Method, system, and computer program product for detection of defects based on multiple references

Patent metadata

Field	Value
Publication number	US-9558548-B2
Application number	US-201514738370-A
Country	US
Kind code	B2
Filing date	Jun 12, 2015
Priority date	Feb 21, 2013
Publication date	Jan 31, 2017
Grant date	Jan 31, 2017

Abstract

A system includes a memory and a processor device operatively coupled to the memory to obtain an inspected noise-indicative value representative of an analyzed pixel of an inspected image of an inspected object, and a reference noise-indicative value representative for each of multiple reference pixels of the inspected image. The processor device computes a representative noise-indicative value based on the inspected noise-indicative value and multiple reference noise-indicative values, calculates a defect-indicative value based on an inspected value representative of the analyzed pixel and determines a presence of a defect in the analyzed pixel based on the representative noise-indicative value and the defect-indicative value.

First claim

What is claimed is:

1. A system comprising:
a memory; and
a processor device operatively coupled to the memory to:
obtain an inspected noise-indicative value representative of an analyzed pixel of an inspected image of an inspected object, and a reference noise-indicative value representative for each of a plurality of reference pixels of the inspected image;
compute a representative noise-indicative value based on the inspected noise-indicative value and a plurality of reference noise-indicative values;
calculate a defect-indicative value based on an inspected value representative of the analyzed pixel; and
determine a presence of a defect in the analyzed pixel based on the representative noise-indicative value and the defect-indicative value.

2. The system of claim 1 , wherein the inspected object is selected from a group consisting of an electronic circuit, a wafer, a photomask, and a reticle.

3. The system of claim 1 , wherein the plurality of reference pixels are selected by:
defining a plurality of reference cells; and
identifying pixels in locations in the plurality of reference cells that are equivalent to a location of the analyzed pixel within a respective cell.

4. The system of claim 1 , wherein the processor is to compute the representative noise-indicative value at least by:
selecting a subset of a plurality of noise-indicative values, the plurality of noise-indicative values comprising the inspected noise-indicative value and a plurality of reference noise-indicative values, the plurality of noise-indicative values being representative of corresponding pixels of a group comprising the analyzed pixel and the plurality of reference pixels, the subset excluding a minimal noise-indicative value out of the plurality of noise-indicative values; and
defining the representative noise-indicative value based on the subset of noise-indicative values.

5. The system of claim 4 , wherein the processor is to select the subset based on a size order between the plurality of noise-indicative values.

6. The system of claim 4 , wherein the processor is to compute the representative noise-indicative value based on the subset which excludes a maximal noise-indicative value out of the plurality of noise-indicative values.

7. The system of claim 1 , wherein the processor is to compute the representative noise-indicative value by selecting one of a plurality of noise-indicative values as the representative noise-indicative value, the plurality of noise-indicative values comprising the inspected noise-indicative value and a plurality of reference noise-indicative values.

8. A method comprising:
obtaining, by a processor device, an inspected noise-indicative value representative of an analyzed pixel of an inspected image of an inspected object, and a reference noise-indicative value representative for each of a plurality of reference pixels of the inspected image;
computing a representative noise-indicative value based on the inspected noise-indicative value and a plurality of reference noise-indicative values;
calculating a defect-indicative value based on an inspected value representative of the analyzed pixel; and
determining a presence of a defect in the analyzed pixel based on the representative noise-indicative value and the defect-indicative value.

9. The method of claim 8 , wherein the inspected object is selected from a group consisting of an electronic circuit, a wafer, a photomask, and a reticle.

10. The method of claim 8 , further comprising:
defining a plurality of reference cells; and
identifying pixels in locations in the plurality of reference cells that are equivalent to a location of the analyzed pixel within a respective cell as the plurality of reference pixels.

11. The method of claim 8 , wherein computing the representative noise-indicative value comprises:
selecting a subset of a plurality of noise-indicative values, the plurality of noise-indicative values comprising the inspected noise-indicative value and a plurality of reference noise-indicative values, the plurality of noise-indicative values being representative of corresponding pixels of a group comprising the analyzed pixel and the plurality of reference pixels, the subset excluding a minimal noise-indicative value out of the plurality of noise-indicative values; and
defining the representative noise-indicative value based on the subset of noise-indicative values.

12. The method of claim 11 , wherein selecting the subset is based on a size order between the plurality of noise-indicative values.

13. The method of claim 8 , wherein computing the representative noise-indicative value is based on the subset which excludes a maximal noise-indicative value out of the plurality of noise-indicative values.

14. The method of claim 8 , wherein computing the representative noise-indicative value comprises:
selecting one of a plurality of noise-indicative values as the representative noise-indicative value, the plurality of noise-indicative values comprising the inspected noise-indicative value and a plurality of reference noise-indicative values.

15. A non-transitory computer-readable storage medium, including instructions that, when executed by a processor device, cause the processing device to perform operations comprising:
obtaining, by the processor device, an inspected noise-indicative value representative of an analyzed pixel of an inspected image of an inspected object, and a reference noise-indicative value representative for each of a plurality of reference pixels of the inspected image;
computing a representative noise-indicative value based on the inspected noise-indicative value and a plurality of reference noise-indicative values;
calculating a defect-indicative value based on an inspected value representative of the analyzed pixel; and
determining a presence of a defect in the analyzed pixel based on the representative noise-indicative value and the defect-indicative value.

16. The non-transitory computer-readable storage medium of claim 15 , the operations further comprising:
defining a plurality of reference cells; and
identifying pixels in locations in the plurality of reference cells that are equivalent to a location of the analyzed pixel within a respective cell as the plurality of reference pixels.

17. The non-transitory computer-readable storage medium of claim 15 , wherein computing the representative noise-indicative value comprises:
selecting a subset of a plurality of noise-indicative values, the plurality of noise-indicative values comprising the inspected noise-indicative value and a plurality of reference noise-indicative values, the plurality of noise-indicative values being representative of corresponding pixels of a group comprising the analyzed pixel and the plurality of reference pixels, the subset excluding a minimal noise-indicative value out of the plurality of noise-indicative values; and
defining the representative noise-indicative value based on the subset of noise-indicative values.

18. The non-transitory computer-readable storage medium of claim 17 , wherein selecting the subset is based on a size order between the plurality of noise-indicative values.

19. The non-transitory computer-readable storage medium of claim 15 , wherein computing the representative noise-indicative value is based on the subset which excludes a maximal noise-indicative value out of the plurality of noise-indicative values.

20. The non-transitory computer-readable storage medium of claim 15 , wherein computing

Assignees

• Applied Materials Israel Ltd

Inventors

• Amzaleg Moshe
• Cohen Yehuda
• Dodzen Nir Ben-David
• Rozenman Efrat

Classifications

• H10P72/0616

  Monitoring of warpages, curvatures, damages, defects or the like · CPC title

• G06T7/0002

  Inspection of images, e.g. flaw detection · CPC title

• G06T2207/30148

  Semiconductor; IC; Wafer · CPC title

• G06T7/001 Primary

  using an image reference approach · CPC title

• H01L21/67288

  Electricity · mapped topic