JP2002350355A - Evaluating device, evaluating method for unevenness of gloss and computer-readable storage medium storing program for this method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an evaluating device, an evaluating method for unevenness of gloss and a computer-readable storage medium storing program for this method which evaluates intensity of reflected light from the surface of a sample, spatial frequency characteristics of the unevenness of gloss, human visual proper ties and sample colors. SOLUTION: This method evaluates unevenness of gloss of a sample according to the following procedure. First, an image pickup device takes an image containing regularly reflected light component from the sample to calculate an average of the image. Second, a deviation of each image of the pixel from the average is calculated to obtain a deviation image. Next, the spatial frequency characteristic of the deviation image is multiplied by that of human eyesight and integrated. The value obtained from the integration is multiplied by a proportion coefficient to obtain an evaluation value of unevenness of gloss.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a gloss unevenness evaluation apparatus for quantitatively measuring and evaluating gloss unevenness on a product surface, the evaluation method, and a storage medium storing a program for executing the method.

[0002]

2. Description of the Related Art Recently, glossiness and unevenness of glossiness on the surface of a printed material have been regarded as important evaluation items in image quality. Gloss measurement methods have already been standardized and many measuring instruments are commercially available. However, in many cases, the evaluation of gloss unevenness was visually determined by an inspector.

Further, a method has been proposed in which the appearance of a product is imaged by an imaging device such as a television camera, and the gloss unevenness of the product appearance is evaluated from the imaging result. For example, a method of calculating the distribution of the brightness level (reflected light intensity) is described in H. H. Fujiwara et. a
l., 1990 TAPPI Coat. Conf. Proc., 209 (1
990)) (hereinafter referred to as Conventional Example 1).
This method modifies the chromatoscanner to 0.4m
A light beam of mφ is scanned on the coated paper surface at an incident reflection angle of 75 °,
It is clear that the standard deviation of the intensity of the reflected light is related to the visual order.

Further, Japanese Patent Laid-Open No. 6-22 / 1994 discloses a method of quantifying gloss unevenness not from the intensity distribution but from the size of the unevenness and its distribution.
2002 (hereinafter referred to as Conventional Example 2). This method is a method of calculating a binary image in which a specific spatial frequency band component is uniformly enhanced from an image captured by an imaging device, and quantifying gloss unevenness from a distribution of areas of white or black portions.

[0005]

However, the method for inspecting gloss unevenness by visual inspection as described above is not limited to a professional inspection for objectively judging pass / fail, as well as to apply personal subjectivity to the quantitative property. Requires a large number of members. In addition, the optical inspection method for uneven gloss has the following disadvantages. Attempts have been made to quantify the gloss unevenness from the reflected light intensity distribution and the magnitude of the gloss unevenness and their distribution, but none of the methods take into account the visual characteristics of humans, and for example, The method using the luminance level distribution may not always correspond to the result of the visual judgment. Further, in the method using the size and distribution of gloss unevenness as in Conventional Example 2, the evaluation result is influenced by the method of obtaining an enhancement coefficient that uniformly emphasizes a specific spatial frequency band component, and the luminance due to the uneven gloss is determined. Because it does not take into account any fluctuations,
In some cases, even a slight luminance variation that is not perceived may be detected as unevenness due to enhancement processing depending on the spatial frequency.

[0006] Further, it is known that the glossiness perceived by a human varies depending on the color of the sample. In other words, it is known that the reflection characteristics on the surface are the same, and even with the same reflection luminance, there is a case where the gloss is felt strongly or not so much depending on the sample color. Therefore, it is natural that the unevenness of the gloss is also affected by the sample color.However, the conventional method does not consider the influence of the sample color at all in quantifying the unevenness of the gloss. Had occurred.

SUMMARY OF THE INVENTION The present invention has been made to solve these problems, and has an apparatus for evaluating gloss unevenness in consideration of the intensity of light reflected from the surface and the spatial frequency characteristics of uneven gloss, human visual characteristics, and sample colors. It is an object of the present invention to provide a gloss unevenness evaluation method and a computer-readable storage medium storing a program for executing the method.

[0008]

In order to solve the above-mentioned problems, an apparatus for evaluating gloss unevenness according to the present invention comprises: an image pickup means capable of picking up an image including specularly reflected light from a sample to be evaluated; An image holding means for storing and holding, an average value calculating means for calculating an average value of the evaluated image stored and held in the image holding means, and a deviation between the evaluated image and the average value obtained by the average value calculating means. Deviation calculating means for calculating; spatial frequency characteristic calculating means for calculating a spatial frequency characteristic of an image obtained by the deviation calculating means; visual characteristic multiplying means for multiplying the spatial frequency characteristic and the spatial frequency characteristic of human vision; There are integrating means for integrating the spatial frequency component calculated by the characteristic multiplying means, and gloss unevenness evaluation amount calculating means for outputting a value obtained by multiplying the value obtained by the integrating means by a proportional coefficient as a gloss unevenness evaluation amount. In particular there is a feature. Therefore, it is possible to provide a gloss unevenness measuring device that calculates a gloss unevenness evaluation amount having a high correlation with the visual evaluation.

Further, by providing a dividing means for dividing the value calculated by the integrating means by the average value calculated by the average value calculating means, it is possible to correct the influence of the average luminance of the sample on the psychological gloss unevenness, A correlation with a higher visual evaluation can be obtained.

Further, a first image containing a specular reflection light component from a reference gloss sample and a second image containing a specular reflection light component from a sample to be evaluated are taken by an image pickup means, and the second image is represented by the first image. By having the dividing means for performing the division, it is possible to prevent the unevenness of the illuminance at the time of imaging the evaluation sample and the influence of the luminance fluctuation of the light source between the measurements, and to perform the stable evaluation of the gloss unevenness.

According to another aspect of the present invention, there is provided a gloss unevenness evaluation method, wherein an image including a specular reflection light component from a sample to be evaluated is captured by an imaging device to obtain an image to be evaluated, and an average value of the image to be evaluated is obtained. Is calculated, a deviation image is calculated by calculating a deviation from the average value for each pixel of the evaluated image, and a value obtained by multiplying a spatial frequency characteristic of the deviation image by a spatial frequency characteristic of human vision is calculated. , And a value obtained by multiplying the value obtained by the integration by a proportional coefficient is defined as a gloss unevenness evaluation amount. Therefore, by calculating a luminance variation component due to gloss unevenness and a spatial frequency characteristic of the variation component, and multiplying the spatial frequency characteristic by a spatial frequency characteristic of human vision, a gloss unevenness evaluation method having a high correlation with visual evaluation. Can be provided.

Further, since the proportional coefficient is a value proportional to the reciprocal of the average value of the evaluated image, the influence of the average luminance of the sample on the gloss unevenness is corrected, and the correlation with the higher visual evaluation is improved. can get.

The image to be evaluated is a first image containing a specularly reflected light component from a reference gloss sample and a second image containing a regularly reflected light component from a sample to be evaluated. Since the image is calculated by dividing by one image, it is possible to prevent unevenness in illuminance at the time of imaging of the evaluation sample and influence of luminance variation of the light source between measurements, and perform stable evaluation of gloss unevenness.

[0014] Furthermore, the gloss unevenness evaluation apparatus according to another aspect of the present invention includes: an imaging unit capable of capturing a color image including specularly reflected light from a sample to be evaluated; an image holding unit configured to store and hold the captured color image; Colorimetric value conversion means for converting each pixel value of the image into a colorimetric value in a color space comprising a lightness component and a chromaticity component, and an average value for each color component of the color value image obtained by the colorimetric value conversion means Average value calculating means for calculating the difference between each pixel value of the color value image and the average value obtained by the average value calculating means for each color component. Spatial frequency calculating means for calculating the spatial frequency of the deviation image, visual characteristic multiplying means for multiplying the spatial frequency component by the spatial frequency characteristic of human vision, and integration for integrating the spatial frequency component calculated by the visual characteristic multiplying means. Means, It is characterized in that it has an addition means for adding different weights to the calculated values for each color component by minute unit. Therefore, it is possible to provide a gloss unevenness evaluation apparatus having a high correlation with the visual evaluation of a gloss unevenness sample having a color.

Further, a first color image containing a specularly reflected light component from the reference gloss sample and a second color image containing a specularly reflected light component from the sample to be evaluated, taken by the imaging means, are inputted. Of the second color image
By dividing by the color image to calculate a third color image, it is possible to prevent illuminance non-uniformity at the time of imaging of the evaluation sample and the influence of the luminance variation of the light source between measurements,
It is possible to perform stable gloss unevenness evaluation.

Further, the weight for the integral value of the brightness component is:
Since the value is proportional to the reciprocal of the average value of the lightness component in the third color image, the influence of the average luminance of the sample on the gloss unevenness is corrected, and a higher correlation with the visual evaluation can be obtained.

The weight for the integral value of the chromaticity component is
By making all values equal to each other, a correlation with a higher visual evaluation can be obtained.

Further, according to the gloss unevenness evaluation method as another invention, an image to be evaluated is obtained by capturing a color image containing a specularly reflected light component from the sample to be evaluated, and each pixel value of the image to be evaluated is determined by brightness. Calculates a color value image by converting to a color specification value in a color space composed of components and chromaticity components, calculates an average value for each color component of the color value image, and calculates each pixel of the color value image for each color component. A deviation image is calculated by calculating a deviation from the average value, a value obtained by multiplying the spatial frequency component of the deviation image by a spatial frequency characteristic of human visual perception is calculated for each color component, and each color component obtained by the integration is calculated. An added value obtained by adding different weights to each value or a value proportional to the added value is defined as the gloss unevenness evaluation amount. Therefore, it is possible to provide a gloss unevenness evaluation method that has a high correlation with the visual evaluation of a gloss unevenness sample having a color.

The image to be evaluated is obtained by capturing a first color image containing a specular reflection component from the reference gloss sample and a second color image containing a specular reflection component from the sample to be evaluated. Is obtained by dividing the color image of the first color image by the first color image, it is possible to prevent illuminance non-uniformity at the time of imaging of the evaluation sample and the influence of the luminance variation of the light source between measurements,
It is possible to perform stable gloss unevenness evaluation.

Further, the weight for the integral value of the brightness component is:
Since the value is proportional to the reciprocal of the average value of the lightness component in the color value image, it is possible to correct the influence of the average luminance of the sample on the gloss unevenness, and obtain a higher correlation with the visual evaluation.

The weight for the integral value of the chromaticity component is
By making all values equal to each other, a correlation with a higher visual evaluation can be obtained.

Further, there is a special charge in a computer-readable storage medium storing a program for executing the above-described gloss unevenness evaluation method. Therefore, by using a medium recorded with a program for executing the gloss unevenness evaluation method of the present invention, an apparatus for constructing a gloss unevenness evaluation system can be generally used without changing an existing system.

[0023]

According to the gloss unevenness evaluation method of the present invention, an image including a specular reflection component from a sample to be evaluated is picked up by an imaging device to obtain an image to be evaluated, and the average value of the image to be evaluated is obtained. Is calculated, a deviation image is calculated by calculating a deviation from the average value for each pixel of the evaluated image, and a value obtained by multiplying a spatial frequency characteristic of the deviation image by a spatial frequency characteristic of human vision is calculated. , And a value obtained by multiplying the value obtained by the integration by a proportional coefficient is defined as a gloss unevenness evaluation amount.

[0024]

FIG. 1 is a block diagram showing a configuration of a gloss unevenness evaluating apparatus according to a first embodiment of the present invention. In the figure, a gloss unevenness evaluation apparatus according to the present embodiment includes an imaging unit 11 for imaging an inspection target, an image captured by the imaging unit 11, and a first image obtained by capturing a reference sample and a sample to be evaluated. An image holding unit 12 for holding the captured second image or at least one image, and a second image
Dividing means 1 for dividing by an image and calculating a third image in which light source fluctuations over time and uneven illuminance in the image have been corrected by the division.
3, an average value calculating means 14 for calculating an average value of the third image calculated by the dividing means 13, and an average calculated by the average value calculating means 14 from each pixel value of the third image calculated by the dividing means 13 A deviation image calculating means 15 for subtracting a value and calculating a deviation image by subtraction; a spatial frequency characteristic calculating means 16 for calculating a spatial frequency characteristic by means such as FFT for the deviation image calculated by the deviation image calculating means 15; A visual characteristic multiplying unit 17 for multiplying the spatial frequency characteristic of the deviation image calculated by the spatial frequency characteristic calculating unit 16 by the spatial frequency characteristic of human vision, and a space obtained by multiplying the spatial frequency characteristic of human vision by the visual characteristic multiplying unit 17. Integral means 18 for integrating the frequency distribution in a predetermined section, and the integration value calculated by the integration means 18 and the average value of the third image calculated by the average value calculation means 14 are used to obtain gloss unevenness. It is configured to include a gloss nonuniformity evaluation quantity calculating means 19 for calculating the value amount.

FIG. 2 is a diagram showing a schematic configuration of a document reading apparatus to which the present invention is applied. In the figure, light from a light source 21 in an imaging apparatus (corresponding to the imaging means 11 in FIG. 1) 10 passes through a diffusion plate 22 and light distribution regulating plates 23a and 23b to a sample 25 to be evaluated, and The light reflected from the sample 24 is irradiated vertically, and the reflected light from the sample 25 to be evaluated passes through the half mirror 24 and is received by the CCD camera 26. The CCD camera 26 converts the received light into an image signal for each pixel and outputs the image signal to the image analyzer 20. Here, the light beam illuminating the sample 25 to be evaluated is preferably substantially parallel light, and if not, sufficient gloss unevenness detection sensitivity may not be obtained. Light distribution regulating plates 23a, 2
3b is a device for bringing illumination light closer to parallel light,
The configuration and function will be described with reference to FIGS. 3 and 4. The light distribution regulating plates 23a and 23b are each formed by forming a plurality of fine louvers on a transparent substrate in a substantially parallel manner. As shown, when the diffused light enters the light distribution regulating plate 23a, the transmitted light component in the direction perpendicular to the stroke direction of the louver is cut, and the light distribution of the transmitted light flux is regulated. The light distribution regulating plates 23a and 23b are arranged so that the directions of the louvers are orthogonal to each other. Thereby, as shown in FIG. 4, the light beam transmitted through the light distribution regulating plates 23a and 23b becomes a light beam parallel or nearly parallel to the optical axis. Of course, if the linear louvers are formed in a lattice shape, the same effect as described above can be obtained with one light distribution regulating plate. Also,
The light source 21 in FIG. 2 is an example using a two-dimensional LED light source array, and a uniform illuminance distribution can be obtained in an imaging screen by combining with a diffusion plate 22. However, the present embodiment is not limited to the imaging apparatus shown in FIG.
A configuration as shown in FIG. The imaging device shown in FIG. 5 converts the light from the illumination light source 27 into parallel light using a pinhole 28 and a lens 29, illuminates the sample to be evaluated at an incident angle θ, and reflects the light in a reflection angle θ direction by a CCD camera 26. Light is received. CCD camera 2 in FIG.
The image signal received by the pixel 6 and converted for each pixel is output to the image analyzer 20 in the same manner as in FIG. Image analysis device 2
At 0, the unevenness of gloss of the sample is calculated based on the input image.

The present invention mainly relates to a method for evaluating unevenness in gloss performed by the image analyzer 20 and an apparatus for evaluating unevenness in gloss that realizes the method, and is an invention based on knowledge obtained through experiments described below. . First, a subjective evaluation experiment will be described, and then a gloss unevenness evaluation method derived based on the results obtained from the experiment will be described.

First, in order to measure psychological gloss unevenness, a solid image sample was prepared using an electrophotographic output device. Eight types of samples having different gloss levels and gloss unevenness by changing output conditions were prepared using black toner. The sample size was 20 × 20 mm.
In order to quantify the degree of psychological gloss unevenness, a subjective evaluation experiment was performed using the Scheffe pairwise comparison method (Nakaya's modified method). The subject compares the presented pair of samples A and B, and the gloss unevenness of B with respect to A is

When A >> B: +2 points When A> B: +1 point When A ≒ B: 0 points When A <B: -1 point When A << B: -2 points The sample is scored. Was.

The above-described evaluation was performed by the subject under an observation environment set so as to directly see the light beam specularly reflected on the sample surface from a position 350 mm away. The number of subjects was 12, and each trial was performed twice. The evaluation points for gloss unevenness of each sample are quantified in the results of the above evaluation experiment.
Calculations were made by applying the Class I analysis method.

Next, a method of predicting the psychological gloss unevenness quantified by the subjective evaluation experiment will be described. Using the imaging device 10 shown in FIG. 2, a reference sample and an evaluation sample having uniform gloss were imaged. Reference samples include:
A black polyester fill having a 60 degree specular gloss of 103.8% was used. The CCD camera 26 has 10 pixels.
A color CCD camera having 00 × 1018 (pixels) and outputting R, G, and B was used. The reading resolution of the CCD camera 26 used was 25.4 (μm / 1 pixel).
The reading range was approximately 1 × 1 inch. The used LED light source 21 was a white LED. For analysis,
Only Green channel data was used. Gre
It is known that the output value of the en channel is approximately linear with the luminance. Image data obtained by imaging a reference (uniform gloss) sample is defined as Gref (x, y). Similarly, let the image data which imaged the evaluation sample be Gs (x, y). Gref (x,
y) and Gs (x, y) are temporarily stored in an image holding unit such as a hard disk or a frame memory. Next, the evaluation sample is normalized (divided) by the reference sample as shown in the equation (1). Let the normalized result be G (x, y). In the equation (1), k is a proportional constant, which has a meaning of preventing a digit loss or the like after calculation, and is not essential in the present invention. In the experiment, k = 100.

G (x, y) = k × Gs (x, y) / Gref (x, y) (1) The average value Gave of G (x, y) calculated by equation (1) is calculate.

[0032]

(Equation 1)

A deviation from the average value Gave for each pixel of the image G (x, y) calculated by the equation (1) is calculated, and a deviation image hg is calculated.
Outputs (x, y).

Hg (x, y) = (G (x, y) −Gave) (3)

The two-dimensional Fourier transform is performed on the deviation image hg (x, y) obtained by the equation (3) to obtain a two-dimensional Wiener spectrum. At this time, the two-dimensional Wiener spectrum is displayed in polar coordinates. The Wiener spectrum displayed in polar coordinates is defined as Hg (λ, θ). (Λ is the spatial frequency (c / d
eg), θ indicates the direction of the image) Wiener spectrum H
g (λ, θ) is integrated with respect to θ in the range of 0 to 2π to make it one-dimensional.

[0036]

(Equation 2)

The two-dimensional to one-dimensional conversion shown in equation (4) is
This is performed based on the finding that the visual spatial frequency characteristics do not largely depend on the direction of the image to be observed, and subsequent calculations can be simplified. However, whether or not to make it one-dimensional is not an essential part in the present invention, and subsequent calculations may be performed in two dimensions.

Next, the one-dimensional Wiener spectrum Hg (λ) is added to the spatial frequency characteristic VTF (λ) (Visua
l Transfer Function) and then integrate over spatial frequency.

[0039]

(Equation 3)

Some VTF (λ) have already been reported. For example, VTF (λ) = 5.05 · exp (−0.138 · λ) · (1-exp (−0.1・ Λ)) (6)

There is a report that is expressed as However, the present invention is not limited to the VTF (λ) of the expression (6), and another VTF (λ) may be used.

The average value Gave and the integral value Xg calculated by the above equations (2) and (5) are used as explanatory variables, and the gloss unevenness of the sample valued by the subjective evaluation is used as a target variable, and the prediction shown in the following equation (7) is used. When a model was set up and coefficient values were obtained by the least squares method, high prediction accuracy was obtained.

Gloss unevenness = p 1 · Gave · p 2 · Xg + p 3 (7)

Here, p1, p2 and p3 are coefficients, and p1
= 1.2479, p2 = -1.0, p3 = -1.4905
Met. p2 = -1.0, and the psychological gloss unevenness is Ga
It can be seen that the relationship is inversely proportional to ve.

FIG. 6 is a characteristic diagram showing the relationship between the predicted value of psychological gloss unevenness obtained by the above equation (7) and the subjective evaluation point obtained by actual measurement. The contribution rate (square of the correlation coefficient) is 0.91
8, indicating a high fit.

FIG. 7 is a block diagram showing the configuration of the gloss unevenness evaluation apparatus according to the second embodiment of the present invention. In the figure, the same reference numerals as those in FIG. 1 indicate the same components. As a different component, the gloss unevenness evaluation apparatus of the present embodiment has a division unit 30 that divides the integrated value from the integration unit 18 and the average value from the average value calculation unit 14, and uses the division result to calculate the gloss. The unevenness evaluation amount calculating means 19 calculates the gloss unevenness evaluation amount.

Next, a subjective evaluation experiment was performed on the color samples to evaluate the gloss unevenness in the same manner. The color samples are six samples in total: four red, one green, and one blue. A part of the black sample was added to the subjective evaluation experiment to match the evaluation points. FIG. 8 is a characteristic diagram showing subjective evaluation points with respect to the predicted value of gloss unevenness calculated using the above equation (7). From the figure, it can be seen that the gloss unevenness predicted value for the color sample is calculated to be smaller than the subjective evaluation point. That is, it has been found that Equation (7), which is a gloss unevenness prediction equation, is effective for a black sample, but has a large error for a color sample. This means
This indicates that the degree of the psychological gloss unevenness is affected by the sample color, which supports the finding that the glossiness is affected by the sample color. This result is a fact first clarified by the experiment of the present invention.

Next, a description will be given of a gloss unevenness prediction method that is effective for color samples. The configuration of the imaging device 10 shown in FIG. The CCD camera 26 outputs R, G, B color signals to the image analyzer 20.

FIG. 9 is a block diagram showing a configuration of a gloss unevenness evaluation apparatus according to a third embodiment of the present invention. In the figure, the same reference numerals as those in FIG. 1 indicate the same components. The gloss unevenness evaluation apparatus of the present embodiment holds an imaging unit 11 for imaging an inspection target, and an image captured by the imaging unit 11,
Image holding means 13 capable of holding a first color image of a reference sample and a second color image of a sample to be evaluated, or at least one of the images.
Dividing means 13 for dividing the second color image by the first color image, and calculating a third color image in which light source fluctuation over time and illuminance unevenness in the image have been corrected by the division; Color conversion means 31 for converting into a color specification value comprising a lightness component and a chromaticity component using the third color image data calculated in step 13, and an average value of the third color image calculated in the color conversion means 31 And the average value calculated by the average value calculating means 14 is subtracted from each color value of the third color image color-converted by the color converting means 31, and the deviation image is calculated by the subtraction. The deviation image calculated by the deviation image calculation means 15
A spatial frequency characteristic calculating means 16 for calculating a spatial frequency characteristic by means such as; a visual characteristic multiplying means 17 for multiplying a spatial frequency characteristic of a human visual by the spatial frequency characteristic of the deviation image calculated by the spatial frequency characteristic calculating means 16; Integration means 18 for performing integration in a predetermined section with respect to a spatial frequency distribution obtained by multiplying the spatial frequency characteristic of human vision by the visual characteristic multiplying means 17;
Integral value calculated by integrating means 18 and average value calculating means 14
And a gloss unevenness evaluation amount calculation means 19 for calculating the gloss unevenness evaluation amount using the average value of the third color image calculated in (1).

Here, the color image signals obtained by imaging the reference samples are Rref (x, y), Gref (x, y), and Bref (x, y). Similarly, color image signals obtained by imaging the evaluation sample are Rs (x, y), Gs (x, y), and Bs (x, y).

Next, as shown in the following equation (8), the evaluation sample is normalized (divided) by a reference sample. Let the normalized result be G (x, y). K in the equation (8) is a proportionality constant and has a meaning of preventing a digit loss or the like after calculation, and is not essential in the present invention. In the experiment, k = 100.

R (x, y) = k × Rs (x, y) / Rref (x, y) G (x, y) = k × Gs (x, y) / Gref (x, y) (8) B (x, y) = k × Bs (x, y) / Bref (x, y)

The image data R (x, y), normalized by the equation (8),
From G (x, y) and B (x, y), tristimulus values in sRGB color space
Convert to (X, Y, Z). The calculated X, Y, Z are converted into CIELAB colorimetric values (L *, a *, b *).

[0054]

(Equation 4)

From the tristimulus values X, Y, Z, the CIELAB colorimetric values L *, a
The conversion into * and b * is a known method, and is omitted here. The color image data represented by the CIELAB color specification values L *, a *, b * is assumed to be L * (x, y), a * (x, y), b * (x, y).

In the above equation (9), the sRGB space is used to convert a color image signal into tristimulus values. This is because the conversion matrix is known, and another space may be used. Although the CIELAB colorimetric values are calculated from the tristimulus values X, Y, and Z, other color spaces may be used as long as they can be converted into lightness components and chromaticity components. For example, a CIELUV uniform color space may be used.

A conversion formula for converting a color image signal into a tristimulus value on an arbitrary color space (for example, a tristimulus value on an arbitrary monitor) is, for example, a chromaticity point or a tristimulus of a phosphor of a monitor. If the values and the white point or tristimulus value of the monitor are known, a conversion matrix can be determined. The method of deriving the transformation matrix is a known technique, and is not limited by the present invention.

L * represented by CIELAB color values L *, a *, b *
Average values of (x, y), a * (x, y), b * (x, y) L * ave, a * ave, b *
Calculate ave.

[0059]

(Equation 5)

L * (x, represented by CIELAB colorimetric values L *, a *, b *
y), a * (x, y), average value L * av for each pixel of b * (x, y)
The deviation from e, a * ave, b * ave is calculated, and the deviation image hL (x,
y), ha (x, y) and hb (x, y) are output.

HL (x, y) = (L * (x, y) −L * ave) ha (x, y) = (a * (x, y) −a * ave) (11) hb (x, y) = (b * (x, y) -b * ave)

The deviation image hL (x, y), ha obtained by the equation (11)
A two-dimensional Fourier transform is applied to (x, y) and hb (x, y) to obtain a two-dimensional Wiener spectrum. At this time, the two-dimensional Wiener spectrum is displayed in polar coordinates.
The Wiener spectrum displayed in polar coordinates is expressed as HL (λ, θ),
Let Ha (λ, θ) and Hb (λ, θ). (Λ is the spatial frequency (c /
deg) and θ indicate the direction of the image) Wiener spectrum H
0 to 2π for L (λ, θ), Ha (λ, θ), Hb (λ, θ)
Are integrated into one range in the range of.

[0063]

(Equation 6)

The two-dimensional to one-dimensional conversion shown in the above equation (12) is performed based on the knowledge that the spatial frequency characteristics of vision do not largely depend on the direction of the image to be observed, and the subsequent calculations are simplified. Can be However, whether or not to be one-dimensional is not an essential part in the present invention, and subsequent calculations may be performed in two dimensions.

Next, the one-dimensional Wiener spectrum
Hg (λ) to human visual spatial frequency characteristics VTF (λ) (Visual
Transfer Function) and then integrate over spatial frequency.

[0066]

(Equation 7)

VTF (λ) is the VTF (λ) of the above equation (6).
However, other VTF (λ) may be used. The average value L * ave and the integral values XL, Xa, and Xb calculated by the above equations (10) and (13) are used as explanatory variables, and gloss unevenness of the sample valued by the subjective evaluation is used as an objective variable (1).
4) The prediction model shown in the equation was established, and the coefficient value was obtained by the least square method.

Gloss unevenness = p1, L * ave, P2, XL + p3, | a * ave | p4, Xa + p5, | b * ave | p6, Xb + p7 (14)

Each coefficient value is p1 = 391.075, p2 =
−1.086, p3 = 2.293, p4 = 0.115, p
5 = 3.867, p6 = -0.091, p7 = -1.61
8, the gloss non-uniformity predicted by the equation (14) is 0.
A high fit of 916 was obtained. In addition, it was found that a high prediction accuracy could be obtained even when the equation (14) was simplified as shown below. That is, p1 = 100.0 × p
1, p2 = -1.0, p4 = p6 = 0.0, p1 = p3 = p5
By rewriting equation (14), it can be written as equation (15).

[0070]

(Equation 8)

Similarly, the coefficients p1, p
7, p1 = 2.773, p7 = −1.58
0, and the contribution ratio is 0.904, which indicates that gloss unevenness can be measured with almost the same accuracy as in the equation (14).
FIG. 10 shows the relationship between the value obtained by estimating the gloss unevenness of the sample using the equation (15) and the subjective evaluation point.

FIG. 11 is a block diagram showing a configuration of a gloss unevenness measuring apparatus according to a fourth embodiment of the present invention. 3, the same reference numerals as those in FIG. 3 indicate the same components. As a different component, the gloss unevenness measuring apparatus of the present embodiment has a dividing unit 30 for dividing the integrated value from the integrating unit 18 and the average value from the average value calculating unit 14, and using this division result, the gloss is calculated. The unevenness evaluation amount calculating means 19 calculates the gloss unevenness evaluation amount.

FIG. 12 is a schematic diagram showing the structure of another document reading apparatus to which the present invention is applied. The measuring device shown in the figure is a reflection original reading device incorporating a gloss detection illumination device 91 including a light source 21, a diffusion plate 22, a light distribution regulating plate 23, and a half mirror 24 in the imaging device 10 shown in FIG. Is shown as an example. The reflection original reading device is capable of reading glossiness unevenness of the original in addition to the ordinary original reading by the illumination device 91 for gloss detection. For example, at the time of normal reading, the half mirror 24 moves to a position that does not hinder reading, and when reading uneven gloss of the document, the half mirror 24 moves so that the light beam from the light source 21 illuminates the document surface perpendicularly. Here, the method of moving the half mirror 24 is not limited, and the entire gloss detecting illumination device 9 may move instead of moving only the half mirror 24. When reading gloss unevenness of a document, the normal document reading light source 92 is turned off, and the document is illuminated only by the illumination light from the gloss detecting illumination device 91. The light beam including the specularly reflected light from the document is imaged on the CCD sensor 95 by the mirror 93 and the imaging lens 94. The image signal photoelectrically converted by the CCD sensor 95 is output to the image analyzer 20. Here, the reference gloss sample to be used is arranged, for example, at a position outside the original reading range adjacent to a white reference plate used in a normal image reading apparatus, and at any timing before or after the original reading operation. The reading of is performed.

FIG. 13 is a schematic diagram showing the structure of a cylindrical scanning type document reading apparatus. The sensor 1 detects the regular reflection light from the document out of the luminous flux emitted from the light source 101.
02 and a sensor 103 for detecting reflected light from a document not including specularly reflected light. The document reading apparatus shown in FIG. 1 is a device that reads a document wound around a rotating cylindrical surface while a light source 101 and sensors 102 and 103 move in the longitudinal direction of the cylinder. Also in the document reading apparatus shown in FIG. 13, when measuring gloss unevenness, the document is photoelectrically converted by the sensor 102 through the condenser lens 104, and an image signal is output to the image analyzer 20.

Note that the present invention is not limited to a specific optical system for detecting gloss unevenness in the document reading apparatus. The image read by the document reading apparatus and containing the specularly reflected light component from the document and the gloss It is possible to read gloss unevenness information of a document by using the unevenness evaluation method.

Next, FIG. 14 is a block diagram showing a system configuration of the present invention. That is, FIG. 7 shows hardware constructed from a microprocessor or the like that executes software according to the gloss unevenness evaluation method in the above embodiment. In the figure, a gloss unevenness evaluation system includes an interface (hereinafter abbreviated as I / F) 61, a CPU 62,
ROM 63, RAM 64, display device 65, hard disk 66, keyboard 67, and CD-ROM drive 68
It is comprised including. In addition, a general-purpose processing device is prepared, and a readable recording medium such as a CD-ROM 69 includes:
A program for executing the gloss unevenness evaluation method of the present invention is recorded. Further, a control signal is input from an external device via the I / F 61, and the keyboard 67 activates a command of the operator or automatically activates the program of the present invention.
Then, the CPU 62 performs the uneven gloss evaluation processing according to the above-described uneven gloss evaluation method according to the program, stores the processing result in a recording device such as the RAM 64 or the hard disk 66, and outputs the result to the display device 65 or the like as necessary. As described above, by using the medium recorded by the program for executing the gloss unevenness evaluation method of the present invention, it is possible to generally use an apparatus for constructing the gloss unevenness evaluation system without changing an existing system. it can.

The present invention is not limited to the above-described embodiment, and needless to say, various modifications and substitutions can be made within the scope of the claims.

[0078]

As described above, the uneven gloss evaluation apparatus of the present invention includes an imaging unit capable of capturing an image including specularly reflected light from a sample to be evaluated, and an image holding unit for storing and holding the captured image. An average value calculating means for calculating an average value of the evaluated image stored and held in the image holding means, and a deviation calculating means for calculating a deviation between the evaluated image and the average value obtained by the average value calculating means, The spatial frequency characteristic calculating means for calculating the spatial frequency characteristic of the image obtained by the deviation calculating means, the visual characteristic multiplying means for multiplying the spatial frequency characteristic by the spatial frequency characteristic of human vision, and the visual characteristic multiplying means. It is characterized in that it has an integrating means for integrating the spatial frequency component and a gloss unevenness evaluation amount calculating means for outputting a value obtained by multiplying the value obtained by the integrating means by a proportional coefficient as a gloss unevenness evaluation amount. Therefore, it is possible to provide a gloss unevenness measuring device that calculates a gloss unevenness evaluation amount having a high correlation with the visual evaluation.

Further, by providing a dividing means for dividing the value calculated by the integrating means by the average value calculated by the average value calculating means, it is possible to correct the psychological unevenness of gloss due to the average luminance of the sample, A correlation with a higher visual evaluation can be obtained.

Further, a first image containing the specular reflection component from the reference gloss sample and a second image containing the specular reflection component from the sample to be evaluated are taken by the image pickup means, and the second image is taken as the first image. By having the dividing means for performing the division, it is possible to prevent the unevenness of the illuminance at the time of imaging the evaluation sample and the influence of the luminance fluctuation of the light source between the measurements, and to perform the stable gloss unevenness evaluation.

According to the gloss unevenness evaluation method as another invention, an image including a specular reflection component from a sample to be evaluated is captured by an imaging device to obtain an image to be evaluated, and an average value of the image to be evaluated is obtained. Is calculated, a deviation image is calculated by calculating a deviation from the average value for each pixel of the evaluated image, and a value obtained by multiplying a spatial frequency characteristic of the deviation image by a spatial frequency characteristic of human vision is calculated. , And a value obtained by multiplying the value obtained by the integration by a proportional coefficient is defined as a gloss unevenness evaluation amount. Therefore, by calculating a luminance variation component due to gloss unevenness and a spatial frequency characteristic of the variation component, and multiplying the spatial frequency characteristic by a spatial frequency characteristic of human vision, a gloss unevenness evaluation method having a high correlation with visual evaluation. Can be provided.

Further, since the proportional coefficient is a value proportional to the reciprocal of the average value of the evaluated image, the influence of the average brightness of the sample on the gloss unevenness is corrected, and the correlation with the higher visual evaluation is improved. can get.

As the image to be evaluated, a first image containing the specular reflection component from the reference gloss sample and a second image containing the specular reflection component from the sample to be evaluated are taken, and the second image is converted to the second image. Since the image is calculated by dividing by one image, it is possible to prevent unevenness in illuminance at the time of imaging of the evaluation sample and influence of luminance variation of the light source between measurements, and perform stable evaluation of gloss unevenness.

Further, a gloss unevenness evaluation apparatus according to another aspect of the present invention includes an image pickup unit capable of picking up a color image including specularly reflected light from a sample to be evaluated, an image holding unit for storing and holding the picked-up color image, Colorimetric value conversion means for converting each pixel value of the image into a colorimetric value in a color space comprising a lightness component and a chromaticity component, and an average value for each color component of the color value image obtained by the colorimetric value conversion means Average value calculating means for calculating the difference between each pixel value of the color value image and the average value obtained by the average value calculating means for each color component. Spatial frequency calculating means for calculating the spatial frequency of the deviation image, visual characteristic multiplying means for multiplying the spatial frequency component by the spatial frequency characteristic of human vision, and integration for integrating the spatial frequency component calculated by the visual characteristic multiplying means. Means, It is characterized in that it has an addition means for adding different weights to the calculated values for each color component by minute unit. Therefore, it is possible to provide a gloss unevenness evaluation apparatus having a high correlation with the visual evaluation of a gloss unevenness sample having a color.

Further, a first color image containing a specularly reflected light component from a reference gloss sample and a second color image containing a specularly reflected light component from a sample to be evaluated, taken by the imaging means, are input. Of the second color image
By dividing by the color image to calculate a third color image, it is possible to prevent illuminance non-uniformity at the time of imaging of the evaluation sample and the influence of the luminance variation of the light source between measurements,
It is possible to perform stable gloss unevenness evaluation.

Further, the weight for the integral value of the brightness component is:
Since the value is proportional to the reciprocal of the average value of the lightness component in the third color image, the influence of the average luminance of the sample on the gloss unevenness is corrected, and a higher correlation with the visual evaluation can be obtained.

The weight for the integral value of the chromaticity component is
By making all values equal to each other, a correlation with a higher visual evaluation can be obtained.

Further, according to the gloss unevenness evaluation method as another invention, an image to be evaluated is obtained by capturing a color image containing a specularly reflected light component from the sample to be evaluated, and each pixel value of the image to be evaluated is determined by the brightness. Calculates a color value image by converting to a color specification value in a color space composed of components and chromaticity components, calculates an average value for each color component of the color value image, and calculates each pixel of the color value image for each color component. A deviation image is calculated by calculating a deviation from the average value, a value obtained by multiplying the spatial frequency component of the deviation image by a spatial frequency characteristic of human visual perception is calculated for each color component, and each color component obtained by the integration is calculated. An added value obtained by adding different weights to each value or a value proportional to the added value is defined as the gloss unevenness evaluation amount. Therefore, it is possible to provide a gloss unevenness evaluation method that has a high correlation with the visual evaluation of a gloss unevenness sample having a color.

As the image to be evaluated, a first color image containing the specular reflection component from the reference gloss sample and a second color image containing the specular reflection component from the sample to be evaluated are picked up. Is obtained by dividing the color image of the first color image by the first color image, it is possible to prevent illuminance non-uniformity at the time of imaging of the evaluation sample and the influence of the luminance variation of the light source between measurements,
It is possible to perform stable gloss unevenness evaluation.

Further, the weight for the integral value of the lightness component is
Since the value is proportional to the reciprocal of the average value of the lightness component in the color value image, it is possible to correct the influence of the average luminance of the sample on the gloss unevenness, and obtain a higher correlation with the visual evaluation.

The weight for the integral value of the chromaticity component is
By making all values equal to each other, a correlation with a higher visual evaluation can be obtained.

Further, there is a special charge in a computer-readable storage medium storing a program for executing the above-described gloss unevenness evaluation method. Therefore, by using a medium recorded with a program for executing the gloss unevenness evaluation method of the present invention, an apparatus for constructing a gloss unevenness evaluation system can be generally used without changing an existing system.

[Brief description of the drawings]

FIG. 1 is a block diagram showing a configuration of a gloss unevenness evaluation apparatus according to a first embodiment of the present invention.

FIG. 2 is a schematic configuration diagram illustrating a configuration of a document reading apparatus to which the present invention is applied.

FIG. 3 is a diagram illustrating a configuration of a light distribution regulating plate.

FIG. 4 is a diagram showing a configuration of a light distribution regulating plate.

FIG. 5 is a schematic configuration diagram illustrating a configuration of an imaging device.

FIG. 6 is a characteristic diagram showing a relationship between a predicted value of psychological gloss unevenness and a subjective evaluation point obtained by actual measurement.

FIG. 7 is a block diagram illustrating a configuration of a gloss unevenness evaluation apparatus according to a second embodiment of the present invention.

FIG. 8 is a characteristic diagram showing a subjective evaluation point with respect to a calculated gloss unevenness prediction value.

FIG. 9 is a block diagram illustrating a configuration of a gloss unevenness evaluation apparatus according to a third embodiment of the present invention.

FIG. 10 is a characteristic diagram showing a relationship between a predicted value of gloss unevenness of a used sample and a subjective evaluation point.

FIG. 11 is a block diagram illustrating a configuration of a gloss unevenness evaluation apparatus according to a fourth embodiment of the present invention.

FIG. 12 is a schematic configuration diagram illustrating a configuration of another document reading apparatus to which the present invention is applied.

FIG. 13 is a schematic configuration diagram showing a configuration of a cylindrical scanning type document reading apparatus to which the present invention is applied.

FIG. 14 is a block diagram showing a system configuration of the present invention.

[Explanation of symbols]

11; imaging means, 12; image holding means, 13, 30; dividing means, 14; average value calculating means, 15; deviation image calculating means, 16; spatial frequency characteristic calculating means, 17; visual characteristic multiplying means, 18; Means 19; gloss unevenness evaluation amount calculating means 31; color conversion means.

──────────────────────────────────────────────────続 き Continued on the front page (51) Int.Cl. ⁷ Identification symbol FI theme coat ゛ (reference) // G01B 11/00 G01B 11/00 HF term (reference) 2F065 BB01 DD04 FF04 GG07 HH12 JJ03 JJ26 LL00 LL21 LL28 QQ03 QQ04 QQ14 QQ24 QQ25 QQ27 QQ31 RR08 2G051 AA34 AB11 BA01 CA03 CA04 CB01 EA08 EA09 EA14 EA16 EA17 EB01 EB02 EC03 EC07 2G059 AA05 FABB EE02 FF11 FF02 FF11 FF11 FF10

Claims (15)

[Claims] An imaging unit capable of capturing an image including specularly reflected light from a sample to be evaluated; an image holding unit for storing and holding the captured image; Average value calculating means for calculating an average value, deviation calculating means for calculating a deviation between the evaluated image and the average value obtained by the average value calculating means, spatial frequency of the image obtained by the deviation calculating means Spatial frequency characteristic calculating means for calculating the characteristic, visual characteristic multiplying means for multiplying the spatial frequency characteristic and the spatial frequency characteristic of human vision, and integrating means for integrating the spatial frequency component calculated by the visual characteristic multiplying means. And a gloss unevenness evaluation amount calculation means for outputting a value obtained by multiplying the value obtained by the integration means by a proportional coefficient as a gloss unevenness evaluation amount. 2. The gloss nonuniformity evaluation device according to claim 1, further comprising a dividing unit for dividing a value calculated by the integrating unit by an average value calculated by the average value calculating unit. 3. A first image including a specularly reflected light component from a reference gloss sample and a second image including a specularly reflected light component from a sample to be evaluated are imaged by the imaging means, and the second image is imaged by the imager. The gloss unevenness evaluation device according to claim 1, further comprising a division unit that divides by one image. 4. An image capturing apparatus captures an image including a specularly reflected light component from a sample to be evaluated to obtain an image to be evaluated, calculates an average value of the image to be evaluated, and calculates an average value for each pixel of the image to be evaluated. To calculate a deviation image from the average value, calculate a value obtained by multiplying the spatial frequency characteristic of the deviation image by the spatial frequency characteristic of human vision, and calculate a value proportional to the value obtained by the integration. A gloss unevenness evaluation method, wherein a value multiplied by a coefficient is used as a gloss unevenness evaluation amount. 5. The method according to claim 4, wherein the proportional coefficient is a value proportional to a reciprocal of an average value of the evaluated image. 6. The image to be evaluated captures a first image including a specular reflection component from a reference gloss sample and a second image including a specular reflection component from a sample to be evaluated. The gloss unevenness evaluation method according to claim 4, wherein the image is an image calculated by dividing the first image. 7. An image pickup means capable of picking up a color image containing specularly reflected light from a sample to be evaluated, an image holding means for storing and holding the picked-up color image, and each pixel value of the color image being represented by a lightness component and a chromaticity. A colorimetric value conversion means for converting to a colorimetric value in a color space composed of components; an average value calculating means for calculating an average value for each color component of a color value image obtained by the colorimetric value conversion means; Deviation image calculation means for calculating, for each color component, a deviation between each pixel value of the color value image and the average value obtained by the average value calculation means; and a spatial frequency of the deviation image obtained by the deviation image calculation means. A spatial frequency calculating means for calculating; a visual characteristic multiplying means for multiplying the spatial frequency component by a spatial frequency characteristic of human vision; an integrating means for integrating the spatial frequency component calculated by the visual characteristic multiplying means; By means Issued gloss unevenness evaluation apparatus characterized by and an addition means for adding different weights to the value of each color component. 8. A first color image including a specular reflection component from a reference gloss sample captured by an imaging unit and a second color image including a specular reflection component from a sample to be evaluated. The gloss unevenness evaluation apparatus according to claim 7, further comprising a division unit configured to calculate a third color image obtained by dividing the second color image thus obtained by the first color image. 9. The weight for the integral value of the lightness component is:
8. The gloss unevenness evaluation device according to claim 7, wherein the value is a value proportional to a reciprocal of an average value of a lightness component in the third color image. 10. The gloss unevenness evaluation device according to claim 7, wherein the weights for the integral values of the chromaticity components are all equal and arbitrary values. 11. An image to be evaluated is obtained by capturing a color image containing a specularly reflected light component from a sample to be evaluated, and each pixel value of the image to be evaluated is represented by a table on a color space including a lightness component and a chromaticity component. A color value image is calculated by converting to a color value, an average value is calculated for each color component of the color value image, and a deviation from each pixel of the color value image and the average value is calculated for each color component. An image is calculated, and a value obtained by multiplying the spatial frequency component of the deviation image by a spatial frequency characteristic of human visual perception is calculated for each color component. A gloss unevenness evaluation method, wherein an added value obtained by performing the addition or a value proportional to the added value is used as a gloss unevenness evaluation amount. 12. The image to be evaluated captures a first color image including a specularly reflected light component from a reference gloss sample and a second color image including a specularly reflected light component from a sample to be evaluated. The gloss unevenness evaluation method according to claim 11, wherein the image is obtained by dividing a second color image by the first color image. 13. The gloss unevenness evaluation method according to claim 11, wherein the weight for the integral value of the lightness component is a value proportional to the reciprocal of the average value of the lightness component in the color value image. 14. The method according to claim 11, wherein the weights for the integral values of the chromaticity components are arbitrary values that are all equal. 15. A computer-readable storage medium storing a program for executing the gloss unevenness evaluation method according to any one of claims 4 to 6, and 11 to 14.