CN105205803A - Display panel defect detection method - Google Patents
Display panel defect detection method Download PDFInfo
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- CN105205803A CN105205803A CN201510507211.9A CN201510507211A CN105205803A CN 105205803 A CN105205803 A CN 105205803A CN 201510507211 A CN201510507211 A CN 201510507211A CN 105205803 A CN105205803 A CN 105205803A
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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
- 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
- G06T7/0008—Industrial image inspection checking presence/absence
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30164—Workpiece; Machine component
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Abstract
The invention discloses a display panel defect detection method. The method comprises steps that, a side surface of a display panel needing detection is shot to acquire detection images of the surface needing detection; tonal values of the detection images are calculated, a defect pattern of the detection images is detected according to the tonal values and change; an edge of the defect pattern is detected; a coordinate system is established to acquire a coordinate of any point on the edge of the defect pattern; the dimension of the defect pattern is calculated according to coordinates of the points on the edge of the defect pattern; whether the display panel is qualified is determined according to the dimension of the defect pattern.
Description
Technical field
The present invention relates to a kind of defects of display panel detection method.
Background technology
Existing display panel needs through automatic optical detection device after finalization of the manufacture to detect whether existing defects.If detect existing defects on display panel, can position the defect detected and this display panel is transported to reparation website and repair.But, in actual repair process, find that described automatic optical detection device is often judged by accident, such as: the flaw size detected is less than standard value, defect is but detected as face defect in glass back, FEOL does not dry up steam is mistaken as defect etc.So existing testing process needs to set up reinspection website and takes pictures to the position that this display panel is detected defect, then is carried out judging whether genuine existing defects according to photo by operating personnel.But this kind of mode can improve production cost, and the situation that examination criteria differs can be there is due to the individual difference of operating personnel.
Therefore, need to provide the defects of display panel detection method can improving the problems referred to above.
Summary of the invention
In order to solve the problems of the technologies described above, embodiments provide a kind of defects of display panel detection method, it comprises:
The side surface detected is needed to take pictures to obtain the detected image on the surface that display panel needs detect to display panel;
Calculate the gray-scale value of this detected image and detect the defect pattern in detected image according to the size of detected image gray-scale value and change;
Detect the edge of this defect pattern;
Set up a coordinate system with the coordinate of any point on the edge obtaining this defect pattern;
The size of this defect pattern is calculated according to the coordinate of the point on defect pattern edge;
Judge that whether this display panel is qualified according to the size of this defect pattern.
Wherein, if the size of this defect pattern is defective, by the size of this defect pattern with preset reparation threshold value compared with to judge that this display panel is the need of reparation.
Wherein, the size of this defect pattern adopts the first size along first direction and the second size along second direction to assess, and repairs threshold value or this defect pattern and is less than or equal to default first direction along the second size of second direction and repairs threshold value, need manually to judge that this defect pattern is the need of reparation if this defect pattern is less than or equal to default first direction along the first size of first direction.
Wherein, repair threshold value or this defect pattern and be greater than default second direction along the second size of second direction if this defect pattern is greater than default first direction along the first size of first direction and repair threshold value, judge that display panel needs to repair.
Wherein, the size of this defect pattern adopts the first size along first direction and the second size along second direction to assess, if this defect pattern is less than or equal to the qualified threshold value of default first direction and this defect pattern along the first size of first direction be less than or equal to the qualified threshold value of default second direction along the second size of second direction, judges the size qualification of this defect pattern.
Wherein, what set up is a rectangular coordinate system, respectively with different first directions and second direction be coordinate system X-axis and Y-axis.
Wherein, detect the regular circle shapes pattern in this detected image and the regular circle shapes pattern detected is screened out.
Wherein, regular circle shapes pattern detects from detected image via Hough transform.
Wherein, Sobel operator edge detection method is used to detect the edge of this defect pattern.
Wherein, calculated by the gray-scale value of Da-Jin algorithm to this detected image, defect pattern is split as prospect from detected image as a setting.
Defects of display panel detection method provided by the present invention is processed captured display panel image by the method for image procossing, the size of automatic analysis defect the size analyzing this defect determine whether to need to repair automatically, thus decrease operating personnel, improve detection efficiency.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the flow chart of steps of the defects of display panel detection method that the embodiment of the present invention provides.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
As shown in Figure 1, the defects of display panel detection method that the embodiment of the present invention provides, it comprises the steps:
Step S1, needs the side surface detected to take pictures to obtain the detected image on the surface that display panel needs detect to display panel.
Step S2, calculates the gray-scale value of this detected image and detects the defect pattern in detected image according to the size of detected image gray-scale value and change.
Concrete, calculated by the gray-scale value of Da-Jin algorithm to this detected image, defect pattern is split as prospect from detected image as a setting.Da-Jin algorithm presets the segmentation threshold of gray threshold T1 as prospect and background, travels through T1, when the value of T1 makes variances sigma from the minimum gradation value of detected image to maximum gradation value
2=w
0(u
0-u
t)
2-w
1(u
1-u
t)
2time maximum, think that T1 is reasonable segmentation threshold.Wherein, w
0+ w
1=1, u
t=w
0* u
0+ w
1* u
1, the size of this detected image is M*N, w
0=N0/M*N, w
1=N1/M*N, N0 are less than the number of pixels of got segmentation threshold T1 for the gray-scale value of pixel in detected image, and N1 is greater than the number of pixels of got segmentation threshold T1 for the gray-scale value of pixel in detected image.
In other implementations, consider in a Da-Jin algorithm reality and sometimes just can not be partitioned into defect, between minimum gradation value and the first segmentation threshold T1 that Da-Jin algorithm obtains for the first time, Da-Jin algorithm again can be used to obtain the second segmentation threshold T2 for gray-scale value, from detected image, be partitioned into defect pattern with the second segmentation threshold T2.
According to step S1 and S2, the defect erroneous judgement situation easily occurred in prior art automatically can be avoided, specific as follows:
If defect is positioned at the back side of display panel, the back side because of display panel is not the surface needing to detect, so can not comprise the defect pattern corresponding to this defect in captured image.
If defect is caused by water vapour, before conveyance process to shot region, water vapor generally can evaporate, so also there will not be the defect pattern corresponding to this defect in captured image.
If before taking pictures through the defect detected by automatic optical detection device be because of automatic optical detection device image sensor noise or optimum configurations is not good caused, then because of in fact display panel not existing defects so captured image also there will not be defect pattern.
Step S3, detects the edge of this defect pattern.In the present embodiment, Sobel operator edge detection method is used to detect the edge of this defect pattern.
Step S4, detects the regular circle shapes pattern in this detected image and is screened out by the regular circle shapes pattern detected.Because this display panel needs the surface of detection can be provided with interval body, and the shape of this interval body is generally regular circle shapes.So, need to be screened out on the impact that follow-up defect pattern analysis causes to reduce interval body pattern.In the present embodiment, the regular circle shapes pattern of this interval body can detect from detected image via Hough transform.
Step S5, sets up a coordinate system with the coordinate of any point on the edge obtaining this defect pattern.In the present embodiment, what set up is a rectangular coordinate system, respectively with different first directions and second direction be coordinate system X-axis and Y-axis.
Step S6, calculates the size of this defect pattern according to the coordinate of the point on defect pattern edge.In the rectangular coordinate system of present embodiment, the X-coordinate of this defect pattern along the two-end-point on first direction is subtracted each other and asked absolute value and show that this defect pattern is along the first size △ X on first direction, the Y-coordinate of this defect pattern along the two-end-point in second direction is subtracted each other and asked absolute value and show that this defect pattern is along the second size △ Y in second direction.Thus, the size of this defect pattern can be evaluated by the size along at least two different dimensions.
According to the size of this defect pattern, step S7, judges that whether this display panel is qualified.By the size of this calculated defect pattern with preset qualified threshold value compared with to judge that whether this display panel qualified.
In the present embodiment, the size of this defect pattern adopts the first size △ X along first direction and the second size △ Y along second direction to assess.So, by this defect pattern along the first size △ X of first direction and the default qualified threshold X of first direction
threlatively.If this defect pattern is less than or equal to the qualified threshold X of default first direction along the first size △ X of first direction
th, then the size qualification of this defect pattern along first direction is judged.If this defect pattern is greater than the qualified threshold X of default first direction along the first size △ X of first direction
th, then needs reparation is judged whether.
By this defect pattern along the second size △ Y of second direction and the default qualified threshold value Y of second direction
threlatively.If this defect pattern is less than or equal to the qualified threshold value Y of default second direction along the second size △ Y of second direction
th, then the size qualification of this defect pattern along second direction is judged.If this defect pattern is greater than the qualified threshold value Y of default second direction along the first size △ X of second direction
th, then needs reparation is judged whether.
If the size of this defect pattern along first direction and the size along second direction are all qualified, then judge that this display panel is qualified, this time defects of display panel detects and terminates.
According to the size on this defect pattern edge, step S8, judges that display panel is the need of reparation.If the size of this defect pattern is defective, by the size of this defect pattern with preset reparation threshold value compared with to judge that this display panel is the need of reparation.
In the present embodiment, the size of this defect pattern adopts the first size △ X along first direction and the second size △ Y along second direction to assess.So, this defect pattern is repaired threshold X along the first size △ X of first direction and default first direction
repairrelatively.If this defect pattern is less than or equal to default first direction reparation threshold X along the first size △ X of first direction
repair, then need manually to judge that this defect pattern is the need of reparation.If this defect pattern is greater than default first direction reparation threshold X along the first size △ X of first direction
repair, then judge that display panel needs to repair.Be understandable that, default first direction repairs threshold X
repairbe greater than the qualified threshold X of default first direction
th.
This defect pattern is repaired threshold value Y along the second size △ Y of second direction and default second direction
repairrelatively.If this defect pattern is less than or equal to default first direction reparation threshold value Y along the second size △ Y of second direction
repair, then need manually to judge that this defect pattern is the need of reparation.If this defect pattern is greater than default second direction reparation threshold value Y along the second size △ Y of second direction
repair, then judge that display panel needs to repair.Be understandable that, default second direction repairs threshold value Y
repairbe greater than the qualified threshold value Y of default second direction
th.
Defects of display panel detection method provided by the present invention is processed captured display panel image by the method for image procossing, not only automatically can avoid erroneous judgement situation of the prior art, can also automatic analysis defect size and automatically determine whether to need to repair by the dimension analysis of this defect, thus decrease operating personnel, improve detection efficiency.
Above disclosedly be only a kind of preferred embodiment of the present invention, certainly can not limit the interest field of the present invention with this, therefore according to the equivalent variations that the claims in the present invention are done, still belong to the scope that the present invention is contained.
Claims (10)
1. a defects of display panel detection method, it comprises:
The side surface detected is needed to take pictures to obtain the detected image on the surface that display panel needs detect to display panel;
Calculate the gray-scale value of this detected image and detect the defect pattern in detected image according to the size of detected image gray-scale value and change;
Detect the edge of this defect pattern;
Set up a coordinate system with the coordinate of any point on the edge obtaining this defect pattern;
The size of this defect pattern is calculated according to the coordinate of the point on defect pattern edge;
Judge that whether this display panel is qualified according to the size of this defect pattern.
2. defects of display panel detection method as claimed in claim 1, is characterized in that, if the size of this defect pattern is defective, by the size of this defect pattern compared with default reparation threshold value to judge that this display panel is the need of reparation.
3. defects of display panel detection method as claimed in claim 2, it is characterized in that, the size of this defect pattern adopts the first size along first direction and the second size along second direction to assess, and repairs threshold value or this defect pattern and is less than or equal to default first direction along the second size of second direction and repairs threshold value, need manually to judge that this defect pattern is the need of reparation if this defect pattern is less than or equal to default first direction along the first size of first direction.
4. defects of display panel detection method as claimed in claim 3, it is characterized in that, repair threshold value or this defect pattern and be greater than default second direction along the second size of second direction if this defect pattern is greater than default first direction along the first size of first direction and repair threshold value, judge that display panel needs to repair.
5. defects of display panel detection method as claimed in claim 1, it is characterized in that, the size of this defect pattern adopts the first size along first direction and the second size along second direction to assess, if this defect pattern is less than or equal to the qualified threshold value of default first direction and this defect pattern along the first size of first direction be less than or equal to the qualified threshold value of default second direction along the second size of second direction, judges the size qualification of this defect pattern.
6. defects of display panel detection method as claimed in claim 1, it is characterized in that, what set up is a rectangular coordinate system, respectively with different first directions and second direction be coordinate system X-axis and Y-axis.
7. defects of display panel detection method as claimed in claim 1, is characterized in that, detect the regular circle shapes pattern in this detected image and screened out by the regular circle shapes pattern detected.
8. defects of display panel detection method as claimed in claim 7, it is characterized in that, regular circle shapes pattern detects from detected image via Hough transform.
9. defects of display panel detection method as claimed in claim 1, is characterized in that, uses Sobel operator edge detection method to detect the edge of this defect pattern.
10. defects of display panel detection method as claimed in claim 1, be is characterized in that, calculated, defect pattern split from detected image as a setting as prospect by the gray-scale value of Da-Jin algorithm to this detected image.
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| CN201510507211.9A CN105205803A (en) | 2015-08-18 | 2015-08-18 | Display panel defect detection method |
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| CN201510507211.9A CN105205803A (en) | 2015-08-18 | 2015-08-18 | Display panel defect detection method |
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| CN107402221A (en) * | 2017-08-08 | 2017-11-28 | 广东工业大学 | A kind of defects of display panel recognition methods and system based on machine vision |
| CN108345134A (en) * | 2018-01-11 | 2018-07-31 | 福建联迪商用设备有限公司 | The test method and intelligent object of display function |
| CN109752870A (en) * | 2019-01-31 | 2019-05-14 | 电子科技大学中山学院 | Electrophoresis electronic paper ghost detection system and detection method |
| CN109932160A (en) * | 2019-03-05 | 2019-06-25 | 武汉精立电子技术有限公司 | AOI and densitometer detection system and method |
| WO2020077784A1 (en) * | 2018-10-18 | 2020-04-23 | 深圳市华星光电半导体显示技术有限公司 | Method and system for determining defect aggregation in image overlay |
| CN112954304A (en) * | 2021-01-18 | 2021-06-11 | 湖北经济学院 | Mura defect evaluation method and system for display panel and readable storage medium |
| CN113345328A (en) * | 2021-05-28 | 2021-09-03 | Tcl华星光电技术有限公司 | Mura repairing method for display panel |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107402221A (en) * | 2017-08-08 | 2017-11-28 | 广东工业大学 | A kind of defects of display panel recognition methods and system based on machine vision |
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Application publication date: 20151230 |