CN106442556A - Device and method for detecting surface defects of perforated plate workpiece - Google Patents
Device and method for detecting surface defects of perforated plate workpiece Download PDFInfo
- Publication number
- CN106442556A CN106442556A CN201611007125.2A CN201611007125A CN106442556A CN 106442556 A CN106442556 A CN 106442556A CN 201611007125 A CN201611007125 A CN 201611007125A CN 106442556 A CN106442556 A CN 106442556A
- Authority
- CN
- China
- Prior art keywords
- image
- shaped
- value
- light source
- special
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000007547 defect Effects 0.000 title claims abstract description 47
- 238000000034 method Methods 0.000 title claims abstract description 14
- 238000001514 detection method Methods 0.000 claims abstract description 16
- 238000001228 spectrum Methods 0.000 claims description 32
- 239000011159 matrix material Substances 0.000 claims description 30
- 238000005286 illumination Methods 0.000 claims description 13
- 230000003044 adaptive effect Effects 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 238000001914 filtration Methods 0.000 claims description 6
- 238000009499 grossing Methods 0.000 claims description 6
- 230000003287 optical effect Effects 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims 1
- 238000003708 edge detection Methods 0.000 description 6
- 238000003709 image segmentation Methods 0.000 description 5
- 238000007781 pre-processing Methods 0.000 description 5
- 230000000007 visual effect Effects 0.000 description 5
- 230000005540 biological transmission Effects 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 230000003595 spectral effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000003384 imaging method Methods 0.000 description 1
- 230000001678 irradiating effect Effects 0.000 description 1
- 238000003754 machining Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/89—Investigating the presence of flaws or contamination in moving material, e.g. running paper or textiles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
- G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
- G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques
Landscapes
- Chemical & Material Sciences (AREA)
- Biochemistry (AREA)
- Pathology (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Immunology (AREA)
- Analytical Chemistry (AREA)
- Engineering & Computer Science (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Signal Processing (AREA)
- Textile Engineering (AREA)
- Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)
Abstract
The invention discloses a device and method for detecting surface defects of a perforated plate workpiece. The system comprises a transfer system, a special-shaped illuminating light source, an industrial charge coupled device (CCD) image sensor, an image acquisition card and a processor. A to-be-detected perforated plate workpiece is horizontally arranged in the transfer system; the special-shaped illuminating light source adopts a shed-shaped structure light source of which the top is arc-shaped and the horizontal section is rectangular, and is arranged at the periphery of a lens of the industrial CCD image sensor; the industrial CCD image sensor comprises a camera main body, a lens and an interface C; the camera main body adopts an industrial CCD camera and is connected with the lens through the interface C; the lens is arranged on the inner side of the special-shaped illuminating light source and is perpendicular to the to-be-detected perforated plate workpiece; the image acquisition card serves as the connector of an image acquisition part and an image processing part; the processor is used for realizing the operation of corresponding codes in a programming environment, calculating and marking the defect positions and intuitively displaying the defect positions. According to the detection device disclosed by the invention, the surface defect positions can be accurately displayed, and the workpiece defect information is acquired instead of human eyes, therefore, the detection accuracy is high.
Description
Technical Field
The invention relates to a device and a method for detecting surface defects of a plate-shaped workpiece with holes, and belongs to the field of visual detection.
Background
Plate-shaped holed workpieces have been widely used in recent years for machining of machine tools, manufacturing of medical instruments, and vehicle devices. At present, most manufacturers still manually search for the surface defects of the plate-shaped porous workpiece, the surface defects are not only harmful to human eyes, but also have low efficiency and high cost, the specific positions of the surface defects of the workpiece cannot be accurately found, and visual errors are easily caused by people, so that the quality of the workpiece is reduced, the missing detection and the false detection are caused, and the product price and the market competitiveness are greatly reduced.
Manufacturers have been able to determine the integrity of the workpiece surface by observing the default degree of point light sources reaching the receiving plate by irradiating the surface of the workpiece with point light sources arranged at multiple points through technical improvement and laser scanning detection. The detection method is complex in action, the positions of the light emitting points of the laser generator need to be arranged in advance, the cost of the laser generator and the later maintenance cost are high, and the cost of flaw detection is increased.
Disclosure of Invention
Aiming at the prior art, the invention provides a device and a method for detecting the surface defects of a plate-shaped perforated workpiece, which are used for solving the technical problems existing in the detection of the surface defects of the plate-shaped perforated workpiece.
The invention relates to a device for detecting surface defects of a plate-shaped workpiece with holes, which adopts the technical scheme that: the device comprises a transmission system, a special-shaped illumination light source, an industrial CCD image sensor, an image acquisition card and a processor; the conveying system is used for horizontally conveying the plate-shaped perforated workpiece to be detected and conveying the plate-shaped perforated workpiece in a uniform-speed linear mode; the special-shaped illuminating light source is used for providing a uniform illuminating light source, and can cover the whole area where the plate-shaped perforated workpiece to be detected is located; the industrial CCD image sensor is used for converting an optical signal into an electric signal to complete an image acquisition part; the image acquisition card is used for receiving the electric signal acquired from the camera, performing A/D conversion on the acquired analog signal, storing and processing image information and transmitting data information to the processor; the processor realizes the running of corresponding codes in a programming environment, calculates and marks defect positions and visually displays the defect positions;
the plate-shaped perforated workpiece to be detected is horizontally arranged in the conveying system; the special-shaped illuminating light source is a shed-shaped structure light source with an arc top and a rectangular horizontal section, and can cover the whole area where the plate-shaped perforated workpiece to be detected is located; the special-shaped lighting source is arranged around the lens of the industrial CCD image sensor and is fixedly connected with the industrial CCD image sensor; the mathematical expression of the geometric model of the special-shaped illumination light source is as follows:
(1)
wherein,、in order to be a coefficient of an unknown number,、、is a boundary value; the industrial CCD image sensor comprises: the camera comprises a camera body, a lens and a C interface; the camera main body adopts an industrial CCD camera; the camera body is connected with the lens through a C interface; the lens is arranged on the inner side of the special-shaped lighting source and is vertical to the plate-shaped workpiece with the holes to be detected; the image acquisition card is an interface between the image acquisition part and the image processing part.
The invention provides a method for detecting surface defects of a plate-shaped perforated workpiece, which utilizes the device for detecting the surface defects of the plate-shaped perforated workpiece and comprises the following steps:
the plate-shaped perforated workpiece to be detected is horizontally arranged in the conveying system and moves through the lower part of the lens at a constant speed in a linear mode, and the lens collects complete image information in real time; the industrial CCD image sensor converts optical signals into electric signals, the image acquisition card receives the electric signals acquired from the camera, the analog signals acquired are subjected to A/D conversion, image information is stored and processed, and the image acquisition card transmits the data information to the processor; in a processor, firstly, preprocessing an image through programming software to improve the visual effect and definition of the image, wherein the preprocessing comprises histogram equalization processing, normalization processing and median filtering, and then, carrying out binarization processing on the image according to the characteristics of the image; secondly, using an edge detection technology, delineating the outline of each object by using edge points while suppressing noise, and analyzing some targets needing to be identified in the image; and then, by means of an image segmentation technology, comparing abnormal positions of the significant values in the image to mark the region, finally extracting image features, and visually finding the positions of the defects.
Step one, calculating a spectrum residual algorithm:
firstly, carrying out two-dimensional discrete Fourier transform on an input gray image, and transferring the image from a spatial domain to a frequency domain:whereinis a spatial domain coordinate of the gray-scale image,is a gray scale image frequency domain coordinate;
(2)
wherein,is the point fourier spectral value. And then, calculating a magnitude spectrum and a phase spectrum:
(3)
(4)
taking logarithm of the amplitude spectrum to obtain a Log spectrum of the amplitude:
(5)
and then, carrying out smooth filtering on the Log spectrum to obtain the approximate shape of the Log spectrum:
(6)
wherein,is oneThe smoothing filter of (2) is preferably a filter,is the spatial bandwidth of the smoothing filter. And solving the difference value of the two to obtain a spectrum residual:
(7)
for spectrum residual errorSum phase spectrumPerforming two-dimensional inverse Fourier transform to obtain
(8)
Wherein,representing the saliency value of each point coordinate in the grayscale image.
Step two, setting a threshold value:
the invention adopts two methods to set the threshold valueRespectively comparing the threshold with the significant value of each pixel point in the same image, marking the pixel point with the significant value more than or equal to the threshold as '1', and marking as a target area; and marking the pixel point with the significant value smaller than the threshold value as 0 and marking as a background area.
Solving for a threshold value according to an adaptive threshold algorithm. Will be provided withSet to the average saliency value for a given image:
(9)
wherein,、corresponding to the length and width of the image. Each significant value of the acquired image is compared with an adaptive threshold valueComparing, marking the pixel points which are more than or equal to the threshold value as '1', marking the pixel points which are less than the threshold value as '0', and marking all the pixels in the imageThe set of points consisting of 0 and 1Line ofColumn matrixAnd (4) showing.
Solving for a threshold value according to the law of the law. Record the range of significant value of the image as，(The most significant value). Presetting a threshold valueThe above image saliency values are divided into two categories:,and will beAndthe variance between the two classes is respectively marked as target and background:
(10)
(11)
(12)
wherein,indicating a saliency value in an image belowThe number of the pixels of (a) is,representing saliency values in an image higher than or equal toThe number of the pixels of (a) is,is belowIs determined by the average saliency value of the total pixels,is higher than or equal toAverage saliency value of the total pixels of (1);
so thatOf greatest valueThe value is the required threshold valueI.e. by. Then will beComparing with each salient value of the image, marking the pixel points which are more than or equal to the threshold value as '1', marking the pixel points which are less than the threshold value as '0', and collecting all the pixel points in the image by using the pixel points consisting of 0 and 1Line ofColumn matrixAnd (4) showing.
Step three, marking defects
Will matrixAnd matrixMultiplying corresponding elements to obtain new matrix. Namely:. The matrix is obtained by the formula of dot multiplicationThe pixel significance value is also composed of elements 0 and 1, wherein the element 1 represents that the pixel significance values are more than or equal to two threshold valuesI.e. the coinciding positions of the target images. Then sequentially searching three matrixes from left to right and from top to bottom、、The connected region of the medium element is 1, and the connected region of each matrix is respectively marked as、、 . Selecting matrixTo matrixAll elements in the list are summed and recorded as(ii) a For matrixAll elements in the list are summed and recorded as. Introducing a functionLet us order(13)
If it isThen the defect location is considered at r. If less thanIt is considered to be an error detection where the workpiece is defect free.
Compared with the prior art, the invention has the beneficial effects that:
according to the device and the method for detecting the surface defects of the plate-shaped perforated workpiece, the special-shaped illumination light source is adopted to replace the existing point light source, the uniform illumination can be realized, the light difference phenomenon does not exist, and the problem that the collected image is not clear due to the fact that the surface detection of the plate-shaped perforated workpiece to be detected is influenced by the illumination degree is solved. The invention has no synchronous time difference to the acquisition mode of the plate-shaped perforated workpiece image to be detected, can display the surface defect position of the plate-shaped perforated workpiece to be detected in real time, has high software and hardware interchange degree, is suitable for the visual imaging of a dynamic target object, and has high image precision and high color reduction degree.
Drawings
FIG. 1 is a structural diagram of a surface defect detecting device for a plate-shaped workpiece with holes, according to the present invention;
FIG. 2 is a schematic view of a special illumination source according to the present invention;
FIG. 3 is a flow chart of a detection system of the device for detecting surface defects of a plate-shaped workpiece with holes provided by the invention.
In the figure: 1-a transmission system, 2-a plate-shaped workpiece with holes to be detected, 3-a special-shaped illumination light source, 4-an industrial CCD image sensor, 5-an image acquisition card and 6-a processor.
Detailed Description
The present invention will be described in further detail with reference to specific embodiments.
As shown in FIG. 1, the device for detecting surface defects of a plate-shaped workpiece with holes comprises a conveying system 1, a special-shaped illumination light source 3, an industrial CCD image sensor 4, an image acquisition card 5 and a processor 6. The conveying system 1 is used for horizontally conveying the plate-shaped perforated workpiece 2 to be detected and conveying the workpiece in a uniform-speed linear mode; the special-shaped illuminating light source 3 is used for providing a uniform illuminating light source, and the special-shaped illuminating light source 3 can cover the whole area where the plate-shaped perforated workpiece 2 to be detected is located; the industrial CCD image sensor 4 is used for converting an optical signal into an electric signal to complete an image acquisition part; the image acquisition card 5 is used for receiving the electric signal acquired from the camera, performing A/D conversion on the acquired analog signal, storing and processing image information, and transmitting data information to the processor 6; the processor 6 realizes the running of corresponding codes in a programming environment, calculates and marks defect positions and visually displays the defect positions.
The plate-shaped perforated workpiece 2 to be detected is horizontally arranged in the conveying system 1; the special-shaped illuminating light source 3 is a light source with a shed-shaped structure, the top of the light source is arc-shaped, the horizontal section of the light source is rectangular, and the special-shaped illuminating light source 3 can cover the whole area where the plate-shaped perforated workpiece 2 to be detected is located; the special-shaped lighting source 3 is arranged around the lens of the industrial CCD image sensor 4 and is fixedly connected with the industrial CCD image sensor 4; the mathematical expression of the geometric model of the special-shaped illumination light source 3 is as follows:
(1)
wherein,、in order to be a coefficient of an unknown number,、、is a boundary value; the industrial CCD image sensor 4 comprises a camera body, a lens and a C interface; the camera main body adopts an industrial CCD camera; the camera body is connected with the lens through a C interface; the lens is vertical to the plate-shaped workpiece 2 with holes to be detected; the image acquisition card 5 is an interface between the image acquisition part and the image processing part.
The invention provides a method for detecting surface defects of a plate-shaped perforated workpiece, which utilizes the device for detecting the surface defects of the plate-shaped perforated workpiece and comprises the following steps:
the plate-shaped perforated workpiece 2 to be detected is horizontally arranged in the conveying system 1 and moves from the lower part of the lens at a constant speed in a straight line form, and the lens collects complete image information in real time; the industrial CCD image sensor 4 converts optical signals into electric signals, the image acquisition card 5 receives the electric signals acquired from the camera, the analog signals acquired are subjected to A/D conversion, image information is stored and processed, and the image acquisition card 5 transmits the data information to the processor 6; in the processor 6, firstly, the image is preprocessed through programming software, the visual effect and the definition of the image are improved, histogram equalization processing, normalization processing and median filtering are included, and then binarization processing is carried out on the image according to the image characteristics; secondly, using an edge detection technology, delineating the outline of each object by using edge points while suppressing noise, and analyzing some targets needing to be identified in the image; and then, by means of an image segmentation technology, comparing abnormal positions of the significant values in the image to mark the region, finally extracting image features, and visually finding the positions of the defects.
As shown in fig. 3, the detection flow of the device for detecting surface defects of a plate-shaped workpiece with holes sequentially comprises light source irradiation, image acquisition and transmission, image preprocessing, image edge detection, image segmentation and image identification, and finally defects are marked.
The light source irradiation adopts the special-shaped illumination light source 3 to project uniform light to the plate-shaped perforated workpiece 2 to be detected.
The image acquisition and transmission is that the lens acquires complete image data in real time, optical signals are converted into electric signals through the industrial CCD image sensor 4, the electric signals acquired from the camera are received through the image acquisition card 5, and the acquired analog signals are subjected to A/D conversion to acquire, store and transmit image information.
The image preprocessing is that the processor 6 firstly establishes a gray level histogram for the image and visually finds the distribution condition of the pixel brightness in the image; then, the histogram is equalized and normalized, so that the gray level of the image is uniformly distributed, the contrast is increased, and the image details are clearer; then, median filtering is carried out, noise of the image is filtered, detail information of the signal is protected, and the edge of the image is protected; and finally, carrying out binarization processing on the image, utilizing the difference of significant values in the image, comparing a set threshold value, classifying each pixel point into an area, marking the target area as '1', and marking the background area as '0', so that a gray image is changed into a binary image.
The image edge detection is to use edge points to outline each object and analyze the target to be identified in the image, i.e. to highlight the edge of the image to extract the image features.
And the image segmentation is to segment points with different brightness in the image after the identification edge detection and divide the points into a plurality of non-overlapping areas.
And the image recognition is to detect the plate-shaped perforated workpiece 2 to be detected by adopting a spectrum residual obvious target detection method and then recognize the surface defect position of the plate-shaped perforated workpiece 2 to be detected by using a comprehensive comparison method.
Step one, calculating a spectrum residual algorithm:
firstly, carrying out two-dimensional discrete Fourier transform on an input gray image, and transferring the image from a spatial domain to a frequency domain:whereinis a spatial domain coordinate of the gray-scale image,is a gray scale image frequency domain coordinate;
(2)
wherein,is the point fourier spectral value. And then, calculating a magnitude spectrum and a phase spectrum:
(3)
(4)
taking logarithm of the amplitude spectrum to obtain a Log spectrum of the amplitude:
(5)
and then, carrying out smooth filtering on the Log spectrum to obtain the approximate shape of the Log spectrum:
(6)
wherein,is oneThe smoothing filter of (2) is preferably a filter,is the spatial bandwidth of the smoothing filter. And solving the difference value of the two to obtain a spectrum residual:
(7)
for spectrum residual errorSum phase spectrumPerforming two-dimensional inverse Fourier transform to obtain
(8)
Wherein,representing the saliency value of each point coordinate in the grayscale image.
Step two, setting a threshold value:
the invention adopts two methods to set the threshold valueRespectively comparing the threshold with the significant value of each pixel point in the same image, marking the pixel point with the significant value more than or equal to the threshold as '1', and marking as a target area; marking the pixel point with the significant value smaller than the threshold value as 0 and marking as a background area;
solving according to an adaptive threshold algorithm. Will threshold valueSet to the average saliency value for a given image:
(9)
wherein,、corresponding to the length and width of the image. Each acquired significant value is compared with an adaptive threshold valueComparing, marking the pixel points which are more than or equal to the threshold value as '1' and the pixel points which are less than the threshold value as '0' through comparison, and gathering all the pixel points in the image and forming the pixel points by 0 and 1Line ofColumn matrixAnd (4) showing.
Solving according to the law of large form. Noting the range of image saliency values as,(The most significant value). Presetting a threshold valueThe above image saliency values are divided into two categories:,and will beAndthe variance between the two classes is respectively marked as target and background:
(10)
(11)
(12)
wherein,indicating a saliency value in an image belowThe number of the pixels of (a) is,representing saliency values in an image higher than or equal toThe number of the pixels of (a) is,is belowIs determined by the average saliency value of the total pixels,is higher than or equal toAverage saliency value of the total pixels of (1);
so thatOf greatest valueThe value is the required threshold valueI.e. by. Comparing T with each significant value of the image, marking the pixel points which are more than or equal to the threshold value as '1', marking the pixel points which are less than the threshold value as '0', and collecting all the pixel points in the image by using the pixel points consisting of 0 and 1Line ofColumn matrixAnd (4) showing.
Step three, marking defects
Will matrixAnd matrixMultiplying corresponding elements to obtain new matrix. Namely:. The matrix is obtained by the formula of dot multiplicationThe pixel significance value is also composed of elements 0 and 1, wherein the element 1 represents that the pixel significance values are more than or equal to two threshold valuesI.e. the coinciding positions of the target images. Then sequentially searching three matrixes from left to right and from top to bottom、、The connected region of the medium element is 1, and the connected region of each matrix is respectively marked as、、 . Selecting matrixTo matrixAll elements in the list are summed and recorded as(ii) a For matrixAll elements in the list are summed and recorded as. Introducing a functionLet us order(13)
If it isThen the defect location is considered at r. If less thanIt is considered to be an error detection where the workpiece is defect free.
In the present invention, the image preprocessing, image edge detection, and image segmentation techniques belong to the common general knowledge in the art, and those skilled in the art can reproduce the image according to the specific requirements of the object to be detected, and are not described herein again.
While the present invention has been described with reference to the drawings, the foregoing description is not intended to limit the invention to the particular form set forth, but is merely illustrative and not restrictive, and that those skilled in the art can, in light of the present teachings, make numerous changes without departing from the spirit or scope of the invention as defined by the appended claims.
Claims (5)
1. A device for detecting surface defects of a plate-shaped workpiece with a hole is characterized by comprising a conveying system (1), a special-shaped illumination light source (3), an industrial CCD image sensor (4), an image acquisition card (5) and a processor (6); the conveying system (1) is used for horizontally conveying the plate-shaped perforated workpiece (2) to be detected and conveying the workpiece in a uniform-speed linear mode; the special-shaped illuminating light source (3) is used for providing a uniform illuminating light source, and the special-shaped illuminating light source (3) can cover the whole area where the plate-shaped perforated workpiece (2) to be detected is located; the industrial CCD image sensor (4) is used for converting an optical signal into an electric signal to complete an image acquisition part; the image acquisition card (5) is used for receiving the electric signal acquired from the camera, performing A/D conversion on the acquired analog signal, storing and processing image information and transmitting data information to the processor (6); the processor (6) realizes the running of corresponding codes in a programming environment, calculates and marks defect positions and visually displays the defect positions;
the plate-shaped workpiece (2) with the hole to be detected is horizontally arranged in the conveying system (1); the special-shaped illuminating light source (3) is a shed-shaped structure light source with an arc-shaped top and a rectangular horizontal section, and the special-shaped illuminating light source (3) can cover the whole area where the plate-shaped perforated workpiece (2) to be detected is located; the special-shaped lighting source (3) is arranged around the lens of the industrial CCD image sensor (4) and is fixedly connected with the industrial CCD image sensor (4); the mathematical expression of the geometric model of the special-shaped illumination light source (3) is as follows:(1)
wherein,、in order to be a coefficient of an unknown number,、、is a boundary value; the industrial CCD image sensor (4) comprises a camera body, a lens and a C interface; the camera main body adopts an industrial CCD camera; the camera body is connected with the lens through a C interface; the above-mentionedThe lens is vertical to the plate-shaped workpiece (2) with holes to be detected; the image acquisition card (5) is an interface between the image acquisition part and the image processing part.
2. The apparatus for detecting surface defects of a plate-like holed workpiece according to claim 1, characterized in that: the special-shaped illuminating light source (3) is a shed-shaped structure light source with an arc-shaped top and a rectangular horizontal section, and the special-shaped illuminating light source (3) can cover the whole area where the plate-shaped perforated workpiece (2) to be detected is located; the special-shaped lighting source (3) is arranged around a lens of the industrial CCD image sensor (4) and is fixedly connected with the industrial CCD image sensor (4); the mathematical expression of the geometric model of the special-shaped illumination light source (3) is as follows:
(1)
wherein,、in order to be a coefficient of an unknown number,、、are boundary values.
3. A method for detecting surface defects of a plate-shaped perforated workpiece, which is characterized by adopting the device for detecting surface defects of a plate-shaped perforated workpiece according to claim 1 to carry out measurement, and comprises the following steps:
step one, calculating a spectrum residual algorithm:
firstly, carrying out two-dimensional discrete Fourier transform on an input gray image, and transferring the image from a spatial domain to a frequency domain:whereinis a spatial domain coordinate of the gray-scale image,is a gray scale image frequency domain coordinate;
(2) wherein,the point Fourier spectrum value is obtained;
and then, calculating a magnitude spectrum and a phase spectrum:
(3)
(4)
taking logarithm of the amplitude spectrum to obtain a Log spectrum of the amplitude:
(5)
and then, carrying out smooth filtering on the Log spectrum to obtain the approximate shape of the Log spectrum:
(6)
wherein,is oneThe smoothing filter of (2) is preferably a filter,is the spatial bandwidth of the smoothing filter;
and solving the difference value of the two to obtain a spectrum residual:
(7)
for spectrum residual errorSum phase spectrumPerforming two-dimensional inverse Fourier transform to obtain
(8)
Wherein,representing the saliency value of each point coordinate in the grayscale image.
4. Step two, setting a threshold value:
the invention adopts two methods to set the threshold valueRespectively comparing the threshold with the significant value of each pixel point in the same image, marking the pixel point with the significant value more than or equal to the threshold as '1', and marking as a target area; marking the pixel point with the significant value smaller than the threshold value as 0 and marking as a background area;
solving according to an adaptive threshold algorithm；
Will threshold valueSet to the average saliency value for a given image:(9)
wherein,、length and width of the corresponding image; each acquired significant value is compared with an adaptive threshold valueComparing, marking the pixel points which are more than or equal to the threshold value as '1' and the pixel points which are less than the threshold value as '0' through comparison, and gathering all the pixel points in the image and forming the pixel points by 0 and 1Line ofColumn matrixRepresents;
solving according to the law of large form(ii) a Noting the range of image saliency values as,(Maximum significant value); presetting a threshold valueThe above image saliency values are divided into two categories:,and will beAndthe variance between the two classes is respectively marked as target and background:
(10)
(11)
(12)
wherein,indicating a saliency value in an image belowThe number of the pixels of (a) is,representing saliency values in an image higher than or equal toThe number of the pixels of (a) is,is belowIs determined by the average saliency value of the total pixels,is higher than or equal toAverage saliency value of the total pixels of (1);
so thatOf greatest valueThe value is the required threshold valueI.e. by(ii) a Then comparing T with each significant value of the image, and comparing the pixel points which are more than or equal to the threshold valueMarking as '1', marking the pixel points less than the threshold as '0', and collecting all pixel points in the image by 0 and 1Line ofColumn matrixAnd (4) showing.
5. Step three, marking defects
Will matrixAnd matrixMultiplying corresponding elements to obtain new matrix(ii) a Namely:(ii) a The matrix is obtained by the formula of dot multiplicationThe pixel significance value is also composed of elements 0 and 1, wherein the element 1 represents that the pixel significance values are more than or equal to two threshold valuesI.e. the coincidence position of the target images; then sequentially searching three matrixes from left to right and from top to bottom、、The connected region of the medium element is 1, and the connected region of each matrix is respectively marked as、、 ；
Selecting matrixTo matrixAll elements in the list are summed and recorded as(ii) a For matrixAll elements in the list are summed and recorded as；
Introducing a functionLet us order(13)
If it isThen, the position r is regarded as a defect position; if less thanIt is considered to be an error detection where the workpiece is defect free.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611007125.2A CN106442556A (en) | 2016-11-16 | 2016-11-16 | Device and method for detecting surface defects of perforated plate workpiece |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611007125.2A CN106442556A (en) | 2016-11-16 | 2016-11-16 | Device and method for detecting surface defects of perforated plate workpiece |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN106442556A true CN106442556A (en) | 2017-02-22 |
Family
ID=58207868
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611007125.2A Pending CN106442556A (en) | 2016-11-16 | 2016-11-16 | Device and method for detecting surface defects of perforated plate workpiece |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106442556A (en) |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107014819A (en) * | 2017-06-09 | 2017-08-04 | 杭州电子科技大学 | A kind of solar panel surface defects detection system and method |
| CN107680086A (en) * | 2017-09-27 | 2018-02-09 | 电子科技大学 | A kind of existing arc-shaped side has the material profile defect inspection method of straight line again |
| CN108732186A (en) * | 2018-07-20 | 2018-11-02 | 梧州学院 | Embedded Surface Flaw automatic checkout system and its control method |
| CN109447989A (en) * | 2019-01-08 | 2019-03-08 | 哈尔滨理工大学 | Defect detecting device and method based on motor copper bar burr growth district |
| CN109584239A (en) * | 2018-12-13 | 2019-04-05 | 华南理工大学 | A kind of bloom body surface defect detecting system and method based on reflected light |
| CN109709105A (en) * | 2019-01-18 | 2019-05-03 | 安徽工程大学 | A kind of hole missing detection device |
| CN110288561A (en) * | 2018-03-14 | 2019-09-27 | 浙江大学山东工业技术研究院 | Refractory brick surface scratch recognition methods based on frequency filtering enhancing |
| CN111272766A (en) * | 2020-02-20 | 2020-06-12 | 上海普密德自动化科技有限公司 | Surface defect detection system based on vision technology and detection method thereof |
| CN111487192A (en) * | 2020-04-26 | 2020-08-04 | 天津海融科技有限公司 | Machine vision surface defect detection device and method based on artificial intelligence |
| CN112859189A (en) * | 2020-12-31 | 2021-05-28 | 广东美的白色家电技术创新中心有限公司 | Workpiece detection device, detection method, and computer-readable storage medium |
| CN113538432A (en) * | 2021-09-17 | 2021-10-22 | 南通蓝城机械科技有限公司 | Part defect detection method and system based on image processing |
| CN113592787A (en) * | 2021-07-13 | 2021-11-02 | 苏州汇川控制技术有限公司 | Light emitting component detection method, light emitting component detection device, terminal equipment and storage medium |
| CN114663430A (en) * | 2022-05-18 | 2022-06-24 | 爱科赛智能科技(浙江)有限公司 | PCB surface defect detection method based on frequency domain information double confirmation |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005172559A (en) * | 2003-12-10 | 2005-06-30 | Seiko Epson Corp | Method and device for detecting line defect on panel |
| CN102305793A (en) * | 2011-05-11 | 2012-01-04 | 苏州天准精密技术有限公司 | Method and equipment for detecting appearance quality of product |
| CN102495069A (en) * | 2011-12-07 | 2012-06-13 | 广东辉丰科技股份有限公司 | Method for detecting defects of chain belts of zipper on basis of digital image processing |
| CN102590330A (en) * | 2011-12-29 | 2012-07-18 | 南京理工大学常熟研究院有限公司 | Image processing-based magnetic particle inspection defect intelligent identification detection system |
| CN104360501A (en) * | 2014-10-15 | 2015-02-18 | 西安交通大学 | Visual detection method and device for defects of liquid crystal display screen |
| CN105181713A (en) * | 2015-07-19 | 2015-12-23 | 中北大学 | Detection device used for optical fiber image inverter surface defects |
| CN106053479A (en) * | 2016-07-21 | 2016-10-26 | 湘潭大学 | System for visually detecting workpiece appearance defects based on image processing |
| CN206223683U (en) * | 2016-11-16 | 2017-06-06 | 哈尔滨理工大学 | A kind of tabular workpiece with hole surface defect detection apparatus |
-
2016
- 2016-11-16 CN CN201611007125.2A patent/CN106442556A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005172559A (en) * | 2003-12-10 | 2005-06-30 | Seiko Epson Corp | Method and device for detecting line defect on panel |
| CN102305793A (en) * | 2011-05-11 | 2012-01-04 | 苏州天准精密技术有限公司 | Method and equipment for detecting appearance quality of product |
| CN102495069A (en) * | 2011-12-07 | 2012-06-13 | 广东辉丰科技股份有限公司 | Method for detecting defects of chain belts of zipper on basis of digital image processing |
| CN102590330A (en) * | 2011-12-29 | 2012-07-18 | 南京理工大学常熟研究院有限公司 | Image processing-based magnetic particle inspection defect intelligent identification detection system |
| CN104360501A (en) * | 2014-10-15 | 2015-02-18 | 西安交通大学 | Visual detection method and device for defects of liquid crystal display screen |
| CN105181713A (en) * | 2015-07-19 | 2015-12-23 | 中北大学 | Detection device used for optical fiber image inverter surface defects |
| CN106053479A (en) * | 2016-07-21 | 2016-10-26 | 湘潭大学 | System for visually detecting workpiece appearance defects based on image processing |
| CN206223683U (en) * | 2016-11-16 | 2017-06-06 | 哈尔滨理工大学 | A kind of tabular workpiece with hole surface defect detection apparatus |
Non-Patent Citations (1)
| Title |
|---|
| 陈向伟;张学军;关山;: "基于计算机视觉的微小轴承表面缺陷检测", 机床与液压 * |
Cited By (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107014819A (en) * | 2017-06-09 | 2017-08-04 | 杭州电子科技大学 | A kind of solar panel surface defects detection system and method |
| CN107680086A (en) * | 2017-09-27 | 2018-02-09 | 电子科技大学 | A kind of existing arc-shaped side has the material profile defect inspection method of straight line again |
| CN107680086B (en) * | 2017-09-27 | 2020-10-23 | 电子科技大学 | Method for detecting material contour defects with arc-shaped edges and linear edges |
| CN110288561A (en) * | 2018-03-14 | 2019-09-27 | 浙江大学山东工业技术研究院 | Refractory brick surface scratch recognition methods based on frequency filtering enhancing |
| CN108732186A (en) * | 2018-07-20 | 2018-11-02 | 梧州学院 | Embedded Surface Flaw automatic checkout system and its control method |
| CN109584239A (en) * | 2018-12-13 | 2019-04-05 | 华南理工大学 | A kind of bloom body surface defect detecting system and method based on reflected light |
| CN109584239B (en) * | 2018-12-13 | 2024-02-06 | 华南理工大学 | High-light object surface defect detection system and method based on reflected light |
| CN109447989A (en) * | 2019-01-08 | 2019-03-08 | 哈尔滨理工大学 | Defect detecting device and method based on motor copper bar burr growth district |
| CN109709105B (en) * | 2019-01-18 | 2021-07-27 | 安徽工程大学 | Hole missing detection device |
| CN109709105A (en) * | 2019-01-18 | 2019-05-03 | 安徽工程大学 | A kind of hole missing detection device |
| CN111272766A (en) * | 2020-02-20 | 2020-06-12 | 上海普密德自动化科技有限公司 | Surface defect detection system based on vision technology and detection method thereof |
| CN111487192A (en) * | 2020-04-26 | 2020-08-04 | 天津海融科技有限公司 | Machine vision surface defect detection device and method based on artificial intelligence |
| CN112859189A (en) * | 2020-12-31 | 2021-05-28 | 广东美的白色家电技术创新中心有限公司 | Workpiece detection device, detection method, and computer-readable storage medium |
| CN113592787A (en) * | 2021-07-13 | 2021-11-02 | 苏州汇川控制技术有限公司 | Light emitting component detection method, light emitting component detection device, terminal equipment and storage medium |
| CN113538432A (en) * | 2021-09-17 | 2021-10-22 | 南通蓝城机械科技有限公司 | Part defect detection method and system based on image processing |
| CN113538432B (en) * | 2021-09-17 | 2021-12-21 | 南通蓝城机械科技有限公司 | Part defect detection method and system based on image processing |
| CN114663430A (en) * | 2022-05-18 | 2022-06-24 | 爱科赛智能科技(浙江)有限公司 | PCB surface defect detection method based on frequency domain information double confirmation |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106442556A (en) | Device and method for detecting surface defects of perforated plate workpiece | |
| CN109816644B (en) | Bearing defect automatic detection system based on multi-angle light source image | |
| CN113592845A (en) | Defect detection method and device for battery coating and storage medium | |
| CN102426649B (en) | Simple steel seal digital automatic identification method with high accuracy rate | |
| CN109490316A (en) | A kind of surface defects detection algorithm based on machine vision | |
| CN115018844B (en) | Plastic film quality evaluation method based on artificial intelligence | |
| CN102654464A (en) | Copper strip surface defect detection system based on multi-feature fuzzy recognition | |
| CN111639629B (en) | Pig weight measurement method and device based on image processing and storage medium | |
| CN103839283A (en) | Area and circumference nondestructive measurement method of small irregular object | |
| CN111972700B (en) | Cigarette appearance detection method and device, equipment, system and medium thereof | |
| CN110334727B (en) | Intelligent matching detection method for tunnel cracks | |
| CN103914708A (en) | Food variety detection method and system based on machine vision | |
| CN111415339B (en) | Image defect detection method for complex texture industrial product | |
| CN117333489B (en) | Film damage detection device and detection system | |
| WO2024016632A1 (en) | Bright spot location method, bright spot location apparatus, electronic device and storage medium | |
| CN115082451A (en) | Stainless steel soup ladle defect detection method based on image processing | |
| CN111242888A (en) | Image processing method and system based on machine vision | |
| CN110874572B (en) | Information detection method and device and storage medium | |
| CN117456195A (en) | Abnormal image identification method and system based on depth fusion | |
| CN108961262A (en) | A kind of Bar code positioning method under complex scene | |
| TWI543117B (en) | Method for recognizing and locating object | |
| KR102030768B1 (en) | Poultry weight measuring method using image, recording medium and device for performing the method | |
| CN108694415B (en) | Image feature extraction method and device and water source image classification method and device | |
| CN117315670B (en) | Water meter reading area detection method based on computer vision | |
| CN111507177B (en) | Identification method and device for metering turnover cabinet |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20170222 |
|
| WD01 | Invention patent application deemed withdrawn after publication |