CN112614095B - Method and system for analyzing liver meridian energy based on image processing - Google Patents
Method and system for analyzing liver meridian energy based on image processing Download PDFInfo
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Abstract
The invention discloses a method and a system for analyzing liver meridian energy based on image processing, and belongs to the technical field of image analysis and processing. The method comprises the following steps: acquiring five-finger GDV images of a plurality of targets before/after the intervention on the liver; determining the energy value of five fingers before/after a plurality of target liver interventions; determining a person correlation coefficient according to the five-finger energy values, and determining that the five-finger energy values before/after the intervention of a plurality of target livers have correlation according to the person correlation coefficient; determining the same change area in the five-finger gray scale map according to the change; dividing the change area into regions every 5 degrees by taking the direction of the finger as a reference to obtain energy values before/after intervention of each interval; and selecting at least 8 groups of interval energy difference data to perform interval calculation, obtaining a larger energy value of a common interval, summing the energy values of the common interval, and determining the liver channel energy value. The invention accords with the meridian theory of traditional Chinese medicine, and the obtained data can be used for the health management of the target.
Description
Technical Field
The present invention relates to the field of image analysis and processing technologies, and in particular, to a method and a system for analyzing liver meridian energy based on image processing.
Background
The health detection method based on the human body discharge image is characterized in that the discharge image is formed according to the human body energy, and the indexes of the human body energy, the bilateral symmetry, the twelve meridian energies and the like can be deduced by combining the traditional Chinese medicine theory with the computer technologies such as image processing, data analysis and the like. At present, the popular human health detection method in China can be roughly divided into substance detection and information detection, wherein the substance detection comprises biological indexes such as blood pressure, blood sugar, heart rate and the like; information detection comprises indexes such as human body pressure, emotion and sleep quality, and a detection method based on human body energy is not widely applied to China at present.
The formation of human discharge images originated at the end of the 19 th century, and 1500 "electric photographs" of human fingers, plant leaves, grains, etc. were taken by one of the Russian scientists Jacob Narkevich-Yodko who developed their own original techniques. In the beginning of the 20 th century, the Suzhou Electrical Engineer Semyo Kirlian and his wife Valentina invented Kirlian photography after observing a patient who received high frequency generator therapy at a hospital in Classnodar, which photographed different emotional states of the person to produce different halos. With a subsequent series of studies, in 1995, professor Korotkov invented the first GDV camera, which could be shown directly on a computer screen. Its basic principle is still the kirian effect, with an overall assessment of human health by measuring the energy of each finger separately.
Disclosure of Invention
In order to solve the above problems, the present invention provides a method for analyzing liver meridian energy based on image processing, comprising:
acquiring five-finger GDV images of a plurality of targets before/after the intervention on the liver;
denoising and graying the five-finger GDV image to obtain a five-finger grayed image, and determining five-finger energy values before/after intervention of a plurality of target livers according to the five-finger grayed image;
determining a person correlation coefficient according to the five-finger energy values, and determining that the five-finger energy values before/after the intervention of a plurality of target livers have correlation according to the person correlation coefficient;
processing the five-finger energy values before/after intervention of a plurality of target livers with correlation, determining the change of the five-finger energy values before/after intervention, and determining the same change area in the five-finger gray-scale map according to the change;
dividing the change area into regions every 5 degrees by taking the direction of the finger as a reference to obtain energy values before/after intervention of each interval;
and selecting at least 8 groups of interval energy difference data to perform interval calculation, obtaining a larger energy value of a common interval, summing the energy values of the common interval, and determining the liver channel energy value.
Optionally, the five fingers include the left and right hand five fingers.
Optionally, the change area is selected for the middle finger of the left hand and the right hand.
Optionally, when the correlation coefficient is greater than or equal to 0.7, the five-finger energy values before/after the intervention of the target liver have correlation.
Optionally, when at least 8 groups of intervals are selected, the intervals are selected according to the fluctuation of energy in the intervals.
The invention also provides a system for analyzing the liver meridian energy based on image processing, which comprises:
the acquisition unit is used for acquiring five-finger GDV images of a plurality of targets before/after the intervention on the liver;
the preprocessing unit is used for carrying out denoising and graying processing on the five-finger GDV image to obtain a five-finger grayed image, and determining five-finger energy values before/after intervention of a plurality of target livers according to the five-finger grayed image;
the correlation analysis unit is used for determining a person correlation coefficient according to the five-finger energy values and determining that the five-finger energy values before/after the intervention of the target livers have correlation according to the person correlation coefficient;
the processing unit is used for processing the five-finger energy values before/after intervention of a plurality of target livers with correlation, determining the change of the five-finger energy values before/after intervention, and determining the same change area in the five-finger gray scale map according to the change;
the partitioning unit is used for partitioning the change area by every 5 degrees by taking the finger direction as a reference to acquire the energy value before/after the intervention of each interval;
and the analysis unit selects at least 8 groups of interval energy difference value data to perform interval calculation, obtains a larger energy value of a common interval, sums the energy values of the common interval and determines the liver channel energy value.
Optionally, the five fingers include the left and right hand five fingers.
Optionally, the change area is selected for the middle fingers of the left and right hands.
Optionally, when the correlation coefficient is greater than or equal to 0.7, the five-finger energy values before/after the intervention of the target liver have correlation.
Optionally, when at least 8 groups of intervals are selected, the intervals are selected according to the fluctuation of energy in the intervals.
The invention accords with the meridian theory of traditional Chinese medicine, and the obtained data can be used for the health management of the target.
Drawings
FIG. 1 is a flow chart of a method for analyzing liver meridian energy based on image processing according to the present invention;
FIG. 2 is a five-finger primitive diagram of the acquisition of the method for analyzing liver meridian energy based on image processing of the present invention;
FIG. 3 is a denoised image of a five-finger primitive image HSV channel denoised by the method for analyzing the liver meridian energy based on image processing;
FIG. 4 is a de-noised image converted into RGB image according to the method for analyzing liver meridian energy based on image processing of the present invention;
FIG. 5 is a finger denoising image of a five-finger original image of a method for analyzing liver meridian energy based on image processing;
FIG. 6 is a gray scale of a five-finger original image of a method for analyzing liver meridian energy based on image processing according to the present invention;
FIG. 7 is a left-hand sectional view of a method for analyzing liver meridian energy based on image processing according to the present invention;
FIG. 8 is a right-hand, partitioned graph of a method for analyzing liver meridian energy based on image processing according to the present invention;
FIG. 9 is a block diagram of a system for analyzing energy of the liver meridian based on image processing according to the present invention.
Detailed Description
Example embodiments of the present invention will now be described with reference to the accompanying drawings, however, the invention may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, which are provided for a complete and complete disclosure of the invention and to fully convey the scope of the invention to those skilled in the art. The terms used in the exemplary embodiments shown in the drawings are not intended to limit the present invention. In the drawings, the same units/elements are denoted by the same reference numerals.
Unless otherwise defined, terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Further, it will be understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense.
The invention provides a method for analyzing liver meridian energy based on image processing, which comprises the following steps of:
acquiring five-finger GDV images of a plurality of targets before/after the intervention on the liver;
denoising and graying the five-finger GDV image to obtain a five-finger grayed image, and determining five-finger energy values before/after intervention of a plurality of target livers according to the five-finger grayed image;
determining a person correlation coefficient according to the five-finger energy values, and determining that the five-finger energy values before/after the intervention of a plurality of target livers have correlation according to the person correlation coefficient;
processing the five-finger energy values before/after intervention of a plurality of target livers with correlation, determining the change of the five-finger energy values before/after intervention, and determining the same change area in the five-finger gray scale map according to the change;
dividing the change area into regions every 5 degrees by taking the direction of the finger as a reference to obtain energy values before/after intervention of each interval;
and selecting at least 8 groups of interval energy difference data to perform interval calculation, obtaining a larger energy value of a common interval, summing the energy values of the common interval, and determining the liver channel energy value.
Wherein the five fingers comprise the five fingers of the left hand and the right hand.
Wherein the change area is selected for the middle fingers of the left hand and the right hand.
When the correlation coefficient is greater than or equal to 0.7, the five-finger energy values before/after the intervention of the target livers have correlation.
Wherein, when at least 8 groups of intervals are selected, the intervals are selected according to the fluctuation of energy in the intervals.
The invention is further illustrated by the following examples:
as shown in fig. 2, the acquired GDV image has a bias of background color due to instrument light leakage and automatic white balance, and there are many noises, and the image is denoised in two steps:
firstly, carrying out aperture denoising;
in order to remove the interference of aperture and the like of an image caused by light leakage of equipment without influencing the original finger position image, the HSV color space is considered, and because the aperture color is yellow, the finger image is purple, and the hue (H) in the HSV space can well distinguish the two colors:
firstly, converting an original GDV image into an HSV color space;
denoising by changing the pixel value of the channel H smaller than a certain threshold value into a background, wherein the denoised pixel value is shown in FIG. 3;
then, converting the denoised HSV image into an RGB image as shown in figure 4;
secondly, denoising the finger image;
as shown in fig. 2 and 4, a finger portion generates a severe shadow effect due to the imprecise device shading mask, and we observe that the finger portion of the GDV image is bluish, so we remove noise and retain information of the finger portion after denoising in a manner of changing pixels of which blue channel B pixel values are smaller than a certain threshold value into a background, as shown in fig. 5.
Graying the image denoised as shown in fig. 5 can be directly executed by using an opencv function cvtColor, and the image denoised as shown in fig. 6 is completed;
in this embodiment, five-finger GDV images of four subjects before and after intervention are obtained, denoising and graying are performed according to the above method, and energy values of five fingers of the left hand and the right hand are obtained, and in order to analyze that the obtained finger GDV data can reflect liver meridian conditions, the following analysis is performed:
determining the correlation of data before and after liver meridian intervention;
we collected five finger images of four subjects before and after intervention, and calculated the energy of the ten fingers and the corresponding person correlation coefficient, and it can be seen that the correlation coefficients are all substantially greater than or equal to 0.7, and it can be seen that the energy data before and after intervention has strong correlation, and the correlation coefficient is shown in table 1:
TABLE 1
Calculating energy reduction change after intervention;
the energy values of each group of subjects before and after two interventions are averaged, and according to traditional Chinese medicine data, the human middle finger is related to the liver channel, so that the human middle finger is mainly concerned with the middle finger of the left hand and the middle finger of the right hand, and as can be seen from table 2, the four groups of experimental dry prognosis is obviously reduced compared with the energy values before the interventions, so that the two-hand middle finger condition is mainly considered, and table 2 is as follows:
TABLE 2
Finding the same change area according to experimenters' data, finding certain area energy of middle finger can reflect the condition of human liver meridian, so we find the common area with large energy fluctuation according to the middle finger energy data of four groups of experiments, which is as follows:
the finger direction is taken as a reference, and the division is performed every 5 degrees, and the division is totally divided into 720 cells. And then calculating the energy values before and after the intervention in each cell.
The obtained 8 groups of inter-cell energy difference data are subjected to interval calculation, a certain fluctuation of the data can be seen according to the energy difference before and after the first intervention of the subject A, an interval with larger fluctuation is required to be found, firstly, a plurality of maximum values of the data are calculated, the average number a of the maximum values is taken, the maximum value points smaller than the average number a are removed, a common interval with larger fluctuation of 8 groups of data is obtained and is used as a finger interval capable of reflecting the liver meridian, and the common interval is calculated to obtain [145,148], [168,184], [197,212] [569,576], and the result is shown in fig. 7 and 8, the left hand is shown in fig. 7, the right hand is shown in fig. 8, the area between two red lines is the obtained partition area, and the liver meridian can be obtained by energy summation of the intervals.
The present invention further provides a system 200 for analyzing liver meridian energy based on image processing, as shown in fig. 9, including:
an acquisition unit 201 that acquires five-finger GDV images of a plurality of targets before/after intervention on the liver;
the preprocessing unit 202 is used for denoising and graying the five-finger GDV image to obtain a five-finger grayed image, and determining five-finger energy values before/after intervention of a plurality of target livers according to the five-finger grayed image;
the correlation analysis unit 203 determines a person correlation coefficient according to the five-finger energy values, and determines that the five-finger energy values before/after the intervention of the target livers have correlation according to the person correlation coefficient;
the processing unit 204 is used for processing the five-finger energy values before/after intervention of a plurality of target livers with correlation, determining the change of the five-finger energy values before/after intervention, and determining the same change area in the five-finger gray scale map according to the change;
the partitioning unit 205 is configured to partition the change area every 5 degrees with the finger direction as a reference, and obtain an energy value before/after intervention in each interval;
the analysis unit 206 selects at least 8 groups of interval energy difference data to perform interval calculation, obtains a larger energy value of a common interval, sums the energy values of the common interval, and determines the liver meridian energy value.
Wherein the five fingers comprise five fingers of left and right hands.
Wherein the change area is selected for the middle fingers of the left and right hands.
When the correlation coefficient is greater than or equal to 0.7, the five-finger energy values before/after the intervention of the target livers have correlation.
Wherein, when at least 8 groups of intervals are selected, the intervals are selected according to the fluctuation of energy in the intervals.
The invention accords with the traditional Chinese medicine meridian theory, and the obtained data can be used for the health management of the target.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein. The solution in the embodiment of the present application may be implemented by using various computer languages, for example, object-oriented programming language Java and transliteration scripting language JavaScript, etc.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While the preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the spirit and scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations as well.
Claims (6)
1. A method of analyzing liver meridian energy based on image processing, the method comprising:
acquiring five-finger GDV images of a plurality of targets before/after the intervention on the liver;
denoising and graying the five-finger GDV image to obtain a five-finger grayed image, and determining five-finger energy values before/after intervention of a plurality of target livers according to the five-finger grayed image;
determining a person correlation coefficient according to the five-finger energy values, and determining that the five-finger energy values before/after the intervention of a plurality of target livers have correlation according to the person correlation coefficient;
processing the five-finger energy values before/after intervention of a plurality of target livers with correlation, determining the change of the five-finger energy values before/after intervention, and determining the same change area in the five-finger gray-scale map according to the change;
dividing the change area into regions every 5 degrees by taking the direction of the finger as a reference to obtain energy values before/after intervention of each interval;
selecting at least 8 groups of interval energy difference value data to perform interval calculation, obtaining a larger energy value of a common interval, summing the energy values of the common interval, and determining a liver channel energy value;
the five fingers comprise left and right hand five fingers;
the change area is selected for the middle fingers of the left hand and the right hand.
2. The method of claim 1, wherein the correlation coefficient is greater than or equal to 0.7, and the five-finger energy values before/after the target liver intervention are correlated.
3. The method of claim 1, wherein the selection of at least 8 intervals is based on energy fluctuations within the interval.
4. A system for analyzing liver meridian energy based on image processing, the system comprising:
the acquisition unit is used for acquiring five-finger GDV images of a plurality of targets before/after the intervention of the liver;
the preprocessing unit is used for carrying out denoising and graying processing on the five-finger GDV image to obtain a five-finger grayed image, and determining five-finger energy values before/after intervention of a plurality of target livers according to the five-finger grayed image;
the correlation analysis unit is used for determining a person correlation coefficient according to the five-finger energy values and determining that the five-finger energy values before/after the intervention of the target livers have correlation according to the person correlation coefficient;
the processing unit is used for processing the five-finger energy values before/after intervention of a plurality of target livers with correlation, determining the change of the five-finger energy values before/after intervention, and determining the same change area in the five-finger gray scale map according to the change;
the partitioning unit is used for partitioning the change area at every 5 degrees by taking the finger direction as a reference to acquire the energy value before/after the intervention in each interval;
the analysis unit selects at least 8 groups of interval energy difference data to perform interval calculation, obtains a larger energy value of a common interval, sums the energy values of the common interval and determines a liver meridian energy value;
the five fingers comprise left and right hand five fingers;
the change area is selected for the middle fingers of the left hand and the right hand.
5. The system of claim 4, wherein the correlation coefficient is greater than or equal to 0.7, wherein the five finger energy values before/after the target liver intervention are correlated.
6. The system of claim 4, wherein the selection of at least 8 intervals is based on energy fluctuations within the interval.
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