JP7452800B2 - Acoustic property measuring device, acoustic property measuring method and program - Google Patents

Description

The present invention relates to an acoustic property measuring device, an acoustic property measuring method, and a program for fibrous materials or porous materials.

Conventionally, methods have been developed for absorbing or blocking sound using fiber materials such as nonwoven fabrics as acoustic materials. For example, in Patent Document 1, sound absorption and sound insulation performance is improved by laminating fiber materials with different air flow rates.

Special Publication No. 2009-542504

As in the technique described in Patent Document 1, a combination of a plurality of types of fibers is used in order to improve the sound absorption and insulation performance of the fiber material. Generally, a fiber material composed of a mixture (mixed cotton) of multiple types of fibers is used. In order for the blended fiber material to exhibit the desired sound absorbing and insulating performance, it is required that different types of fibers are mixed uniformly.

Additionally, porous materials such as polyurethane foam are used as other acoustic materials. For example, when a porous material is used as a sound absorbing and insulating material, in order to exhibit desired sound absorbing and insulating performance, it is required that pores (voids) are uniformly contained in the porous material.

When measuring acoustic properties such as sound absorption and insulation performance of fiber materials and porous materials, the measurement is performed using specialized equipment such as a soundproof room and a high-performance sound collection microphone. Therefore, it is difficult to measure acoustic characteristics at a mass production site of fiber materials or porous materials.

The present invention has been made in view of the above-mentioned circumstances, and provides an acoustic property measuring device, an acoustic property measuring method, and a program that can easily measure the acoustic properties of acoustic materials such as fiber materials and porous materials. The purpose is to

In order to achieve the above object, an acoustic characteristic measuring device according to a first aspect of the present invention includes:
a grayscale image generation unit that generates a grayscale image by converting the image of the measurement target into grayscale;
a coarse-graining unit that divides the grayscale image into a plurality of blocks and averages the brightness of pixels in the blocks to generate a coarse-grained image;
and a measurement unit that measures the acoustic characteristics of the measurement target from the degree of dispersion of brightness of the coarse-grained image.

Further, the measurement target is a fiber base material containing multiple types of fibers,
It may also be a thing.

Further, the measurement target is a porous material,
It may also be a thing.

Further, the coarse-graining unit generates the coarse-grained image by reducing the luminance gradation of the block.
It may also be a thing.

Further, the block is a rectangle with one side of 4 mm or more and 350 mm or less,
It may also be a thing.

Moreover, the acoustic characteristic measuring method according to the second aspect of the present invention includes:
a grayscale image generation step of generating a grayscale image by converting the image of the measurement target into grayscale;
a coarse-graining step of dividing the grayscale image into a plurality of blocks and averaging the brightness of pixels in the blocks to generate a coarse-grained image;
The method includes a measuring step of measuring an acoustic characteristic of the measurement target based on the degree of dispersion of brightness of the coarse-grained image.

Further, the program according to the third aspect of the present invention is
computer,
a grayscale image generation unit that generates a grayscale image by converting the image of the measurement target into grayscale;
a coarse-graining unit that divides the grayscale image into a plurality of blocks and averages the brightness of pixels in the blocks to generate a coarse-grained image;
a measuring unit that measures acoustic characteristics of the measurement target from the degree of dispersion of brightness of the coarse image;
function as

According to the acoustic characteristic measuring device, acoustic characteristic measuring method, and program of the present invention, the acoustic characteristic is easily measured by using an image of the measuring object and calculating the degree of dispersion of brightness indicating the uniformity of the measuring object. It is possible to measure the acoustic properties of fibrous and porous materials.

FIG. 1 is a functional block diagram showing an acoustic characteristic measuring device according to an embodiment of the present invention. 7 is a flowchart showing acoustic characteristic measurement processing according to the embodiment. It is a diagram showing an example of an image to be measured, in which (A) is the original image, (B) is a grayscale image, (C) is a coarse-grained image divided into blocks, and (D) is the gradation of (C). This is a coarse-grained image with reduced . These are images showing test piece 1 and test piece 2 as examples of measurement targets, in which (A) is a grayscale image and (B) is a coarse-grained image. It is a histogram of coarse images of test piece 1 and test piece 2. 1 is a diagram showing examples of characteristic values of test piece 1 and test piece 2, in which (A) is a table of each characteristic value, and (B) is a graph showing the relationship between standard deviation and flow resistance.

Hereinafter, an acoustic characteristic measuring device 1 according to an embodiment of the present invention will be described with reference to the drawings. In this embodiment, an acoustic property measuring device 1 that measures acoustic properties of a fiber material containing a plurality of types of fibers will be described as an example. Note that the measurement of acoustic characteristics in this specification includes determining whether the acoustic characteristics of the object to be measured are within a predetermined permissible performance range. The acoustic characteristic measuring device 1 according to the present embodiment includes a control section 11, a storage section 12, a display section 13, and an input section 14, as shown in the block diagram of FIG. Further, the acoustic characteristic measuring device 1 is connected to an imaging section 30.

The imaging unit 30 is a camera that images an acoustic material such as a fiber material or a porous material whose acoustic characteristics are to be measured. The type of camera used as the imaging unit 30, the number of pixels, etc. are not particularly limited, but it is preferable that the resolution is such that a plurality of pixels are included in a block in coarse-graining, which will be described later. The camera serving as the imaging unit 30 according to this embodiment captures a color image.

Here, the fiber base material of the fiber material to be measured in this embodiment includes multiple types of fibers, for example, thick adhesive fibers (melt fibers) and thin fibers (main component). Composed of two types of fibers. Generally, these different types of fibers have different hues, and in a captured image, the brightness of pixels corresponding to each fiber differs. In this embodiment, as will be described in detail later, it is evaluated whether the fibers are uniformly mixed by using differences in brightness between different fibers. Therefore, it is preferable that the difference in brightness between fibers is clear. For example, in the case of a fiber base material containing two different types of fibers, one fiber may be pre-dyed black and the other white, or only one fiber may contain a large amount of fluorescent material. is preferred.

The control unit 11 includes a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), etc., and controls the operation of the acoustic characteristic measuring device 1. Further, the control unit 11 measures the acoustic characteristics of the measurement target, determines whether the acoustic characteristics of the measurement target are within a predetermined range, etc., based on the image of the measurement target captured by the imaging unit 30.

The control unit 11 reads various operating programs and data stored in the ROM, storage unit 12, etc. of the control unit 11 into the RAM and operates the CPU and GPU, thereby performing each function of the control unit 11 shown in FIG. Make it happen. Thereby, the control unit 11 operates as an image data acquisition unit 111, a grayscale image generation unit 112, a coarse-graining unit 113, and a measurement unit 114.

The image data acquisition unit 111 controls the imaging unit 30 to capture an image (original image I _o ) of the fiber base material to be measured. The image data acquisition unit 111 also acquires image data of the captured original image _Io from the imaging unit 30.

The grayscale image generation unit 112 generates a grayscale image _Ig by converting the original image Io of the fiber base material, which is a color image acquired by the image data acquisition unit 111 _, into grayscale. The gray scale conversion method is not particularly limited, and known methods such as a method of averaging RGB, a method of using gamma correction, etc. can be used. Further, the number of gradations of the grayscale image _Ig is not particularly limited, and is, for example, 256 gradations (8 bits).

The coarse-graining unit 113 divides the grayscale image _Ig generated by the grayscale image generation unit 112 into a plurality of blocks. The size and shape of the block are not particularly limited, but in order to measure the acoustic characteristics appropriately, the size should correspond to the wavelength (1 wavelength or 1/4 wavelength) of the sound wave of the frequency that is the target range of the acoustic characteristics measurement. It is preferable. For example, when the frequency range to be measured is 1 to 20 kHz, the wavelengths of the sound waves that affect the acoustic characteristics are approximately 350 mm, which is one wavelength of 1 kHz, approximately 90 mm, which is 1/4 wavelength, and 1/4 of 20 kHz. For example, the wavelength is approximately 4 mm. Therefore, the block is preferably a rectangle with a side corresponding to the fiber base material of 4 mm or more and 350 mm or less, more preferably 4 mm or more and 90 mm or less.

The coarse-graining unit 113 generates a coarse-grained image _Ic by averaging the luminance of pixels within each divided block. More specifically, the coarse-graining unit 113 calculates the average value of the brightness of pixels in the block, and sets the brightness of the pixels in the block to the brightness of the calculated average value. The coarse-graining unit 113 performs the above-mentioned averaging for each block, and generates a coarse-grained image _Ic as a set of blocks whose brightness is averaged.

Furthermore, the coarse-graining unit 113 performs processing to reduce the luminance gradation in order to facilitate evaluation of the luminance distribution for each block. Specifically, for example, the brightness of the coarse-grained image I _c expressed in 256 gradations is divided into six categories: 0 to 42, 43 to 85, 86 to 127, 128 to 170, 171 to 212, and 213 to 255. The median value (21, 64, 107, 149, 192, 234) of each section is taken as the brightness of each section. The coarse-graining unit 113 corrects the brightness of pixels in each block to the brightness of the median value of the division corresponding to the brightness of each block. Thereby, the coarse-graining unit 113 reduces the gradations of the coarse-grained image _Ic from 256 gradations to 6 gradations.

The measuring unit 114 calculates the degree of dispersion of the coarse-grained image _Ic generated by the coarse-graining unit 113. The fiber base material to be measured contains a plurality of different types of fibers. If these different types of fibers are uniformly mixed (blended), the brightness of each block in the coarse-grained image _Ic will be uniform. On the other hand, if there is a bias (variation) in the different types of fibers included in the fiber base material, there will be variation in the brightness of each block of the coarse image _Ic . Therefore, it is estimated that the smaller the luminance dispersion, for example, the standard deviation, of the coarse-grained image I _c , the more uniform the fiber mixing degree is, and the larger the standard deviation, the more dispersion has occurred in the fiber mixing degree.

The measurement unit 114 measures the acoustic characteristics of the measurement target and determines the acoustic characteristics of the measurement target based on a preset index indicating the relationship between the uniformity of the measurement target and the acoustic characteristics and the estimated uniformity of the measurement target. It is determined whether or not the characteristics are within a predetermined range. The predetermined range is a range predetermined as an allowable range for the acoustic characteristics of the measurement target. In this embodiment, the acoustic characteristics of the fiber material to be measured are measured based on a preset index indicating the relationship between the fiber mixing degree and the acoustic characteristics, and the estimated fiber mixing degree. It is determined whether the acoustic characteristics of the object are within a predetermined range.

The storage unit 12 is a nonvolatile memory such as a hard disk or a flash memory, and stores image data of the original image _Io to be measured, a program for generating a grayscale image _Ig and a coarse-grained image _Ic , and information on the uniformity of the measurement target. Stores programs and data such as indicators indicating relationships with acoustic characteristics.

The display unit 13 is a display device provided in the acoustic characteristic measuring device 1, and is, for example, a liquid crystal display. The display unit 13 displays the original image I _o of the measurement target captured by the imaging unit 30, the measurement results of the acoustic characteristics by the measurement unit 114, and the like.

The input unit 14 is an input device for inputting settings of an index indicating the relationship between the uniformity of the measurement target and the acoustic characteristics, instructions for starting and ending measurement, and the like. The input unit 14 is a keyboard, a touch panel, a mouse, etc. provided in the acoustic characteristic measuring device 1.

Next, an acoustic characteristic measuring method using the acoustic characteristic measuring device 1 will be explained with reference to the flowchart of FIG. In this embodiment, as shown in FIG. 3A, an example will be described in which a disc-shaped fiber material is imaged as a measurement target and the acoustic characteristics of the fiber material are measured based on the captured image. do.

When the acoustic characteristic measurement process is started by inputting a measurement start instruction to the input unit 14, in step S11, the image data acquisition unit 111 controls the imaging unit 30 to capture the original fiber base material to be measured. An image I _o is captured, and image data of the original image I _o is obtained from the imaging unit 30 . Further, the image data acquisition unit 111 transmits the acquired image data of the original image _Io to the grayscale image generation unit 112.

Subsequently, as a grayscale image generation step, the grayscale image generation unit 112 grayscales the original image _Io based on the received image data to generate a grayscale image _Ig (step S12). As shown in FIG. 3A, the original image _Io according to this embodiment includes a background image. The grayscale image generation unit 112 first deletes the background image to create an image of only the fiber material. Specifically, the grayscale image generation unit 112 performs processing to make the background part black (brightness=0) and not include it in the count of brightness values. The background of the original image _Io is preferably a single color such as green or blue so that the keying process for deleting the background image can be performed appropriately.

The grayscale image generation unit 112 converts the original image _Io of only the fiber material into grayscale. In this embodiment, the grayscale image generation unit 112 performs grayscale conversion using the NTSC weighted average method to generate a grayscale image I _g (FIG. 3(B)) of the fiber material.

Subsequently, as a coarse-graining step, the coarse-graining unit 113 divides the grayscale image _Ig generated by the grayscale image generating unit 112 into a plurality of blocks (step S13). In this embodiment, the original image _Io is divided into blocks with a size of 160×160 pixels, so that one side of one square block is approximately 15 mm of the fiber material.

Then, for each divided block, the coarse-graining unit 113 averages the luminance of pixels within the block to generate a coarse-grained image _Ic (step S14). In a block including a boundary between a fiber material and a background, the coarse-graining unit 113 averages the luminance of pixels within the block without including pixels indicating the background. This makes it possible to calculate the average brightness only for the fiber material portion. The coarse-graining unit 113 sets the brightness of pixels within the block to the calculated average brightness, and generates a coarse-grained image I _c (FIG. 3(C)).

Further, the coarse-graining unit 113 performs processing to reduce the number of gradations of the coarse-grained image _Ic (step S15). Specifically, as described above, the coarse-graining unit 113 divides the luminance of each block into six categories for the coarse-grained image _Ic , which is an image grayscaled with 256 gradations. Then, the coarse-graining unit 113 corrects the luminance of each block to the median luminance of each section. Thereby, the coarse-graining unit 113 generates a coarse-grained image _Ic with reduced gradations.

Subsequently, as a measurement step, the measurement unit 114 calculates the degree of dispersion indicating the variation in brightness for each block for the coarse-grained image _Ic generated in step S15, and estimates the degree of fiber mixing (step S16). As the degree of dispersion, various indicators such as dispersion and standard deviation can be used. For example, standard deviation is used. As described above, the calculated degree of dispersion represents the degree of mixing of a plurality of fibers contained in the fiber base material. The measurement unit 114 estimates the degree of fiber mixing based on the calculated degree of dispersion. The degree of mixing is an arbitrary index set in advance, and can be used as an index of the degree of mixing, for example, by dividing the value of the standard deviation of luminance into sections in an arbitrary range.

The measuring unit 114 measures the acoustic characteristics of the fiber material based on the degree of fiber mixing estimated from the degree of dispersion (step S17). The acoustic properties of the fiber material are determined based on preset measurement indicators. The measurement index is set in advance as an index indicating the relationship between the degree of mixing of fibers and the acoustic characteristics based on actual measurement data and the like, and is stored in the storage unit 12.

More specifically, the better the fiber base material is blended and the more uniformly different types of fibers are mixed, the greater the flow resistance (difficulty in air flow) of the fiber material and the higher the sound absorption coefficient. On the other hand, the less well blended the fibers are and the greater the unevenness of the fibers, the lower the flow resistance of the fibrous material and the lower its sound absorption coefficient. For example, the measurement index is created as a table showing the relationship between the mixing degree of fibers and the sound absorption coefficient based on such characteristics, and is stored in the storage unit 12 in advance as an index showing the relationship between the mixing degree of fibers and the acoustic characteristics. be remembered.

The measuring unit 114 causes the storage unit 12 to store the sound absorption coefficient corresponding to the degree of mixing of fibers estimated from the degree of dispersion as a measurement result of the acoustic properties of the fiber material to be measured, and causes the display unit 13 to display the sound absorption coefficient ( In step S18), the acoustic characteristic measuring device 1 ends the acoustic characteristic measuring process.

(Measurement example)
Hereinafter, a measurement example related to the acoustic characteristic measuring method according to the present embodiment will be described. In this example, the acoustic characteristics of a fiber material made of two types of fibers, fiber A and fiber B, were measured. In addition, in this example, test pieces 1 and 2 having different mixing degrees of fiber A and fiber B were created, and their acoustic characteristics were evaluated.

Fiber A is a white PET fiber with a fiber diameter of 0.5 dt and a fiber length of about 50 mm. Moreover, the fiber B is a black low melting point PET fiber having a fiber diameter of 2 dt and a fiber length of about 50 mm.

Test piece 1 is a nonwoven fabric made by mixing fibers A and B. Specifically, first, compressed fiber A and fiber B were blended at a weight ratio of 7:3, and opened and mixed using a sample opener machine (Takeuchi Seisakusho Co., Ltd., OP-400). Thereafter, the spread and mixed materials were mixed and carded using a sample roller card machine (Takeuchi Seisakusho Co., Ltd., SRC-400) to produce a nonwoven fabric with a width of 400 mm and a length of 900 mm. Then, after preheating the nonwoven fabric in an oven, it was cooled while maintaining the thickness at 50 mm to produce a nonwoven fabric sheet. Further, a piece having a diameter of 100 mm was cut out from the nonwoven fabric sheet to obtain a test piece 1.

Test piece 2, like test piece 1, is a nonwoven fabric made by mixing fibers A and B. Specifically, first, compressed fiber A and fiber B were mixed at a weight ratio of 7:3, and a sample opener machine (with a fiber opening frequency reduced to approximately 0.06 times compared to the case of test specimen 1) was used. The fibers were opened and mixed using Takeuchi Seisakusho Co., Ltd. (OP-400). After that, the spread and mixed materials were processed using a sample roller card machine (Takeuchi Seisakusho Co., Ltd.) where the gap between the cylinder roller and worker roller was increased three times compared to the case of test piece 1 to reduce carding properties. , SRC-400) and carded to produce a nonwoven fabric with a width of 400 mm and a length of 900 mm. Then, after preheating the nonwoven fabric in an oven, it was cooled while maintaining the thickness at 50 mm to produce a nonwoven fabric sheet. Further, a test piece 2 with a diameter of 100 mm was cut out from the nonwoven fabric sheet.

Regarding the above-mentioned test piece 1 and test piece 2, the degree of dispersion of the mixed fibers was measured by the acoustic measurement method according to the present embodiment. Specifically, as shown in FIG. 4(A), three images each of the front and back sides (total of 6 images) of Test Piece 1 and Test Piece 2 were photographed with a size of 45 mm x 30 mm. The resolution at this time is about 4.7 μm/pixel, which is smaller than the fiber diameters of fibers A and B.

Subsequently, as shown in FIG. 4(B), the photographed image was divided into 9×6 blocks (approximately 5 mm/block), and the brightness of pixels within the blocks was averaged to generate a coarse image _Ic. . Further, 8-bit gradation histogram data was generated from the six generated coarse images _Ic , and average histogram data, which is the average of the six coarse images _Ic , was calculated. Furthermore, the standard deviation was calculated from the average histogram data. Furthermore, when the standard deviation was set to 8, the total number of counts outside the range of ±3σ was calculated. FIG. 5 is an average histogram of two samples each of test piece 1 and test piece 2.

Flow resistance was measured as an index indicating the acoustic characteristics of the above-mentioned test piece 1 and test piece 2. Specifically, the weights of test piece 1 and test piece 2 were measured using an analytical balance (Shimadzu Corporation, AUX320), and the bulk density of each was calculated. Then, the flow resistance per unit thickness of Test Piece 1 and Test Piece 2 was measured using a flow resistance measurement system (Mecanum, SIGMA). Furthermore, the flow resistance per bulk density was calculated by dividing the flow resistance per unit thickness by the bulk density.

FIGS. 6A and 6B are diagrams showing the above-mentioned measurement data regarding test piece 1 and test piece 2. As shown in Figures 6(A) and (B), there is a correlation between the standard deviation, which represents the degree of mixing of fibers calculated using image processing, and the flow resistance, which represents acoustic characteristics. It can be seen that the acoustic characteristics of the measurement target can be estimated from the degree of mixing. In particular, for fiber materials whose fiber composition and target bulk density are clear, the flow resistance can be estimated by the image analysis according to this embodiment.

In addition, by setting an arbitrary threshold value (range of multiples of allowable standard deviation, etc.) in advance and using a coarse-grained image of the measurement target (coarse-grained image I _c ), it is possible to easily detect products whose acoustic characteristics are outside the allowable performance range. It becomes possible to detect.

As shown in FIG. 5, even test pieces with the same configuration have different brightness peaks depending on the sample. Furthermore, when the reproducibility of image capture is low, deviations in brightness peaks, brightness distribution, etc. may occur. Such deviations in brightness peaks and distributions caused by photographic reproducibility can be reduced by optimizing the resolution of the photographed images, and deviations in brightness peaks and distributions for each sample can be more accurately corrected. can be measured. More specifically, by making the spatial resolution (μm/pixel) of the photographed image smaller than the solid part skeleton diameter of the porous material, it is possible to correct variations in brightness reproducibility for each pixel in the photographed image. It is possible to improve the imaging reproducibility of the peak position of the brightness histogram, brightness distribution, etc.

As explained above, in the acoustic property measuring device and the acoustic property measuring method according to the present embodiment, the degree of mixing of a plurality of types of fibers constituting the fiber base material is determined using an image of the fiber base material to be measured. That is, by estimating the uniformity of the measurement target, the acoustic characteristics are measured, and it is determined whether the acoustic characteristics are within a predetermined range. Therefore, it is possible to easily measure the acoustic properties of fiber materials, fiber composite materials, etc., and determine whether the acoustic properties are within a predetermined range.

Furthermore, in this embodiment, the acoustic characteristic measuring device 1 measures the acoustic characteristics based on the grayscale image _Ig obtained by converting the original image _Io to a grayscale, so that the degree of dispersion is calculated by simple processing. However, it is possible to measure the acoustic characteristics and determine whether the acoustic characteristics are within a predetermined range.

Furthermore, the acoustic characteristic measuring device 1 according to the present embodiment divides the grayscale image _Ig into blocks and averages the brightness of pixels within the blocks. Further, the acoustic characteristic measuring device 1 calculates the degree of dispersion based on the coarse image _Ic generated by reducing the luminance gradation of each block. Thereby, it is possible to calculate the degree of dispersion with simpler processing, measure the acoustic characteristics, and determine whether the acoustic characteristics are within a predetermined range.

In this embodiment, the grayscale image _Ig is generated by directly converting the original image _Io to grayscale, but the present invention is not limited to this. For example, the grayscale image generation unit 112 may perform grayscale conversion after performing gradation correction on the original image _Io . This makes it possible to evaluate the degree of blending of fibers over a wide range of gradations, making it possible to estimate the degree of blending with higher accuracy.

Furthermore, in the present embodiment, the acoustic property measuring device 1 is connected to the imaging section 30 and acquires the original image _Io of the fiber base material imaged by the imaging section 30, but this is not limited to this. I can't. For example, an original image _Io captured in advance and stored in the storage unit 12 may be used.

Further, in this embodiment, the fiber base material to be measured includes two different types of fibers, but is not limited to this, and may include three or more types of fibers. In this case, each fiber is preferably dyed in advance so that the difference in brightness of each fiber becomes clear when converted to gray scale.

Further, although the acoustic material to be measured according to the present embodiment is a fiber material, it is not limited to this. For example, the acoustic material to be measured may be a porous material such as polyurethane foam, felt, or glass wool. In this case, the uniformity of the porous material, that is, the degree of distribution of the pores (voids), is estimated based on the difference in brightness between the area where the material such as polyurethane exists and the pores (voids), and the acoustic characteristics are measured. It may be determined whether or not the acoustic characteristics of the object are within a predetermined range.

Moreover, the acoustic characteristic measuring method according to the embodiment described above can be realized using a normal computer system. For example, a computer program for executing the acoustic characteristic measurement according to the above embodiment is stored and distributed in a computer-readable recording medium such as a USB memory or a DVD-ROM, and the computer program is installed on the computer. By doing so, the computer device can function as an acoustic characteristic measuring device that executes the above-mentioned acoustic characteristic measurement.

The present invention is suitable for measuring the acoustic properties of fiber base materials such as nonwoven fabrics, porous materials such as polyurethane foam, and determining whether the acoustic properties are within a predetermined range. In particular, it is suitable for measuring the acoustic properties of a fiber base material containing a plurality of fibers with different hues, and determining whether the acoustic properties are within a predetermined range.

Reference Signs List 1 acoustic characteristic measuring device, 11 control unit, 111 image data acquisition unit, 112 grayscale image generation unit, 113 coarse-graining unit, 114 measurement unit, 12 storage unit, 13 display unit, 14 input unit, 30 imaging unit

Claims (7)

a grayscale image generation unit that generates a grayscale image by converting the image of the measurement target into grayscale;
a coarse-graining unit that divides the grayscale image into a plurality of blocks and averages the brightness of pixels in the blocks to generate a coarse-grained image;
a measurement unit that measures the acoustic characteristics of the measurement target from the luminance dispersion of the coarse image;
An acoustic characteristic measuring device characterized by: The measurement target is a fiber base material containing multiple types of fibers,
The acoustic characteristic measuring device according to claim 1, characterized in that: The measurement target is a porous material,
The acoustic characteristic measuring device according to claim 1, characterized in that: The coarse-graining unit generates the coarse-grained image by reducing the luminance gradation of the block.
The acoustic characteristic measuring device according to any one of claims 1 to 3. The block is a rectangle with one side of 4 mm or more and 350 mm or less,
The acoustic characteristic measuring device according to any one of claims 1 to 4. a grayscale image generation step of generating a grayscale image by converting the image of the measurement target into grayscale;
a coarse-graining step of dividing the grayscale image into a plurality of blocks and averaging the brightness of pixels in the blocks to generate a coarse-grained image;
a measuring step of measuring the acoustic characteristics of the measurement target from the luminance dispersion of the coarse image;
A method for measuring acoustic characteristics characterized by the following. computer,
a grayscale image generation unit that generates a grayscale image by converting the image of the measurement target into grayscale;
a coarse-graining unit that divides the grayscale image into a plurality of blocks and averages the brightness of pixels in the blocks to generate a coarse-grained image;
a measuring unit that measures acoustic characteristics of the measurement target from the degree of dispersion of brightness of the coarse image;
A program that functions as