A Moire fringe characteristic detection method based on edge extraction

Abstract

The present invention discloses a method for detecting moiré fringe characteristics based on edge extraction, comprising the following steps: obtaining a moiré fringe image to be detected; performing grayscale processing to obtain a grayscale-processed moiré fringe image; intercepting an image of the moiré fringe region to be processed from the grayscale-processed image; extracting edge information from the image of the moiré fringe region to be processed; determining pixel points at the fringe edge based on the fringe intensity and edge information of the moiré fringe region to be processed; and calculating the moiré fringe width based on the coordinates of the pixel points at the fringe edge. The present invention can reduce the error generated by calculating the width based on point selection based on the moiré fringe intensity distribution, making the measurement results more accurate and improving the accuracy of moiré fringe characteristic detection.

Description

Technical Field

[0001] The invention relates to a moire fringe characteristic detection method based on edge extraction, and belongs to the technical field of optical measurement. Background Art

[0002] Moiré tomography, a branch of optical computed tomography, offers the advantages of real-time, stable, and non-contact detection, making it widely used in flow field detection. Research has shown that the high-magnification optical properties of moiré fringes allow for high-precision detection using displacement measurements.

[0003] Therefore, the accuracy of Moire fringe characteristic detection is crucial, and the fringe width is one of the most important parameters in the Moire fringe characteristics.

[0004] In the prior art, the calculation of the width based on point selection of the moiré fringe intensity distribution will produce errors, resulting in insufficient accuracy in the detection of moiré fringe characteristics. Summary of the Invention

[0005] Purpose of the Invention: To overcome the shortcomings of existing technologies and address practical challenges in moiré characteristic measurement, the present invention provides a moiré fringe characteristic detection method based on edge extraction. This method performs edge extraction and width measurement on moiré fringes. The goal is to reduce the error in width calculation based on point selection based on the moiré fringe intensity distribution, resulting in more accurate measurement results and improved accuracy in moiré fringe characteristic detection.

[0006] Technical solution: To solve the above technical problems, the technical solution adopted by the present invention is:

[0007] In a first aspect, a method for detecting moiré fringe characteristics based on edge extraction is provided, comprising:

[0008] Step S1: Acquire a moiré fringe image to be detected;

[0009] Step S2: performing grayscale processing on the moiré fringe image to be detected to obtain a grayscale-processed moiré fringe image;

[0010] Step S3: intercepting the image of the moiré fringe to be processed area from the grayscale processed image;

[0011] Step S4: extracting edge information from the image of the moiré fringe area to be processed;

[0012] Step S5: determining pixel points at the edge of the fringe based on the fringe intensity of the grayscale-processed moiré fringe image and the extracted edge information;

[0013] Step S6: Calculate the moiré fringe width based on the pixel coordinates of the fringe edge.

[0014] In some embodiments, the step S4 of extracting edge information from the image of the moiré fringe area to be processed includes:

[0015] Use Gaussian filtering to perform row-column convolution on the moiré fringe image;

[0016] f(x,y)=I(x,y)*G(x,y)

[0017] Where f(x,y) is the light intensity distribution of the moiré fringe image after Gaussian filtering; G(x,y) is the Gaussian function, and I(x,y) is the light intensity distribution of the original moiré fringe image in the area to be processed;

[0018] Use the Gaussian function to take the partial derivatives of f(x,y) in the x and y directions to get the gradient of f(x,y), including:

[0019]

[0020]

[0021] Where σ is the variance of the Gaussian function;

[0022] f(x,y)=dx(i,j)+dy(i,j)

[0023] dx(i,j)=f(i+1,j)-f(i,j)

[0024] dy(i,j)=f(i,j+1)-f(i,j)

[0025] By limiting the calculated gradient angle of f(x,y) to 0 degrees to 180 degrees, the preliminary image edge is determined;

[0026] Find the local maximum of the argument along the gradient direction, and filter the image edge points from the preliminary image edge according to the local maximum;

[0027] The image edge points are normalized, a frequency histogram is obtained according to the normalized image edge points, a threshold is determined according to the frequency histogram, and a final edge point is determined from the image edge points according to the threshold, thereby determining edge information.

[0028] In some embodiments, the moiré fringe width D is calculated as follows:

[0029]

[0030] Where Δp is the coordinate difference of two edge pixels of a moiré fringe in the y direction, P i and M represent the maximum radial pixel length and actual length of the moiré fringes in the original moiré fringe image to be detected, respectively.

[0031] In some embodiments, in step S2, a binarization method is used to perform grayscale processing.

[0032] In some embodiments, step S3: intercepting the image of the moiré fringe to-be-processed area from the grayscale-processed image includes:

[0033] A middle area of ​​320 pixels × 320 pixels is cut out from the grayscale processed image as the moiré fringe area image to be processed.

[0034] In a second aspect, the present invention provides a moiré fringe characteristic detection device based on edge extraction, comprising a processor and a storage medium;

[0035] The storage medium is used to store instructions;

[0036] The processor is configured to operate according to the instructions to execute the steps of the method according to the first aspect.

[0037] In a third aspect, the present invention provides a storage medium having a computer program stored thereon, which implements the steps of the method described in the first aspect when executed by a processor.

[0038] Beneficial Effects: Compared with existing technologies, this invention offers the following advantages: It addresses practical issues in moiré characteristic measurement by providing an edge detection method primarily based on a Gaussian function, which is then used to extract edges and measure the width of moiré fringes. This method aims to reduce the error in width calculations based on point selection based on the moiré fringe intensity distribution, resulting in more accurate measurement results and improved accuracy in moiré fringe characteristic detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 Schematic diagram of an experimental system for obtaining a moiré fringe image according to an embodiment of the present invention;

[0040] Figure 2 The moiré fringe image (a) and the moiré fringe image after grayscale processing (b) according to an embodiment of the present invention are shown;

[0041] Figure 3 The image of the moiré fringe area to be processed (a) and the moiré fringe image after edge extraction (b) according to an embodiment of the present invention are shown;

[0042] Figure 4 This is a point selection diagram based on the image light intensity (a) and edge information (b) of the area to be processed based on the moiré fringe according to an embodiment of the present invention.

[0043] In the figure: 1-laser; 2, 3-beam expansion and collimation system; 4, 5-Ronchi grating; 6, 8-imaging lens; 7-filter; 9-receiving screen; 10-CCD. DETAILED DESCRIPTION

[0044] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below in conjunction with specific embodiments.

[0045] In the description of the present invention, "several" means more than one, "plurality" means more than two, "greater than," "less than," and "exceed" are understood to exclude the number itself, while "above," "below," and "within" are understood to include the number itself. The use of "first" and "second" in the description is solely for the purpose of distinguishing technical features and should not be construed as indicating or implying relative importance, implicitly specifying the number of the indicated technical features, or implicitly specifying the order of the indicated technical features.

[0046] In the description of the present invention, reference to terms such as "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the exemplary expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0047] Example 1

[0048] A moire fringe characteristic detection method based on edge extraction, comprising:

[0049] Step S1: Acquire a moiré fringe image to be detected;

[0050] Step S2: performing grayscale processing on the moiré fringe image to be detected to obtain a grayscale-processed moiré fringe image;

[0051] Step S3: intercepting the image of the moiré fringe to be processed area from the grayscale processed image;

[0052] Step S4: extracting edge information from the image of the moiré fringe area to be processed;

[0053] Step S5: determining pixel points at the edge of the fringe based on the fringe intensity of the grayscale-processed moiré fringe image and the extracted edge information;

[0054] Step S6: Calculate the moiré fringe width based on the pixel coordinates of the fringe edge.

[0055] In some embodiments, the step S4 of extracting edge information from the image of the moiré fringe area to be processed includes:

[0056] Use Gaussian filtering to perform row-column convolution on the moiré fringe image;

[0057] f(x,y)=I(x,y)*G(x,y)

[0058] Where f(x,y) is the light intensity distribution of the moiré fringe image after Gaussian filtering; G(x,y) is the Gaussian function, and I(x,y) is the light intensity distribution of the original moiré fringe image in the area to be processed;

[0059] Use the Gaussian function to take the partial derivatives of f(x,y) in the x and y directions to get the gradient of f(x,y), including:

[0060]

[0061]

[0062] Where σ is the variance of the Gaussian function; when at the edge, the light intensity distribution has a larger gradient value. On the contrary, in the smooth part of the image, the gray value changes less, and the corresponding gradient is also smaller;

[0063] f(x,y)=dx(i,j)+dy(i,j)

[0064] dx(i,j)=f(i+1,j)-f(i,j)

[0065] dy(i,j)=f(i,j+1)-f(i,j)

[0066] By limiting the calculated gradient angle of f(x,y) to 0 degrees to 180 degrees, the preliminary image edge is determined;

[0067] Find the local maximum of the argument along the gradient direction, and filter the image edge points from the preliminary image edge according to the local maximum;

[0068] The image edge points are normalized, a frequency histogram is obtained according to the normalized image edge points, a threshold is determined according to the frequency histogram, and a final edge point is determined from the image edge points according to the threshold, thereby determining edge information.

[0069] In some embodiments, the moiré fringe width D is calculated as follows:

[0070]

[0071] Where Δp is the coordinate difference of two edge pixels of a moiré fringe in the y direction, P i and M represent the maximum radial pixel length and actual length of the moiré fringes in the original moiré fringe image to be detected, respectively.

[0072] In some embodiments, in step S2, a binarization method is used to perform grayscale processing.

[0073] In some embodiments, step S3: intercepting the image of the moiré fringe to-be-processed area from the grayscale-processed image includes:

[0074] A middle area of ​​320 pixels × 320 pixels is cut out from the grayscale processed image as the moiré fringe area image to be processed.

[0075] In some specific embodiments, the experimental system is as follows Figure 1 As shown. G1 and G2 are a pair of Ronchi gratings with a grating constant of d. The grating spacing is Δ. In order to obtain fringes with better contrast, Δ should satisfy the Talbot distance, i.e. Δ = jd 2 The lines of the two gratings form angles of +α / 2 and -α / 2 with the y-axis, respectively. From the rear surface of grating G2 to the receiving screen is a typical 4-f system.

[0076] use Figure 1 The experimental system was used to conduct the experiment. A pair of Ronchi gratings with a grating constant of d = 0.02 mm was selected, and the CCD recorded the first-order filtered moiré fringes. In the experiment, the angle between the two grating lines was 20' (i.e. ).

[0077] The first-level filtered moiré fringes obtained in the experiment were gray-scale processed as follows Figure 2 As shown. Cut out the middle area of ​​320 pixels × 320 pixels, as shown Figure 3 Then, edge information is extracted according to the steps described in this patent, and the result is as follows: Figure 3 As shown in (b) in .

[0078] Finally, respectively Figure 3 (a) and (b) are used to select points based on light intensity and edge information (e.g. Figure 4 and further calculate the stripe width.

[0079] In this example, P i =660, M=50mm. Finally, the experimental moiré fringe width can be obtained by calculation. To improve the accuracy, different fringes can be selected for calculation to obtain the average fringe width. In this example, Figure 4 The three groups of moiré fringes are averaged, and the relevant comparison results are shown in Table 1.

[0080] Table 1 Comparison of results

[0081]

[0082] Among them, the theoretical value of the moiré fringe width is

[0083] It can be seen from Table 1 that the error of the method used in this patent is smaller than that of the width measurement based on light intensity point selection, which confirms the feasibility and accuracy of the method described in this patent.

[0084] Example 2

[0085] In a second aspect, this embodiment provides a moiré fringe characteristic detection device based on edge extraction, comprising a processor and a storage medium;

[0086] The storage medium is used to store instructions;

[0087] The processor is configured to operate according to the instructions to execute the steps of the method according to embodiment 1.

[0088] Example 3

[0089] In a third aspect, this embodiment provides a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the method described in Example 1 are implemented.

[0090] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0091] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0092] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1The function specified in one or more boxes.

[0093] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0094] It is understood from common technical knowledge that the present invention may be implemented by other embodiments that do not depart from its spirit or essential features. Therefore, the embodiments disclosed above are, in all respects, merely illustrative and not exclusive. All modifications within the scope of the present invention or equivalent to the scope of the present invention are intended to be encompassed by the present invention.

Claims

1. A moiré fringe characteristic detection method based on edge extraction, characterized in that: include: Step S1: Acquire a moiré fringe image to be detected; Step S2: performing grayscale processing on the moiré fringe image to be detected to obtain a grayscale-processed moiré fringe image; Step S3: intercepting the image of the moiré fringe to be processed area from the grayscale processed image; Step S4: extracting edge information from the image of the moiré fringe area to be processed, including: Use Gaussian filtering to perform row-column convolution on the moiré fringe image; f(x,y)=I(x,y)*G(x,y) Where f(x,y) is the light intensity distribution of the moiré fringe image after Gaussian filtering; G(x,y) is the Gaussian function, and I(x,y) is the light intensity distribution of the original moiré fringe image in the area to be processed; Use the Gaussian function to take the partial derivatives of f(x,y) in the x and y directions to get the gradient of f(x,y), including: Where σ is the variance of the Gaussian function; f(x,y)=dx(i,j)+dy(i,j) dx(i,j)=f(i+1,j)-f(i,j) dy(i,j)=f(i,j+1)-f(i,j) By limiting the calculated gradient angle of f(x,y) to 0 degrees to 180 degrees, the preliminary image edge is determined; Find the local maximum of the argument along the gradient direction, and filter the image edge points from the preliminary image edge according to the local maximum; Normalizing the image edge points, obtaining a frequency histogram based on the normalized image edge points, determining a threshold value based on the frequency histogram, and determining a final edge point from the image edge points based on the threshold value, thereby determining edge information; Step S5: determining pixel points at the edge of the fringe based on the fringe intensity of the grayscale-processed moiré fringe image and the extracted edge information; Step S6: Calculate the moiré fringe width based on the pixel coordinates of the fringe edge. The calculation method of the moiré fringe width D is: Where Δp is the coordinate difference of two edge pixels of a moiré fringe in the y direction, P i and M represent the maximum radial pixel length and actual length of the moiré fringes in the original moiré fringe image to be detected, respectively.

2. The moiré fringe characteristic detection method based on edge extraction according to claim 1, characterized in that: In step S2, a binarization method is used to perform grayscale processing.

3. The moiré fringe characteristic detection method based on edge extraction according to claim 1, characterized in that: Step S3: intercepting the image of the moiré fringe to be processed area from the grayscale processed image, including: A middle area of ​​320 pixels × 320 pixels is cut out from the grayscale processed image as the moiré fringe area image to be processed.

4. A moiré fringe characteristic detection device based on edge extraction, characterized in that: including processors and storage media; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 3.

5. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 3 are implemented.

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