101, for example, a lamp light source, a laser light source, an LED light source, or the like can be used. When irradiating light of a single wavelength, it is preferable to use a laser light source or an LED light source.

  The spatial light modulator (SLM) 103 has a plurality of minute light modulation elements arranged in two dimensions, and electrically controls the spatial distribution of the amplitude, phase, polarization, etc. of the light from the light source 101. Then, the light is modulated to display the dot pattern 1 two-dimensionally. Examples of the spatial light modulator (SLM) 103 include a reflective liquid crystal (LCOS) type, a transmissive liquid crystal type, a ferroelectric liquid crystal type, and a micromirror (DMD: Digital Mirror Device) type. and so on.

  The imaging device 105 includes an imaging element (not shown) such as a CCD or a CMOS image sensor.

  A sample 5 is disposed between the spatial light modulator (SLM) 103 and the imaging device 105. The spatial light modulator (SLM) 103 is an LCOS type. The sample 5 is arranged at a position deviating from the image forming position 107 of the input image in FIG. It is preferable to adjust the distance from the imaging position 107 of the input image according to the scattered light level of the sample 5. When the scattered light level of the sample 5 is large, the image formation position 107 and the position of the sample 5 may be matched. When the sample 5 has light scattering and distortion, the blur and the disturbance of the output image increase as the sample 5 is separated from the imaging position 107. For this reason, when evaluating samples with a large scattered light level, if the sample 5 is moved away from the imaging position 107, the output image is greatly disturbed due to the influence of scattering, and the evaluation becomes difficult. It is preferable to do this. Conversely, when evaluating samples with low scattered light levels, if the sample 5 is placed at the imaging position 107, the output image of any sample is less disturbed and it becomes difficult to evaluate the difference between the samples. It is preferable to arrange at a position away from the position 107.

  Further, the visibility evaluation apparatus 100 includes a polarization beam splitter (PBS) 111 for separating polarization components, a half-wave plate (HWP) 113 that gives a phase difference of λ / 2 to the polarization plane of incident light, a first Lens 115, second lens 117, and third lens 119. The polarization beam splitter (PBS) 111 is used to efficiently obtain light from the LCOS type spatial light modulator (SLM) 103 with high contrast. A half-wave plate (HWP) 113 is used for light amount adjustment. The first lens 115 and the second lens 117 are relay lenses for forming an input image at the imaging position 107. Note that the first lens 115 and the second lens 117 may be either one. The third lens 119 is a lens for forming an image on an imaging element (not shown) of the imaging device 105.

  Further, the visibility evaluation apparatus 100 includes a control unit 500 that performs image processing and arithmetic processing. Each component of the visibility evaluation device 100 is connected to the control unit 500 and controlled. The control unit 500 includes a controller 501 including a CPU, a user interface 502, and a storage unit 503. The controller 501 has a computer function, and controls and controls each component in the visibility evaluation apparatus 100, and performs image processing and processing on the dot pattern image 3 that is an output image generated by the imaging apparatus 105. Perform arithmetic processing. The user interface 502 includes a keyboard on which an administrator performs command input operations for managing the visibility evaluation apparatus 100, a display for visualizing and displaying output images and calculation results, and the like. The storage unit 503 stores a control program (software), processing condition data, and the like for realizing the processing executed by the visibility evaluation apparatus 100 under the control of the controller 501. The user interface 502 and the storage unit 503 are connected to the controller 501.

  The visibility evaluation apparatus 100 having the above configuration guides the light emitted from the light source 101 to the polarization beam splitter (PBS) 111 via the half-wave plate (HWP) 113, and this polarization beam splitter (PBS) 111. The light is incident on the spatial light modulator (SLM) 103 to display the two-dimensional dot pattern 1. The dot pattern 1 displayed by the spatial light modulator (SLM) 103 is imaged from the polarization beam splitter (PBS) 111 through the first lens 115, the second lens 117, the sample 5, and the third lens 119. An image is captured by 105.

  For the dot pattern image 3 as an output image picked up by the image pickup device 105, the control unit 500 performs the processes of the above steps C and D, and calculates the signal-to-noise ratio (SNR value). Can be evaluated as objective numerical data. Further, by comparing the calculated SNR value with the reference SNR value obtained by photographing the dot pattern 1 without using the sample 5 in the visibility evaluation apparatus 100 and performing the processes of steps C and D, the sample 5 Visibility may be evaluated.

[Second Embodiment]
FIG. 6 is a schematic configuration diagram of a visibility evaluation apparatus according to the second embodiment of the present invention. The visibility evaluation apparatus 200 includes a monitor 201 that displays the dot pattern 1, a spacer 203 attached to the monitor 201, and an imaging device 105 that captures the dot pattern 1.

  The monitor 201 is, for example, a liquid crystal display or an LED display, and displays the two-dimensional dot pattern 1 that is an input image on the screen.

  The spacer 203 is made of a light transmissive material such as transparent glass. The spacer 203 is attached in close contact with the surface of the monitor 201. The thickness of the spacer 203 is preferably adjusted according to the scattered light level of the sample 5.

  The configuration of the imaging device 105 is the same as that of the first embodiment.

  Further, the visibility evaluation device 200 includes a lens 205 between the sample 5 and the imaging device 105. The lens 205 is a lens for forming an image on an imaging element (not shown) of the imaging device 105.

  Further, the visibility evaluation apparatus 200 includes a control unit 500 that performs image processing and arithmetic processing. The configuration of the control unit 500 is the same as that of the first embodiment.

  In the visibility evaluation device 200, the sample 5 is disposed so as to be interposed between the monitor 201 and the imaging device 105. The sample 5 is disposed in close contact with the spacer 203. When the scattered light level of the sample 5 is high, the sample 5 may be disposed in close contact with the monitor 201 without providing the spacer 203. When the sample 5 has light scattering and distortion, the more the sample 5 is separated from the monitor 201, the greater the blur and disturbance of the output image. For this reason, when evaluating samples having a large scattered light level, if the sample 5 is separated from the monitor 201, the output image is greatly disturbed due to the influence of scattering, and the evaluation becomes difficult. It is preferable that the sample 5 is directly adhered. Conversely, when evaluating samples having a low scattered light level, if the sample 5 is brought into close contact with the monitor 201 directly, the output image of any sample is less disturbed and it is difficult to evaluate the difference between the samples. The spacer 203 is preferably provided at a position away from the monitor 201.

  The visibility evaluation apparatus 200 having the above configuration displays the two-dimensional dot pattern 1 on the monitor 201. The dot pattern 1 is imaged by the imaging device 105 through the spacer 203 and the sample 5.

  For the dot pattern image 3 as an output image picked up by the image pickup device 105, the control unit 500 performs the processes of the above steps C and D, and calculates the signal-to-noise ratio (SNR value). Can be evaluated as objective numerical data. Further, the calculated SNR value is obtained by photographing the dot pattern 1 without using the sample 5 in the visibility evaluation apparatus 200 and comparing the calculated SNR value with the SNR value of the reference subjected to the processes C and D. Visibility may be evaluated.

[Third Embodiment]
FIG. 7 is a schematic configuration diagram of a visibility evaluation apparatus according to the third embodiment of the present invention. The visibility evaluation device 300 includes an input image 301 on which the dot pattern 1 is printed, a spacer 303 disposed between the input image 301 and the sample 5, an imaging device 105 that captures the input image 301, and an input. A light source 307 for irradiating the image 301 with light is provided.

  The input image 301 can be obtained by printing the two-dimensional dot pattern 1 on an arbitrary medium such as high-quality paper.

  The spacer 303 is made of a light transmissive material such as transparent glass. The spacer 303 is attached in close contact with the surface of the input image 301. The thickness of the spacer 303 is preferably adjusted according to the scattered light level of the sample 5.

  The configuration of the imaging device 105 is the same as that of the first embodiment.

  One or a plurality of light sources 307 can be provided as shown in FIG.

  In addition, a transparent plate 309 can be provided between the sample 5 and the imaging device 105 in close contact with the sample 5. The transparent plate 309 is, for example, a glass plate, an acrylic plate, a quartz plate, or the like, and is used for the purpose of fixing the sample 5. The transparent plate 309 can be omitted.

  A lens 311 can be provided between the sample 5 and the imaging device 105. The lens 311 is a lens for forming an image on an imaging element (not shown) of the imaging device 105.

  Further, the visibility evaluation apparatus 300 includes a control unit 500 that performs image processing and arithmetic processing. The configuration of the control unit 500 is the same as that of the first embodiment.

  In the visibility evaluation device 300, the sample 5 is disposed so as to be interposed between the input image 301 and the imaging device 105. The sample 5 is disposed in close contact with the spacer 303, for example. When the scattering level of the sample 5 is large, the spacer 5 may not be provided, and the sample 5 may be brought into close contact with the input image 301 directly.

  In the visibility evaluation apparatus 300 having the above-described configuration, the imaging apparatus captures the two-dimensional dot pattern 1 of the input image 301 via the spacer 303, the sample 5, and the transparent plate 309 while irradiating the input image 301 with light from the light source 307. An image is captured by 105.

  For the dot pattern image 3 as an output image picked up by the image pickup device 105, the control unit 500 performs the processes of the above steps C and D, and calculates the signal-to-noise ratio (SNR value). Can be evaluated as objective numerical data. Further, the calculated SNR value is obtained by photographing the dot pattern 1 without using the sample 5 in the visibility evaluation device 300 and comparing it with the SNR value of the reference subjected to the processes C and D. Visibility may be evaluated.

[Fourth Embodiment]
FIG. 8 is a schematic configuration diagram of a visibility evaluation apparatus according to the fourth embodiment of the present invention. This visibility evaluation apparatus 400 uses a CCL 401 on which a two-dimensional dot pattern 1 is formed.

  The visibility evaluation device 400 includes a CCL 401, a light source 403 that emits light toward the CCL 401, and an imaging device 105 that captures a dot pattern 1 that is an input image formed on the CCL 401.

  The CCL 401 includes a copper foil and a synthetic resin layer. As CCL401, what formed the through-opening corresponding to the dot pattern 1 in copper foil, or what printed the dot pattern 1 can be used. When the through opening corresponding to the dot pattern 1 is formed on the copper foil, a black or white plate material or paper may be bonded to the back surface side of the copper foil as necessary. Moreover, in this Embodiment, the synthetic resin layer of CCL401 becomes the sample 5 which is the object of visibility evaluation. The CCL 401 is disposed such that the synthetic resin layer that is the sample 5 faces the imaging device 105.

  One or a plurality of light sources 403 can be provided. The light source 403 irradiates light to the back side (copper foil side) or the front side (synthetic resin layer side) of the CCL 401.

  The configuration of the imaging device 105 is the same as that of the first embodiment.

  A lens 407 can be provided between the CCL 401 and the imaging device 105. The lens 407 is a lens for forming an image on an imaging element (not shown) of the imaging device 105.

  In addition, the visibility evaluation apparatus 400 includes a control unit 500 that performs image processing and arithmetic processing. The configuration of the control unit 500 is the same as that of the first embodiment.

  In the visibility evaluation apparatus 400 having the above configuration, the two-dimensional dot pattern 1 formed on the copper foil of the CCL 401 is imaged through the synthetic resin layer as the sample 5 while irradiating the CCL 401 with light from the light source 403. Imaging is performed by the device 105.

  For the dot pattern image 3 as an output image picked up by the image pickup device 105, the control unit 500 performs the processes of the above steps C and D, and calculates the signal-to-noise ratio (SNR value). The visibility of (the synthetic resin layer of CCL401) can be evaluated as objective numerical data. Further, the calculated SNR value is obtained by photographing the dot pattern 1 in the visibility evaluation device 400 without using the sample 5 and comparing it with the reference SNR value obtained by performing the processes C and D. Visibility may be evaluated.

[Example]
Next, experimental results confirming the effects of the present invention will be described. As sample 5, sample A, sample B, sample C, sample D and sample E of five kinds of polyimide films were prepared. About these samples, visibility evaluation was performed using the visibility evaluation apparatus 100 shown in FIG. 5 or the visibility evaluation apparatus 200 shown in FIG. The results are shown in Table 1. In Table 1, the measurement results of haze value and light transmittance for each sample are also shown.

  From Table 1, the SNR values for samples A to E obtained by the visibility evaluation method of the present invention have a certain degree of correlation with the values of haze value and light transmittance, while haze value or light transmittance. It also showed a tendency that could not be obtained with either one of them. The reason is considered that the visibility evaluation method of the present invention can comprehensively evaluate the visibility of the sample in a state closer to visual observation.

  FIG. 9A shows a luminance histogram obtained by evaluating the sample A by the visibility evaluation apparatus 100 shown in FIG. 5, and FIG. 9B shows an output image in that case. The vertical axis of the histogram of FIG. 9A indicates the number of data, and the horizontal axis indicates the signal level divided into 256 (the same applies to FIGS. 10A, 11A, 12A, 13A, and 14A).

  FIG. 10A shows a luminance histogram obtained by evaluating the sample B by the visibility evaluation apparatus 100 shown in FIG. 5, and FIG. 10B shows an output image in that case.

  FIG. 11A shows a luminance histogram in a reference test performed without using a sample by the visibility evaluation apparatus 100 shown in FIG. 5, and FIG. 11B shows an output image in that case.

  FIG. 12A shows a luminance histogram obtained by evaluating the sample A by the visibility evaluation apparatus 200 shown in FIG. 6, and FIG. 12B shows an output image in that case.

  FIG. 13A shows a luminance histogram obtained by evaluating the sample C by the visibility evaluation apparatus 200 shown in FIG. 6, and FIG. 13B shows an output image in that case.

  FIG. 14A shows a histogram of luminance obtained by evaluating the sample D by the visibility evaluation apparatus 200 shown in FIG. 6, and FIG. 14B shows an output image in that case.

  FIG. 15A shows a luminance histogram in a reference test performed without using a sample by the visibility evaluation apparatus 200 shown in FIG. 6, and FIG. 15B shows an output image in that case.

  FIG. 16 is a graph showing the results of measuring the angle profile of the scattered light for samples A to E using a goniophotometer. The vertical axis in FIG. 16 indicates the scattered light level on a logarithmic scale, and the horizontal axis indicates the detection angle. The scattered light level was measured by irradiating polyimide with 635 nm laser light, which is considered to have low absorption, and scanning the photodetector within an angular range of −45 degrees to 45 degrees. Note that the scattered light level was normalized by the 0th order transmitted light.

  From FIG. 16, even when the materials are the same polyimide, the scattered light level has a large difference between the samples A to E, and a difference of 3 to 4 digits at the maximum is recognized. Further, when comparing the results shown in FIG. 16 with the results shown in Table 1, the order of the scattered light levels is consistent with the order of the SNR values, which are the results of the visibility evaluation by the visibility evaluation apparatus 100, and has a strong correlation. The relationship was recognized. From this, it was confirmed that the visibility evaluation method of the present invention expresses optical characteristics including the scattered light level of the sample as objective numerical data.

  As samples, three types of copper-clad laminates CCL-1, CCL-2, and CCL-3 were prepared. CCL-1, CCL-2, and CCL-3 are double-sided copper clad laminates each having a 12 μm copper foil layer and a 25 μm polyimide layer. CCL-1 used rolled copper foil, and CCL-2 and CCL-3 used electrolytic copper foil. The copper foil layer on one side in each CCL was removed by etching, and a dot pattern similar to the dot pattern 2 (see FIG. 1B) was formed on the copper foil layer on the other side by etching. For these samples, an apparatus having the same configuration as the visibility evaluation apparatus 300 shown in FIG. 7 was used, and Steps A to D were performed, and an SNR ′ value was calculated based on the above equation (2). Step C was performed by the following processing method a or processing method b based on the modified example including the processing of i) to vi). The brightness of each dot and each pixel was digitized by dividing it into 256 gradations.

(Processing method a)
In the processing method “a”, a square dot pattern image 3 as an output image is trimmed to a 250 × 250 pixel square, and then divided into 50 × 50 = 2500 dots (each dot is also a square), and the dot boundary is 2 pixels wide. Excluded from the processing target.

(Processing method b)
In the processing method b, the square dot pattern image 3 that is an output image is enlarged to the outside of the upper, lower, left, and right sides by 1/2 pixel width from the contour 3a, trimmed into a square of 251 × 251 pixels, and then 50 × 50 = It was divided into 2500 dots (each dot is also a square), and the dot boundary was excluded from the processing target with a 1-pixel width.

(Processing method c)
For comparison, in the processing method c, a square dot pattern image 3 as an output image is trimmed to a square of 250 × 250 pixels and then divided into 50 × 50 = 2500 dots (each dot is also a square). Was used (the dot boundary was not excluded from the processing target).

In the visibility evaluation apparatus 300 in FIG. 7, the change in the SNR ′ value when the output of the white LED light as the light source 307 was changed was measured. The experimental results by the processing method a are shown in FIGS. 17A and 17B, the experimental results by the processing method b are shown in FIGS. 18A and 18B, and the experimental results by the processing method c are shown in FIGS. 19A and 19B, respectively. In each figure, the vertical axis represents the SNR ′ value obtained by the equation (2), and the horizontal axis represents the output of the LED light. 18C to 18H show a dot pattern image 3 that is an output image before image processing including trimming is performed. Here, FIG. 18C is the dot pattern image 3 at the LED light output 3 mW / cm ² of CCL-1, (a) is an overall image, and (b) is an enlarged image of a part thereof. FIG. 18D is a dot pattern image 3 at an LED light output of CCL-1 of 8 mW / cm ² , (a) is an overall image, and (b) is an enlarged image of a part thereof. FIG. 18E is a dot pattern image 3 with an LED light output of 3 mW / cm ² of CCL-2, where (a) is an overall image and (b) is an enlarged image of a part thereof. FIG. 18F is a dot pattern image 3 at an LED light output of CCL-2 of 8 mW / cm ² , (a) is an overall image, and (b) is an enlarged image of a part thereof. FIG. 18G is a dot pattern image 3 with an LED light output of 3 mW / cm ² of CCL-3, where (a) is an overall image and (b) is an enlarged image of a part thereof. FIG. 18H is a dot pattern image 3 at an LED light output of CCL-3 of 8 mW / cm ² , (a) is an overall image, and (b) is an enlarged image of a part thereof.

Further, for CCL-1, the luminance histogram by the processing method a is shown in FIGS. 20A and 20B, the luminance histogram by the processing method b is shown in FIGS. 21A and 21B, and the luminance histogram by the processing method c is shown in FIGS. The results are shown in 22B. The LED light output in these experiments is 3 mW / cm ² . In each figure, the vertical axis represents the number of data, and the horizontal axis represents the signal level divided into 256 gradations. In addition, the solid line in each figure has shown the result approximated by Gaussian distribution.

  The luminance SNR 'values aggregated in dot units are shown in FIGS. 17A, 18A, and 19A, and the luminance SNR' values aggregated in pixel units are shown in FIGS. 17B, 18B, and 19B. From these results, it was found that the difference between the three types of sample CCLs increased as the pixel width excluded from the processing target increased at the dot boundary. This is presumably because the contrast at the center of the dot was strongly reflected in the SNR ′ value.

  In addition, in the processing method b in which the pixel width excluded from the processing target is narrowed at the dot boundary, the SNR ′ value when the illumination is brightened tends to decrease. This is presumably because the brighter the illumination, the larger the area of white dots, which is reflected in the influence of the black dots. In particular, in CCL-1, the influence of rolling stripes is taken into account, and this tendency appears to be remarkable. This can also be read from FIGS. 18C-18H. That is, in FIGS. 18C to 18H, which are output images before image processing, in the same sample, it can be seen that the brighter the illumination, the larger the white dot area to the black dot area. In the processing method b, it is considered that the influence of the spread can be accurately reflected in the SNR ′ value by excluding the dot boundary portion by one pixel width.

  As shown in FIGS. 19A and 19B, in the processing method c that does not exclude the dot boundary from the processing target, it is difficult for the original characteristics of each CCL to be reflected by the noise at the dot boundary.

  20A, 21A, and 22A show luminance histograms aggregated in dot units, and FIGS. 20B, 21B, and 22B show luminance histograms aggregated in pixel units. From these results, especially when counting by pixel, the distribution becomes asymmetrical and the deviation from the Gaussian distribution becomes large when the pixel width excluded from the processing target at the dot boundary is narrowed or when the dot boundary is not excluded. Thus, there was a tendency for the black and white distribution to overlap. This is presumed to be the effect of black and white bleeding at the dot boundary.

Next, reproducibility evaluation was performed by repeatedly calculating the SNR ′ value for the three types of CCL obtained by the processing method b. The output of the LED light in this reproducibility evaluation experiment was set to 5.3 mW / cm ² . The results are shown in FIG. The vertical axis in FIG. 23 is the SNR ′ value (aggregation in dot units) obtained by equation (2), and the horizontal axis indicates the number of measurements. From FIG. 23, by measuring a dot pattern similar to the dot pattern 2 (see FIG. 1B) by the processing method b including the process C of the modified example including the above processes i) to vi), variation in data is suppressed. It was confirmed that high reproducibility was obtained.

  As mentioned above, although embodiment of this invention was described in detail for the purpose of illustration, this invention is not restrict | limited to the said embodiment, A various deformation | transformation is possible. For example, in the first to fourth embodiments, the visibility evaluation devices 100, 200, 300, and 400 are illustrated, but the device configuration for implementing the visibility evaluation method of the present invention is limited to these. It is not something.

  DESCRIPTION OF SYMBOLS 1 ... Dot pattern, 3 ... Dot pattern image, 5 ... Sample, 101 ... Light source, 103 ... Spatial light modulator (SLM), 105 ... Imaging device, 111 ... Polarization beam splitter (PBS), 113 ... 1/2 wavelength plate (HWP), 115 ... first lens, 117 ... second lens, 119 ... third lens, 100, 200, 300, 400 ... visibility evaluation apparatus, 500 ... control unit, 501 ... controller, 502 ... user Interface, 503... Storage unit

Claims (22)

Next step A to step D;
A) preparing a two-dimensionally distributed dot pattern;
B) Photographing the dot pattern with an imaging device through the sample, and generating the photographed dot pattern image as an output image;
C) The output image is divided into the same number of dots as the dot pattern that is the input image, each dot is classified into two or more types, and the luminance is quantified for each classified type of dot to obtain a frequency distribution. Calculating the average value and standard deviation of the brightness for each type, and
D) calculating a signal-to-noise ratio from the average value and standard deviation of the luminance,
A method for evaluating the visibility of a sample containing Next step E;
E) a step of comparing the signal-to-noise ratio with a signal-to-noise ratio calculated in the same manner for the output image of the dot pattern obtained when the image is taken without passing through the sample;
The sample visibility evaluation method according to claim 1, further comprising:   The sample visibility evaluation method according to claim 1, wherein the sample is a synthetic resin film.   The method for evaluating the visibility of a sample according to any one of claims 1 to 3, wherein the sample is placed at a position deviating from an imaging position of the input image and photographing is performed by the imaging device.   The sample dot evaluation method according to any one of claims 1 to 4, wherein the dot pattern is formed with nonuniform spatial frequencies.   The sample visibility evaluation method according to claim 5, wherein the dot pattern has a spatial frequency equal to or higher than that of the two-dimensional code.   The said sample is the said synthetic resin layer in the metal-clad laminated body with which the metal layer and the synthetic resin layer were laminated | stacked, The said dot pattern is formed in the said metal layer. A method for evaluating the visibility of a sample.   The sample dot evaluation method according to claim 7, wherein the dot pattern is formed by the metal layer and an opening formed in the metal layer.   The sample dot evaluation method according to claim 7, wherein the dot pattern is printed on the metal layer. Step C is a treatment of the following i) to vi);
i) a process of trimming the outline of the output image with a size including a margin of a predetermined range and assigning a plurality of pixels;
ii) the process of digitizing the brightness of each pixel;
iii) A process of dividing a trimmed output image into the same number of dots as the dot pattern as an input image, with a plurality of pixels as one dot,
iv) A process of selecting a pixel group to be processed by excluding pixels existing at the boundary of each dot,
v) a process of classifying each dot as either a white dot or a black dot, assuming that one dot is constituted by the selected pixel group;
vi) A process for calculating the frequency distribution by digitizing the luminance for each classified white dot or black dot, and calculating the average value and standard deviation of the luminance for each white dot or black dot;
The method for evaluating the visibility of a sample according to any one of claims 1 to 9.   The sample visibility evaluation method according to any one of claims 1 to 9, wherein in the step C, the dots of the output image are classified into either white dots or black dots. The sample visibility evaluation method according to claim 10 or 11, wherein, in the step D, a signal noise ratio is calculated based on the following formula (1).
[In the formula, SNR represents the signal-to-noise ratio, μ ₀ is the average value of the luminance of the black dots, μ ₁ is the average value of the luminance of the white dots, σ ₀ is the standard deviation of the luminance of the black dots, and σ ₁ is the white dot This means the standard deviation of the brightness. ] The sample visibility evaluation method according to claim 10 or 11, wherein in the step D, a signal-to-noise ratio is calculated based on the following formula (2).
[In the formula, SNR ′ represents a signal-to-noise ratio, and σ _L represents the larger one of the standard deviation of luminance of black dots and the standard deviation of luminance of white dots. ]   The two-dimensionally distributed dot pattern includes a plurality of first dots and a plurality of second dots different from the first dots, and the first dots and the second dots The ratio (first dot: second dot) is in the range of 45:55 to 55:45, and either the first dot or the second dot is 1 to 15 in the two-dimensional direction. The method for evaluating the visibility of a sample according to any one of claims 1 to 10, wherein a sample having a region that appears continuously within a range is used. The first dot and the second dot form a quadrangle, and the entire dot pattern has a quadrangular outline,
Having an alignment region composed of a plurality of the second dots at positions deviating from the four corners of the rectangular outline;
The sample visibility evaluation method according to claim 14, wherein the dots at the four corners closest to the alignment region are all configured by the first dots.   The sample visibility evaluation method according to claim 14 or 15, wherein the first dot is a white dot and the second dot is a black dot. The sample is the synthetic resin layer in a metal-clad laminate in which a metal layer and a synthetic resin layer are laminated,
The metal layer is partially etched to form the dot pattern;
The sample visibility evaluation method according to claim 14 or 15, wherein the first dot is constituted by the metal layer, and the second dot is constituted by an opening formed in the metal layer.   A plurality of first dots and a plurality of second dots different from the first dots, wherein the first dots and the second dots are two-dimensionally distributed; The ratio of the dot to the second dot (first dot: second dot) is in the range of 45:55 to 55:45, and either the first dot or the second dot The dot pattern for visibility evaluation which has the area | region which appears continuously within the range of 1-15 in a two-dimensional direction, and is used in order to evaluate the visibility of a sample. The first dot and the second dot form a quadrangle, and the entire dot pattern has a quadrangular outline,
Having an alignment region composed of a plurality of the second dots at positions deviating from the four corners of the rectangular outline;
The dot pattern for visibility evaluation according to claim 18, wherein all the dots at the four corners closest to the alignment region are configured by the first dots.   The dot pattern for visibility evaluation according to claim 18 or 19, wherein the first dot is a white dot and the second dot is a black dot. The sample is the synthetic resin layer in a metal-clad laminate in which a metal layer and a synthetic resin layer are laminated,
The metal layer is partially etched to form a dot pattern;
The dot pattern for visibility evaluation according to claim 18 or 19, wherein the first dot is constituted by the metal layer, and the second dot is constituted by an opening carved in the metal layer.   A metal-clad laminate in which a metal layer and a synthetic resin layer are laminated, and having the dot pattern for visibility evaluation according to any one of claims 17 to 21.