KR101551814B1 - Method, system and recording medium for analysing tongue diagnosis using a quantifying evalution indicator of tongue diagnosis image - Google Patents

Abstract

A system and a recording medium thereof, the method comprising the steps of: calling an image of a measurement object photographed by using a light source selected from a plurality of light sources; Extracting a first region from the first region, extracting a second region from the first region, and extracting first information for the first region and the second region, the first information for the first region and the second region, 2 information and the first area are divided into N zones (N is a natural number of 2 or more), analyzing the distribution information of each zone of the second zone, and displaying the analyzed information The subjective judgment of the observer on the stereoscopic image can be excluded as much as possible, and the convenience of subsequent medical treatment and medical record creation can be obtained.

Description

TECHNICAL FIELD [0001] The present invention relates to an image analysis method, a system, and a recording medium for quantifying an evaluation index of an observer image,

TECHNICAL FIELD The present invention relates to an analysis method, system, and recording medium thereof, and more particularly, to a method, system, and recording medium for analyzing an organic matter by quantifying an evaluation index of an organic image.

In general, tongue diagnosis is a field of Oriental medicine that diagnoses based on visual information. It is a diagnostic method that can diagnose the health condition of the testee relatively simply and inexpensively by observing the color and shape of the tongue and the color of the testee Lt; / RTI > This is a representative diagnostic method of Oriental medicine together with the pulse, and so far, it has been done by relying on visual observation of skilled oriental medicine.

The oriental doctor examines the presence, thickness, color, and wetness of the sickle first, and examines the color, shape, and activity status of the sickle in order to diagnose the patient's disease or to determine the health condition of the patient.

The material covered with moss on the tongue, called the sutae, can be examined through its color, degree of wetness, thickness, shape and extent of the sutae, and the nature of the fraud, the site of invasion, and the presence of essence.

In this way, information of the patient's tongue is important information in determining the health status of the patient. Recently, it has been found that sickle is a major cause of halitosis, and studies are being actively carried out to quantitatively evaluate some of the sickle.

However, because the diagnosis is based on the experience of oriental medicine doctors, it has a problem that it can not provide more information than the observer can grasp. In addition, since the diagnosis is based on the subjective judgment of the observer, the objective criteria for diagnosis and standardization of diagnosis are required.

In response to this demand, Chinese researchers completed the automatic identification system in the 1990s, and then produced a digital snowing analyzer to create a system that can evaluate the color, thickness, and wetness of the tongue and suture.

On the other hand, the researchers in Taiwan have also completed the computerized system, and have proposed algorithms for indirect estimation of thickness of images by Fourier transformation. In Korea, various research institutes have made the external design of the system, the design of the lighting system, and the computer analysis of the light color, and the system has been developed accordingly.

An example of a skin test through an abstract image according to the prior art is shown in FIG.

Referring to FIG. 1, first, the examinee shoots his or her opinion image through an illustrator (S1). The picked up image is displayed on a display unit provided in the picker, and the examinee examines whether the picked up image taken through the displayed picked image is photographed suitable for diagnosing the state of the tongue (S3). If it is determined that the preview image is accurately photographed, the previewer transmits the preview image photographed by the inspection server through the wired / wireless network (S5).

On the other hand, the inspector connects to the inspection server using the terminal, receives the preview image of the subject, and displays the tongue state of the subject through the received preview image. The examiner transmits the results of the examination to the examination server again, and the examinee contacts the examination server through the examination machine and receives the examination results (S7). In this case, the explorer and the terminal have a communication function to connect to the inspection server by connecting to the wired / wireless network. The received searing result is displayed on the display unit of the searched unit, and the examinee can confirm his / her health status through the searched result (S9).

Korean Patent Publication No. 10-2008-0087965 (published on October 02, 2008)

However, in the prior art including the patent documents, diagnosis is performed only through observation by the observer, so subjective judgment of the observer can be intervened, and there is a problem that objective diagnostic criteria can not be provided.

It is an object of the present invention to solve the above-mentioned problems, and it is an object of the present invention to provide an information processing apparatus and a method for processing information on color information, area information, information on distribution ratios of a suture, information on ultraviolet fluorescence state, The present invention also provides a method and system for analyzing an organic matter by quantifying an evaluation index, such as probabilistic information that can be classified into three categories.

According to another aspect of the present invention, there is provided an analysis method for quantifying an evaluation index according to the present invention, including the steps of: calling an image of a measurement object photographed using a light source selected from a plurality of light sources; Extracting a first region from the image and extracting a second region from the first region; (N is a natural number of 2 or more) of the first area, the second information different from the first information for the first area and the second area, and the first area for the first area and the second area, And analyzing distribution information of each zone of the second area; And displaying the analyzed information.

And the first region is a sulphate region.

And the second region is a speech recognition region.

Wherein the first information is at least one of first color information consisting of red, green and blue based on the RGB color model, and second color information composed of lightness, redraw, and hue based on the CIE-Lab color model.

And the second information is at least one of a total number of pixels of the first area, a total number of pixels of the second area, and an area ratio (%) of the second area with respect to the first area.

Wherein the analyzing step comprises the steps of: selecting a third region from the called image through a mouse dragging; selecting first color information consisting of red, green, and blue based on the RGB color model for the third region; And analyzing at least one of the first color information, the second color information, which is based on the brightness, the green color, and the hue.

Wherein the analyzing is based on a color value of red (R) and green (G) based on the RGB color model for the first region and an HSV color model when the called image is an image photographed using an ultraviolet light source And analyzing the third color information made up of the brightness value (V).

The analyzing step may further include the step of analyzing probability information that can be classified into a sate, a thinning, and a categorization using the first information and the second information according to a logistic regression equation.

Wherein the extracting of the first region comprises providing M control points (M is a natural number greater than or equal to 10) to the acquired image; Arranging the M adjustment points on a contour of the first area; And extracting an area surrounded by the M control points into the first area.

The extracting of the second region may include extracting a region having a value smaller than the threshold value into the second region using a threshold value according to the degree of redness.

According to another aspect of the present invention, there is provided a system for analyzing an object by quantifying an evaluation index according to the present invention. The system includes an image call unit for calling an image of a measured object using a light source selected from a plurality of light sources, A first extracting means for extracting a snowy region from the called image, a second extracting means for extracting a snowy region from the snowy region, a color analyzing means for analyzing color information on the snowy region and the snowy region, Area analyzing means for analyzing the area information on the area and the above-mentioned squeezing area, and area analyzing part for dividing the above-mentioned area into N areas (N is a natural number of 2 or more) And a display unit for displaying the color information, the area information, and the distribution ratio of each zone .

According to another aspect of the present invention, there is provided a computer-readable medium having stored thereon a program for causing a computer to execute a method of causing a computer to function as: A code for causing the computer to extract a region of snow from the invoked image; code for causing the computer to extract a region of interest from the region of interest; Code for causing the computer to analyze the area information about the snow area and the snow area; and code for causing the computer to search the snow area for N zones (where N is a natural number of 2 or more ), Codes for analyzing distribution ratios of zones in the stomach area, To display the color information, the area information, and the distribution ratio of each zone.

As described above, according to the analysis method, system, and recording medium of the present invention, which quantify the evaluation index according to the preferred embodiment of the present invention, the subjective judgment of the observer observing the preview image can be excluded as much as possible, It is possible to obtain the effect of facilitating the preparation of future medical care and medical records.

FIG. 1 is a flow chart for performing a skin test according to the prior art,
FIG. 2 is a block diagram showing an analysis system for analyzing an evaluation index according to the present invention,
FIG. 3 is a flow chart showing a method of analyzing an oily skin by quantifying an evaluation index according to the present invention,
FIG. 4 is a diagram illustrating a method of analyzing an image by using the evaluation index quantification shown in FIG. 3, a photograph called a video obtained using a visible light source,
5A to 5C are photographs showing a step of extracting a first region from among the analysis methods by the evaluation index quantification shown in FIG. 3,
FIG. 6 is a photograph showing a step of extracting a second region among the texture analysis methods through the evaluation index quantification shown in FIG. 3,
FIG. 7 is a photograph showing a step of displaying a second region distribution ratio by region in the method of analyzing an organic matter through the evaluation index quantification shown in FIG. 3;
8 is a diagram illustrating a photograph showing a result of color analysis of a third area by selecting a third area through dragging of a mouse,
9 is a photograph of a picture obtained by using an ultraviolet light source,
10 is a photograph showing fluorescence reaction analysis results of an image obtained using an ultraviolet light source.
11 is a photograph showing an analysis result report including quantified color information, area information, fluorescence response information, zone-specific information, and probability information to be classified into a background / background / background.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A method and apparatus for quantifying an evaluation index according to a preferred embodiment of the present invention will now be described in detail with reference to the accompanying drawings.

FIG. 2 is a block diagram illustrating a system for analyzing an oily skin by quantifying evaluation indexes of an olfactory image according to a preferred embodiment of the present invention. The skin analysis system according to the preferred embodiment of the present invention includes an image calling unit 200, an image analysis unit 300, and a display unit 400.

The image calling unit 200 calls an image (e.g., an image of the tongue) of a measurement object photographed using any one of the light sources selected from the plurality of light sources.

Here, it is preferable that the plurality of light sources emit light in different wavelength regions. For example, the plurality of light sources may include a light source in the visible light region, a light source in the ultraviolet region, and a light source in the infrared region. The light source may preferably be a light source using a lamp-type light source or a light emitting diode (LED), but it may be any type of light source suitable for imaging an image of the measurement object.

The region analysis unit 300 extracts necessary regions (e.g., a snowy region and a snowy region) from the called image, and analyzes color information, area information, and distribution ratio information of the extracted region so as to be quantifiable.

Preferably, the image analysis unit 300 analyzes the tongue image obtained under the visible light LED light source, the color information of the target area / area, the area information of the tongue / tongue area, and the tongue distribution map, We analyze the fluorescence intensity of the sulcus through acquired tongue images, and easily grasp the shape of the tongue of the user through the tongue images obtained under the infrared LED light source.

The image analysis unit 300 includes a first extraction unit 301, a second extraction unit 303, a color / area analysis unit 305, and a zone analysis unit 307. In addition, the image analysis unit 300 may include a region of interest analyzing unit 309, a fluorescence reaction analyzing unit 311, and a probability information analyzing unit 313.

The first extraction means 301 extracts the first region from the called image using M control points (M is a natural number, preferably M is a natural number of 10 or more). Preferably, the first region is a dermal region or a tongue region. The second extraction means 303 extracts the second region from the first region. Preferably, the second region is a speech region.

The color / area analyzing unit 305 analyzes first information (e.g., color information) and second information (e.g., area information) about the first area and the second area. Preferably, the first information is at least one of first color information composed of red, green and blue based on the RGB color model and second color information composed of lightness, redraw, and hue based on the CIE-Lab color model, 2 information is at least one of the total number of pixels of the first area, the total number of pixels of the second area, and the area ratio (%) of the second area with respect to the first area.

The analysis means 307 analyzes the distribution ratios of the second regions (e.g. As an example, the zone analyzing means 307 may analyze the distribution ratio of the gesture region of each zone after dividing the first zone (e.g., the snowy zone) into a plurality of zones.

The region of interest analyzing means 309 analyzes the color information of the third region selected from the tongue image or the skin image by dragging the mouse. Preferably, the third region is a region of interest in which the user wishes to analyze the color information.

The fluorescence response analyzing unit 311 analyzes the fluorescence of the red (R) color image based on the RGB color model for the first region (for example, the skin region) when the image called by the image calling unit 200 is an image photographed using the ultraviolet light source. ) And green (G) color information and a brightness value (V) based on the HSV color model.

Alternatively, or in addition, the fluorescence response analyzing means 311 may be configured to determine whether the image called by the image calling unit 200 is an image photographed using an ultraviolet light source, the RGB color of the first region (for example, It is possible to analyze the fourth color information including the color information of red (R) and green (G) based on the model and the brightness value based on the HSL color model.

The difference between the HSV color model and the HSL color model is well known to those skilled in the art, and a detailed description thereof will be omitted here.

The fluorescence reaction analyzing means 311 can effectively separate the sulcus region and the sulcus region by using fluorescence properties of various microorganisms present in the spermatozoa even if the color of the sperm is pale or the spermatogenesis is discolored or discolored.

The probability information analyzing unit 313 analyzes the probability information that can be classified into the sate, the thinning, and the sate using the color information and the area information according to the logistic regression equation.

The display unit 400 displays the color information of the skin / stomach area analyzed by the image analysis unit 300, the area information of the skin / stomach area, the distribution ratio of the stomach area, the area color of interest, And at least one of the probability information that can be classified into the pattern / pattern.

FIG. 3 is a flow chart illustrating an analysis method of an evaluation index by quantification of an evaluation index according to the present invention, FIG. 4 is a photograph of an image obtained by using a visible light source among the analysis method shown in FIG. 3, FIG. 5C is a photograph showing a step of extracting a first region of the skinning analysis method shown in FIG. 3, FIG. 6 is a photograph showing a step of extracting a second region of the skinning analysis method shown in FIG. 3, 3 is a photograph showing a step of analyzing and displaying the distribution ratios of the second regions of the dissection analysis method shown in FIG.

The method of analyzing an object by quantifying an evaluation index according to a preferred embodiment of the present invention includes the steps of: calling an image of a measurement object (S30); extracting a first region (S31); extracting a second region from the first region (S32), analyzing and displaying the first information for the first area and the second area (S33), analyzing and displaying the second information different from the first information for the first area and the second area And dividing the first area into N zones (N is a natural number of 2 or more), and analyzing and displaying the distribution ratios of the zones in the second zone (S35).

In the step S30 of calling an image of the measurement object, the image of the measurement object photographed using one of the light sources selected from the plurality of light sources is called.

As described above, the plurality of light sources may include a light source in the visible light region, a light source in the ultraviolet region, and a light source in the infrared region. Such a light source may be a light source using a lamp-shaped light source or a light emitting diode (LED), but it may be any type of light source suitable for imaging an image of a measurement object.

As an example, FIG. 4 is a photograph of an image photographed using a visible light source. Referring to FIG. 4, when the user clicks the open button 401, an image (for example, a tongue image) called by the image calling unit 200 is displayed on the image window 403.

Hereinafter, the tongue image photographed using the visible light source will be described on the basis of the tongue image, but it goes without saying that the following technique can also be applied to the tongue image photographed using the ultraviolet or infrared light source.

The step S31 of extracting the first region extracts the first region from the called image using M control points (M is a natural number, preferably M is a natural number of 10 or more). Preferably, the first region is a dermal region or a tongue region.

5A to 5C, when the user clicks the outline extraction button 501, the first extraction means 301 displays M control points 505, preferably 17 control points, on the called image do. Then, as shown in FIG. 5B, the M control points 505 are arranged on the outline of the first area (for example, a snowy area) by drag-and-drop using the mouse and then the first area is set do. When the setting of the first area is completed, as shown in FIG. 5C, the first extracting unit 301 extracts the first area 507 by blackening the background excluding the inside of the selected first area.

That is, the user can directly set and extract the SURFACE area 505 by manipulating M control points directly, which can reduce the uncertainty that may occur when automatically extracting the SURFACE area.

The step of extracting the second area (S32) is a step of extracting a second area (e.g., a stomach area) from the first area (e.g., a snowy area). 6, when the user clicks on the tongue extraction button 601 and moves the threshold value adjustment bar 603, the second extraction unit 303 extracts the tongue area corresponding to the adjusted threshold value.

In general, the color of the stomach is white, yellow, dark yellow, etc., while the color of the stomach is red or light blue. Therefore, after extracting the region of the tongue from the tongue image obtained using the visible light source, a value smaller than the corresponding threshold value can be extracted as the tongue region using the threshold value according to the redness and greenness of the image.

The steps (S33, S34, S35) of analyzing and displaying the distribution ratios of the second areas for the first information and the second information for the first area and the second area, respectively, The color information and the area information of the second area (for example, the rendering area) are calculated and quantified, and then the quantified data is displayed on the screen.

Preferably, the first information is at least one of first color information composed of red, green and blue based on the RGB color model and second color information composed of lightness, redraw, and hue based on the CIE-Lab color model, 2 information is at least one of the total number of pixels of the first area, the total number of pixels of the second area, and the area ratio (%) of the second area with respect to the first area.

7, when the user clicks on the color area result button 701, the color / area analyzing unit 305 and the zone analyzing unit 307 calculate the color information, the area information, And the display unit 400 displays the color analysis result window 703, the area analysis result window 705, and the searched area distribution window 707, respectively.

For example, the color / area analyzing unit 305 analyzes the R, G, and B color values based on the RGB color model for the snowy region and the snowy region as a color analysis result, and then transmits the color values to the display unit 400. Additionally or alternatively, the color / area analyzing means 305 may analyze the brightness, the green color, and the hue degree color information based on the CIE-Lab color model for the snowy region and the snowy region, .

As is known to those having ordinary skill in the art, the RGB color model is a method of representing colors consisting of three primary colors of light, red (R), green (G), and blue (B) Is a color system redefined in 1976 by the international standard color measuring instrument called CIE. In Lab color, L means luminosity which is brightness. A combination is complementary color from green to red, and b combination means complementary color from yellow to blue. do.

The method for analyzing the color of the evaluation index according to the preferred embodiment of the present invention quantitatively provides not only color information based on the RGB color model but also color information based on the CIE-Lab color model do. Such a CIE-Lab color model can effectively remove the highlight of an image caused by the surrounding environment.

In addition, the color / area analyzing unit 305 quantitatively analyzes the area ratio of the screening area to the area of the screening area and the screening area as a result of the area analysis, and transmits the analysis result to the display unit 400. For example, the area of the sulcus area and the sulcus area can be calculated as the total number of pixels of each area, and the area ratio can be calculated as the total number of pixels of the sulcus area with respect to the total number of pixels of the sulium area.

In addition, the zone analyzing means 307 divides the snowy region into a plurality of zones by analyzing the distribution ratios of the snowy regions in each zone, and then transmits the analyzed results to the display unit 400. FIG. For example, as shown in FIG. 7, the number of pixels in the area of each area for each number of pixels in the snowy region (or tongue region) for each zone is divided into six zones, Can be calculated and displayed.

In addition, the method for analyzing an indicator by quantifying an evaluation index according to a preferred embodiment of the present invention may further include the step of selecting a third region through dragging of a mouse and analyzing and displaying color information of the third region. Preferably, the third region is a region of interest in which the user wishes to analyze the color information.

8 is a photograph showing a result of color analysis of the third region by selecting a third region through dragging of the mouse.

Referring to FIG. 8, in order to obtain color information for a specific region of a tongue image called by the image calling unit 200, when the user selects a desired region through dragging the mouse, Green color, and hue degree color information based on the R, G, and B color values and / or the CIE-Lab color model based on the RGB color model of the region of interest 805 as a color analysis result, Can display it on the area of interest window 803.

In addition, the user can also drag and select a desired region in the extracted image of only the snowy region (or tongue region) shown in FIG. 7, and then confirm the color information of the selected region of interest.

In addition, the method of analyzing an indicator by quantifying the evaluation index according to a preferred embodiment of the present invention may further include analyzing and displaying the fluorescence response of the tongue image.

FIG. 9 is a photograph of an image photographed using an ultraviolet light source, and FIG. 10 is a photograph showing a result of fluorescence analysis of an image photographed using an ultraviolet light source.

9 and 10, the image calling unit 200 calls up a tongue image photographed under an ultraviolet light source and displays the tongue image on the image window 903.

Next, as described above, the first extracting unit 301 of the image analyzing unit 300 extracts only the skin region or the tongue region from the called tongue image using the M control points. When the user clicks the fluorescence analysis result button 1001, the fluorescence analyzing unit 311 of the image analyzing unit 300 analyzes the fluorescence reaction of the called image, and the display unit 400 displays the analysis result And displays it on the result screen window 1003. Preferably, the fluorescence response analysis screen window 1003 displays color values of red (R) and green (G) based on the RGB color model for the snowy region or the tongue region, and a brightness value (V) based on the HSV color model The resulting color value is displayed.

FIG. 11 is a photograph showing an analysis result report including quantified color information, area information, fluorescence response information, zone information, and probability information that can be classified as background / background / background.

11, when the user clicks on a result report button (not shown), the display unit 400 displays the analysis result through a separate window 1101. FIG. The additional window 1101 may include patient information including, for example, a name, gender, age, and the like entered through an input unit (not shown). The color information analyzed by the image analysis unit 300 Results, area analysis, fluorescence response, distribution of spermatozoa, and gingival findings may be included.

As an example, the probability information analyzing unit 313 calculates probability information that can be classified into the shape / shape / shape using the color information and the area information of the snow / shine region according to the logistic regression equation Thereafter, the display unit 400 displays the text in the separate window 1101 as a text. As shown in Fig. 11, the probability of the patient to be classified as a child is 2.34%, the probability of being classified as a parent is 88.51%, and the probability of classification as a parent is 9.15%.

Meanwhile, the present invention can be realized by storing computer-readable codes in a computer-readable storage medium. The computer-readable storage medium includes all kinds of storage devices in which data that can be read by a computer system is stored.

The computer readable code is configured to perform steps that, when read and executed by a processor (e.g., CPU / DSP 170a) from the computer readable storage medium, implement a method of quantifying an indicator metric in accordance with the present invention do. The computer readable code may be implemented in a variety of programming languages. And functional programs, codes, and code segments for implementing embodiments of the present invention may be readily programmed by those skilled in the art to which the present invention pertains.

Examples of computer-readable storage media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, and the like, as well as implementations in the form of carrier waves (e.g., transmission over the Internet). In addition, the computer-readable storage medium may be distributed over a networked computer system so that computer readable code is stored and executed in a distributed fashion.

Although the present invention has been described in detail with reference to the above embodiments, it is needless to say that the present invention is not limited to the above-described embodiments, and various modifications may be made without departing from the spirit of the present invention.

200: image calling unit 300: image analysis unit
400:

Claims (19)

Calling an image of a photographed measurement object using any one of a plurality of light sources;
Extracting a first region from the called image;
Extracting a second region from the first region;
(N is a natural number of 2 or more) of the first area, the second information different from the first information for the first area and the second area, and the first area for the first area and the second area, And analyzing distribution information of each zone of the second area; And
And displaying the analyzed information,
The step of extracting the first region
Providing M extracted image points with M control points (M is a natural number greater than or equal to 10);
Arranging the M adjustment points on a contour of the first area; And
And extracting an area surrounded by the M control points into the first area. 2. The method of claim 1,
Wherein the method comprises the steps of: The method of claim 1, wherein the second region
Wherein the method comprises the steps of: 4. The method according to any one of claims 1 to 3, wherein the first information
Wherein the first color information is composed of red, green, and blue based on the RGB color model, and the second color information is based on the CIE-Lab color model, and the second color information is composed of lightness, redness, and hue. 4. The method according to any one of claims 1 to 3, wherein the second information
The total number of pixels of the first area, the total number of pixels of the second area, and the area ratio (%) of the second area with respect to the first area. 4. The method according to any one of claims 1 to 3,
A third region is selected from the called image through a mouse drag, and first color information including red, green, and blue based on the RGB color model for the third region, brightness based on the CIE-Lab color model, And second color information made up of hues. ≪ Desc / Clms Page number 20 > 4. The method according to any one of claims 1 to 3,
If the called image is an image photographed using an ultraviolet light source, a color value of red (R) and green (G) based on the RGB color model for the first region and a brightness value (V) based on the HSV color model, And analyzing the third color information made up of the first color information and the second color information. 4. The method according to any one of claims 1 to 3,
Further comprising the step of analyzing probability information that can be classified into a sate, a thinning, and a categorization using the first information and the second information according to a logistic regression equation. delete 4. The method of any one of claims 1 to 3, wherein extracting the second region
And extracting a region having a value smaller than the threshold value into the second region using a threshold value according to the degree of redness and greenness. An image calling unit for calling an image of a measured object using one of the plurality of light sources;
First extraction means for arranging a contour on the called image using M control points (M is a natural number equal to or greater than 10), and extracting a snowy region from an area surrounded by the M control points, A color analyzing means for analyzing color information on the skin region and the screening region, an area analyzing means for analyzing area information on the skin region and the screening region, (N is a natural number equal to or greater than 2), and analyzing the distribution ratio (%) of the searched area by the area;
And a display unit for displaying the color information, the area information, and the distribution ratio of each zone. 12. The method of claim 11,
Wherein the first color information is composed of red, green, and blue based on the RGB color model, and the second color information is composed of the lightness, the green color, and the hue based on the CIE-Lab color model. 12. The method according to claim 11,
The total number of pixels of the skin area, the total number of pixels of the skin area, and the area ratio (%) of the skin area with respect to the skin area. 14. The image processing apparatus according to any one of claims 11 to 13,
When the image called by the image calling unit is an image photographed using an ultraviolet light source, the color values of red (R) and green (G) based on the RGB color model for the snowy region, and the brightness based on the HSV color model Further comprising fluorescence reaction analysis means for analyzing third color information made up of the value (V)
Wherein the display unit further displays the third color information. 14. The image processing apparatus according to any one of claims 11 to 13,
If the image called by the image calling unit is an image photographed using an ultraviolet light source, the color values of red (R) and green (G) based on the RGB color model for the snowy region, Further comprising a fluorescence reaction analyzing means for analyzing the fourth color information made up of the value (L)
Wherein the display unit further displays the fourth color information. 14. The image processing apparatus according to any one of claims 11 to 13,
Further comprising probability information analyzing means for calculating probability information that can be classified into a sate, a thinning, and a tile using the color information and the area information according to a logistic regression equation,
Wherein the display unit further displays the probability information.








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