KR102136094B1 - Method of measuring intraocular pressure using Moire pattern - Google Patents

Abstract

According to one aspect of the present invention, a method of measuring intraocular pressure using a moiré pattern is provided. According to an embodiment of the present invention, a method for measuring intraocular pressure using the moiré pattern includes (a) a first lens having a first pattern and a second lens having a second pattern overlapping each other. Obtaining image information; (b) deriving a gradient vector graph from the acquired image information; And (c) inferring intraocular pressure by comparing the information of the derived gradient vector graph with a previously stored DB, wherein the DB is the information of the gradient vector graph that is changed according to a predetermined range of intraocular pressure. It may be configured.

Description

Method of measuring intraocular pressure using Moire pattern

The present invention relates to a method of analyzing a change in a moire pattern corresponding to a change in intraocular pressure, and measuring intraocular pressure therefrom.

In general, intraocular pressure is an important factor in diagnosing glaucoma, but the method of measuring intraocular pressure in a comprehensive examination is measured by a one-time intraocular pressure measurement method. However, if the intraocular pressure is high, the intraocular pressure fluctuates depending on the timing of measurement, so it is subject to re-measurement or, in severe cases, hospitalization to monitor fluctuations in intraocular pressure. Therefore, a technique for continuously measuring while monitoring intraocular pressure is needed. Accordingly, a method of measuring the intraocular pressure using a contact lens has been proposed to continuously monitor the intraocular pressure non-invasively, but there is a method of inserting a sensor into the contact lens, but the reader is relatively large, making it difficult for the patient to live in daily life.

The present invention is to solve the above problems, a series of image processing steps of acquiring an image of a moire pattern generated when two or more lenses having a predetermined pattern are overlapped, and processing and analyzing the acquired image information The object of the present invention is to provide a method of finally deriving the intraocular pressure of the user. However, these problems are exemplary, and the scope of the present invention is not limited thereby.

According to one aspect of the present invention, a method of measuring intraocular pressure using a moiré pattern is provided.

According to an embodiment of the present invention, a method for measuring intraocular pressure using the moiré pattern includes: (a) a first lens having a first pattern and a second lens having a second pattern overlapping each other; Obtaining image information; (b) deriving a gradient vector graph from the acquired image information; And (c) inferring intraocular pressure by comparing the information of the derived gradient vector graph with a previously stored DB, wherein the DB is the information of the gradient vector graph that is changed according to a predetermined range of intraocular pressure. It may be configured.

According to another embodiment of the present invention, a method for measuring intraocular pressure using a moire pattern includes: (a) an image of a moire pattern generated by overlapping a first lens having a first pattern and a second lens having a second pattern. Obtaining information; (b) deriving a gradient vector graph from the acquired image information; And (c) deriving a slope period graph including frequency peak information from the slope vector graph. (d) deriving first frequency peak information corresponding to the moire pattern among frequency peak information included in the slope period graph; And (e) comparing the first frequency peak information derived in step (d) with a pre-stored DB to infer the intraocular pressure corresponding to the frequency peak information, wherein the DB is measured in advance and It may be composed of the first frequency peak information that changes depending on the intraocular pressure.

According to one embodiment of the present invention made as described above, it is possible to easily and simply measure the intraocular pressure of the user by acquiring the moire pattern as an image and processing it. Of course, the scope of the present invention is not limited by these effects.

1 and 2 are flow charts showing step-by-step analysis methods using a moiré pattern according to a first embodiment of the present invention and reference drawings for each step.
3 is a top view exemplarily showing a shape of a first lens or a second lens constituting the lens set for detecting intraocular pressure.
4 is a view showing a change in the moiré pattern according to pressure.
5 is a graph illustrating a gradient vector graph according to pressure and a gradient vector value at a specific angle depending on pressure.
6 and 7 are flow charts and step-by-step reference drawings showing the intraocular pressure analysis method using a moiré pattern according to a second embodiment of the present invention.
8 is a flowchart illustrating detailed steps constituting the processing step (step S340).
9 shows an apparatus for performing a first experimental example of the present invention.
10 is a view showing the results obtained step by step when performing the first experimental example of the present invention.
11 is a graph showing peak information of harmony frequency 3 according to pressure derived from a slope period graph derived by the first experimental example of the present invention.
12 shows an apparatus for performing a second experimental example of the present invention.
13 is a graph showing peak information of harmony frequency 3 according to pressure derived from a slope period graph derived by a second experimental example of the present invention.
14 is a graph showing peak information of harmony frequency 3 according to pressure derived from a slope period graph derived by a third experimental example of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below, but can be implemented in various different forms, and the following embodiments make the disclosure of the present invention complete, and the scope of the invention to those skilled in the art It is provided to inform you completely. In addition, for convenience of description, in the drawings, the size of components may be exaggerated or reduced.

1 and 2 show a flow chart and step-by-step reference drawings showing the intraocular pressure analysis method using the moiré pattern according to the first embodiment of the present invention.

First, a set of lenses for detecting intraocular pressure is prepared for intraocular pressure measurement. The intraocular pressure sensing lens may overlap the first lens and the second lens on which a predetermined pattern is formed. In the state in which the first lens on which the first pattern is formed and the second lens on which the second pattern is formed are superimposed, various moiré patterns of various types appear due to interference between the first pattern and the second pattern. The moiré pattern means a pattern that is visually created by interference between patterns when a pattern having a repeating pattern is overlapped several times.

3 is a top view exemplarily showing a shape of a first lens or a second lens constituting the lens set for detecting intraocular pressure. As shown in FIG. 3, the intraocular pressure sensing lens 10 includes a body 1 convexly formed in the shape of an eyeball and an alignment mark 2 formed on at least one side of the body 1 and a reference pattern. A first pattern 3 formed on the body 1 may be included in a circular pattern having the same cycle covering the eye so that the intraocular pressure can be calculated by comparative analysis. The lens 10 may be formed of the same shape or material as a contact lens that a user generally uses for vision correction, and an alignment mark 2 displayed on one side for alignment with the contact lens may be formed.

Referring to FIG. 1, image information of a moire pattern formed on the eye pressure sensing lens set is obtained from an eyeball wearing the above-described eye pressure sensing lens set (step S100). The image information is acquired by the image acquisition device. The image acquisition device may be a camera capable of photographing a moire pattern, and may be a smartphone, an image camera, or other imaging device. FIG. 2(a) shows a photograph of a lens set for detecting intraocular pressure applied with a predetermined pressure with a camera. In addition, the results of observing how the shape of the moiré pattern changes according to the pressure of 0, 10, 20, and 30 mmHg in the above-described lens set for intraocular pressure detection in FIG.

Optionally, the image information of the obtained moiré pattern may be processed using an image editing program to remove unnecessary information and secure meaningful data to increase the accuracy and reliability of the results. 2(b) shows the result of the image processing.

Next, a gradient vector graph (Histogram of oriented Gradients, HOG) is derived using the obtained moire pattern image information (step S110). The gradient vector graph indicates the magnitude and direction (or angle) of brightness for a specific area as histogram information, and is applied to the shape recognition field of an object. In addition, it is very useful for analyzing moiré pattern images because it has advantages in area and geometric processing by using histogram information on vectors. In this embodiment, the cell and block sizes are set to 8×8 and 4×4, respectively. The correlation between the pressure and the specific direction component cell is directly related to the calculation of the histogram. The histogram of the cell is calculated by adding the weight to the size of the direction. The difference in the surrounding pixel values has a characteristic that varies depending on the change in illumination, so a normalization process is essential. The gradient vector graph can be viewed as a normalized vector as a histogram of blocks. In order to implement a local normalization process, a block composed of cells of arbitrary size was constructed. 2C shows a gradient vector graph derived from a moiré pattern on which image processing has been performed.

Next, a step of inferring intraocular pressure is performed by comparing the information of the derived gradient vector graph with a previously stored DB (step S120). The DB may be configured with information of the gradient vector that changes depending on the intraocular pressure in a predetermined range. At this time, the information of the gradient vector graph may be a gradient vector value at a specific angle.

(A), (b) and (c) of FIG. 5 is a gradient vector graph derived when the pressure is 0, 10, and 20 mmHg, and (d) is a graph showing the gradient vector value at a specific angle according to pressure. . In this way, a DB is constructed by storing all gradient vector values that change with pressure in advance. When the unknown gradient vector is derived through the above-described steps, such a DB is a criterion for inferring what value is the intraocular pressure corresponding to the unknown gradient vector value. That is, it is possible to infer the intraocular pressure corresponding to the unknown gradient vector value by comparing the unknown gradient vector value with the DB information.

On the other hand, as a modification of the first embodiment, the eye pressure sensing lens set may include a first lens worn on an actual eyeball and a virtually generated second lens. In this case, the moire pattern can be virtually derived by merging the image of the first pattern obtained from the first lens worn on the actual eyeball and the image of the second pattern of the software generated second lens using a computer program. .

When two lenses are overlapped, there is an advantage that the moiré pattern can be immediately identified. However, due to frictional forces generated between the two layers, deterioration in detection occurs and it is difficult to manufacture the lens. There may be an uncomfortable problem for the patient due to foreign body sensation. In this regard, the above-described problems can be solved by configuring only the first lens as a real lens that can be worn on the eye, and the second lens as a virtual lens formed by software. FIG. 4(b) shows the appearance of the moire pattern when the image of the first lens, which is the actual lens, and the image of the virtual second lens are merged, according to pressure.

For convenience of description, the following description will be made only for the case where the lens for detecting intraocular pressure consists of a first lens that can be worn on an actual eyeball and a virtually generated second lens. This is for convenience of explanation and the technical idea of the present invention for deriving the intraocular pressure from the moiré pattern can be applied even when using an intraocular pressure sensing lens composed of a plurality of real lenses.

6 and 7 show a flow chart and a process chart showing the intraocular pressure analysis method using a moiré pattern according to a second embodiment of the present invention step by step.

First, in order to measure intraocular pressure, first image information is obtained from an eyeball wearing a lens for detecting an intraocular pressure having a first pattern (step S300). 7A shows image information of the eye pressure sensing lens worn on the eye.

Next, image processing is performed using a video editing program to remove unnecessary information from the acquired video image and secure meaningful data to improve the accuracy and reliability of the result (step S310). 7(b) shows the result of the image processing.

In this step S310, an image editing program may be used to extract and analyze patterns using, for example, Matlab. The image can be defined by a two-dimensional function f(x, y). Here, x and y are spatial coordinates, and a gray image represents the size of f(x, y) on the coordinates as image brightness at that point. Since digital images have finite discontinuity values of x, y, and f(x, y) sizes, a device that can normalize them is embedded in the algorithm. The image processing algorithm is divided into point processing, area processing, geometric processing, and frame processing. Therefore, in the process of editing an image, the operation of changing a unit value of a pixel, changing a pixel value based on a neighbor value, changing a position or arrangement of pixels, or generating a pixel value based on operations on images may be performed. do.

Next, as a previous step for forming the moire pattern, second image information including a virtual second pattern is generated in software (step S320). The third image information including the moiré pattern is obtained by software-integrating the second image information including the second pattern thus generated and the first image information including the first pattern obtained in step S110 (S330). step). In this embodiment, the third image information including the moire pattern image is obtained by software-generating the image information including the virtual second pattern, and combining the obtained first pattern with the software. FIG. 7(c) shows the result of forming the moire pattern by merging the first pattern and the second pattern in the above-described method.

Next, a gradient vector graph can be derived from the obtained image information of the moire pattern. At this time, the step of selectively processing the image information of the obtained moiré pattern before deriving the gradient vector graph may be performed first (step S340). These processing steps include converting the obtained moire pattern image into frequency information using a two-dimensional Fourier transform, processing a region of the converted frequency information, enhancing the sharpness of the moire pattern image, and the frequency. It may further include any one or more of the steps of converting the coordinates of the information into a polar coordinate system.

In FIG. 8, detailed steps constituting the processing step (step S340) are illustrated, and will be described with reference to this.

First, a process of transforming the obtained moire pattern image into frequency information by using a two-dimensional Fourier transform (step S341).

Since an image is a change in brightness or color in space, it can be considered that the image is also a kind of signal. Therefore, the image can be viewed by converting it into a frequency space called a high frequency region or a low frequency region. In the case of a moiré pattern image, it can be said that it is more efficient to process by using the characteristics of the frequency component in the frequency domain through frequency conversion of the image than to process the image itself to emphasize the edge portion of the image or to suppress the noise component. have.

The Fourier transform refers to the transformation from the time domain to the frequency domain. It is based on the basic principle that all waveforms can be expressed as a simple sum of sinusoids. The image is a two-dimensional signal that changes according to the x-direction and the y-direction orthogonal to the light intensity or color change. Therefore, the image can be transformed into a frequency domain by applying a two-dimensional discrete Fourier transform. The Fourier transform of the image f(x,y) of the M×N size produces an M×N coefficient matrix. Since the inverse transform reconstructs the original image from this set of coefficients, it can be said that the coefficients perfectly represent the information the image has. When image processing is performed by manipulating F(u,v), it is said that it is processed in the frequency domain. Conversely, if the pixel value of f(x,y) is manipulated by convolution operations, it can be said that the image is processed in the spatial domain. When the image processing is performed in the frequency domain or the spatial domain, some loss occurs in the information possessed by the image. However, there is an advantage that such a loss does not occur in a Fourier transform or an inverse Fourier transform process. 7(d) shows the result of the two-dimensional discrete Fourier transform of the moire pattern image.

Next, frequency domain processing may be performed on the result of the 2D Fourier transform (step S342). The purpose of the frequency conversion of the image is to grasp the frequency components included in the image and filter the image based on it. As shown in (d) of FIG. 7, when the Fourier transform is performed, low-frequency components are distributed in the central portion. Since it is convenient to perform filter processing in the frequency domain with such a structure, shuffling is performed in which the position of the low frequency portion is shifted to the center by moving the frequency quadrant. 7(e) shows the result of the frequency domain processing. 7(e) is an image obtained by finely filtering the center portion of the brightness portion of the frequency image image shown in FIG. 7(d). In the image space region, blurring an image is an operation of passing a low-frequency component included in the image, whereas passing a high-frequency component is intended to clearly highlight a desired image. The frequency components included in the image were appropriately adjusted through filtering processing in the image spatial domain.

Next, a process of further enhancing the sharpness of the moire pattern image may be performed (step S343). The step of enhancing the image sharpness may be understood as a step of increasing the contrast difference between the moire pattern and other patterns (for example, the first and second patterns). Using an appropriate band pass filter, you can selectively enhance the image of the image. The filtering process of the image was performed in the frequency domain, and manipulation of the frequency components was performed quantitatively. Spatial low-pass filters attenuate high-frequency components. Therefore, the component value of the spectrum tends to increase in frequency as it moves away from the origin (center). A low-pass filter and a high-pass filter were used in combination to improve the clarity of the moiré pattern image. FIG. 7F shows a moiré pattern image with enhanced sharpness.

Next, the moire pattern image may be converted into a polar coordinate system (step S344). The image of the first image information obtained in step S300 is an RGB color image. The RGB color image is an M, N, 3 array of color pixels, and each color pixel corresponds to red, green, and blue components of the RGB image at a specific spatial location. Therefore, in order to perform image processing, it is necessary to convert an RGB image to a gray scale. The image edited in the gray scale was limited in reflecting the slope with the Cartesian coordinate system, so the Cartesian coordinate system was converted to a polar coordinate system to solve this problem. After the conversion to the polar coordinate system, it was confirmed that the slope value of the moiré pattern was maximized. 7(g) shows the result after the conversion to the polar coordinate system.

After processing the image information of the moire pattern, a gradient vector graph (Histogram of Oriented Gradients, HOG) is derived using the processed information (step S350). 7(h) shows a gradient vector graph derived therefrom.

The conversion to the polar coordinate system and the derivation of the gradient vector may be performed using functions provided in an image processing program. For example, in the image processing program Matlab, the HOG array can be derived using the function extractHOGFeatures. Histogram of oriented gradients (HOG) used in this example are normalized vectors of image histograms. Matlab's command extractHOGFeatures splits a user-specified region into cells of the same size. In addition, it has a function to derive the histogram value of each cell based on the pixel direction. HOG has the advantage of not being sensitive to changes in the brightness of the image because it uses edge information of any shape. In addition, it is very suitable for identifying objects with the unique information of the edge, which is adopted in the intraocular pressure measurement algorithm.

As in the first embodiment described above, even in the case of the second embodiment, when a gradient vector graph is derived, it is possible to derive intraocular pressure by comparing it with a previously stored DB. However, in the second embodiment, a step of obtaining a slope period graph by processing the slope vector graph may be further added (S360). The step of inferring intraocular pressure may be further performed by comparing peak information of a specific frequency (or frequency) of the obtained slope period graph with a DB composed of peak information that changes according to pressure.

Fig. 7(i) shows a graph of the polar slope period derived from the polar gradient vector graph. The slope period graph shows a shape of a spectrum in which peaks are formed at a specific frequency over various frequency bands as shown in FIG. 7(i).

In the coding of the Moiré pattern algorithm, the option values that affect the principal frequency are period, amplitude, amplitude threshold, cell size, block size, NumBins and others. You can derive a linear graph for each input by setting option values appropriate for the moiré pattern.

In the low frequency band, the main frequency (Principle Frequency) showed a tendency to increase in an arbitrary component value linearly, whereas the high frequency band was confirmed to have a low level of change compared to the low frequency. As a result of the Inverse Fast Fourier Transform, the high-frequency region is estimated as the grating pattern region, and the low-frequency region is estimated as the moiré pattern region. Accordingly, it can be analyzed in the low frequency band determined to be the moiré pattern region.

A frequency band determined as a moiré pattern region is selected from the plurality of peaks shown in FIG. 7(i). For example, in the spectrum shown in (j) of FIG. 10, which is the result of the first experimental example, a peak with a frequency of 2.1834x10 ⁴ (indicated by a red arrow) is a frequency peak corresponding to the moire pattern region.

The peak information such as the size, area, or maximum height of the peak of the frequency corresponding to the moiré pattern region changes in response to the deformation of the moiré pattern. For example, as the amount of change in the moire pattern increases, the magnitude of the corresponding frequency may also increase. The amount of change in the moiré pattern corresponds to the size of the intraocular pressure. Therefore, the amount of deformation of the moire pattern according to the change in intraocular pressure is secured in advance through the spectral analysis and DB is made. When any user wants to measure intraocular pressure, after wearing the intraocular pressure sensing lens, after obtaining the peak information at the frequency corresponding to the final moire pattern in the same manner as in the above-described embodiment, it is obtained from the previously secured DB. It is possible to estimate what the user's current intraocular pressure is by comparing it with the value. In this way, the user's intraocular pressure can be measured.

By using embodiments of the present invention, users can easily measure the intraocular pressure of themselves or others. For example, by using a computer or smartphone equipped with a microprocessor driven according to the algorithm shown in the embodiment of the present invention, the user can measure intraocular pressure in a short time.

For example, after the user wears the first lens on his or her eyeball, the user photographs the first lens worn on the eyeball using a camera built into a smartphone. The microprocessor mounted in the smartphone receives the image of the photographed first lens, generates a virtual second lens image in software, and then merges it with the image of the first lens to form a moiré pattern. Next, the microprocessor derives the user's intraocular pressure by performing the steps presented in the above-described embodiments, and then outputs the intraocular pressure to the user's display unit so that the user can know how much his or her intraocular pressure is currently.

Hereinafter, an experimental example in which the above-described technical idea is applied to help understanding of the present invention will be described. However, the following experimental examples are only to help understanding of the present invention, and the present invention is not limited by the following experimental examples.

[First Experimental Example: Experimental Method Using Latex]

As a device for simulating the pressure of the eyeball, a device in which the latex can be inflated according to the pressure in the portion where the sample is located, using a latex that easily expands as the pressure increases, was devised. To this end, a portion of the latex was cut off and attached to the position of the lens as shown in the right figure of FIG. 9. Latex was formed with a pattern of a plurality of concentric circles with different diameters. The tube was fixed at the bottom of the latex and the tube was connected to a pressure gauge. The pressure was applied with a syringe pump, and the applied pressure was monitored by binding to the pressure gauge connection. It was formed in a structure that transmits pressure to the latex through a tube connected to the latex while measuring the pressure.

10 (a) to (f) of FIG. 10, the results performed step by step in a state in which pressure is not applied to the latex (0 mmHg) are presented in order. The following result is a result of deriving the values set as period = 14, amplitude = 2, amplitudeThreshold = 14.5, CellSize = 8, BlockSize = 2, and NumBins = 9 from the algorithm code option.

Fig. 10(a) shows the result of image processing after the latex was directly photographed with the camera without pressure being applied. FIG. 10B shows a virtual second pattern formed in software by computer programming. 5C illustrates a moire pattern image formed when the image-processed first pattern and the virtual second pattern are merged so as to overlap.

FIG. 10D shows the result of performing the 2D Fourier transform, and FIG. 10E shows the result of performing frequency domain processing. Meanwhile, FIG. 10(f) is a result of clearly enhancing the moire pattern image through frequency filtering processing. Also, FIG. 10(g) is a result of changing to a polar coordinate system, and FIG. 10(h) is a 2D graph showing the inclination in each coordinate system of the image as a value between 0 and 1, and FIG. 10(i) is It is a spectrum graph of the derived gradient vector. Finally, (j) of FIG. 10 is a result of processing the gradient vector graph and plotting the harmonic frequency 3 of the period graph spectrum of the gradient.

As a result of spectrum analysis, Principle frequency = 2457, harmonic frequency 1 = 542.5, harmonic frequency 2 = 247.6, and harmonic frequency 3 = 379 were calculated. In the experiment using latex, it was confirmed that the low frequency band harmonic frequency 3 (refer to the red arrow mark when the frequency is 2.1834x10 ⁴ ) is a moire pattern image component capable of discerning intraocular pressure of 0 mmHg.

Subsequently, while applying 5, 10, 15, 20, 25, 30, 35, 40, and 45 mmHg pressure to the latex, a periodic graph (spectrum) of the slope was derived in the same manner as the method described above, and the intraocular pressure in each periodic graph was determined. As the meaningful value that can be discerned, peak information (value on the y-axis in the graph) named harmonic frequency 3 was obtained.

11 shows a graph showing changes in harmonic frequency 3 values for each pressure applied to the latex as a result of spectrum analysis. The change in harmonic frequency 3 is interpreted to mean a change in curvature of the first pattern formed in the latex while the latex expands according to the pressure applied from the outside.

For the latex to which the unknown pressure is applied, after deriving the value of harmonic frequency 3 in the same manner as the above-described method, infer the unknown pressure applied to the latex through the operation of matching the data in FIG. 11 You can do it.

[Second Experimental Example: Experimental Method Using Pig Eyes]

The pig eye test apparatus is designed to be swollen by fixing the pig eye according to the pressure in the portion where the sample is located, as shown in FIG. 12. To this end, as shown in the figure on the right in FIG. 12, a plastic rod was used to prevent the image from moving while the pig's eyeball was expanding. The syringe needle was connected through a nerve bundle in the eye. The nerve bundle has a higher density of nerve fibers, so that the needle is injected, the metal surface and the nerve layer are in close contact. Therefore, there is an advantage that no leakage occurs. The syringe tube was connected to the pressure gauge. The pressure was applied with a syringe pump, and the applied pressure was monitored by binding to the pressure gauge connection. It was designed to measure pressure and transmit pressure to the pig's eye through a tube connected to the pig's eye.

The following result is the result of deriving the values set as period = 15, amplitude = 4, amplitudeThreshold = 16.5, CellSize = 8, BlockSize = 2, and NumBins = 9 from the algorithm code option.

13 shows a graph showing a change in the harmonic frequency 3 value for each pressure of the pig eye as a result of spectrum analysis. Although the trend line is shown in a straight line in the graph, it was confirmed that the degree of harmonic frequency 3 increases nonlinearly according to the applied pressure.

[Third Experimental Example: Experimental method using actual pinball eye]

An experiment was performed while changing the intraocular pressure after mounting a lens for detecting an intraocular pressure in which a first pattern was formed on the rabbit's eyeball. It was confirmed that the pattern of the intraocular pressure sensing lens placed on the rabbit eye changed with respect to the linear fluctuation of the pressure. The rabbit eye test apparatus was designed to expand the cornea as artificially injected BSS (Balanced Salt Solution) in front of the rabbit eye using an actual anesthetized rabbit. For this, a fixing device was prepared and supported so that the rabbit did not move. A space for needles was secured using an open eye, and the syringe was connected to a pressure gauge. The pressure was applied with a syringe pump, and the applied pressure was monitored by binding to the pressure gauge connection. It was a structure to measure pressure and deliver BSS to the front through a connected tube. 10 is a result showing how the pattern of the lens for detecting intraocular pressure according to the intraocular pressure of an actual rabbit eye is changed.

The following results are the results of deriving the values set in period = 23, amplitude = 1, amplitudeThreshold = 14.8, CellSize = 8, BlockSize = 2, and NumBins = 9 from the algorithm code option.

14 shows a graph showing the change in the harmonic frequency 3 value for each actual rabbit eye pressure as a result of spectrum analysis. Although the trend line is shown in a straight line in the graph, it was confirmed that the degree of harmonic frequency 3 increases nonlinearly according to the applied pressure.

The present invention has been described with reference to the embodiments shown in the drawings, but these are merely exemplary, and those skilled in the art will understand that various modifications and equivalent other embodiments are possible therefrom. Therefore, the true technical protection scope of the present invention should be determined by the technical spirit of the appended claims.

1: Body
2: Alignment mark
3: first pattern
10: lens

Claims (7)

As a method of measuring intraocular pressure using a moiré pattern,
(a) obtaining image information of a moire pattern generated by overlapping of a first lens having a first pattern and a second lens having a second pattern;
(b) deriving a gradient vector graph from the acquired image information; And
(c) comparing the information of the derived gradient vector graph with pre-stored DB to infer intraocular pressure,
The DB consists of information of the gradient vector graph, which is changed in accordance with a predetermined range of intraocular pressure, measured in advance.
Further comprising the step of processing the image information of the moire pattern before step (b) after step (a),
The processing step,
Comprising the step of converting the frequency information through a two-dimensional Fourier transform,
How to measure intraocular pressure using moiré patterns. As a method of measuring intraocular pressure by analyzing a moiré pattern,
(a) obtaining image information of a moire pattern generated by overlapping of a first lens having a first pattern and a second lens having a second pattern;
(b) deriving a gradient vector graph from the acquired image information; And
(c) deriving a slope period graph including frequency peak information from the slope vector graph;
(d) deriving first frequency peak information corresponding to the moire pattern among frequency peak information included in the slope period graph; And
(e) comparing the first frequency peak information derived in step (d) with a previously stored DB to infer the intraocular pressure corresponding to the first frequency peak information,
The DB is composed of the first frequency peak information measured in advance and changed according to the intraocular pressure in a predetermined range.
How to measure intraocular pressure using moiré patterns. The method of claim 1 or 2,
The moire pattern,
The first lens and the second lens is formed by being mounted on the eyeball in an overlapped state,
How to measure intraocular pressure using moiré patterns. The method of claim 1 or 2,
The moire pattern,
The image of the first pattern when the first lens is mounted on the eyeball and the image of the second pattern of the second lens, which is a software-generated virtual lens, are formed by merging with each other.
How to measure intraocular pressure using moiré patterns. According to claim 1,
The information of the gradient vector graph that changes depending on the intraocular pressure,
A value of a gradient vector at a specific angle of the first lens or the second lens,
How to measure intraocular pressure using moiré patterns. According to claim 2,
After the step (a), before the step (b), further comprising the step of processing the image information of the moire pattern,
The processing step,
Comprising the step of converting the frequency information through a two-dimensional Fourier transform,
How to measure intraocular pressure using moiré patterns. The method according to claim 1 or 6,
The processing step,
Comprising any one or more of the step of processing the area of the frequency information, enhancing the sharpness of the moire pattern image, and converting the coordinates of the frequency information to a polar coordinate system,
How to measure intraocular pressure using moiré patterns.

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