JP6342280B2 - Method, apparatus and computer program for identifying high intensity components in coal. - Google Patents

Description

  The present invention relates to a coal analysis method, a coal analysis apparatus, and a computer program for identifying high-luminance components such as inertite structures and minerals contained in coal.

  It is known that when the coal used as the raw material for coke contains a coarse inertite structure, the inertite structure is known to contribute to lowering the strength of the coke, so that the inertite structure is appropriately sized. Coke is produced after crushing.

  As a method for identifying inertite structure in coal, a method for analyzing coal based on JIS M8816 is known. In this method, a coal structure is visually identified using a polarizing microscope. Non-Patent Document 1 describes that an inert knit structure in coke, not coal, is visually identified using a microscope and the size is measured.

As another method, for example, Patent Document 1 discloses a method of measuring coal using an X-ray CT apparatus and identifying a coal structure (inertite structure, vitrinite structure, ecdynite structure) from an X-ray CT image .

JP 2005-338011 A

Iron and steel, “Effect of inert particle size on coke strength”, Kubota Yasuhiro, Nomura Seiji, Arima Takashi, Kato Kenji, Vol.92 (2006) No.12 P141-148, P833-840, Japan Iron and Steel Association Publication

  However, in Non-Patent Document 1 and JIS M8816 which is a general analysis method, it is described or stipulated that a human visually observes an image obtained by a microscope and identifies whether it is an inert knit structure based on experience. . Since the measurer discriminates by visual confirmation and marks the site recognized as an inert tissue, the analysis takes a long time, and further, the determination criteria differ depending on the measurer, resulting in low reproducibility.

  On the other hand, when using an X-ray CT apparatus as in Patent Document 1, it cannot be said to be a method of using a microscope defined in JIS M8816, and the cost increases because an X-ray CT apparatus is required. .

The present invention was made in view of such problems, and an object is achieved by a method of using a microscope, measuring person due to possible shorter and analysis time eliminate the variation in identification accuracy, A coal analysis method, a coal analysis apparatus, and a computer program are provided.

  In order to achieve this object, the present invention takes the following measures.

  The coal analysis method according to the present invention includes a first image obtained by capturing an image of a coal sample in a horizontal Nicol state in which the angle of the polarizer with respect to the analyzer is set to 0 °, and an angle of the polarizer with respect to the analyzer. Storing in the storage unit a second image obtained by imaging the same part as the first image in a state where the angle is set to 80 ° or more and 90 ° or less, and ORing the first image and the second image A step of generating a monochrome image obtained by converting the image generated by the logical sum operation into a gray scale, and a pixel having a brightness brighter than a predetermined reference brightness value among the plurality of pixels constituting the monochrome image is a high brightness Identifying a pixel corresponding to the component.

The coal analyzer according to the present invention uses a reflection type polarization microscope having an analyzer and a polarizer, and a first image obtained by imaging a coal sample in a horizontal Nicol state in which the angle of the polarizer with respect to the analyzer is 0 °, and the angle of the polarizer with respect to the analyzer A storage unit for storing the first image and the second image obtained by imaging the same part in a state where the angle is set to 80 ° or more and 90 ° or less, and logically calculates the first image and the second image, A logical sum operation unit for generating a new image by a sum operation;
A monochrome image generation unit that generates a monochrome image obtained by converting the image generated by the OR operation unit into a gray scale, and a plurality of pixels that form the monochrome image generated by the monochrome image generation unit are predetermined. An identification unit for identifying that a pixel having a brightness brighter than the reference brightness value is a pixel corresponding to a high brightness component.

  The computer program of the present invention is a program for causing a computer to execute each step constituting the above method.

The first image picked up in the state of horizontal Nicol is a bright image with high brightness as a whole, and is easy to observe with human eyes. However, the luminance histogram has a smooth distribution, the brightness and darkness according to the properties of the coal component is not clear, and it is impossible to automatically identify whether the luminance component is a high luminance component such as an inert structure using the luminance as an index.
The second image captured in a state in which the angle of the polarizer with respect to the analyzer is set to 80 ° or more and 90 ° or less has light and dark depending on the property of the coal component that the inertite structure is easy to shine and the other structures are dark. However, since the entire image is dark and the distribution width of the luminance histogram is narrow, it is impossible to automatically identify whether it is a high-luminance component such as an inert tissue using luminance as an index.
For these, according to the above method, apparatus and computer program, a logical OR operation to significantly high luminance portion of the two images by performing the first image and the second image, the whole image is bright and coal An image with remarkable brightness and darkness can be generated according to the property of the component, and it can be automatically determined from the image whether the component is a high luminance component according to the luminance value. Accordingly, since the method is based on the standard and can be automatically identified, variations in identification accuracy by the measurer can be eliminated and the analysis time can be shortened.

The block diagram which shows the structure of the coal analyzer in this embodiment. The figure which shows the example of a 1st image and its brightness | luminance histogram. The figure which shows the example of a 2nd image and its brightness | luminance histogram. The figure which shows the example of the monochrome image produced | generated based on the OR operation of a 1st image and a 2nd image, and its luminance histogram. The figure which shows the result of having identified whether it is a high-intensity component by the coal analyzer of this embodiment. The flowchart which shows the coal analysis method of this embodiment. The figure which shows the result of having identified whether it is a high-intensity component by the conventional visual observation. The figure which shows the identification result at the time of imaging a 2nd image by making the polarizer angle with respect to an analyzer into 90 degrees. The figure which shows the identification result at the time of imaging a 2nd image by making the polarizer angle with respect to an analyzer into 80 degrees. The figure which shows the identification result at the time of imaging a 2nd image by making the polarizer angle with respect to an analyzer 70 degrees. The figure which shows the identification result at the time of imaging a 2nd image by making the polarizer angle with respect to an analyzer into 60 degrees. The figure which shows the identification result at the time of imaging a 2nd image by making the polarizer angle with respect to an analyzer into 10 degrees.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

  The coal analysis method of the present embodiment uses a reflected light polarization microscope having an analyzer (analyzer) and a polarizer (polarizer), obtains a microscopic image of the sample from the reflected light of the light irradiated on the coal sample, and displays the image on a computer. This is a method for automatically identifying high-luminance components in coal by executing processing. The coal analyzer of this embodiment is an apparatus used when using the said method. In the present specification, the “high brightness component” means an inertite structure and a mineral. In the present embodiment, the main example is to identify the inert knit structure.

<Coal analyzer>
As shown in FIG. 1, the coal analyzer 1 includes a storage unit 10, an input unit 11, a logical sum operation unit 12, a monochrome image generation unit 13, an identification unit 14, a marking unit 15, and image group recognition. A unit 16 and an output unit 17. These units 10 to 17 are realized in cooperation with software and hardware by executing a processing routine (not shown) stored in advance by the CPU in an information processing apparatus such as a personal computer equipped with a CPU, memory, various interfaces, and the like. Is done.

  The storage unit 10 illustrated in FIG. 1 stores a first image and a second image. The input unit 11 captures the first image and the second image captured by the microscope into the apparatus 1 (computer) and stores them in the storage unit 10. The input unit 11 may be configured to connect, for example, a microscope and the apparatus 1 and automatically store an image captured by the microscope in the storage unit 10, or the apparatus 1 using a user operation as a trigger. The image data may be captured via a storage medium connected to the communication network or a communication network and stored in the storage unit 10. The storage unit 10 is preset (stored) with a reference luminance value that serves as an index for determining whether or not it is a high luminance component. The reference luminance value is registered in advance by the user.

  The first image is an image obtained by capturing an image of a coal sample in a horizontal Nicol state in which the angle of the polarizer with respect to the analyzer is 0 °, using an epi-polarization microscope having an analyzer and a polarizer. The second image is an image obtained by capturing the same part as the first image in a state where the angle of the polarizer with respect to the analyzer is 80 ° or more and 90 ° or less.

The upper part of FIG. 2 shows an example of the first image, and the lower part of FIG. 2 shows a luminance histogram when the first image is grayscaled. FIG. 2 is a microscopic image of a sample using a coal brand having a coalification degree (vitrinite average reflectance) Ro of 0.8 and a luminance histogram thereof. According to JIS M8816, the sample is ground and ground pulverized coal. The black block at the lower left in the figure is resin. In the luminance histogram, the vertical axis indicates the number of pixels, the horizontal axis indicates the luminance, and the left axis is dark and the right side is bright. As shown in FIG. 2, the distribution of pixels in the luminance histogram is wide, and the image is bright as it is apparent. However, since the distribution of the luminance histogram is smooth, it is not possible to automatically determine whether or not it is a high luminance component using the luminance as an index.

The upper part of FIG. 3 shows an example of the second image, and the lower part of FIG. 3 shows a luminance histogram when the second image is grayscaled. The example of FIG. 3 is an image obtained by imaging the same part as the first image in a state of orthogonal Nicols with the polarizer angle with respect to the analyzer being 90 °. As shown in FIG. 3, the pixel distribution in the luminance histogram is in a narrow range gathered on the low luminance side, and is a dark image as apparent from the appearance. Since the luminance distribution is narrow, it is impossible to automatically determine whether or not it is a high luminance component using luminance as an index.

  Note that the first image shown in FIG. 2 and the second image shown in FIG. 3 are gray scales due to limitations of the application drawings, but are actually color images. The number of colors of the color image is, for example, 24 bits, but various changes such as 16 bits and 32 bits can be made for color images.

  The logical sum operation unit 12 illustrated in FIG. 1 performs a logical sum operation on the first image illustrated in FIG. 2 and the second image illustrated in FIG. 3, and generates a new image by the logical sum operation. The logical sum operation is a process that makes a high-luminance portion of two images noticeable. Although this new image is not shown, it is a color image having the same number of colors as the first image and the second image.

  The monochrome image generation unit 13 illustrated in FIG. 1 generates a monochrome image (see FIG. 4) obtained by converting the new image generated by the logical sum calculation unit 12 into a gray scale. The number of colors of the monochrome image is, for example, 8 bits (256 colors). According to the luminance histogram shown in FIG. 4, the pixel distribution is wide and peaks and valleys clearly appear.

  The identification unit 14 illustrated in FIG. 1 identifies that a pixel having a brightness brighter than a predetermined reference luminance value among the plurality of pixels constituting the monochrome image illustrated in FIG. 4 is a pixel corresponding to a high luminance component. To do. Specifically, all the pixels constituting the monochrome image illustrated in FIG. 4 are referred to, and if the luminance of the referenced pixel is equal to or higher than a predetermined reference luminance value, the pixel corresponds to the high luminance component. If the luminance of the referenced pixel is smaller than a predetermined luminance value, it is determined that the pixel does not correspond to the high luminance component. In the example of FIG. 4, 160 is set as the reference luminance value, and it is determined that pixels having luminance values of 160 to 255 are pixels corresponding to the high luminance component. Although the reference luminance value is determined in advance, the determination method is to determine whether it is a high-luminance component with the human eye as before, the luminance of the determined pixel is 160 or more, and the luminance value A valley appears clearly in the vicinity of 160, and it is determined by determining that the luminance value 160 is suitable as a boundary between the high luminance component and the other components. Of course, in the present embodiment, the luminance value 160 is set as the reference luminance value, but the value is appropriately changed according to the sample and the imaging environment. Once the standard luminance value is determined, the same brand and the same imaging environment can be applied as they are, and thereafter automatic determination can be performed.

  The marking unit 15 illustrated in FIG. 1 outputs an image corresponding to an image marked on a pixel corresponding to a high luminance component among a plurality of pixels constituting the monochrome pixel illustrated in FIG. The output image may be an image colored in the above-described monochrome image, or may be a binary image in which the pixels of the high luminance component are the first color and the pixels other than the high luminance component are the second color as shown in FIG. Good. FIG. 5 is an example of a binary image in which pixels with high luminance components are the first color and pixels other than the high luminance components are the second color. Although it is not a black-and-white binary image due to restrictions on the application documents, gray is a pixel with a high luminance component, and black is another pixel. The arrows in the figure are for explanation. The marking unit 15 can be appropriately omitted as a configuration of the apparatus.

  The image group recognition unit 16 shown in FIG. 1 recognizes a series of pixel groups composed of a plurality of pixels when pixels corresponding to high luminance components are adjacent to each other, as indicated by gray in FIG. The series of pixel groups is surrounded by pixels other than the high luminance component to form an island. As a specific algorithm for recognition, a known labeling process can be used. In the binarized image, the labeling process is a process of assigning the same number to an image in which a portion of the first color or the second color is continuous, and the pixels assigned the same number are identified as a series of pixel groups. it can. As a labeling method, either 4-connection or 8-connection may be adopted. The 4-connection is a method of making pixels that are continuous in the vertical direction and the horizontal direction the same label, and the 8-connection is a method of making pixels that are continuous in the vertical direction, the horizontal direction, and the diagonal direction the same label. .

Output unit 17 shown in FIG. 1 calculates and outputs a parameter for a set of picture element group which is recognized in the image group recognition unit 16. As an output mode, it may be output to a display or may be output in a file format that can be read by various application software such as spreadsheet software. The parameters relating to the series of pixel groups include the area, maximum length, number, area ratio, etc. of the series of pixel groups. In the present embodiment, the maximum length of each series of pixel groups (the length indicated by the white arrow in FIG. 5) is output. Specifically, since the dimension value per pixel is determined based on the imaging conditions (such as magnification) of the first image and the second image, the area or the maximum length is calculated using the dimension value. The output unit 17 outputs the number, area ratio, and the like. Of course, the output information is not limited to the area, maximum length, number, and area ratio. The image group recognition unit 16 and the output unit 17 can be omitted as appropriate in the configuration of the apparatus.

<Coal analysis method>
A coal analysis method using the apparatus 1 will be described with reference to FIG.

  First, in step ST1, a coal sample is imaged by using an epi-polarization polarization microscope having an analyzer and a polarizer to obtain a first image and a second image. The first image is an image obtained by capturing an image of a coal sample in a horizontal Nicol state where the angle of the polarizer with respect to the analyzer is 0 °. The second image is an image obtained by capturing the same part as the first image in a state where the angle of the polarizer with respect to the analyzer is 80 ° or more and 90 ° or less.

  In the next step ST2, the device 1 stores the first image and the second image in the storage unit 10. In the next step ST3, the logical sum operation unit 12 performs a logical sum operation on the first image and the second image to generate a new image. In the next step ST4, the monochrome image generation unit 13 grayscales the image generated by the logical sum calculation unit 12 to generate a monochrome image.

  Next, the identification unit 14 executes the processes in steps ST5 to ST8, so that an image in which a pixel brighter than a predetermined reference luminance value among the plurality of pixels constituting the monochrome image corresponds to a high luminance component. Is identified.

  In the next step ST9, the marking unit 15 outputs an image corresponding to the image marked on the pixel corresponding to the high luminance component among the plurality of pixels constituting the monochrome pixel shown in FIG. In the next step ST10, the image group recognizing unit 16 recognizes a series of pixel groups (so-called islands) composed of pixels of high luminance components. In the next step ST11, the output unit 17 calculates and outputs parameters related to a series of pixel groups recognized by the image group recognition unit 16. For example, in the example of FIG. 5, the maximum length of the pixel group is output as a parameter, the maximum length of the island in the upper left white arrow portion is 118 μm, the maximum length of the island in the lower arrow portion is 133 μm, The maximum length of the island in the arrow portion on the right is 273 μm, and the maximum length of the island in the arrow portion on the upper right is 129 μm. Note that steps ST9 to ST10 can be omitted as appropriate. Of course, the information output from the output unit 17 is not limited to the area, the maximum length, the number, and the area ratio.

  The effectiveness of the coal analyzer 1 and the coal analysis method will be described.

The image in FIG. 5 shows a portion in which a monochrome image is generated using the coal analysis device 1 and the device 1 identifies as a high luminance component (inertite structure) based on the monochrome image in gray. The image in FIG. 7 is an image in which a portion identified as a high-luminance component (inertite tissue) with human eyes is colored gray using a first image obtained by imaging the same part. The first and second images are taken under the following conditions by using a polarized microscope (DM2500P LEICA), a CCD camera (DFC290H D LEICA) and application software (Application Suite V3 LEICA) after polishing. It is an image. Of course, changes other than the analyzer and the polarizer angle need to be appropriately changed according to the microscope and the sample.
Polarization microscope light source: The light source intensity was changed according to the coal sample by measuring the light source intensity in the standard sample Ro = 1.027. For coal samples with a coalization degree Ro = 0.8, standard sample Ro = 1.027 and light source intensity 9450 “Counts”, for Ro = 1.0 coal samples with standard sample Ro = 1.027 and light source intensity 7480 “Counts”, Ro = 1.3 coal In the sample, the standard sample Ro = 1.027 and the light source intensity was 4270 “Counts”.
Polarizing microscope objective lens: 20 times (total magnification 200 times)
Exposure: 130.6ms
Gain: 1.7x
Saturation: 1 . 00
Gamma: 0.60
<First image>: Analyzer angle: 0 °, Polarizer angle: 0 °
<Second image>: Analyzer angle: 0 °, polarizer angle: 90 °

  Comparing FIG. 5 by automatic determination with FIG. 7 by visual determination, in FIG. 7, the lower right arrow part is identified as a large inert structure, but in FIG. 5 it is recognized as a small dispersed structure. Although it is different, the main parts are almost the same. It can be seen that the accuracy of automatic identification by the apparatus and method of this embodiment is high. Above all, a luminance histogram suitable for automation could not be obtained with only one microscope image, and automation could not be performed, but in this embodiment, identification of high luminance components is performed by using the first image and the second image. I was able to automate.

  Next, in order to know the optimum angle of the analyzer angle and the polarizer angle for the second image, five images with different angle conditions are taken, and the high-luminance component (inertite tissue) is identified by the apparatus and method of this embodiment. Went. FIG. 8 shows an example in which identification is performed by capturing a second image with the analyzer set to 0 ° and the polarizer set to 90 °. FIG. 9 shows an example in which identification is performed by capturing a second image with the analyzer set to 0 ° and the polarizer set to 80 °. FIG. 10 shows an example in which identification is performed by capturing a second image with the analyzer set to 0 ° and the polarizer set to 70 °. FIG. 11 shows an example in which identification is performed by capturing a second image with the analyzer set to 0 ° and the polarizer set to 60 °. FIG. 12 shows an example in which identification is performed by capturing a second image with the analyzer set to 0 ° and the polarizer set to 10 °. The upper part of FIGS. 8-12 shows the image which colored the pixel recognized as a high-intensity component among white and black images in white. The lower part of FIGS. 8 to 12 shows a luminance histogram of a monochrome image.

  Comparing FIG. 8 (polarizer angle 90 °) and FIG. 9 (polarizer angle 80 °), a part of the structure other than the inertite structure and mineral is discriminated as a high luminance component in FIG. Although it occurred, it was acceptable. Comparing the luminance histograms of FIGS. 8 and 9, both waveforms are similar, and it has been found that high luminance components can be identified although some noise is present even at a polarizer angle of 80 °.

  8 and FIG. 9, FIGS. 10 to 12 misidentify a wide range portion of the image including the inertite structure and mineral as a high luminance component, and it has been found that it cannot be used practically. Comparing the luminance histograms of FIGS. 8 to 9 and the luminance histograms of FIGS. 10 to 12, the characteristics of the waveforms of the luminance histograms of FIGS. It is considered that information necessary for identification is lost.

  8 to 12, it can be understood that the second image needs to be imaged with a polarizer angle of 80 ° or more and 90 ° or less with respect to the analyzer. Of course, it can be understood that it is preferable to obtain a second image by imaging in a state of orthogonal Nicols with a polarizer angle of 90 ° with respect to the analyzer.

As described above, the coal analysis method of the present embodiment uses the epi-polarization polarization microscope having the analyzer and the polarizer, and the first image obtained by imaging the coal sample in a horizontal Nicol state in which the angle of the polarizer with respect to the analyzer is 0 °; Storing the first image and the second image obtained by imaging the same part in a state where the angle of the polarizer with respect to the analyzer is 80 ° or more and 90 ° or less (ST1 to ST2);
A step of performing a logical sum operation on the first image and the second image, and generating a monochrome image obtained by converting the image generated by the logical sum operation into a gray scale (ST3, 4);
Identifying a pixel having a brightness brighter than a predetermined reference brightness value among a plurality of pixels constituting a monochrome image as a pixel corresponding to a high brightness component (ST5 to 8);
including.

In addition, the coal analyzer 1 of the present embodiment uses a reflection type polarization microscope having an analyzer and a polarizer, a first image obtained by imaging a coal sample in a horizontal Nicol state in which the angle of the polarizer with respect to the analyzer is 0 °, and an analyzer A storage unit 10 for storing the first image and the second image obtained by imaging the same part in a state where the angle of the polarizer with respect to the first image is not less than 80 ° and not more than 90 °;
A logical sum operation unit 12 for performing a logical sum operation on the first image and the second image and generating a new image by the logical sum operation;
A monochrome image generation unit 13 that generates a monochrome image obtained by converting the image generated by the logical sum calculation unit 12 into a gray scale;
An identification unit 14 that identifies a pixel having a brightness brighter than a predetermined reference luminance value among a plurality of pixels constituting the monochrome image generated by the monochrome image generation unit 13 as a pixel corresponding to a high luminance component. And comprising.

As illustrated in FIG. 2, the first image picked up in a horizontal Nicol state is a bright image with high brightness as a whole and is easy to observe with human eyes. However, the luminance histogram has a smooth distribution, the brightness and darkness according to the properties of the coal component is not clear, and it is impossible to automatically identify whether the luminance component is a high luminance component such as an inert structure using the luminance as an index.
As illustrated in FIG. 3, the second image captured in a state where the angle of the polarizer with respect to the analyzer is 80 ° or more and 90 ° or less is due to the property of the coal component that the inertite structure is easy to shine and other structures are dark. Correspondingly, light and dark becomes noticeable. However, since the entire image is dark and the distribution width of the luminance histogram is narrow, it is impossible to automatically identify whether it is a high-luminance component such as an inert tissue using luminance as an index.
On the other hand, according to the method and apparatus of the present embodiment, the entire image is brightened by performing a logical sum operation on the first image and the second image to make the bright portion of the two images noticeable. An image with remarkable brightness and darkness can be generated according to the property of the coal component, and it can be automatically determined from the image whether the component is a high luminance component according to the luminance value. Accordingly, since the method is based on the standard and can be automatically identified, variations in identification accuracy by the measurer can be eliminated and the analysis time can be shortened.

  In the method and apparatus of the present embodiment, the second image is preferably an image captured in a state of orthogonal Nicols in which the angle of the polarizer with respect to the analyzer is 90 °. Compared with the case where the angle of the polarizer with respect to the analyzer is 80 °, there is less noise and high-precision identification is possible.

The method of this embodiment includes a step (ST9) of outputting an image corresponding to an image marked on a pixel corresponding to a high luminance component among a plurality of pixels constituting a monochrome image.
The apparatus of the present embodiment includes a marking unit 15 that outputs an image corresponding to an image marked on a pixel corresponding to a high luminance component among a plurality of pixels constituting a monochrome image.
According to this method and apparatus, the identification result can be provided as an easy-to-understand image with human eyes, and convenience is improved.

The method according to the present embodiment includes a step of recognizing a series of pixel groups composed of the plurality of pixels when pixels corresponding to a high luminance component are adjacent, and calculating and outputting parameters regarding the recognized series of pixel groups. (ST10, 11) are included.
The apparatus according to the present embodiment includes an image group recognition unit 16 that recognizes a series of pixel groups including a plurality of pixels when pixels corresponding to a high luminance component are adjacent to each other, and a series recognized by the image group recognition unit 16. And an output unit 17 that calculates and outputs a parameter related to the pixel group.
According to this method and apparatus, the parameter for the high luminance component can be easily known, so the convenience of coal analysis can be improved.

  The computer program of the present embodiment is a program that causes a computer to execute each step constituting the above method.

  The storage medium of the present embodiment is a computer-readable storage medium that stores the computer program. By executing this program, it is possible to obtain the operational effects of the above method. In other words, it can be said that the apparatus uses the method.

  As mentioned above, although embodiment of this invention was described based on drawing, it should be thought that a specific structure is not limited to these embodiment. The scope of the present invention is shown not only by the above description of the embodiments but also by the scope of claims for patent, and further includes all modifications within the meaning and scope equivalent to the scope of claims for patent.

  For example, each of the units 10 to 17 illustrated in FIG. 1 is realized by executing a predetermined program by a CPU of a computer, but each unit may be configured by a dedicated memory or a dedicated circuit.

  The structure employed in each of the above embodiments can be employed in any other embodiment. The specific configuration of each unit is not limited to the above-described embodiment, and various modifications can be made without departing from the spirit of the present invention.

DESCRIPTION OF SYMBOLS 10 ... Memory | storage part 12 ... OR operation part 13 ... Monochrome image generation part 14 ... Identification part 15 ... Marking part 16 ... Image group recognition part 17 ... Output part

Claims (8)

A first image obtained by imaging a coal sample in a horizontal Nicol state where the angle of the polarizer with respect to the analyzer is 0 ° using an episcopic polarization microscope having an analyzer and a polarizer, and the angle of the polarizer with respect to the analyzer is 80 ° or more and 90 ° or less Storing the second image obtained by imaging the same part as the first image in the storage unit in a storage unit;
Performing a logical OR operation on the first image and the second image, and generating a monochrome image obtained by converting the image generated by the logical OR operation into a gray scale;
Identifying a pixel having a brightness brighter than a predetermined reference brightness value among a plurality of pixels constituting the monochrome image as a pixel corresponding to a high brightness component;
A method for identifying high intensity components in coal, comprising: The second image, method person according to claim 1, wherein the image captured in a state of crossed nicols with the angle of the polarizer with respect to the analyzer and 90 °. Wherein among the plurality of pixels constituting the monochromatic image, comprising the step of outputting an image corresponding to the image marking pixels corresponding to the high luminance component, methods who according to claim 1 or 2. The method includes the steps of recognizing a series of pixel groups composed of the plurality of pixels when pixels corresponding to the high luminance component are adjacent to each other, calculating parameters related to the recognized series of pixel groups, and outputting the parameters. Law who according to any one of to 3. A first image obtained by imaging a coal sample in a horizontal Nicol state where the angle of the polarizer with respect to the analyzer is 0 ° using an episcopic polarization microscope having an analyzer and a polarizer, and the angle of the polarizer with respect to the analyzer is 80 ° or more and 90 ° or less A storage unit that stores a second image obtained by imaging the same part as the first image in the state of
An OR operation unit that performs an OR operation on the first image and the second image, and generates a new image by the OR operation;
A monochrome image generation unit that generates a monochrome image in which the image generated by the OR operation unit is grayscaled;
An identification unit for identifying a pixel having a brightness brighter than a predetermined reference brightness value as a pixel corresponding to a high brightness component among a plurality of pixels constituting the monochrome image generated by the monochrome image generation unit; A device for identifying a high luminance component in coal. Wherein among the plurality of pixels constituting the monochromatic image, equipment of claim 5 having a marking unit for outputting an image corresponding to the image marking pixels corresponding to the high luminance component. An image group recognition unit for recognizing a series of pixel groups composed of the plurality of pixels by adjoining pixels corresponding to the high luminance component;
Equipment according to claim 5 or 6 having an output unit for outputting the calculated parameters for a set of pixel groups image group recognition unit has recognized, the.   The computer program which makes a computer perform each step which comprises the method in any one of Claims 1-4.