Adaptive Signature Detection

• US 20110170766A1
• Filed: 05/28/2010
• Published: 07/14/2011
• Est. Priority Date: 06/03/2009
• Status: Active Grant

• Current Assignee: KLA-Tencor Corporation
• Original Assignee: KLA-Tencor Corporation
• Inventors: Gao, Yong, Gao, Lisheng, Huang, Junqing
• Granted Patent: US 8,059,886 B2
• Time in Patent Office: Days
• US Class Current: 382/149
• CPC Class Codes: G01B 11/303 using photoelectric detection means
• CPC Class Codes: G01N 2021/95638 for PCB's
• CPC Class Codes: G01N 21/9501 Semiconductor wafers manufacturing processes per se of semiconductor devices implementing a measuring step H01L22/10
• CPC Class Codes: G06T 2207/10061 from scanning electron microscope
• CPC Class Codes: G06T 2207/20008 Globally adaptive
• CPC Class Codes: G06T 2207/30148 Semiconductor; IC; Wafer
• CPC Class Codes: G06T 7/0006 using a design-rule based approach

Abstract

A processor-based method for detecting defects in an integrated circuit, by creating an image of at least a portion of the integrated circuit with a sensor, grouping pixels of the image into bins based at least in part on a common characteristic of the pixels that are grouped within a given bin, creating a histogram of the pixels in each of the bins, calculating a mean value of the histogram for each of the bins, comparing the mean value for each of the bins to a threshold value, flagging as defect candidates those bins where the mean value of the bin varies from the threshold value by more than a predetermined amount, and performing signature detection on the bins that are flagged as defect candidates, where the image of the integrated circuit is not directly compared to any other image of an integrated circuit.

Claims

1. A processor-based method for detecting defects in an integrated circuit, the method comprising the steps of:

creating an image of at least a portion of the integrated circuit with a sensor,

grouping pixels of the image into bins based at least in part on a common characteristic of the pixels that are grouped within a given bin,

creating a histogram of the pixels in each of the bins,

calculating a mean value of the histogram for each of the bins,

comparing the mean value for each of the bins to a threshold value,

flagging as defect candidates those bins where the mean value of the bin varies from the threshold value by more than a predetermined amount, and

performing signature detection on the bins that are flagged as defect candidates,

where the image of the integrated circuit is not directly compared to any other image of an integrated circuit.

2. The method of claim 1, wherein the common characteristic is at least one of intensity, gradient, texture, projection along the x axis, projection along the y axis, location, range of pixel in the neighborhood, maximum value in the neighborhood, and minimum value in the neighborhood.

3. The method of claim 1, wherein the sensor comprises at least one of a camera, a charge coupled device, a time domain and integration device, an electron beam microscope, a bright field microscope, a dark field microscope, and a surfscan.

4. The method of claim 1, wherein the histogram is created based on the intensity of the pixels in the bin.

5. The method of claim 1, wherein the signature detection includes at least one of under-polish, over-polish, pattern shift, gross defects that affect more than one integrated circuit, and process-induced variations.

6. A apparatus for detecting defects in an integrated circuit, comprising:

a sensor for creating an image of at least a portion of the integrated circuit,

a processor for,

grouping pixels of the image into bins based at least in part on a common characteristic of the pixels that are grouped within a given bin,

creating a histogram of the pixels in each of the bins,

calculating a mean value of the histogram for each of the bins,

comparing the mean value for each of the bins to a threshold value,

flagging as defect candidates those bins where the mean value of the bin varies from the threshold value by more than a predetermined amount, and

performing signature detection on the bins that are flagged as defect candidates,

where the image of the integrated circuit is not directly compared to any other image of an integrated circuit, and

a display for presenting results of at least the signature detection process.

7. The apparatus of claim 6, wherein the common characteristic is at least one of intensity, gradient, texture, projection along the x axis, projection along the y axis, location, range of pixel in the neighborhood, maximum value in the neighborhood, and minimum value in the neighborhood.

8. The apparatus of claim 6, wherein the sensor comprises at least one of a camera, a charge coupled device, a time domain and integration device, an electron beam microscope, a bright field microscope, a dark field microscope, and a surfscan.

9. The apparatus of claim 6, wherein the histogram is created based on the intensity of the pixels in the bin.

10. The apparatus of claim 6, wherein the signature detection includes at least one of under-polish, pattern shift, gross defects that affect more than one integrated circuit, and process-induced variations.

11. A processor-based method for detecting defects in an integrated circuit, the method comprising the steps of:

creating an image of at least a portion of the integrated circuit with a sensor,

grouping pixels of the image into bins,

calculating a mean value of a characteristic of the pixels in each bin,

comparing the mean value for each of the bins to a threshold value,

flagging as defect candidates those bins where the mean value of the bin varies from the threshold value by more than a predetermined amount, and

performing signature detection on the bins that are flagged as defect candidates,

where the image of the integrated circuit is not directly compared to any other image of an integrated circuit.

12. The method of claim 11, wherein the pixels as grouped based upon at least one of common pixel characteristic, pixel segment, pixel region, and design data information.

13. The method of claim 11, wherein the characteristic is at least one of intensity, gradient, texture, projection along the x axis, projection along the y axis, location, range of pixel in the neighborhood, maximum value in the neighborhood, and minimum value in the neighborhood.

14. The method of claim 11, wherein the sensor comprises at least one of a camera, a charge coupled device, a time domain and integration device, an electron beam microscope, a bright field microscope, a dark field microscope, and a surfscan.

15. The method of claim 11, wherein the signature detection includes at least one of under-polish, over-polish, pattern shift, gross defects that affect more than one integrated circuit, and process-induced variations.

16. The method of claim 11, further comprising the step of filtering the characteristic of the pixels prior to grouping the pixels into bins.

17. The method of claim 11, further comprising the step of filtering the characteristic of the pixels after grouping the pixels and prior to performing signature detection.