Method and device for sealant coating inspection

Patent metadata

Field	Value
Publication number	US-10026162-B2
Application number	US-201515030977-A
Country	US
Kind code	B2
Filing date	Dec 8, 2015
Priority date	Dec 8, 2014
Publication date	Jul 17, 2018
Grant date	Jul 17, 2018

Abstract

The present disclosure provides a method and a device of inspecting a sealant coating on a substrate. An image of a sample substrate is captured. The sample substrate is selected from a plurality of substrates. A non-coating area is identified from the image of the sample substrate. Abnormal points are identified in the non-coating area. Positions of the abnormal points are recorded. An image of a sealant-coated substrate having a sealant coating on one of the plurality of substrates is captured. Defect positions of the sealant coating are identified from the image of the sealant-coated substrate. Defects located in a non-coating area of the sealant-coated substrate at positions corresponding to the positions of the abnormal points identified based on the sample substrate are considered as normal.

First claim

What is claimed is:

1. A method of sealant coating inspection, comprising:
capturing an image of a sample substrate selected from a plurality of substrates;
identifying a non-coating area from the image of the sample substrate, identifying abnormal points in the non-coating area, and recording positions of the abnormal points with respect to an alignment mark, wherein the abnormal points include areas or points on the sample substrate, and, in the areas or points, brightness and contrast are similar to or comparable with brightness and contrast of a sealant coating on the sample substrate;
capturing an image of a sealant-coated substrate having the sealant coating on one of the plurality of substrates; and
identifying defect positions of the sealant coating from the image of the sealant-coated substrate, wherein defects located in a non-coating area of the sealant-coated substrate at positions corresponding to the positions of the abnormal points identified based on the sample substrate are considered as normal.

2. The method of claim 1 , further comprising:
selecting a group of sample substrates from the plurality of substrates, wherein the group of sample substrates includes the sample substrate,
capturing images of the group of sample substrates,
identifying abnormal points in non-coating areas of the group of sample substrates, and
considering a combination of the abnormal points from the images of the group of sample substrates as normal for identifying the defect positions of the sealant coating of the sealant-coated substrate.

3. The method of claim 1 , further including:
repeatedly capturing the image of the sample substrate to obtain a plurality of images of the sample substrate, wherein:
the abnormal points include a combination of abnormal points from each image of the plurality of images of the sample substrate.

4. The method of claim 1 , prior to identifying the non-coating area from the image of the sample substrate, further including:
examining brightness and contrast of the image of the sample substrate to determine whether the brightness and the contrast is each within a pre-configured range, and
proceeding to identify the non-coating area from the image of the sample substrate, when the brightness and the contrast is each within a pre-configured range.

5. The method of claim 1 , further including a light source configured on at least one side of the sample substrate or the sealant-coated sample substrate for illumination.

6. The method of claim 1 , further including a light source configured on each of opposing sides of the sample substrate or the sealant-coated sample substrate for illumination.

7. The method of claim 5 , further including monitoring a light intensity of the light source.

8. The method of claim 1 , further including:
configuring mark points on the sample substrate, wherein:
the non-coating area is identified by examining a position of an alignment pattern containing the mark points and based on a relationship between positions of the mark points and a coating area supposed for coating the sealant material, to identify the coating area supposed for the sealant coating and the non-coating area outside of the coating area.

9. The method of claim 8 , wherein at least two mark points are configured on the sample substrate.

10. The method of claim 1 , wherein identifying the abnormal points in the non-coating area includes:
acquiring brightness and contrast characteristics of the sealant coating, and
comparing brightness and contrast characteristics of the image of the sample substrate in the non-coating area with the brightness and contrast characteristics of the sealant coating, wherein:
when the brightness and contrast characteristics of certain areas or points in the image of the sample substrate have substantially same brightness and contrast characteristics of the sealant coating, the certain areas or points are identified as the abnormal points.

11. A device for sealant coating inspection, comprising:
a camera, configured to capture an image of a sample substrate selected from a plurality of substrates; and
a processor, configured to
identify a non-coating area from the image of the sample substrate, identify abnormal points in the non-coating area, and record positions of the abnormal points with respect to an alignment mark, wherein the abnormal points include areas or points on the sample substrate, and, in the areas or points, brightness and contrast are similar to or comparable with brightness and contrast of a sealant coating on the sample substrate; and
identify defect positions of the sealant coating from an image of a sealant-coated substrate having the sealant coating on one of the plurality of substrates, wherein defects located in a non-coating area of the sealant-coated substrate at positions corresponding to the positions of the abnormal points identified based on the sample substrate are considered as normal.

12. The device of claim 11 , further including light sources to illuminate the sample substrate or the sealant-coated substrate for inspection.

13. The device of claim 12 , wherein the light sources include first light source components and second light source components, configured on opposing sides of the sample substrate or the sealant-coated substrate for inspection.

14. The device of claim 12 , wherein the processor is further configured to measure and monitor a light intensity of the light sources.

15. The device of claim 11 , wherein the processor is further configured to measure and monitor a lens surface transmittance of the camera.

16. The device of claim 11 , wherein the processor is further configured to analyze the image of the sealant coating and to identify mark points on the sealant-coated substrate corresponding to mark points configured on the sample substrate.

17. The device of claim 16 , wherein the processor comprises:
one or more selected from a CCD system configuration unit, a mark point configuration unit, an imaging system configuration unit, a light source system configuration unit, a light source parameter configuration unit, an image processing unit, a coating platform control unit, and a status recording unit.

18. A method of sealant coating inspection, comprising:
selecting a group of sample substrates from a plurality of substrates;
capturing images of the group of sample substrates;
identifying a non-coating area from each of the images of the group of the sample substrates, identifying abnormal points in the non-coating area on each of the group of sample substrates, and recording positions of a combination of the abnormal points of the group of sample substrates;
capturing an image of a sealant-coated substrate having a sealant coating on one of the plurality of substrates; and
identifying defect positions of the sealant coating from the image of the sealant-coated substrate, wherein defects located in a non-coating area of the sealant-coated substrate at positions corresponding to the positions of the combination of the abnormal points identified based on the images of the group of sample substrates are considered as normal.

Assignees

• Boe Technology Group Co Ltd
• Hefei Boe Optoelectronics Tech
• Boe Technology Group Co Ltd

Inventors

• Jing Yangkun
• Ding Jia
• Che Xiaopan
• Li Haibo

Classifications

• G01N21/84 Primary

  Systems specially adapted for particular applications · CPC title

• G06T7/0004 Primary

  Industrial image inspection · CPC title

• H04N25/71

  Charge-coupled device [CCD] sensors; Charge-transfer registers specially adapted for CCD sensors · CPC title

• H04N23/56

  provided with illuminating means · CPC title

• G06F18/24

  Classification techniques · CPC title