CN114280058A - Grating projection-based refractory brick surface defect detection method - Google Patents
Grating projection-based refractory brick surface defect detection method Download PDFInfo
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Abstract
A refractory brick surface defect detection method based on grating projection comprises the following steps: s1: generating a standard sinusoidal grating pattern by using a computer; s2: projecting a grating pattern onto the surface of the refractory brick by a projector; s3: synchronously acquiring a grating pattern projected on the surface of the refractory brick by a camera and transmitting the grating pattern to a computer; s4: extracting the phase by using a six-step phase shift method to obtain a wrapped phase diagram; s5: expanding the phase by using a three-frequency heterodyne method to obtain an absolute phase diagram; s6: extracting the defect edge of the absolute phase diagram through the abnormal change of the absolute phase at the defect; s7: carrying out bilateral filtering on the defect edge to filter edge noise; s8: carrying out threshold segmentation on the filtered image to obtain a binary image; s9: performing morphological treatment and marking defects. The method adopts six-step phase shift to extract the phase, ensures the accuracy of phase extraction, meets the requirement of surface quality detection of the refractory bricks, and has higher detection accuracy.
Description
Technical Field
The invention relates to the technical field of refractory brick surface defect detection, in particular to a refractory brick surface defect detection method based on grating projection.
Background
In the production process of resistant firebrick, because of the technology level, the outward appearance defects such as the mole, the solution cavity, crackle that cause such as personnel's misoperation have seriously influenced resistant firebrick's life, present, resistant firebrick surface quality detects mainly through traditional manual detection's method, manual detection exists detection efficiency low, the accuracy is not high, receive the great scheduling problem of influence of artificial experience and subjective factor, and resistant firebrick has complicated texture background, the degree of difficulty of defect detection such as mole, the solution cavity has been increased, it has become the problem that awaits the solution urgently.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: how to improve the accuracy of the surface defect detection of the refractory brick, avoid manual errors and realize the automation of the surface defect detection of the refractory brick, thereby providing a method for detecting the surface defect of the refractory brick based on grating projection.
The purpose of the invention is realized by the following technical scheme:
a refractory brick surface defect detection method based on grating projection comprises the following steps:
s1: generating a standard sinusoidal grating pattern by using a computer;
s2: projecting a grating pattern onto the surface of the refractory brick by a projector;
s3: synchronously acquiring a grating pattern projected on the surface of the refractory brick by a camera and transmitting the grating pattern to a computer;
s4: extracting the phase by using a six-step phase shift method to obtain a wrapped phase diagram;
s5: expanding the phase by using a three-frequency heterodyne method to obtain an absolute phase diagram;
s6: extracting the defect edge of the absolute phase diagram through the abnormal change of the absolute phase at the defect;
s7: carrying out bilateral filtering on the defect edge to filter edge noise;
s8: carrying out threshold segmentation on the filtered image to obtain a binary image;
s9: performing morphological treatment and marking defects.
In step S1, a standard raster pattern is generated by a computer as follows:
wherein, I is the gray value of a pixel point in the image; g is the maximum value of the raster image gray scale, generally 255; n is a horizontal and vertical pixel point in the image; t is the grating fringe period; δ is the initial phase.
The raster image of the firebrick surface acquired by the camera in step S3 is as follows:
wherein, Ii(x, y) is the gray value at the image pixel coordinate (x, y); a (x, y) is the average gray scale of the image; b (x, y) is a modulation degree of the image;
is the wrapped phase at pixel coordinate (x, y); n is a positive integer.
In the step S4, a six-step phase shift method is used for extracting the phase to obtain the wrapping phase
The following equation.
In step S5, the wrapping phase is unwrapped by using a three-frequency heterodyne method, and the obtained absolute phase is as follows:
where φ (x, y) is the absolute phase at the pixel coordinate (x, y) and k (x, y) is the fringe order.
The defect edge extraction in step S6 mainly refers to performing defect edge extraction by performing two convolutions in the horizontal and vertical directions, respectively.
The first convolution is to perform convolution operation on an absolute phase value of each pixel point in an image by using a convolution kernel of a Sobel operator in the horizontal direction of 1 × 3 and a convolution kernel of a Sobel operator in the vertical direction of 3 × 1, wherein the convolution kernels are as follows:
a horizontal direction and a vertical direction;
the second convolution is performed by using a convolution kernel with 3 × 3 horizontal and vertical directions as follows:
the horizontal direction is vertical.
The bilateral filtering in step S7 is to perform bilateral filtering on the phase map after two convolutions in order to better maintain the edge and remove the noise of the defective edge.
In step S8, the filtered image is subjected to threshold segmentation, mainly by using a single global threshold.
The morphological processing mainly comprises the steps of carrying out expansion first and then corrosion processing on the binary image, and communicating the edge area of the defect to obtain the defect.
The invention has the beneficial effects that: by adopting the technical scheme, the phase is extracted by adopting six-step phase shift, so that the accuracy of phase extraction is ensured; performing phase expansion on the wrapped phase by using a three-frequency heterodyne principle to obtain an accurate absolute phase; and accurately extracting the defect edge in the absolute phase diagram by using an edge extraction algorithm. The method meets the requirements of the surface quality detection of the refractory bricks, has high detection precision, and realizes the accurate identification and positioning of the surface defects of the refractory bricks.
Drawings
FIG. 1 is a system structure diagram of a method for detecting surface defects of refractory bricks based on grating projection according to the present invention;
FIG. 2 is a flow chart of a method for detecting surface defects of refractory bricks based on grating projection provided by the invention;
FIG. 3 is a computer-generated raster pattern of a particular embodiment of the present invention;
FIG. 4 is a graph of a firebrick surface deformation grating collected by a camera in accordance with an embodiment of the present invention;
FIG. 5 is a phase unwrapped absolute phase diagram of an embodiment of the present invention;
FIG. 6 is an edge extraction diagram according to an embodiment of the present invention;
FIG. 7 is a filter diagram of an embodiment of the present invention;
fig. 8 is a defect diagram of an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, a method for detecting surface defects of refractory bricks based on grating projection comprises a computer 1, and a DLP projector 3 and a camera 2 connected with the computer, wherein the DLP projector 3 and the camera 2 are both facing the refractory bricks on a workbench, and the method is as shown in fig. 2:
s1: generating a standard sinusoidal grating pattern by using a computer 1;
s2: projecting the sinusoidal grating pattern onto the surface of the refractory brick by a projector 3;
s3: the camera 2 synchronously acquires the sinusoidal grating patterns projected on the surface of the refractory brick and transmits the sinusoidal grating patterns to the computer 1;
s4: extracting the phase by using a six-step phase shift method to obtain a wrapped phase diagram;
s5: expanding the phase by using a three-frequency heterodyne method to obtain an absolute phase diagram;
s6: extracting the defect edge of the absolute phase diagram through the abnormal change of the absolute phase at the defect;
s7: carrying out bilateral filtering on the defect edge to filter edge noise;
s8: carrying out threshold segmentation on the filtered image to obtain a binary image;
s9: performing morphological treatment and marking defects.
In step S1, a standard raster pattern is generated by a computer as follows:
wherein, I is the gray value of a pixel point in the image; g is the maximum value of the raster image gray scale, generally 255; n is a horizontal and vertical pixel point in the image; t is the grating fringe period; δ is the initial phase.
The raster image of the firebrick surface acquired by the camera 2 in step S3 is as follows:
wherein, Ii(x, y) is the gray value at the image pixel coordinate (x, y); a (x, y) is the average gray scale of the image; b (x, y) is a modulation degree of the image;
is the wrapped phase at pixel coordinates (x, y), N is a positive integer.
In the step S4, a six-step phase shift method is used for extracting the phase to obtain the wrapping phase
The following were used:
in step S5, the wrapping phase is unwrapped by using a three-frequency heterodyne method, and the obtained absolute phase is as follows:
where φ (x, y) is the absolute phase at the pixel coordinate (x, y) and k (x, y) is the fringe order.
The defect edge extraction in step S6 mainly refers to performing defect edge extraction by performing two convolutions in the horizontal and vertical directions, respectively.
The first convolution is to perform convolution operation on an absolute phase value of each pixel point in an image by using a convolution kernel of a Sobel operator in the horizontal direction of 1 × 3 and a convolution kernel of a Sobel operator in the vertical direction of 3 × 1, wherein the convolution kernels are as follows:
horizontal direction and vertical direction
The second convolution is performed by using a convolution kernel with 3 × 3 horizontal and vertical directions as follows:
horizontal direction and vertical direction
The bilateral filtering in step S7 is to perform bilateral filtering on the phase map after two convolutions in order to better maintain the edge and remove the noise of the defective edge.
In step S8, the filtered image is subjected to threshold segmentation, mainly by using a single global threshold.
The morphological processing in step S9 mainly includes: and (4) carrying out expansion and corrosion treatment on the binary image, communicating the edge area of the defect, and accurately identifying the defect.
The method comprises the following specific embodiments:
generating a standard sinusoidal grating pattern by using a computer; the standard sinusoidal grating in this example mainly refers to 36 grating patterns of horizontal and vertical grating patterns with frequencies of 23, 27 and 174, respectively, and 18 grating patterns in the horizontal and vertical directions are shown in fig. 3; projecting a grating pattern onto the surface of the refractory brick by a projector; the projector in this example is a DLP projector with a resolution of 1280 × 720.
Synchronously acquiring a grating pattern projected on the surface of the refractory brick by a camera and transmitting the grating pattern to a computer; the camera in this example was a CMOS camera with a resolution of 5472 x 3468 and was triggered to acquire simultaneously as the projector projected the grating pattern onto the firebrick surface, the acquired anamorphic grating pattern being as shown in fig. 4.
In the embodiment, a six-step phase shift method is adopted for phase extraction; the phase is unwrapped using a three-frequency heterodyne method to obtain an absolute phase diagram, as shown in fig. 5.
Extracting the defect edge of the absolute phase diagram through the abnormal change of the absolute phase at the defect; in this example, the Sobel operator is used to obtain the defect edge, and the gradient map obtained by the first convolution is shown in fig. 6 below. And carrying out image enhancement on the image, and carrying out second convolution.
The defective edge is filtered bilaterally to remove edge noise, as shown in fig. 7.
Carrying out threshold segmentation on the filtered image to obtain a binary image; in this example, the segmentation is directly performed by a single global threshold, and the set threshold is 40, which can be specifically set according to the actual situation.
Performing morphological treatment and marking defects; in this example, the morphological processing mainly refers to performing an operation of expanding and then corroding on the binary image, connecting the defect edges and filling according to the edges to obtain real defects, as shown in fig. 8.
The minimum defect that can detect in this example is degree of depth 0.2mm, and width 0.5mm has satisfied the requirement that firebrick surface quality detected, has higher detection accuracy.
The invention has been described in detail by way of example and implementation techniques, but it is not intended to limit the scope of the invention. Modifications to the present invention will occur to those skilled in the art and are intended to be within the scope of the present invention, which is defined by the appended claims.
Claims (10)
1. A refractory brick surface defect detection method and system based on grating projection are characterized by comprising the following steps:
s1: generating a standard sinusoidal grating pattern by using a computer;
s2: projecting the sinusoidal grating pattern onto the surface of the refractory brick by a projector;
s3: a camera synchronously acquires the sinusoidal grating patterns projected on the surface of the refractory brick and transmits the sinusoidal grating patterns to a computer;
s4: extracting the phase by using a six-step phase shift method to obtain a wrapped phase diagram;
s5: expanding the phase by using a three-frequency heterodyne method to obtain an absolute phase diagram;
s6: extracting the defect edge of the absolute phase diagram through the abnormal change of the absolute phase at the defect;
s7: carrying out bilateral filtering on the defect edge to filter edge noise;
s8: carrying out threshold segmentation on the filtered image to obtain a binary image;
s9: performing morphological treatment and marking defects.
2. The method for detecting defects on the surface of refractory bricks based on grating projection as claimed in claim 1, wherein the standard grating pattern generated by the computer in step S1 is as follows:
wherein, I is the gray value of a pixel point in the image; g is the maximum value of the raster image gray scale, generally 255; n is a horizontal and vertical pixel point in the image; t is the grating fringe period; δ is the initial phase.
3. The method for detecting the surface defects of the refractory bricks based on the grating projection as claimed in claim 1, wherein the camera in the step S2 is a CMOS camera, and the projector is a DLP projector.
4. The method for detecting defects on the surface of refractory bricks based on grating projection as claimed in claim 1, wherein the grating image of the surface of refractory bricks acquired by the camera in step S3 is as follows:
wherein, Ii(x, y) is the gray value at the image pixel coordinate (x, y); a (x, y) is the average gray scale of the image; b (x, y) is a modulation degree of the image;
is the wrapped phase at pixel coordinate (x, y); n is a positive integer.
5. The method for detecting the surface defects of refractory bricks based on grating projection as claimed in claim I, wherein the step S4 is to extract the phase by six-step phase shift method to obtain the wrapped phase
The following were used:
6. the method for detecting the defects on the surface of the refractory brick based on the grating projection as claimed in claim 1, wherein the wrapping phase is phase-unwrapped by the triple-frequency heterodyne method in step S5, and the obtained absolute phase Φ (x, y) is as follows:
where φ (x, y) is the absolute phase at the pixel coordinate (x, y) and k (x, y) is the fringe order.
7. The method as claimed in claim 1, wherein the defect edge extraction in step S6 is performed by performing two convolutions in horizontal and vertical directions respectively.
8. The method for detecting the defects on the surface of the refractory brick based on the grating projection as claimed in claim 7, wherein the first convolution uses a convolution kernel of 1 x 3 in the horizontal direction and a convolution kernel of 3 x 1 in the vertical direction of a Sobel operator to perform convolution operation on the absolute phase value of each pixel point in the image, and the convolution kernels are as follows:
a horizontal direction and a vertical direction;
the second convolution uses a convolution kernel that is 3 × 3 horizontally and vertically as follows:
the horizontal direction is vertical.
9. The method for detecting defects on surfaces of refractory bricks based on grating projection as claimed in claim 1, wherein the bilateral filtering in step S7 is: in order to better preserve the edges and remove the noise of the defective edges, the twice-convolved phase map is filtered.
10. The method for detecting the surface defects of the refractory bricks based on the grating projection as claimed in claim 1, wherein the morphological processing in step S9 mainly comprises: and (4) carrying out expansion and corrosion treatment on the binary image, communicating the edge area of the defect, and accurately identifying the defect.
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| CN116559179A (en) * | 2023-07-06 | 2023-08-08 | 海伯森技术（深圳）有限公司 | Reflective surface morphology and defect detection method and system thereof |
| CN116958049A (en) * | 2023-06-15 | 2023-10-27 | 湖南视比特机器人有限公司 | Automatic detection method for automobile paint defects based on deep learning and storage medium |
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Cited By (5)
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| CN114923437A (en) * | 2022-05-19 | 2022-08-19 | 四川大学 | Novel three-dimensional measurement method and device based on defocusing binary square wave stripes |
| CN114923437B (en) * | 2022-05-19 | 2023-09-26 | 四川大学 | Three-dimensional measurement method and device based on defocused binary square wave fringes |
| CN116958049A (en) * | 2023-06-15 | 2023-10-27 | 湖南视比特机器人有限公司 | Automatic detection method for automobile paint defects based on deep learning and storage medium |
| CN116559179A (en) * | 2023-07-06 | 2023-08-08 | 海伯森技术（深圳）有限公司 | Reflective surface morphology and defect detection method and system thereof |
| CN116559179B (en) * | 2023-07-06 | 2023-09-12 | 海伯森技术（深圳）有限公司 | Reflective surface morphology and defect detection method and system thereof |
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