CN109297972A - Defect inspecting system and defect detecting method - Google Patents
Defect inspecting system and defect detecting method Download PDFInfo
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- CN109297972A CN109297972A CN201810800030.9A CN201810800030A CN109297972A CN 109297972 A CN109297972 A CN 109297972A CN 201810800030 A CN201810800030 A CN 201810800030A CN 109297972 A CN109297972 A CN 109297972A
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- 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
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- 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
- G01N21/01—Arrangements or apparatus for facilitating the optical investigation
-
- 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
- G01N21/8806—Specially adapted optical and illumination features
-
- 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
- G01N21/95—Investigating the presence of flaws or contamination characterised by the material or shape of the object to be examined
- G01N21/958—Inspecting transparent materials or objects, e.g. windscreens
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- 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
- G01N21/8806—Specially adapted optical and illumination features
- G01N2021/8809—Adjustment for highlighting flaws
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- 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
Abstract
The present invention provides defect inspecting system and defect detecting method.Defect inspecting system (1) has light source (2), image pickup part (3), delivery section (4) and image processing part (5), the data accumulated to the result of the relevant rote learning of the identification of classification for the defect for being included to two dimensional image (F) are based on by image processing part (5), to identify the classification for the defect for being included by a series of two dimensional image that discrete time is shot by image pickup part (3), therefore improve accuracy of identification by the two dimensional image for being suitable for shooting by discrete time by rote learning, in addition to this, it is shot by image pickup part (3) in two dimensional image and the changed two dimensional image of brightness on the consistent direction conveying direction (X), therefore rote learning is applied to the changed two dimension of brightness at each position along conveying direction in the two dimensional image shot by discrete time Image can be improved the accuracy of identification of defect (D).
Description
Technical field
The present invention relates to defect inspecting system and defect detecting methods.
Background technique
As the defect inspecting system checked based on the shooting image of check object the defect of check object, example
As it has been known that there is the defect inspections of the defect of stacked film used in the diaphragm of the detection optical films such as polarizing coating and phase difference film, battery etc.
Look into system.This defect inspecting system is along conveying direction transport membrane, by the two dimensional image of discrete time shooting film, based on shooting
Two dimensional image out carries out defect inspection.For example, Japan's patent the 4726983rd system generates column split image, it should
Column split image is shot along multiple column and making of conveying direction arrangement by discrete time by being divided into two dimensional image
Two dimensional image respectively in the Leie of same position arranged according to the sequence of time series.Column split image is processed into enhancing
The defect enhancing processing image of brightness change.Pass through defect enhancing processing image, in this way it is easy to determine the presence or absence of defect of film, film
The position of defect.
In addition, even if the two dimensional image of check object is processed into defect enhancing processing image as above-mentioned technology, most
Eventually also by the identification for carrying out defect based on the judgement of people, there are rooms for improvement for the accuracy of identification of defect.
Summary of the invention
Then, the purpose of the present invention is to provide the defect inspecting systems for the accuracy of identification that can be improved defect and defect to examine
Checking method.
The present invention relates to a kind of defect inspecting systems, have: light source, to check object irradiation light；Image pickup part is pressed
Discrete time shoots two dimensional image, which is based on that check object is irradiated and penetrated from light source to check object or is being checked
On object reflect after light and formed；Delivery section, check object is opposite along conveying direction relative to light source and image pickup part
Ground conveying；And image processing part, the image data for the two dimensional image shot by image pickup part is handled, image pickup part is clapped
It takes out in two dimensional image and the changed two dimensional image of brightness on the consistent direction of conveying direction, image processing part is based on pair
The data that the result of rote learning relevant to the identification of the classification for the defect that two dimensional image is included is accumulated, to know
The classification for the defect for not included by a series of two dimensional image that discrete time is shot by image pickup part.
According to this structure, defect inspecting system has: light source, to check object irradiation light；Image pickup part, by it is discrete when
Between shoot two dimensional image, the two dimensional image be based on check object is irradiated and penetrated from light source to check object or in check object
Light after reflection and formed；Delivery section relatively conveys check object relative to light source and image pickup part along conveying direction；
And image processing part, the image data for the two dimensional image shot by image pickup part is handled, wherein by image procossing
The result of the relevant rote learning of identification of the portion based on the classification to the defect for being included to two dimensional image is accumulated
Data, to identify the classification for the defect for being included by a series of two dimensional image that discrete time is shot by image pickup part, therefore
Improve accuracy of identification by the two dimensional image for being suitable for shooting by discrete time by rote learning, in addition to this, by taking the photograph
As portion is shot in two dimensional image and the changed two dimensional image of brightness on the consistent direction of conveying direction, therefore mechanics
Habit is applied to brightness at each position along conveying direction in the two dimensional image shot by discrete time and changes
Two dimensional image, can be improved the accuracy of identification of defect.
In which case it is preferable that defect inspecting system is also equipped with occulter, which is located at light source and inspection pair
It is blocked as between, and to a part of the light irradiated from light source to check object, thus pressing discrete time by image pickup part
Form bright portion and dark portion on the two dimensional image of shooting, delivery section by check object relative to light source, occulter and image pickup part along
The conveying direction intersected with the line of demarcation in bright portion and dark portion relatively conveys.
According to this structure, from the occulter between light source and check object to the light irradiated from light source to check object
A part blocked, to form bright portion and dark portion on the two dimensional image shot by image pickup part by discrete time, by
Delivery section is by check object relative to light source, occulter and image pickup part along the conveying side intersected with the line of demarcation in bright portion and dark portion
Each position of check object into a series of two dimensional image for relatively conveying, therefore shooting by discrete time enters bright
Portion and dark portion this two side, the presentation mode at each position of the check object in a series of two dimensional image by discrete time more substantially
Ground variation, therefore can be improved the accuracy of identification of defect.
On the other hand, the present invention relates to a kind of defect detecting methods comprising: from the light source of defect inspecting system to inspection
The irradiation process of object irradiation light；The camera shooting process of two dimensional image is shot by discrete time by the image pickup part of defect inspecting system,
Wherein, two dimensional image is based on irradiating and penetrate check object from light source to check object in irradiation process or in check object
Light after reflection and formed；By the delivery section of defect inspecting system by check object relative to light source and image pickup part along conveying side
To the conveying operation relatively conveyed；And by defect inspecting system image processing part to camera shooting process in shoot two
The image procossing process that is handled of image data of dimension image is shot in two dimensional image and conveying in the camera shooting process
The changed two dimensional image of brightness on the consistent direction in direction, in image procossing process, based on being wrapped to two dimensional image
The data that the result of the relevant rote learning of identification of the classification of the defect contained is accumulated, to identify in camera shooting process
By the classification for the defect that a series of two dimensional image that discrete time is shot is included.
In which case it is preferable that the occulter using defect inspecting system is passing through camera shooting work in irradiation process
Bright portion and dark portion are formed on the two dimensional image that sequence is shot by discrete time, wherein occulter be located at light source and check object it
Between, and a part of the light irradiated from light source to check object is blocked, in conveying operation, by check object relative to
Light source, occulter and image pickup part are relatively conveyed along the conveying direction intersected with the line of demarcation in bright portion and dark portion.
Detailed description of the invention
Fig. 1 is the perspective view for indicating the defect inspecting system of embodiment.
Fig. 2 is the figure of the configuration of the light source for indicating the defect inspecting system of Fig. 1, image pickup part, occulter and check object.
Fig. 3 is the flow chart for indicating the process of defect detecting method of embodiment.
Fig. 4 is the figure for indicating the two dimensional image shot by image pickup part.
Fig. 5 is the figure for indicating convolutional neural networks.
Specific embodiment
Hereinafter, explaining the preferred reality of defect inspecting system and defect detecting method of the invention in detail referring to attached drawing
Apply mode.
As shown in Figures 1 and 2, the defect inspecting system 1 of embodiments of the present invention has light source 2, image pickup part 3, conveying
Portion 4, image processing part 5, occulter 6, parallel light lens 7 and display device 8.The defect inspecting system of present embodiment will polarize
The optical films such as film and phase difference film, battery diaphragm used in the films such as stacked film as check object T, detect check object T
Defect.Check object T extends along the conveying direction X of delivery section 4, has on the width direction Y orthogonal with conveying direction X
Preset width.Refer to the state different from desired state in the defect that check object T is generated, such as can enumerate different
Object, scratch, bubble (bubble for generating etc. in forming), foreign bubble (bubble generated by being mixed into for foreign matter etc.), scar,
Crackle (crackle etc. generated by broken line trace etc.) and striped (striped etc. generated by the difference of thickness).Defect inspection
The classification of these defects of the identification of system 1.
As shown in Figures 1 and 2, light source 2 is to check object T irradiation light.It is parallel with width direction Y that light source 2 is configured to irradiation
Linear light.As light source 2, as long as the irradiations such as metal halide lamp, halogen transmission lamp, fluorescent lamp are not given as inspection pair
As the lamp for the light that the composition and property of the film of T affect, it is not particularly limited.
Image pickup part 3 shoots two dimensional image by discrete time, which is based on irradiating simultaneously from light source 2 to check object T
Light after reflecting through check object T or on check object T and formed.There are image pickup part 3 multiple optical components and photoelectricity to turn
Change element.Optical component includes optical lens, optical gate etc., makes to penetrate as the light after the film of check object T in photoelectric conversion element
The surface of part is imaged.Photo-electric conversion element is the CCD (Charge Coupled Device) or CMOS by shooting two dimensional image
The face sensor that photographing elements such as (Complementary Metal-Oxide Semiconductor) are constituted.Image pickup part 3 can also
To be the component either shot in two dimensional image and colorful two dimensional image without color.
Delivery section 4 relatively conveys check object T-phase light source 2 and image pickup part 3 along conveying direction X.Delivery section 4
Such as has and, along the conveying direction X outlet roller conveyed and receiving roll, rotary encoder etc. will be passed through as the film of check object T
To measure conveying distance.In the present embodiment, delivery section 4 is set to edge to the check object T conveying speed conveyed
Conveying direction X be 2~100m/ minutes this degree.The conveying speed of delivery section 4 is by the equal setting of image processing part 5 and control.
The image data for the two dimensional image that the processing of image processing part 5 is shot by image pickup part 3.Image processing part 5 be based on pair
The data that the result of rote learning relevant to the identification of the classification for the defect that two dimensional image is included is accumulated, to know
The classification for the defect for not included by a series of two dimensional image that discrete time is shot by image pickup part 3.Image processing part 5
If carrying out the component of the image procossing of two-dimensional image data, just it is not particularly limited, such as can be applicable in and image procossing is installed
The PC (personal computer) of software, FPGA (the Field Programmable Gate for carrying image processing circuit on the books
Array image pick-up card etc.).The data accumulated to the result of rote learning are stored in comprising image processing part 5
The storage devices such as the hard disk of PC, and be updated with the result of rote learning.
It should be noted that in the present embodiment, it is related to the identification of the classification for the defect for being included to two dimensional image
Rote learning the data that are accumulated of result in addition to including to the image pickup part 3 with the inside by defect inspecting system 1
The knot of the relevant rote learning of identification of the classification for the defect for being included by a series of two dimensional image that discrete time is shot
Other than the data that fruit is accumulated, further include to the two dimensional image institute that is separately generated in the outside of defect inspecting system 1
The data that the result of the relevant rote learning of identification of the classification for the defect for including is accumulated.That is, in present embodiment
In, in addition to include in the state that the inside of defect inspecting system 1 has carried out rote learning identify defect classification scheme with
Outside, further include based on in the state that the inside of defect inspecting system 1 not yet carries out rote learning in defect inspecting system 1
The data that the result of rote learning that outside separately generates is accumulated, come identify defect classification scheme.
Occulter 6 is between light source 2 and check object T, and by the light irradiated from light source 2 to check object T
A part is blocked, and bright portion and dark portion are thus formed on the two dimensional image shot by image pickup part 3 by discrete time.By
Occulter 6, image pickup part 3 are shot in two dimensional image and the changed X-Y scheme of brightness on the consistent direction conveying direction X
Picture.More specifically, delivery section 4 by check object T-phase for light source 2, parallel light lens 7, occulter 6 and image pickup part 3 along
The conveying direction X intersected with the line of demarcation in bright portion and dark portion is relatively conveyed.In the present embodiment, line of demarcation be parallel to it is defeated
Send the width direction Y that direction X is vertical.It should be noted that as long as image pickup part 3 can be shot in two dimensional image and conveying side
The changed two dimensional image of brightness, may not possess occulter 6 on the consistent direction X.Parallel light lens 7 make from
The direction of travel of light source 2 to the light that check object T and occulter 6 irradiate is parallel.Parallel light lens 7 for example can be by telecentric optics
System is constituted.
The display device 8 connecting with image processing part 5 is constituted such as by PC (personal computer), will be by image processing part
The classification of 5 defects identified is shown in LC (Liquid Crystal) display panel, plasma display panel, EL
(Electro Luminescence) display panel etc..It should be noted that after image processing part 5 also can have display processing
Image display device.
Hereinafter, illustrating the defect detecting method of present embodiment.As shown in figure 3, carrying out the light source from defect inspecting system 1
2 to check object T irradiation light irradiation process (S1).As shown in figure 4, in irradiation process, using positioned at light source 2 and inspection pair
As the occulter of the defect inspecting system 1 blocked between T and to a part of the light irradiated from light source 2 to check object T
Bright portion 1 and dark portion d are formed on 6, the two dimensional image F in camera shooting process by discrete time shooting.
As shown in figure 3, carrying out camera shooting process (S2) by the image pickup part 3 of defect inspecting system 1, in the camera shooting process, press
Discrete time shoots two dimensional image, which is based on irradiating in irradiation process from light source 2 to check object T and penetrating inspection
It checks the light as T or on check object T after reflection and is formed.As shown in figure 4, camera shooting process in, by occulter 6 block from
Light source 2 therefore is shot in two dimensional image F and conveying direction X consistent direction to a part of the check object T light irradiated
The upper changed two dimensional image F of brightness.
In addition, as shown in figure 3, being carried out check object T-phase for light source 2 and being taken the photograph by the delivery section 4 of defect inspecting system 1
The conveying operation (S3) relatively conveyed as portion 3 along conveying direction X.As shown in figure 4, in conveying operation, by check object T
Relative to light source 2, parallel light lens 7, occulter 6 and image pickup part 3 along the conveying intersected with the line of demarcation b in bright portion 1 and dark portion d
Direction X is relatively conveyed.In the present embodiment, line of demarcation b is parallel to the width direction Y orthogonal with conveying direction X, but demarcates
Line b and conveying direction X angulation are also possible to the angle other than 90 °.In addition, line of demarcation b is not necessarily stringent line of demarcation,
Line of demarcation b refers to the maximum position of brightness of the two dimensional image F comprising bright portion 1 and the brightness of the two dimensional image F comprising dark portion d most
The line of the centre at small position.
As shown in figure 3, being carried out by the image processing part 5 of defect inspecting system 1 to the two dimension shot in camera shooting process
The image procossing process (S4) that the image data of image F is handled.In image procossing process, based on to two dimensional image F
The data that the result of the relevant rote learning of identification of the classification for the defect D for being included is accumulated, are imaging to identify
By the classification of a series of two dimensional image F that discrete time the is shot defect D for being included in process.Rote learning is for example by rolling up
Product neural network carries out.As long as can also be used it should be noted that the classification of defect can be identified by rote learning
Neural network or other methods other than convolutional neural networks.
As shown in figure 5, convolutional neural networks 100 have input layer 110, hidden layer 120 and output layer 130.It is examined by defect
The image processing part 5 of system 1 is looked by a series of two dimensional image F shot in camera shooting process by discrete time to input layer
110 inputs.Hidden layer 120 have based on weight filter carry out image procossing convolutional layer 121,123, reduce in length and breadth
The pond layer 122 for the processing being effectively worth is remained from the two-dimensional array that convolutional layer 121,123 exports and updates the power of each layer
The full articulamentum 124 of weight coefficient n.In output layer 130, recognition result of the output rote learning to the classification of defect D.In convolution
In neural network 1 00, the error of the recognition result of output and normal solution value is learnt to the weight of each layer to the inverse propagation of reverse R.
For example, in advance that multiple two dimensional image F are defeated to image processing part 5 together with the normal solution of the identification of the classification of defect D
Enter and learn image processing part 5, the classification for thus successively identifying that a series of two dimensional image F newly inputted is included is
The no classification for specific defect D, and it is sequentially output recognition result.The error of the recognition result and normal solution that are sequentially output is to reverse
R is inverse to be propagated, and is successively updated the weight coefficient n of each layer and is accumulated as data.In the shape for the weight for successively having updated each phase
Under state, further successively identify classification that a series of two dimensional image F newly inputted is included whether be specific defect class
Not, and it is sequentially output recognition result, the error based on the recognition result and normal solution that are sequentially output successively updates the weight of each layer
Coefficient n is simultaneously accumulated as data, and repeatedly, thus the error of recognition result and normal solution becomes smaller, the knowledge of the classification of defect D
Other precision improves.
According to the present embodiment, it is related to a kind of defect inspecting system 1, which has: light source 2, to inspection
It checks as T irradiation light；Image pickup part 3 shoots two dimensional image F by discrete time, and two dimensional image F is based on from light source 2 to inspection
Object T irradiate and penetrate check object T or on check object T reflect after light and formed；Delivery section 4, by check object T
It is relatively conveyed relative to light source 2 and image pickup part 3 along conveying direction X；And image processing part 5, processing are clapped by image pickup part 3
The image data of the two dimensional image F taken out, wherein by image processing part 5 based on to the defect D for being included with two dimensional image F
The data that the result of the relevant rote learning of identification of classification is accumulated, are clapped by image pickup part 3 by discrete time to identify
The classification for the defect D that a series of two dimensional image F taken out is included, therefore by being suitable for rote learning to press discrete time
The two dimensional image F that shoots and improve accuracy of identification, in addition to this, shot by image pickup part 3 in two dimensional image F and conveying
The changed two dimensional image F of brightness on the consistent direction direction X, therefore rote learning is applied to shoot by discrete time
The changed two dimensional image F of brightness at each position along conveying direction X in two dimensional image F out, so as to improve
The accuracy of identification of defect D.
In addition, in the present embodiment, from the occulter 6 between light source 2 and check object T to from light source 2 to inspection
It checks as T a part of light irradiated is blocked, thus on the two dimensional image F shot by image pickup part 3 by discrete time
Form bright portion 1 and dark portion d, by delivery section 4 by check object T-phase for light source 2, occulter 6 and image pickup part 3 along with bright portion 1
The a series of two dimension for relatively conveying with the line of demarcation b of the dark portion d conveying direction X intersected, therefore being shot by discrete time
Each position of check object T in image F enters bright portion 1 and dark portion d this two side, the inspection pair in a series of two dimensional image F
As the presentation mode at each position of T is more significantly changed by discrete time, therefore it can be improved the accuracy of identification of defect D.
It this concludes the description of embodiments of the present invention, but the present invention is not limited to above embodiment, it can be with various sides
Formula is implemented.For example, in the above-described embodiment, it is illustrated centered on the case where by check object being film, but of the invention
Defect inspecting system and defect detecting method for example can be suitable for being filled in the loading inspection of the liquid of container in production line
It looks into.By the defect inspecting system 1 and defect detecting method of present embodiment, it can check that liquid does not reach institute's phase in container
The position of prestige or liquid are less than the defects of desired position in container.
In addition, the defect inspecting system 1 and defect detecting method of present embodiment can be suitable for glass in production line
The visual examinations such as fracture, the scar of product etc..When applying illumination to glassware to shoot, one in image is being shot
In the case where the existing defects of part, defect can be extracted using the high this case in brightness ratio others position.
Claims (4)
1. a kind of defect inspecting system, which is characterized in that have:
Light source, to check object irradiation light；
Image pickup part shoots two dimensional image by discrete time, which is based on shining from the light source to the check object
Penetrate and penetrate the check object or in the check object reflect after the light and formed；
Delivery section relatively conveys the check object relative to the light source and the image pickup part along conveying direction；
And
Image processing part handles the image data for the two dimensional image shot by the image pickup part,
The image pickup part is shot in the changed with brightness on the consistent direction of the conveying direction of the two dimensional image
The two dimensional image,
The relevant rote learning of identification of the described image processing unit based on the classification to the defect for being included to the two dimensional image
The data that are accumulated of result, to identify a series of two dimension shot by the image pickup part by discrete time
The classification for the defect that image is included.
2. defect inspecting system according to claim 1, wherein
The defect inspecting system is also equipped with occulter, and the occulter is and right between the light source and the check object
A part of the light irradiated from the light source to the check object is blocked, thus discrete being pressed by the image pickup part
Bright portion and dark portion are formed on the two dimensional image of time shooting,
The delivery section by the check object relative to the light source, the occulter and the image pickup part along with stated clearly
The conveying direction of portion and the intersection of the line of demarcation of the dark portion relatively conveys.
3. a kind of defect detecting method characterized by comprising
From the light source of defect inspecting system to the irradiation process of check object irradiation light；
The camera shooting process of two dimensional image is shot by discrete time by the image pickup part of the defect inspecting system, wherein the two dimension
Image is based on irradiating and penetrate the check object from the light source to the check object in the irradiation process or in institute
It states the light after reflecting in check object and is formed；
By the delivery section of the defect inspecting system by the check object relative to the light source and the image pickup part along defeated
Send the conveying operation that direction relatively conveys；And
Figure by the image processing part of the defect inspecting system to the two dimensional image shot in the camera shooting process
As the image procossing process that data are handled,
In the camera shooting process, shoots and occur in the two dimensional image with brightness on the consistent direction of the conveying direction
The two dimensional image of variation,
In described image treatment process, the relevant machine of identification based on the classification to the defect for being included to the two dimensional image
The data that are accumulated of result of tool study, come identify shot in the camera shooting process by discrete time it is a series of
The two dimensional image defect that is included classification.
4. defect detecting method according to claim 3, wherein
In the irradiation process, the occulter using the defect inspecting system is pressing discrete time by the camera shooting process
Bright portion and dark portion are formed on the two dimensional image shot, wherein the occulter is located at the light source and the inspection pair
It is blocked as between, and to a part of the light irradiated from the light source to the check object,
In the conveying operation, by the check object relative to the light source, the occulter and the image pickup part along
The conveying direction intersected with the line of demarcation in stated clearly portion and the dark portion relatively conveys.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2017142922A JP2019023587A (en) | 2017-07-24 | 2017-07-24 | Defect inspection system and defect inspection method |
| JP2017-142922 | 2017-07-24 |
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| Publication Number | Publication Date |
|---|---|
| CN109297972A true CN109297972A (en) | 2019-02-01 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810800030.9A Pending CN109297972A (en) | 2017-07-24 | 2018-07-19 | Defect inspecting system and defect detecting method |
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| Country | Link |
|---|---|
| JP (1) | JP2019023587A (en) |
| KR (1) | KR20190011198A (en) |
| CN (1) | CN109297972A (en) |
| TW (1) | TW201908719A (en) |
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| CN111899184A (en) * | 2020-03-31 | 2020-11-06 | 珠海市杰理科技股份有限公司 | Image defect repairing and neural network training method, device, equipment and system |
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| KR102027951B1 (en) * | 2019-06-07 | 2019-10-04 | 권일수 | Method and apparatus for controlling integrated circuit manufacturing process |
| CN114556416A (en) * | 2019-10-18 | 2022-05-27 | 株式会社日立高新技术 | Inspection system and non-transitory computer readable medium |
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| JP2019023587A (en) | 2019-02-14 |
| KR20190011198A (en) | 2019-02-01 |
| TW201908719A (en) | 2019-03-01 |
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