Defect detection and classification based on attributes determined from a standard reference image
US-2015221076-A1 · Aug 6, 2015 · US
US10186028B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10186028-B2 |
| Application number | US-201615352664-A |
| Country | US |
| Kind code | B2 |
| Filing date | Nov 16, 2016 |
| Priority date | Dec 9, 2015 |
| Publication date | Jan 22, 2019 |
| Grant date | Jan 22, 2019 |
A practical reading order for non-experts. Skip the full description unless you need deep technical detail.
What the patent document calls the invention.
A short plain-language summary of the technical disclosure.
Who owns or filed the patent and who is credited as inventor.
Filing, priority, publication, and grant dates set the timeline.
The legal scope of protection — read this for what is actually claimed.
Technology tags used to group this patent with similar filings.
Prior art links and similar publications in this corpus.
Official abstract text for this publication.
Gray level histograms for a test image and a reference image are adjusted by histogram scaling. Parameters from the histogram scaling are applied to the test image and the reference image. After the parameters are applied, the reference image and the test image are compared to produce a difference image, such as by subtracting the reference image from the test image. Noise in the difference image can be reduced, which improves defect identification in the difference image. In addition, noisy structures in the difference image which are elongated in vertical or horizontal direction can be found. If the noise exceeds a certain threshold, the structures may not be inspected.
Opening claim text (preview).
What is claimed is: 1. A system comprising: a stage configured to hold a wafer; an image generation system configured to generate a test image, wherein the test image is an image of a portion of the wafer; an electronic data storage unit in which at least one reference image is stored; and a controller in electronic communication with the image generation system and the electronic data storage unit, wherein the controller is configured to: receive the test image from the image generation system and the reference image from the electronic data storage unit; calculate a gray level histogram for the test image; calculate a gray level histogram for the reference image; adjust the gray level histogram of the test image and the gray level histogram of the reference image by histogram scaling, wherein the histogram scaling of each of the test image and the reference image is configured to subtract a mean gray level intensity of a first image from a gray level intensity of the first image thereby calculating a difference, to multiply the difference by a gain factor based on maximum and minimum gray level intensity values of the first image and a second image thereby calculating a multiplication result, and to add a constant intensity offset to the multiplication result, wherein the constant intensity offset is based the second image, wherein the first image is one of the test image and the reference image and the second image is the other of the test image and the reference image; compare the reference image and the test image to produce a difference image after adjusting the gray level histograms of the test image and the reference image by the histogram scaling; and identify a defect on the difference image with an algorithm. 2. The system of claim 1 , wherein the controller includes a processor and a communication port in electronic communication with the processor and the electronic data storage unit. 3. The system of claim 1 , wherein the image generation system is part of a scanning electron microscope. 4. The system of claim 1 , wherein the image generation system is configured to use at least one of an electron beam, a broad band plasma, or a laser to generate the test image. 5. The system of claim 1 , wherein the image generation system is configured to use one of bright field or dark field illumination. 6. The system of claim 1 , wherein the gain factor is a ratio of a difference between maximum and minimum gray level intensity values of one of the first image or the second image and maximum and minimum gray level intensity values of the other of the first image or the second image, and wherein the constant intensity offset is a mean gray level intensity. 7. The system of claim 1 , wherein the difference image is configured to be generated by subtracting the reference image from the test image. 8. The system of claim 1 , wherein the test image and the reference image correspond to a same region of the wafer. 9. The system of claim 1 , wherein the controller is further configured to: calculate projections for the difference image perpendicular to an x axis for a first length; calculate projections for the difference image perpendicular to a y axis for a second length; and mask one or more pixels in the difference image along the first length that exceed an x projection threshold or along the second length that exceed a y projection threshold. 10. A method comprising: receiving a test image from a system, wherein the test image is an image of a portion of a wafer; calculating, using a controller, a gray level histogram for the test image; calculating, using the controller, a gray level histogram for a reference image; adjusting, using the controller, the gray level histogram of the test image and the gray level histogram of the reference image by histogram scaling, wherein the histogram scaling of each of the test image and the reference image is configured to subtract a mean gray level intensity of a first image from a gray level intensity of the first image thereby calculating a difference, to multiply the difference by a gain factor based on maximum and minimum gray level intensity values of the first image and a second image thereby calculating a multiplication result, and to add a constant intensity offset to the multiplication result, wherein the constant intensity offset is based the second image, wherein the first image is one of the test image and the reference image and the second image is the other of the test image and the reference image; comparing, using the controller, the reference image and the test image to produce a difference image after adjusting the gray level histograms of the test image and the reference image by the histogram scaling; and identifying, using the controller, a defect on the difference image with an algorithm. 11. The method of claim 10 , wherein the gain factor is a ratio of a difference between maximum and minimum gray level intensity values of one of the first image or the second image and maximum and minimum gray level intensity values of the other of the first image or the second image, and wherein the constant intensity offset is a mean gray level intensity. 12. The method of claim 10 , wherein the test image is a microscope image. 13. The method of claim 10 , wherein the comparing includes subtracting the reference image from the test image. 14. The method of claim 10 , wherein the test image and the reference image correspond to a same region of the wafer. 15. The method of claim 10 , further comprising: calculating projections for the difference image perpendicular to an x axis for a first length; calculating projections for the difference image perpendicular to a y axis for a second length; and masking one or more pixels in the difference image along the first length that exceed an x projection threshold or along the second length that exceed a y projection threshold.
Related publications grouped by family.
Answers are generated from the same data shown on this page.