SYSTEM FOR DEFECT DETECTION AND REPAIR

• US 20130034293A1
• Filed: 08/04/2011
• Published: 02/07/2013
• Est. Priority Date: 08/04/2011
• Status: Active Grant

• Current Assignee: Sharp Kabushiki Kaisha (Hon Hai Precision Industry Co., Ltd.)
• Original Assignee: Sharp Laboratories of America Incorporated (Hon Hai Precision Industry Co., Ltd.)
• Inventors: Xu, Xinyu, Yuan, Chang
• Granted Patent: US 9,092,842 B2
• Time in Patent Office: Days
• US Class Current: 382/141
• CPC Class Codes: G06T 2207/20224 Image subtraction
• CPC Class Codes: G06T 2207/30121 CRT, LCD or plasma display
• CPC Class Codes: G06T 2207/30141 Printed circuit board [PCB]
• CPC Class Codes: G06T 7/001 using an image reference approach

Abstract

A system for identifying a repair cut location for a defect in a liquid crystal device includes receiving an input image, a defect mask image, and a landmark structure image. The system determines a repair cut location, based upon the input image, the defect mask image, and the landmark structure image, for a liquid crystal device proximate the defect. The determination may be based upon a type of said defect, a cause of said defect, a position of said defect, and a spatial relationship of the defect and a structure of the landmark image.

Claims

1. A method for identifying a repair cut location for a defect in a liquid crystal device comprising:

(a) receiving an input image of a portion of said liquid crystal device;

(b) receiving a defect mask image;

(c) receiving a landmark structure image;

(d) determining said repair cut location, based upon said input image, said defect mask image, and said landmark structure image, for said liquid crystal device proximate said defect based upon;

(1) a type of said defect,

(2) a cause of said defect,

(3) a position of said defect, and

(4) a spatial relationship of said defect and a structure of said landmark image.

2. The method of claim 1 wherein said cut location is selected based upon said position and a size of said defect in such a manner to avoid cutting said defect.

3. The method of claim 1 wherein said cut location and a cut size is selected substantially closer to said defect among a set of valid selections.

4. The method of claim 1 wherein said cut location and a cut size is selected based on defect type and defect cause.

5. The method of claim 1 wherein said cut position and a cut size is determined by analyzing the spatial relationship between LCD landmarks and said defect to avoid cutting unintended structures.

6. The method of claim 1 wherein the orientation of a cut for said cut position is determined based on the orientation of landmarks of said landmark structure image.

7. The method of claim 1 wherein a pool of candidate cut positions are obtained, a search determines said cut position that is close to said defect and does not hit on said defect.

8. The method of claim 1 wherein a width of a repair cut at said cut position is determined based on said defect size and landmark line width.

13. The method of claim 1 wherein said mask image is based upon a reduction on the effects of irregular lighting patterns.

14. The method of claim 1 wherein said mask image is based upon image difference based pre-filtering.

15. The method of claim 14 wherein said image difference is based upon squared differences.

16. The method of claim 1 wherein said mask image is based upon a plurality of difference maps.

17. The method of claim 15 wherein said difference maps is based upon pixel color differences.

18. The method of claim 15 wherein said difference maps is based upon local window based pixel color differences.

19. The method of claim 1 wherein said mask image is based upon an integral image.

20. The method of claim 1 wherein said mask image is based upon local windows.

21. The method of claim 1 wherein said mask image is based upon variations on one or more lines.

22. The method of claim 1 wherein said mask image is based upon a statistical model based upon pixel level detection.

23. The method of claim 1 wherein said mask image is based upon a blob level defect refinement.

24. The method of claim 1 wherein a plurality of input vectors are determined for a plurality of pixels of said input image.

25. The method of claim 24 wherein one of said input vectors is based upon a pixel based comparison.

26. The method of claim 24 wherein one of said input vectors is based upon a local color difference map.

27. The method of claim 24 wherein one of said input vectors is based upon a local window based comparison.

28. The method of claim 24 wherein one of said input vectors is based upon a landmark label image.

29. The method of claim 23 wherein one of said input vectors is based upon a distance to image edges.

30. The method of claim 23 wherein one of said input vectors is based upon an image gradient magnitude.

31. The method of claim 23 wherein one of said input vectors is based upon an image gradient orientation.

9. A method for identifying a defect in a liquid crystal device comprising:

(a) receiving an input image of a portion of said liquid crystal device;

(b) receiving a defect-free model image of said liquid crystal device;

(c) receiving a landmark structure image of said liquid crystal device;

(d) identifying a defect position and a defect size of said defect based of said defect-free model image, said landmark structure image, and input image.

10. The method of claim 9 wherein said mask image substantially reduces the effects of color patterns in said input image.

11. The method of claim 9 wherein said mask image substantially reduces the effects of bubbles in said input image.

12. The method of claim 10 wherein said mask image is based upon a pair of primary colors.