[go: up one dir, main page]

CN212321466U - Image acquisition device and visual detection system - Google Patents

Image acquisition device and visual detection system Download PDF

Info

Publication number
CN212321466U
CN212321466U CN202021696153.1U CN202021696153U CN212321466U CN 212321466 U CN212321466 U CN 212321466U CN 202021696153 U CN202021696153 U CN 202021696153U CN 212321466 U CN212321466 U CN 212321466U
Authority
CN
China
Prior art keywords
light source
sample
image
detection
industrial camera
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.)
Active
Application number
CN202021696153.1U
Other languages
Chinese (zh)
Inventor
王健伟
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shanghai Shishi Intelligent Technology Co ltd
Original Assignee
Shanghai Shishi Intelligent Technology Co ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Shanghai Shishi Intelligent Technology Co ltd filed Critical Shanghai Shishi Intelligent Technology Co ltd
Priority to CN202021696153.1U priority Critical patent/CN212321466U/en
Application granted granted Critical
Publication of CN212321466U publication Critical patent/CN212321466U/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Investigating Materials By The Use Of Optical Means Adapted For Particular Applications (AREA)

Abstract

The utility model relates to a metal liquid sampling test technical field in the metallurgical industry, in particular to image acquisition device and visual inspection system. An image acquisition apparatus, comprising: the device comprises an industrial camera, a coaxial light source, an annular light source and a support frame; the industrial camera, the coaxial light source and the annular light source are coaxially arranged on the support frame from top to bottom; when the image is collected, the sample is placed below the annular light source. The coaxial light source is suitable for detecting the defects of an object with extremely high reflectivity, such as a sample detection surface, the annular light source can provide irradiation at different angles, the three-dimensional information of the sample is highlighted, and the problem of diagonal irradiation shadow is effectively solved by uniform diffusion of light. When the coaxial light source of sample testing face out of plumb, coaxial light source and annular light source all have the light reflex to form images to the industry camera in, the utility model discloses guaranteed that the formation of image is clear, luminance is even, and no ghost produces. And simultaneously, the utility model also discloses a visual detection system.

Description

Image acquisition device and visual detection system
Technical Field
The utility model relates to a metal liquid sampling test technical field in the metallurgical industry, in particular to image acquisition and detection device.
Background
In the metallurgical production process flow, the sampling in front of the furnace for component detection is the basis for determining whether the chemical components in the molten metal reach the mixture ratio, and is also the important basis and main means for ensuring the product quality for a long time.
The general procedure for sample analysis is: sampling in front of the furnace, cooling and forming, sample removing, transporting, processing of a detection surface, visual detection, detection of a fluorescence analyzer and detection of a photoelectric direct-reading spectrometer, and finally reporting the detection result to a production system. If the sample contains impurities, the surface of the sample may have defects such as impurities, cracks, pits, water stains and the like after the sample is prepared; in the sample preparation process, the defects of too rough machined surface, pits and the like can also occur. When detecting, if the excitation point is selected on the defects, the detection result will deviate from the actual result seriously.
The traditional detection method is characterized in that the surface of a sample is identified and judged by means of experienced manual work, after available detection points on the sample are found out, the sample is overturned and placed on a detection platform, the detection points are aligned to detection ports on a detector, and then the detector is started to detect. The sample is opaque, and the detection mouth of detector is also less, and the check point aligns the detection mouth when difficult to guarantee to place, need check after the detector finishes detecting, whether the point that has detected coincides with the point of preselection, and the point that does not coincide needs to detect again. The manual lofting efficiency is low, and errors are easy to occur. The vision system is used for replacing manual selection of a detection point, and the robot system is guided to place a sample, so that the production automation is imperative. The premise of realizing the detection automation is that qualified detection points on the sample are found intelligently. Therefore, the technology for acquiring the detection point information of the sample detection surface is a serious problem to be solved urgently in the field of metallurgical sample detection automation.
In the prior art, a coaxial light source and an industrial camera are mostly adopted to photograph the surface of a sample, but when a sample detection surface is not perpendicular to the coaxial light source and reaches a certain angle, the quantity of light reflected back to the industrial camera from the detection surface is reduced, and insufficient image brightness or uneven brightness is caused, so that the visual identification effect is influenced. The sample is manufactured by adopting a mold forming method, the outer edge surface of the cylindrical sample has a certain mold drawing angle, the detection surface is not parallel to the upper surface and the lower surface of the camera after clamping, and a certain angle is possible, so that the problem of insufficient brightness of reflected light during shooting is caused, the problem of misjudgment is caused to a great extent through simple threshold calculation, and the analysis result or the waste sample rate is seriously influenced.
SUMMERY OF THE UTILITY MODEL
The utility model aims at: aiming at the defects of the prior art, an image acquisition device and a visual detection system are provided.
The utility model discloses a technical scheme is: an image acquisition apparatus, comprising: industrial cameras, coaxial light sources, ring light sources, and support stands.
The industrial camera, the coaxial light source and the annular light source are coaxially arranged on the support frame from top to bottom.
When the image is collected, the sample is placed below the annular light source.
A plurality of small light sources on the inner side of the coaxial light source are scattered on the semi-transparent semi-reflective light splitting sheet through the diffusion plate, the light is reflected to the detection surface of the sample by the light splitting sheet, and then the light is reflected by the detection surface of the sample and then penetrates through the light splitting sheet to enter the industrial camera.
A plurality of small light sources which are arranged in a conical shape are arranged in the annular light source, the small light sources are scattered on the sample detection surface from a plurality of angles and a plurality of directions, and a part of the light sources can be projected into the industrial camera; because of the multiple light sources and the multi-angle light irradiation, when the detection surface is not parallel to the upper surface of the light source shell, light is also projected into the industrial camera for imaging.
After the coaxial light source and the annular light source are used in a combined mode, even if the sample detection surface is not perpendicular to the coaxial light source, the coaxial light source has a few parts of light reflection imaging to the industrial camera, and meanwhile, the annular light source also has a part of light reflection imaging to the industrial camera, so that the imaging is clear, the brightness is uniform, and no ghost or shadow surface is generated.
On the basis of the scheme, further, in order to avoid the influence of external illumination on detection, light shields are arranged on the periphery and the top of the industrial camera, the coaxial light source and the annular light source.
In the above scheme, specifically, the support frame is an L-shaped structure and comprises a horizontal fixing seat and a back plate. The fixing seat can be fixedly connected with the ground or the panel, and the back plate can be used for installing the industrial camera, the coaxial light source and the annular light source.
Furthermore, the back plate is provided with a mounting plate with a sliding groove. The industrial camera is fixedly installed on the top of the installation plate through the first installation frame. The coaxial light source is installed in the mounting panel through first slider, and first slider cooperatees with the spout, realizes reciprocating. The annular light source is installed in the mounting panel through the second slider, and the second slider cooperatees with the spout, realizes reciprocating.
In the above scheme, specifically, the industrial camera is a camera with 500 ten thousand or more pixels.
The utility model discloses a another technical scheme is: a visual inspection system comprising an image capture device as described above, and further comprising: an image recognition device; the image recognition device is in signal connection with the industrial camera and used for analyzing and processing images collected by the industrial camera and searching detection points suitable for detection. The detection point is free from pits, bulges, burrs and impurities.
For a fluorescence detector, a circular surface with the diameter of 10mm at the central part of a sample detection surface is generally selected as a detection point; for a direct-reading spectrometer, a circular surface with the diameter of 6-10 mm can be selected as an excitation point at any position of a sample detection surface, and during detection, the excitation point is firstly excited, and then emitted spectrum light is collected and analyzed.
When the image recognition equipment recognizes the image, the following principles are followed:
t1, judging whether a circle with the size of a fluorescence detection point at the center of a sample detection surface has defects or not, if so, not carrying out subsequent detection, and directly judging as an unqualified sample; if not, the step T2 is carried out.
T2, searching whether the rest parts of the sample detection surface have defects or not, and if not, executing a step T4; if yes, the step T3 is performed after determining the defect location and size.
T3, judging whether the defect on the detection surface of the sample is removed and the fluorescent detection point at the center is removed, and then selecting a circle with a diameter of a specific value in the residual area, if so, executing a step T4; if not, the subsequent detection is not carried out, and the sample is judged to be unqualified.
T4, setting a circle with a diameter of a specific value as an excitation point in the residual area of the sample detection surface except for the defect; in order to ensure that as many excitation points are arranged on the detection surface as possible, the excitation points should be tangent to the defect position and the edge of the detection surface as possible.
The method for extracting the detection points on the surface of the sample by the visual inspection system comprises the following steps:
A. and processing the sample detection surface image to obtain a set of defect points on the detection surface image.
B. And extracting detection points of the fluorometer.
Checking whether a defect point appears in a set circular surface at the center of the sample detection surface, and finishing extraction if the defect point exists in the position; if there is no defect point, the fluorometer detection point is marked in the circular plane at the center of the sample detection plane, and step C is performed.
C. And extracting an excitation point of the direct-reading spectrometer.
Checking whether more than one excitation point of the direct-reading spectrometer can be selected in the residual area of the detection surface image without the detection points of the fluorometer and all the defect points, if not, finishing the extraction, and if so, marking the excitation point of the direct-reading spectrometer on the sample detection surface; in order to mark the excitation points as much as possible, the excitation points of the direct-reading spectrometer are tangent to the outer contour and the defect points of the sample detection surface; and entering the step D.
D. And establishing a rectangular coordinate system by taking the center of the image of the sample detection surface as an original point, and quantifying the positions of the detection point of the fluorescence instrument and the excitation point of the direct-reading spectrometer.
And after coordinate points of a detection point of the fluorometer and an excitation point of the direct-reading spectrometer are obtained, the coordinate points are sent to a control system.
In the foregoing scheme, specifically, the method for identifying the defect point in step a includes:
s1, obtaining a sample detection surface image, and processing the image to generate a gray-scale image.
And S2, setting the pixel with the gray scale larger than the set threshold value in the gray scale image as 255 and setting the pixel with the gray scale smaller than the set threshold value as 0 to obtain the binary image.
And S3, identifying the outline of the sample detection surface, and eliminating a single pixel point with a pixel value of 255, which is not communicated with adjacent pixels, in the binary image within the outline range.
And S4, confirming the starting position and the ending position of each row of connected domains in the binary image.
And S5, comparing the starting position and the ending position of a certain connected domain in the ith row with the starting position and the ending position of the connected domain in the (i + 1) th row, and judging whether the two adjacent rows of connected domains are intersected or not.
And S6, obtaining a region set of all intersected connected domains with the pixel value of 255 in the binary image, wherein the set is a set of defect points on the detection surface image.
On the basis of the scheme, further, the excitation points of the direct-reading spectrometers, which are respectively located at two ends of the same diameter and close to the outer contour of the sample detection surface, are found out from all the excitation points of the direct-reading spectrometers and serve as the excitation points of the optimal direct-reading spectrometers.
Has the advantages that: the utility model discloses a combination light source, coaxial light source suit are used for the high object of reflectance, like the defect detection of sample testing face, and annular light source can provide different angles and shine, the three-dimensional information of outstanding sample, and the shadow problem is shone to the diagonal angle effectively to the even diffusion of light. When the coaxial light source of sample testing face out of plumb, coaxial light source and annular light source all have the light reflex formation of image to the industry camera in, the utility model discloses guaranteed that the formation of image is clear, luminance is even, the production of no ghost and sun-shading face.
The visual detection system comprises the image acquisition device and the image recognition equipment, the image recognition equipment recognizes the image which is clear in imaging and uniform in brightness, the recognition accuracy is improved, the positions of excitation points can be reasonably arranged, and the detection accuracy is improved.
Drawings
Fig. 1 is a schematic structural view of the present invention in embodiment 1;
fig. 2 is an exploded view of the present invention in example 1;
fig. 3 is a diagram of optical path transmission according to the present invention in embodiment 1;
FIG. 4 is a block diagram showing the constitution of the present invention in example 2;
FIG. 5 is a flowchart of a method in example 3;
FIG. 6 is a schematic diagram of selecting excitation points of the direct-reading spectrometer in example 3;
in the figure: 1-an industrial camera, 11-a first mounting frame, 2-a coaxial light source, 21-a first sliding block, 3-a ring light source, 31-a second sliding block, 4-a support frame, 41-a fixed seat, 42-a back plate, 43-a sliding chute, 44-a mounting plate, 5-a sample, 6-a light shield and 7-image recognition equipment.
Detailed Description
Embodiment 1, referring to fig. 1 and 2, an image capturing apparatus includes: industrial camera 1, coaxial light source 2, annular light source 3 and support frame 4.
The industrial camera 1, the coaxial light source 2 and the annular light source 3 are coaxially arranged on the support frame 4 from top to bottom; in this embodiment, the supporting frame 4 is an L-shaped structure, and includes a horizontal fixing base 41 and a back plate 42. The fixing base 41 can be used for fixing and connecting the ground or the panel, and the back plate 42 can be used for installing the industrial camera 1, the coaxial light source 2 and the annular light source 3.
Preferably, the back plate 42 is provided with a mounting plate 44 having a sliding slot 43. The industrial camera 1 is fixedly mounted on top of the mounting plate 44 by means of the first mounting bracket 11. The coaxial light source 2 is mounted on the mounting plate 44 through the first slider 21, and the first slider 21 is matched with the sliding groove 43 to realize up-and-down movement. The annular light source 3 is arranged on the mounting plate 44 through the second sliding block 31, and the second sliding block 31 is matched with the sliding groove 43 to realize up-and-down movement.
When the image is acquired, the sample 5 is placed under the ring light source 3.
In order to avoid the influence of external illumination on detection, the industrial camera 1, the coaxial light source 2 and the annular light source 3 are provided with light shields 6 around and on the top.
In this example, the pixels of the industrial camera 1 are 500 ten thousand. In practical use, a proper camera lens is selected according to the size and requirements of a sample, the actual distance and other factors.
Referring to fig. 3, after the coaxial light source 2 and the annular light source 3 are used in combination, when the detection plane of the sample 5 is not perpendicular to the coaxial light source 2, a part of light of the coaxial light source is reflected and imaged into the industrial camera 1, and a part of light of the annular light source 3 is reflected and imaged into the industrial camera 1, at this time, the imaging is clear, the brightness is uniform, and no ghost is generated.
Embodiment 2, referring to fig. 4, a visual inspection system comprising the apparatus for image capture of a metallurgical sample according to embodiment 1, further comprising: an image recognition device 7; the image recognition device 7 establishes a signal connection with the industrial camera 1, and is used for analyzing and processing the image acquired by the industrial camera 1 and searching a detection point suitable for detection. The detection point is free from pits, bulges, burrs and impurities.
In this example, a circular surface with a diameter of 10mm at the center of the detection surface of the sample 5 is selected as a detection point of the fluorometer; a circular surface with the diameter of 8mm is selected as an excitation point of the direct-reading spectrometer.
When the image recognition device 7 recognizes an image, the following principles are followed:
t1, judging whether a circle with the diameter of 10mm at the center of the detection surface of the sample 5 has a defect or not, if so, not carrying out subsequent detection, and directly judging as an unqualified sample; if not, the step T2 is carried out.
T2, searching whether the rest part of the detection surface of the sample 5 has defects or not, and if not, executing the step D; if yes, the step T3 is performed after determining the defect location and size.
T3, judging whether more than one circle with the diameter of 8mm can be selected in the residual area after the defects are removed from the detection surface of the sample 5 and the fluorescent detection point with the diameter of 10mm at the center is detected, and if so, executing the step T4; if not, the subsequent detection is not carried out, and the sample is judged to be unqualified.
T4, setting a circle with the diameter of 8mm as an excitation point in the residual area of the detection surface of the sample 5 except for the defect; in order to ensure that as many excitation points are arranged on the detection surface as possible, the excitation points should be tangent to the defect position and the edge of the detection surface as possible.
Embodiment 3, referring to fig. 5, a method for detecting point extraction based on the visual inspection system according to embodiment 2 comprises the following steps:
A. and processing the sample detection surface image to obtain a set of defect points on the detection surface image.
In this example, the method for identifying the defect point is as follows:
s1, obtaining a sample detection surface image, and processing the image to generate a gray-scale image.
And S2, setting the pixel with the gray scale larger than the set threshold value in the gray scale image as 255 and setting the pixel with the gray scale smaller than the set threshold value as 0 to obtain the binary image.
And S3, identifying the outline of the sample detection surface, and eliminating a single pixel point with a pixel value of 255, which is not communicated with adjacent pixels, in the binary image within the outline range.
And S4, confirming the starting position and the ending position of each row of connected domains in the binary image.
And S5, comparing the starting position and the ending position of a certain connected domain in the ith row with the starting position and the ending position of the connected domain in the (i + 1) th row, and judging whether the two adjacent rows of connected domains are intersected or not.
And S6, obtaining a region set of all intersected connected domains with the pixel value of 255 in the binary image, wherein the set is a set of defect points on the detection surface image.
B. And extracting detection points of the fluorometer.
Checking whether a defect point appears in a set circular surface at the center of the sample detection surface, and finishing extraction if the defect point exists in the position; if there is no defect point, the fluorometer detection point is marked in the circular plane at the center of the sample detection plane, and step C is performed.
C. And extracting an excitation point of the direct-reading spectrometer.
Checking whether more than one excitation point of the direct-reading spectrometer can be selected in the residual area of the detection surface image without the detection points of the fluorometer and all the defect points, if not, finishing the extraction, if so, marking the excitation points of the direct-reading spectrometer as much as possible in the residual area, and enabling the excitation points of the direct-reading spectrometer to be tangent to the outline and the defect points of the sample detection surface; and entering the step D.
In this example, 4 excitation points are selected, and if four circular rings with the same area as the excitation points cannot be placed in the remaining area, the sample is a failed sample, and the sample needs to be prepared again.
Preferably, the optimal excitation point is selected from all excitation points of the direct-reading spectrometer; the optimal excitation point is the farthest group of the excitation points of all the direct-reading spectrometers, namely, the excitation points of the direct-reading spectrometers, which are respectively located at two ends of the same diameter and close to the outer contour of the sample detection surface, are found and used as the excitation points of the optimal direct-reading spectrometers. Referring to fig. 6, four circular rings with the same size as the excitation points are symmetrically arranged on the sample detection surface, the four circular rings are tangent to the edge of the sample detection surface and rotate around the center of the sample detection surface, and when no defect point exists in any of the four circular rings, the positions of the four circular rings are marked as an excitation point 1, an excitation point 2, an excitation point 3 and an excitation point 4, wherein the excitation point 1 and the excitation point 2 are a group of optimal excitation points, and the excitation point 3 and the excitation point 4 are a group of optimal excitation points; if the situation that defect points do not exist in the four circular rings simultaneously after the four circular rings rotate for one circle does not exist, the optimal excitation point does not exist on the detection surface of the sample. Under the condition that the optimal excitation point does not exist, 4 excitation points which are farthest away from each other are selected from all the excitation points of the direct-reading spectrometers.
During detection, the excitation point 1 and the excitation point 2 are detected, if the deviation of the detection results at the excitation point 1 and the excitation point 2 is large, the excitation point 3 is detected, and if the deviation of the detection results at the excitation point 3, the excitation point 1 and the excitation point 2 is still large, the excitation point 4 is continuously detected. If the deviation of the detection results of the excitation point 1, the excitation point 2, the excitation point 3 and the excitation point 4 is large, the sample is unqualified, and the sample needs to be prepared again and the excitation point needs to be selected.
D. And establishing a rectangular coordinate system by taking the center of the image of the sample detection surface as an original point, and quantifying the positions of the detection point of the fluorescence instrument and the excitation point of the direct-reading spectrometer.
And after coordinate points of a detection point of the fluorometer and an excitation point of the direct-reading spectrometer are obtained, the coordinate points are sent to a control system.
Although the invention has been described in detail with respect to the general description and the specific embodiments, it will be apparent to those skilled in the art that modifications and improvements can be made based on the invention. Therefore, such modifications and improvements are intended to be within the scope of the invention as claimed.

Claims (9)

1. An image acquisition apparatus, comprising: industrial camera (1), coaxial light source (2), characterized in that it also includes: an annular light source (3) and a support frame (4);
the industrial camera (1), the coaxial light source (2) and the annular light source (3) are coaxially arranged on the support frame (4) from top to bottom;
when the image is collected, the sample (5) is arranged below the annular light source (3).
2. An image capturing device as claimed in claim 1, characterized in that a light shield (6) is arranged around and on top of the industrial camera (1), the coaxial light source (2) and the annular light source (3).
3. An image capturing device as claimed in claim 1 or 2, characterized in that the support frame (4) is of L-shaped configuration, comprising a horizontal fixing base (41) and a back plate (42).
4. An image acquisition device as claimed in claim 3, characterized in that the back plate (42) is provided with a mounting plate (44) with a sliding slot (43).
5. An image acquisition device according to claim 4, characterized in that the industrial camera (1) is fixedly mounted on top of the mounting plate (44) by means of a first mounting bracket (11).
6. An image capturing device as claimed in claim 4, characterized in that the coaxial light source (2) is mounted to the mounting plate (44) by means of a first slide (21), the first slide (21) cooperating with the slide (43) for up and down movement.
7. An image capturing device as claimed in claim 4, characterized in that the ring light source (3) is mounted to the mounting plate (44) via a second slide (31), the second slide (31) cooperating with the slide groove (43) for up and down movement.
8. An image acquisition device as claimed in claim 1 or 2, characterized in that the industrial camera (1) is selected from cameras having a pixel of 500 tens of thousands or more.
9. A visual inspection system comprising the image capture device of any of claims 1-8, further comprising: an image recognition device (7); the image recognition device (7) is in signal connection with the industrial camera (1) and is used for analyzing and processing the images acquired by the industrial camera (1).
CN202021696153.1U 2020-08-14 2020-08-14 Image acquisition device and visual detection system Active CN212321466U (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202021696153.1U CN212321466U (en) 2020-08-14 2020-08-14 Image acquisition device and visual detection system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202021696153.1U CN212321466U (en) 2020-08-14 2020-08-14 Image acquisition device and visual detection system

Publications (1)

Publication Number Publication Date
CN212321466U true CN212321466U (en) 2021-01-08

Family

ID=74034755

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202021696153.1U Active CN212321466U (en) 2020-08-14 2020-08-14 Image acquisition device and visual detection system

Country Status (1)

Country Link
CN (1) CN212321466U (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111812103A (en) * 2020-08-14 2020-10-23 上海识时智能科技有限公司 Image acquisition device, visual detection system and detection point extraction method

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111812103A (en) * 2020-08-14 2020-10-23 上海识时智能科技有限公司 Image acquisition device, visual detection system and detection point extraction method
CN111812103B (en) * 2020-08-14 2024-07-05 上海识时智能科技有限公司 Image acquisition device, visual detection system and detection point extraction method

Similar Documents

Publication Publication Date Title
CN111812103B (en) Image acquisition device, visual detection system and detection point extraction method
CN109765234B (en) Device and method for simultaneously carrying out optical detection on front and back surfaces of object
KR101324015B1 (en) Apparatus and method for detecting the surface defect of the glass substrate
US20080247630A1 (en) Defect inspecting apparatus and defect-inspecting method
US6661912B1 (en) Inspecting method and apparatus for repeated micro-miniature patterns
CN101014850B (en) System and method for inspecting electrical circuits utilizing reflective and fluorescent imagery
WO2007074770A1 (en) Defect inspection device for inspecting defect by image analysis
JPWO2004036197A1 (en) Glass bottle inspection equipment
TWI442194B (en) Alignment mark detection method
CN110208269B (en) Method and system for distinguishing foreign matters on surface of glass from foreign matters inside glass
KR20180095972A (en) High-speed automated optical inspection apparatus supporting double scan approach
KR101060428B1 (en) Edge inspection method for substrates such as semiconductors
JP3893825B2 (en) Defect observation method and apparatus for semiconductor wafer
US11255798B1 (en) Method of detecting lens cleanliness using out-of-focus differential flat field correction
US11300527B1 (en) Method for detecting lens cleanliness using spectral differential flat field correction
CN118566249A (en) Transparent wafer surface nanoscale scratch detection system and method
CN113686903A (en) Optical element defect detection system and detection method
CN212321466U (en) Image acquisition device and visual detection system
CN114113112B (en) A method for locating and identifying surface micro-defects based on a three-light source microscope system
CN112326681B (en) Method for correcting and detecting lens cleanliness by utilizing defocusing difference flat field
JPH0636016A (en) Optical inspection method and device for fault of surface of body
JP4184511B2 (en) Method and apparatus for defect inspection of metal sample surface
JP2009236760A (en) Image detection device and inspection apparatus
JP4523310B2 (en) Foreign matter identification method and foreign matter identification device
JP2001194322A (en) External appearance inspection device and inspection method

Legal Events

Date Code Title Description
GR01 Patent grant
GR01 Patent grant