Detection image processing method and device, electronic equipment and storage medium

Abstract

The invention discloses a detection image processing method and device, electronic equipment and a storage medium. The method comprises the following steps: collecting a detection image of a honeycomb sandwich structure part containing a metal net; performing Fourier transform on the detection image to obtain a first transform result; filtering the first transformation result according to the characteristics of the metal net to obtain a filtering result; and carrying out inverse Fourier transform on the filtering result to obtain a processed detection image. According to the technical scheme, the detection image after Fourier transform is filtered according to the characteristics of the metal net, interference of the frequency domain is removed, and then the filtering result is subjected to inverse Fourier transform to obtain the processed detection image, so that interference information brought by the metal net can be effectively eliminated, and the detection accuracy is improved. Meanwhile, the inherent structure image characteristics of the honeycomb core under the metal net coverage area are not influenced, the recognizability of the defects of the honeycomb core under the metal net layer in the honeycomb sandwich structure part is improved, and the quality nondestructive testing evaluation problem of the honeycomb core in the honeycomb sandwich structure part can be solved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of image processing technology, and in particular to a detection image processing method, device, electronic device and storage medium. Background Art

[0002] Honeycomb sandwich structures have the advantages of light weight, strong bending rigidity, and low impact damage expansion. They have been widely used in areas such as wing surfaces, rudder surfaces, and doors of civil aircraft. However, the strength of the honeycomb core structure in this structure is slightly weak, and it is easy to cause defects such as honeycomb core deformation, collapse, and node separation due to improper production process control, which will have an adverse effect on the performance of the honeycomb sandwich structure. At present, in the production process, the structure is usually evaluated for non-destructive quality by combining ultrasound and radiation, but the metal mesh in the honeycomb sandwich structure will seriously interfere with the radiation detection results, resulting in the inability to evaluate the quality of the honeycomb core in the honeycomb sandwich structure containing the metal mesh, which brings product quality risks. Summary of the invention

[0003] The present invention provides a detection image processing method, device, electronic equipment and storage medium to realize processing of detection images.

[0004] In a first aspect, an embodiment of the present invention provides a detection image processing method, comprising:

[0005] Collect inspection images of honeycomb sandwich structure parts containing metal mesh;

[0006] Performing Fourier transform on the detection image to obtain a first transform result;

[0007] Filtering the first transformation result according to the characteristics of the metal mesh to obtain a filtering result;

[0008] Perform inverse Fourier transform on the filtering result to obtain the processed detection image.

[0009] In a second aspect, an embodiment of the present invention provides a detection image processing device, including:

[0010] An image acquisition module, used for acquiring detection images of honeycomb sandwich structure parts including metal mesh;

[0011] A Fourier transform module, used for performing Fourier transform on the detection image to obtain a first transform result;

[0012] A filtering module, used for filtering the first transformation result according to the characteristics of the metal mesh to obtain a filtering result;

[0013] The inverse Fourier transform module is used to perform inverse Fourier transform on the filtering result to obtain a processed detection image.

[0014] In a third aspect, an embodiment of the present invention provides an electronic device, including:

[0015] at least one processor; and

[0016] a memory communicatively connected to at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the detection image processing method as described in the first aspect.

[0018] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the detection image processing method as described in the first aspect.

[0019] The embodiment of the present invention provides a detection image processing method, device, electronic device and storage medium, firstly collects the detection image of the honeycomb sandwich structure part containing the metal mesh, then performs Fourier transformation on the detection image to obtain the first transformation result, then filters the first transformation result according to the characteristics of the metal mesh to obtain the filtering result, and finally performs Fourier inverse transformation on the filtering result to obtain the processed detection image. The above technical scheme, by performing Fourier transformation on the detection image of the honeycomb sandwich structure part containing the metal mesh, then filtering the detection image after Fourier transformation according to the characteristics of the metal mesh, and finally performing Fourier inverse transformation on the filtering result, obtains the processed detection image, which can effectively eliminate the interference information brought by the metal mesh in the image of the traditional X-ray detection method, and at the same time does not affect the inherent structural image characteristics of the honeycomb core under the metal mesh coverage area, improves the identifiability of the defects of the honeycomb core under the metal mesh layer in the honeycomb sandwich structure part, and helps to solve the problem of non-destructive detection and evaluation of the quality of the honeycomb core in such honeycomb sandwich structure parts.

[0020] It should be understood that the contents described in this section are not intended to identify the key or important features of the embodiments of the present invention, nor are they intended to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0022] Figure 1 A flowchart of a detection image processing method provided in Embodiment 1 of the present invention;

[0023] Figure 2 A flowchart of a detection image processing method provided in Embodiment 2 of the present invention;

[0024] Figure 3 A schematic diagram of a detection image of an untreated honeycomb sandwich structure part containing a metal mesh provided in the second embodiment of the present invention;

[0025] Figure 4 A schematic diagram of a processed detection image of a honeycomb sandwich structure part containing a metal mesh provided in the second embodiment of the present invention;

[0026] Figure 5 A flowchart of a detection image processing method provided in Embodiment 3 of the present invention;

[0027] Figure 6 A schematic diagram of a detection image of a honeycomb sandwich structure part including a metal mesh before treatment provided in Embodiment 3 of the present invention;

[0028] Figure 7 A schematic diagram of a processed detection image of a honeycomb sandwich structure part containing a metal mesh provided in Embodiment 3 of the present invention;

[0029] Figure 8 A schematic diagram of the structure of a detection image processing device provided in Embodiment 4 of the present invention;

[0030] Fig. 9 This is a schematic diagram of the structure of an electronic device provided in Embodiment 5 of the present invention. DETAILED DESCRIPTION

[0031] The present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. In addition, the embodiments of the present invention and the features in the embodiments can be combined with each other without conflict. It is also necessary to explain that, for the convenience of description, only the parts related to the present invention are shown in the accompanying drawings, rather than all structures.

[0032] It should be mentioned before discussing the exemplary embodiments in more detail that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe the steps as sequential processes, many of the steps therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the steps can be rearranged. The process can be terminated when its operation is completed, but can also have additional steps not included in the accompanying drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0033] It should be noted that the concepts such as "first" and "second" mentioned in the embodiments of the present invention are only used to distinguish different devices, modules, units or other objects, and are not used to limit the order or interdependence of the functions performed by these devices, modules, units or other objects.

[0034] Embodiment 1

[0035] Figure 1 The present invention provides a flowchart of a detection image processing method according to the first embodiment of the present invention. This embodiment can be applied to the case of processing detection images. Specifically, the detection image processing method can be executed by a detection image processing device, which can be implemented by software and / or hardware and integrated in an electronic device. Furthermore, the electronic device includes but is not limited to: electronic devices such as desktop computers, laptop computers, smart phones, and servers.

[0036] like Figure 1 As shown, the method specifically comprises the following steps:

[0037] S110, collecting a detection image of a honeycomb sandwich structure part including a metal mesh.

[0038] In this embodiment, the honeycomb sandwich structure parts containing metal mesh can be understood as parts with honeycomb sandwich structure, the honeycomb sandwich structure includes honeycomb core, upper and lower skins, and at least two layers of film, and in order to avoid lightning damage, a layer of equipotential metal mesh is usually covered on its surface, and the honeycomb sandwich structure parts containing metal mesh can be used in areas such as wing surfaces, rudder surfaces, and doors of civil aircraft. Among them, equipotential can be understood as the metal mesh and the honeycomb sandwich structure parts containing metal mesh are equipotential; the metal mesh can be composed of multiple small grid structures, and the metal mesh can be, for example, a copper mesh, an aluminum mesh, or other metals, which is not limited in this embodiment.

[0039] Specifically, the inspection image of the honeycomb sandwich structure part including the metal mesh can be collected by a ray inspection device, which can be, for example, a digital ray inspection device or a film ray inspection device.

[0040] S120, performing Fourier transform on the detection image to obtain a first transformation result.

[0041] In this embodiment, Fourier transform can be understood as a mathematical tool for converting a signal (such as a detection image) from the time domain to the frequency domain. The principle is to decompose a signal into a superposition of sine and cosine waves of different frequencies, thereby obtaining a representation of the signal in the frequency domain, which can be widely used in signal processing, image processing, communication systems and other fields. Fourier transform can decompose the detection image into patterns of different frequencies, and can easily find subtle differences hidden in the detection image, thereby facilitating subsequent processing of the detection image. Among them, the time domain can be used to describe the relationship between mathematical functions or physical signals and time, and the frequency domain can be used to describe the characteristics of the signal in terms of frequency. It is a coordinate system used.

[0042] Specifically, Fourier transform is performed on the detection image to convert the detection image from the time domain to the frequency domain to obtain a first transformation result.

[0043] S130: Filter the first transformation result according to the characteristics of the metal mesh to obtain a filtering result.

[0044] In this embodiment, the characteristics of the metal mesh may include the size of the metal mesh, the tilt angle of the metal mesh, the size or tilt angle of the diamond structure in the metal mesh, which can be obtained based on a separate metal mesh image that is consistent with the specifications of the honeycomb sandwich structure part containing the metal mesh, or based on the actual honeycomb sandwich structure part containing the metal mesh. Filtering can be understood as an operation of filtering out a specific band frequency in the first transformation result image, which is an important measure to suppress and prevent interference, that is, filtering can filter out the metal mesh interference information in the detection image.

[0045] Specifically, the first transformation result is filtered according to the characteristics of the metal mesh to eliminate the metal mesh structure information and retain the honeycomb core structure information for subsequent processing.

[0046] S140, performing inverse Fourier transform on the filtering result to obtain a processed detection image.

[0047] In this embodiment, the inverse Fourier transform can be the inverse transform of the Fourier transform, which can convert the frequency domain signal of the filtering result into a time domain signal to obtain a processed detection image. In other words, a detection image with only honeycomb core structure information but no metal mesh structure information is obtained, which can effectively solve the problem of honeycomb core quality evaluation in a honeycomb sandwich structure containing a metal mesh.

[0048] Optionally, capture inspection images of honeycomb sandwich structure parts containing metal mesh, including:

[0049] Use digital radiographic testing equipment to collect test images of honeycomb sandwich structure parts containing metal mesh; or,

[0050] A film radiographic inspection device is used to shoot radiographic films of the honeycomb sandwich structure parts containing metal meshes, and a film scanner is used to convert the radiographic films of the honeycomb sandwich structure parts containing metal meshes into inspection images.

[0051] In one embodiment, the ray detection equipment can be used to detect the internal structure of a product or the internal defects of a workpiece. The digital ray detection equipment can be an advanced non-destructive detection equipment that uses digital imaging technology to digitize the detected signal, that is, it can collect digital images, with higher detection efficiency and accuracy, which helps to improve the processing efficiency and accuracy of the detected image, and can achieve online elimination of metal mesh interference information and online evaluation of the quality of the honeycomb core under the metal mesh layer. The digital ray detection equipment can be, for example, a computer radiography device (Computed Radiography, CR) or a digital flat-panel direct imaging device (Direct Radiography, DR).

[0052] Film X-ray detection equipment can be understood as a conventional non-destructive X-ray detection equipment. Its principle is that the rays emitted by the radiation source pass through the object to be inspected (such as a honeycomb sandwich structure part containing a metal mesh), and use the different degrees of attenuation of the radiation intensity between the object to be inspected and its internal defective medium to carry the internal information of the object to be inspected, and record it with X-ray film. After development, fixing and other processing, a perspective projection image (such as a detection image) is formed on the film. The use of film X-ray detection equipment is simple to operate, easy to use, and highly reliable.

[0053] A film scanner can be understood as an instrument that digitizes information from film and can be used to digitally scan negatives after non-destructive testing. That is, a film scanner can scan and digitize X-ray films of honeycomb sandwich structure parts containing metal mesh into test images.

[0054] A detection image processing method provided in the first embodiment of the present invention first collects a detection image of a honeycomb sandwich structure part containing a metal mesh, then performs Fourier transformation on the detection image to obtain a first transformation result, then filters the first transformation result according to the characteristics of the metal mesh to obtain a filtering result, and finally performs inverse Fourier transformation on the filtering result to obtain a processed detection image. The above technical scheme, by performing Fourier transformation on the detection image of the honeycomb sandwich structure part containing a metal mesh, then filtering the detection image after Fourier transformation according to the characteristics of the metal mesh, and finally performing inverse Fourier transformation on the filtering result, obtains a processed detection image, which can effectively eliminate the interference information brought by the metal mesh in the image of the traditional X-ray detection method, and at the same time does not affect the inherent structural image characteristics of the honeycomb core under the metal mesh coverage area, improves the identifiability of the defects of the honeycomb core under the metal mesh layer in the honeycomb sandwich structure part, and helps to solve the problem of non-destructive detection and evaluation of the quality of the honeycomb core in such honeycomb sandwich structure parts.

[0055] Embodiment 2

[0056] Figure 2 This is a flow chart of a detection image processing method provided in the second embodiment of the present invention. This embodiment is a refinement based on the above embodiment, and specifically describes the process of detection image processing. It should be noted that the technical details not described in detail in this embodiment can be referred to any of the above embodiments.

[0057] Specifically, Figure 2 As shown, the method specifically comprises the following steps:

[0058] S210, collecting a detection image of a honeycomb sandwich structure part including a metal mesh.

[0059] S220: Perform Fourier transform on the detection image to obtain a first transformation result.

[0060] S230: Collect sample images of the metal mesh.

[0061] In this embodiment, the sample image can be understood as an image of a separate metal mesh having the same specifications as the metal mesh in the honeycomb sandwich structure part containing the metal mesh. The sample image of the metal mesh can be collected by a digital radiographic detection device, or a film radiographic detection device can be used to shoot a radiographic film of the separate metal mesh, and the radiographic film of the separate metal mesh can be converted into a sample image by a film scanner. The specifications can be consistent in terms of material, size, number of metal meshes, or inclination angle of the metal meshes.

[0062] S240: Determine the rotation amount and scaling amount of the sample image.

[0063] In this embodiment, the rotation amount can be understood as the value of rotating the sample image when the tilt angles of the metal grid images in the detection image and the sample image are inconsistent. The scaling amount can be understood as the value of enlarging or reducing the sample image when the sizes of the detection image and the sample image are inconsistent.

[0064] S250 , rotating and scaling the sample image according to the rotation amount and the scaling amount, so that the size of the sample image and the metal mesh grid arrangement angle are consistent with the detection image.

[0065] In this embodiment, the metal mesh grid may be, for example, a plurality of small diamond structures constituting the metal mesh.

[0066] S260: Perform Fourier transform on the sample image to obtain a second transform result.

[0067] Specifically, Fourier transform is performed on the sample image to convert the sample image in the time domain into the sample image in the frequency domain, thereby obtaining the second transform result.

[0068] S270: Filter the first transformation result according to the frequency domain characteristics of the second transformation result to obtain a filtering result.

[0069] Specifically, the first transformation result is filtered using the characteristics of the sample image in the frequency domain as a filter to eliminate interference information of the metal mesh and obtain a filtering result.

[0070] S280, performing inverse Fourier transform on the filtering result to obtain a processed detection image.

[0071] Optionally, determine the amount of rotation and scaling of the sample image, including:

[0072] Calculate the ratio coefficient between the length of the specified side of the metal grid in the sample image and the length of the corresponding side of the metal grid in the detection image as the scaling amount;

[0073] The offset angle of the tilt angle of the specified edge of the metal mesh in the sample image and the tilt angle of the corresponding edge of the metal mesh in the detection image is calculated as the rotation amount.

[0074] In one embodiment, the designated sides can be understood as the long sides and short sides of the metal mesh, and the tilt angle can be understood as the tilt angle of the corresponding side of the metal mesh of the diamond structure.

[0075] For example, Figure 3 This is a schematic diagram of a detection image of an untreated honeycomb sandwich structure part containing a metal mesh provided in Example 2 of the present invention. Figure 3 As shown, there are obvious grid-like shadows in the inspection image of the untreated honeycomb sandwich structure part containing a metal mesh.

[0076] For example, Figure 4A schematic diagram of a processed detection image of a honeycomb sandwich structure part containing a metal mesh provided in Example 2 of the present invention. First, prepare a separate metal mesh with the same specifications as the metal mesh in the honeycomb sandwich structure part containing the metal mesh, and flatten it. If the separate metal mesh has poor self-sustaining power, it can be covered on a low-density and high-rigidity thin plate material and fixed; then use reasonable exposure parameters (such as reasonable voltage, current, exposure time or focal length, etc.), use digital X-ray detection equipment, or first film X-ray detection equipment, and then use a film scanner to collect a sample image I0 of the metal mesh and a detection image I1 of the honeycomb sandwich structure part containing the metal mesh; when the metal mesh is a diamond structure, then measure the long side length a0 of the metal mesh in I0, the inclination angle α0 of the long side length of the metal mesh in I0, the short side length b0 of the metal mesh in I0, the inclination angle β0 of the short side length of the metal mesh in I0, the long side length a1 of the metal mesh in I1, and the long side length I1 of the metal mesh in I1. The inclination angle α1 of the short side length of the metal mesh in I1 is b1, and the inclination angle β1 of the short side length of the metal mesh in I1 is calculated; then the proportional coefficient k of a1 / a0 or b1 / b0, the deflection angle θ of α1-α0 or β1-β0 are calculated, and then I0 is rotated and scaled to be transformed into I0', so that its size and grid arrangement angle are consistent with those in I1; then I1 is Fourier transformed from the time domain to the frequency domain to obtain the first transformation result F1, and I0 is Fourier transformed from the time domain to the frequency domain to obtain the second transformation result F0; then the frequency domain characteristics of F0 are used as a filter to filter the frequency domain information of I1 to obtain the filtering result, that is, F1'=F1-F0; finally, F1' is inversely Fourier transformed to obtain a detection image in which the metal mesh structure information is eliminated and the honeycomb core structure information is retained, that is, the processed detection image is obtained, as shown Figure 4 As shown, an intuitive quantitative evaluation of the defect quality of the honeycomb core in metal mesh honeycomb sandwich structure parts can be achieved.

[0077] A detection image processing method provided in a second embodiment of the present invention is refined on the basis of the above-mentioned embodiment, firstly, a detection image of a honeycomb sandwich structure part including a metal mesh is collected; then, Fourier transform is performed on the detection image to obtain a first transform result; then, a sample image of the metal mesh is collected; then, the rotation amount and scaling amount of the sample image are determined; then, the sample image is rotated and scaled according to the rotation amount and scaling amount, so that the size of the sample image and the metal mesh grid arrangement angle are consistent with the detection image; then, Fourier transform is performed on the sample image to obtain a second transform result; then, the first transform result is filtered according to the frequency domain characteristics of the second transform result to obtain a filtered result; finally, the filtered result is inverse Fourier transformed to obtain a processed detection image. The above technical scheme collects the structural feature information of the separately existing metal mesh at one time, filters the first transformation result according to the frequency domain characteristics of the second transformation result, removes the interference in the frequency domain, and then obtains the processed detection image by inverse Fourier transforming the filtering result. The structural feature information of the separately existing metal mesh is used as the interference image feature reference, has high directivity, is only sensitive to the metal mesh interference information in the detection image, will not change the detection image result of the honeycomb core morphology under the metal mesh layer, and will not introduce additional interference images, which helps to obtain the processed detection image more simply, efficiently and accurately, improves the identifiability of the defects of the honeycomb core under the metal mesh layer in the honeycomb sandwich structure parts, and helps to solve the problem of non-destructive detection and evaluation of the quality of the honeycomb core in such honeycomb sandwich structure parts.

[0078] Embodiment 3

[0079] Figure 5 This is a flowchart of a detection image processing method provided in Embodiment 3 of the present invention. This embodiment is a refinement based on the above embodiment, and specifically describes the process of detection image processing. It should be noted that the technical details not described in detail in this embodiment can be referred to any of the above embodiments.

[0080] Specifically, Figure 5 As shown, the method specifically comprises the following steps:

[0081] S310, collecting a detection image of a honeycomb sandwich structure part including a metal mesh.

[0082] S320, performing Fourier transform on the detection image to obtain a first transformation result.

[0083] S330, establishing an array bandpass filter according to the tilt angle of the metal mesh and the size of the minimum repeating unit.

[0084] In this embodiment, the inclination angle of the metal mesh can be understood as the inclination angle of the edge of the grid in the metal mesh. The minimum repeating unit can be understood as the smallest grid unit constituting the metal mesh, for example, it can be a diamond structure. It should be noted that the inclination angle of the metal mesh and the size of the minimum repeating unit can both come from the actual value of the honeycomb sandwich structure parts containing the metal mesh, which can be obtained through metrology technologies such as X-ray detection technology, optical measurement technology, or by querying the technical information of its supplier. The array bandpass filter can be understood as a bandpass filter composed of multiple array points, for example, it can be a Butterworth filter, wherein the bandpass filter can be understood as a device that allows signals (features) of a specific frequency band to pass through while shielding other frequency bands.

[0085] Optionally, the center frequency of the array bandpass filter is the same as the center frequency of the first transformation result;

[0086] The ratio of the spacing between notch positions in the array bandpass filter is the same as the ratio of the long side to the short side of the minimum repeating unit, and the angles of the array points are respectively perpendicular to the long side and the short side of the minimum repeating unit.

[0087] S340 , filtering the first transformation result through an array bandpass filter to obtain a filtering result.

[0088] S350, performing inverse Fourier transform on the filtering result to obtain a processed detection image.

[0089] Exemplarily, a detection image I1 of a honeycomb sandwich structure part including a metal mesh is collected; a Fourier transform is performed on the detection image to obtain a first transformation result F1; when the minimum repeating unit of the metal mesh is a diamond structure, the two diagonal lengths of the diamond structure, the long side length c, the short side length d, the inclination angle δ corresponding to the long side, and the inclination angle φ corresponding to the short side are measured to establish an array-type bandpass filter f0 whose center frequency is the same as the center frequency of F1, the ratio of the spacing between the notch positions is the same as the ratio of the long side c and the short side d of the minimum repeating unit, and the angles of the array points are respectively perpendicular to the long side and the short side of the minimum repeating unit; and the notch positions in f0 are proportionally amplified according to the magnification k of the size of I1 relative to the size of the honeycomb sandwich structure part including the metal mesh. F1 is filtered by f0 to obtain a filtering result, that is, F=F1-f0×k; the filtered frequency domain signal F is subjected to inverse Fourier transform processing to obtain a detection image of the honeycomb sandwich structure part in which the interference information of the metal mesh structure is eliminated and the honeycomb core structure information is retained, that is, a processed detection image is obtained.

[0090] For example, Figure 6 This is a schematic diagram of a detection image of a honeycomb sandwich structure part containing a metal mesh before treatment provided in the third embodiment of the present invention. Figure 6 As shown, there is an obvious grid-like shadow in the rectangular frame.

[0091] For example, Figure 7 This is a schematic diagram of a processed detection image of a honeycomb sandwich structure part containing a metal mesh provided in the third embodiment of the present invention. Figure 7 As shown, there is only honeycomb core structure information in the rectangular frame.

[0092] A detection image processing method provided in Example 3 of the present invention is refined on the basis of the above-mentioned embodiment. First, a detection image of a honeycomb sandwich structure part including a metal mesh is collected; then, a Fourier transform is performed on the detection image to obtain a first transformation result; then, an array bandpass filter is established according to the inclination angle of the metal mesh and the size of the minimum repeating unit, and an array bandpass filter is directly generated according to the structural characteristics of the metal mesh, which helps to improve the effect of eliminating interference information of the metal mesh; then, the first transformation result is filtered by the array bandpass filter to obtain a filtered result; finally, the filtered result is inverse Fourier transformed to obtain a processed detection image. The above technical scheme establishes an array bandpass filter according to the inclination angle of the metal mesh and the size of the minimum repeating unit, and filters the first transformation result according to the array bandpass filter to remove interference in the frequency domain, and then inverse Fourier transforms the filtering result to obtain a processed detection image, which can effectively suppress or remove the interference image caused by the metal mesh, and is only sensitive to the metal mesh interference information in the detection image. During the image processing process, the detection image result of the honeycomb core morphology under the metal mesh layer will not be changed, and no additional interference images will be introduced, which helps to obtain the processed detection image more simply, efficiently and accurately, improves the identifiability of defects in the honeycomb core under the metal mesh layer in the honeycomb sandwich structure parts, and helps to solve the problem of non-destructive detection and evaluation of the quality of the honeycomb core in such honeycomb sandwich structure parts.

[0093] Embodiment 4

[0094] Figure 8 This is a schematic diagram of the structure of a detection image processing device provided in Embodiment 4 of the present invention, and the device can execute the detection image processing method provided in the embodiment of the present invention. The detection image processing device provided in this embodiment includes:

[0095] The image acquisition module 410 is used to acquire the detection image of the honeycomb sandwich structure part including the metal mesh.

[0096] The Fourier transform module 420 is used to perform Fourier transform on the detection image to obtain a first transformation result;

[0097] A filtering module 430, configured to filter the first transformation result according to the characteristics of the metal mesh to obtain a filtering result;

[0098] The inverse Fourier transform module 440 is used to perform inverse Fourier transform on the filtering result to obtain a processed detection image.

[0099] A detection image processing device provided in the fourth embodiment of the present invention first collects a detection image of a honeycomb sandwich structure part containing a metal mesh, then performs Fourier transformation on the detection image to obtain a first transformation result, then filters the first transformation result according to the characteristics of the metal mesh to obtain a filtering result, and finally performs inverse Fourier transformation on the filtering result to obtain a processed detection image. The above technical scheme, by performing Fourier transformation on the detection image of the honeycomb sandwich structure part containing a metal mesh, then filtering the detection image after Fourier transformation according to the characteristics of the metal mesh, and finally performing inverse Fourier transformation on the filtering result, obtains a processed detection image, which can effectively eliminate the interference information caused by the metal mesh in the image of the traditional X-ray detection method, and at the same time does not affect the inherent structural image characteristics of the honeycomb core under the metal mesh coverage area, improves the identifiability of the defects of the honeycomb core under the metal mesh layer in the honeycomb sandwich structure part, and helps to solve the problem of non-destructive detection and evaluation of the quality of the honeycomb core in such honeycomb sandwich structure parts.

[0100] Optionally, the image acquisition module 410 is specifically used for:

[0101] Use digital radiographic testing equipment to collect test images of honeycomb sandwich structure parts containing metal mesh; or,

[0102] A film radiographic inspection device is used to shoot radiographic films of the honeycomb sandwich structure parts containing metal meshes, and a film scanner is used to convert the radiographic films of the honeycomb sandwich structure parts containing metal meshes into inspection images.

[0103] Optionally, the filtering module 430 includes:

[0104] An image acquisition unit, used for acquiring a sample image of the metal mesh;

[0105] A Fourier transform unit, used for performing Fourier transform on the sample image to obtain a second transform result;

[0106] The first filtering unit is used to filter the first transformation result according to the frequency domain characteristics of the second transformation result to obtain a filtering result.

[0107] Optionally, before the Fourier transform unit, the device further includes:

[0108] A determination unit, used to determine the rotation amount and scaling amount of the sample image;

[0109] The processing unit is used to rotate and scale the sample image according to the rotation amount and the scaling amount, so that the size of the sample image and the metal mesh grid arrangement angle are consistent with the detection image.

[0110] Optionally, determine the unit, specifically for:

[0111] Calculate the ratio coefficient between the length of the specified side of the metal grid in the sample image and the length of the corresponding side of the metal grid in the detection image as the scaling amount;

[0112] The offset angle of the tilt angle of the specified edge of the metal mesh in the sample image and the tilt angle of the corresponding edge of the metal mesh in the detection image is calculated as the rotation amount.

[0113] Optionally, the filtering module 430 includes:

[0114] An establishing unit, used for establishing an array bandpass filter according to the tilt angle of the metal mesh and the size of the minimum repeating unit;

[0115] The second filtering unit is used to filter the first transformation result through an array bandpass filter to obtain a filtering result.

[0116] Optionally, the center frequency of the array bandpass filter is the same as the center frequency of the first transformation result;

[0117] The ratio of the spacing between notch positions in the array bandpass filter is the same as the ratio of the long side to the short side of the minimum repeating unit, and the angles of the array points are respectively perpendicular to the long side and the short side of the minimum repeating unit.

[0118] The detection image processing device provided in the fourth embodiment of the present invention can be used to execute the detection image processing method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0119] Embodiment 5

[0120] Fig. 9 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device 10 can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, user equipment, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or required herein.

[0121] like Fig. 9As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0122] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, wireless networks.

[0123] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the detection image processing method.

[0124] In some embodiments, the detection image processing method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the detection image processing method in any other appropriate manner (e.g., by means of firmware).

[0125] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0126] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0127] In the context of the present invention, a computer-readable storage medium may be a tangible medium that may contain or store a computer program for use by or in combination with an instruction execution system, device or equipment. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0128] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device 10 having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device 10. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0129] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0130] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0131] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in the present invention can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of the present invention can be achieved, and this document does not limit this.

[0132] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A detection image processing method, characterized in that: include: Collect inspection images of honeycomb sandwich structure parts containing metal mesh; Performing Fourier transform on the detection image to obtain a first transform result; Filtering the first transformation result according to the characteristics of the metal mesh to obtain a filtering result; Perform inverse Fourier transform on the filtering result to obtain a processed detection image.

2. The method according to claim 1, characterized in that Capture inspection images of honeycomb sandwich structure parts containing metal mesh, including: Use digital radiographic testing equipment to collect test images of honeycomb sandwich structure parts containing metal mesh; or, A film ray detection device is used to shoot a ray film of a honeycomb sandwich structure part containing a metal mesh, and a film scanner is used to convert the ray film of the honeycomb sandwich structure part containing a metal mesh into a detection image.

3. The method according to claim 1, characterized in that Filtering the first transformation result according to the characteristics of the metal mesh includes: Collecting a sample image of the metal mesh; Performing Fourier transform on the sample image to obtain a second transform result; The first transformation result is filtered according to the frequency domain characteristics of the second transformation result to obtain a filtering result.

4. The method according to claim 3, characterized in that Before performing Fourier transform on the sample image to obtain a second transform result, the method further includes: Determining a rotation amount and a scaling amount for the sample image; The sample image is rotated and scaled according to the rotation amount and the scaling amount, so that the size of the sample image and the metal mesh grid arrangement angle are consistent with the detection image.

5. The method according to claim 4, characterized in that The determining of the rotation amount and the scaling amount of the sample image comprises: Calculating a ratio coefficient between the length of a designated side of the metal grid in the sample image and the length of a corresponding side of the metal grid in the detection image as the scaling amount; The tilt angle of the designated side of the metal grid in the sample image and the offset angle of the tilt angle of the corresponding side of the metal grid in the detection image are calculated as the rotation amount.

6. The method according to claim 1, characterized in that Filtering the first transformation result according to the characteristics of the metal mesh includes: Establishing an array bandpass filter according to the tilt angle of the metal mesh and the size of the minimum repeating unit; The first transformation result is filtered by the array bandpass filter to obtain a filtering result.

7. The method according to claim 6, characterized in that The center frequency of the array bandpass filter is the same as the center frequency of the first transformation result; The ratio of the spacing between notch positions in the array bandpass filter is the same as the ratio of the long side to the short side of the minimum repeating unit, and the angles of the array points are respectively perpendicular to the long side and the short side of the minimum repeating unit.

8. A detection image processing device, characterized in that: include: An image acquisition module, used for acquiring detection images of honeycomb sandwich structure parts including metal mesh; A Fourier transform module, used for performing Fourier transform on the detection image to obtain a first transform result; A filtering module, used for filtering the first transformation result according to the characteristics of the metal mesh to obtain a filtering result; The inverse Fourier transform module is used to perform inverse Fourier transform on the filtering result to obtain a processed detection image.

9. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the detection image processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the detection image processing method as described in any one of claims 1 to 7 is implemented.

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