Migdal Haemeq

US2020141879A1 · US · A1

Patent metadata
FieldValue
Publication numberUS-2020141879-A1
Application numberUS-201816619941-A
CountryUS
Kind codeA1
Filing dateJun 14, 2018
Priority dateJun 14, 2017
Publication dateMay 7, 2020
Grant date

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

A method for automatic defect classification, the method may include (i) acquiring, by a first camera, at least one first image of at least one area of an object; (ii) processing the at least one first image to detect a group of suspected defects within the at least one area; (iii) performing a first classification process for initially classifying the group of suspected defects; (iii) determining whether a first subgroup of the suspected defects requires additional information from a second camera for a completion of a classification; (iv) when determining that the first subgroup of the suspected defects requires additional information from the second camera then: (a) acquiring second images, by the second camera, of the first subgroup of the suspected defects; and (b) performing a second classification process for classifying the first subgroup of suspected defects.

First claim

Opening claim text (preview).

We claim: 1 . A method for automatic defect classification, the method comprises: acquiring, by a first camera, at least one first image of at least one area of an object; processing the at least one first image to detect a group of suspected defects within the at least one area; performing a first classification process for initially classifying the group of suspected defects; determining whether a first subgroup of the suspected defects requires additional information from a second camera for a completion of a classification; when determining that the first subgroup of the suspected defects requires additional information from the second camera then: acquiring second images, by the second camera, of the first subgroup of the suspected defects; and performing a second classification process for classifying the first subgroup of suspected defects. 2 . The method according to claim 1 comprising acquiring the second images without acquiring images of suspected defects that do not belong to the first subgroup of suspected defects. 3 . The method according to claim 1 wherein a throughput of the first camera exceeds a throughput of the second camera. 4 . The method according to claim 1 wherein a resolution of the first camera is coarser than resolution of the second camera. 5 . The method according to claim 1 wherein the first camera is a black and white camera and the second camera is selected out of an infrared camera, a near infrared camera and a three dimension profiler. 6 . The method according to claim 1 comprising maintaining the wafer on a chuck during the acquiring of the at least one first image, during the acquiring of the second images, and between the acquiring of the at least one first image and the acquiring of the second images. 7 . The method according to claim 1 wherein the determining is responsive to a difference between image acquisition parameters of the first camera and second camera. 8 . The method according to claim 1 wherein the determining is responsive to a criticality of the suspected defects. 9 . The method according to claim 1 wherein the determining is responsive to an accuracy of the first classification process. 10 . The method according to claim 1 wherein the determining is executed without human intervention. 11 . The method according to claim 1 wherein the determining is responsive to difference between a reliability, related to a type of suspected defect, of the first classification process and a reliability, related to a type of suspected defect, of the second classification process. 12 . A non-transitory computer program product that stores instructions that once executed by a computerized system cause the computerized system to execute the steps of: acquiring, by a first camera, at least one first image of at least one area of an object; processing the at least one first image to detect a group of suspected defects within the at least one area; performing a first classification process for initially classifying the group of suspected defects; determining whether a first subgroup of the suspected defects requires additional information from a second camera for a completion of a classification; when determining that the first subgroup of the suspected defects requires additional information from the second camera then: acquiring second images, by the second camera, of the first subgroup of the suspected defects; and performing a second classification process for classifying the first subgroup of suspected defects. 13 . The non-transitory computer readable medium according to claim 12 that stores instructions for acquiring the second images without acquiring images of suspected defects that do not belong to the first subgroup of suspected defects. 14 . The non-transitory computer readable medium according to claim 12 wherein a throughput of the first camera exceeds a throughput of the second camera. 15 . The non-transitory computer readable medium according to claim 12 wherein a resolution of the first camera is coarser than resolution of the second camera. 16 . The non-transitory computer readable medium according to claim 12 wherein the first camera is a black and white camera and the second camera is selected out of an infrared camera, a near infrared camera and a three dimension profiler. 17 . The non-transitory computer readable medium according to claim 12 that stores instructions for maintaining the wafer on a chuck during the acquiring of the at least one first image, during the acquiring of the second images, and between the acquiring of the at least one first image and the acquiring of the second images. 18 . The non-transitory computer readable medium according to claim 12 wherein the determining is responsive to a difference between image acquisition parameters of the first camera and second camera. 19 . The non-transitory computer readable medium according to claim 12 wherein the determining is responsive to a criticality of the suspected defects. 20 . The non-transitory computer readable medium according to claim 12 wherein the determining is responsive to an accuracy of the first classification process. 21 . The non-transitory computer readable medium according to claim 12 wherein the determining is executed without human intervention. 22 . The non-transitory computer readable medium according to claim 12 wherein the determining is responsive to difference between a reliability, related to a type of suspected defect, of the first classification process and a reliability, related to a type of suspected defect, of the second classification process. 23 . A system for automatic defect classification, the system comprises: a first camera that is constructed and arranged to acquire at least one first image of at least one area of an object; a second camera; at least one processor that is constructed and arranged to (i) process the at least one first image to detect a group of suspected defects within the at least one area; (ii) perform a first classification process for initially classifying the group of suspected defects; and (iii) determine whether a first subgroup of the suspected defects requires additional information from a second camera for a completion of a classification; when determining that the first subgroup of the suspected defects requires additional information from the second camera then: the second is constructed and arranged to acquire second images, by the second camera, of the first subgroup of the suspected defects; and the at least one processor is constructed and arranged to perform a second classification process for classifying the first subgroup of suspected defects.

Assignees

Inventors

Classifications

  • Grading and classifying of flaws · CPC title

  • based on image processing techniques · CPC title

  • of area, perimeter, diameter or volume · CPC title

  • Color image · CPC title

  • using sequentially two or more inspection runs, e.g. coarse and fine, or detecting then analysing · CPC title

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Frequently asked questions

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What does patent US2020141879A1 cover?
A method for automatic defect classification, the method may include (i) acquiring, by a first camera, at least one first image of at least one area of an object; (ii) processing the at least one first image to detect a group of suspected defects within the at least one area; (iii) performing a first classification process for initially classifying the group of suspected defects; (iii) determin…
Who is the assignee on this patent?
Camtek Ltd
What technology area does this patent fall under?
Primary CPC classification G06T7/001. Mapped technology areas include Physics.
When was this patent published?
Publication date Thu May 07 2020 00:00:00 GMT+0000 (Coordinated Universal Time) (A1). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).