公开(公告)号：US20250036030A1

公开(公告)日：2025-01-30

申请号：US18716111

申请日：2022-11-18

Applicant: ASML Netherlands B.V.

Inventor： Haoyi LIANG ,  Ye GUO ,  Zhichao CHEN

IPC: G03F7/00 ,  G03F1/84 ,  G06T7/00 ,  G06T7/30 ,  H01L21/66

Abstract: An improved method and system for image alignment of an inspection image are disclosed. An improved method comprises acquiring an inspection image, acquiring a reference image corresponding to the inspection image, acquiring a target alignment between the inspection image and the reference image based on characteristics of the inspection image and the reference image, estimating an alignment parameter based on the target alignment, and applying the alignment parameter to a subsequent inspection image.

公开(公告)号：US20240331115A1

公开(公告)日：2024-10-03

申请号：US18577678

申请日：2022-06-02

Applicant: ASML Netherlands B.V.

Inventor： Haoyi LIANG ,  Zhichao CHEN ,  Lingling PU ,  Fang-Cheng CHANG ,  Liangjiang YU ,  Zhe WANG

IPC: G06T5/80 ,  G06T7/00 ,  G06T7/33

CPC classification number: G06T5/80 ,  G06T7/001 ,  G06T7/337 ,  G06T2207/10061 ,  G06T2207/20081 ,  G06T2207/30148

Abstract: An improved systems and methods for correcting distortion of an inspection image are disclosed. An improved method for correcting distortion of an inspection image comprises acquiring an inspection image, aligning a plurality of patches of the inspection image based on a reference image corresponding to the inspection image, evaluating, by a machine learning model, alignments between each patch of the plurality of patches and a corresponding patch of the reference image, determining local alignment results for the plurality of patches of the inspection image based on a reference image corresponding to the inspection image, determining an alignment model based on the local alignment results, and correcting a distortion of the inspection image based on the alignment model.

公开(公告)号：US20240037890A1

公开(公告)日：2024-02-01

申请号：US18267748

申请日：2021-11-24

Applicant: ASML Netherlands B.V.

Inventor： Haoyi LIANG ,  Bing MA ,  Zhichao CHEN ,  Marc Jurian KEA

IPC: G06V10/24 ,  G06T3/40 ,  G06T5/00 ,  G06T7/50 ,  G06T7/62 ,  G06T7/70

CPC classification number: G06V10/24 ,  G06T3/40 ,  G06T5/002 ,  G06T7/50 ,  G06T7/62 ,  G06T7/70

Abstract: Systems and methods of image alignment are disclosed herein. The method of image alignment may comprise obtaining an image of a sample, obtaining information associated with a corresponding reference image, generating a modified rendered image by blurring a rendered image of the corresponding reference image such that a topology of the rendered image is substantially preserved, wherein a degree of blurring is based on a characteristic of the topology, and aligning the image of the sample with the blurred rendered image. The method may further comprise aligning the image of the sample with the corresponding reference image based on an alignment between the image of the sample and the blurred rendered image.

公开(公告)号：US20240331132A1

公开(公告)日：2024-10-03

申请号：US18577684

申请日：2022-06-03

Applicant: ASML Netherlands B.V.

Inventor： Haoyi LIANG ,  Yani CHEN ,  Ming-Yang YANG ,  Yang YANG ,  Xiaoxia HUANG ,  Zhichao CHEN ,  Liangjiang YU ,  Zhe WANG ,  Lingling PU

IPC: G06T7/00 ,  G01N23/2251 ,  G06T7/73

CPC classification number: G06T7/001 ,  G01N23/2251 ,  G06T7/0006 ,  G06T7/74 ,  G01N2223/6116 ,  G06T2200/24 ,  G06T2207/10061 ,  G06T2207/20081 ,  G06T2207/30148

Abstract: Systems and methods for detecting a defect on a sample include receiving a first image and a second image associated with the first image; determining, using a clustering technique, N first feature descriptor(s) for L first pixel(s) in the first image and M second feature descriptor(s) for L second pixel(s) in the second image, wherein each of the L first pixel(s) is co-located with one of the L second pixel(s), and L, M, and N are positive integers; determining K mapping probability between a first feature descriptor of the N first feature descriptor(s) and each of K second feature descriptor(s) of the M second feature descriptor(s), wherein K is a positive integer; and providing an output for determining whether there is existence of an abnormal pixel representing a candidate defect on the sample based on a determination that one of the K mapping probability does not exceed a threshold value.

公开(公告)号：US20220404712A1

公开(公告)日：2022-12-22

申请号：US17772529

申请日：2020-10-01

Applicant: ASML NETHERLANDS B.V.

Inventor： Qiang ZHANG ,  Yunbo GUO ,  Yu CAO ,  Jen-Shiang WANG ,  Yen-Wen LU ,  Danwu CHEN ,  Pengcheng YANG ,  Haoyi LIANG ,  Zhichao CHEN ,  Lingling PU

IPC: G03F7/20 ,  G06V10/774 ,  G06V10/82 ,  G06T7/32 ,  G06T7/33

Abstract: A method for training a machine learning model to generate a predicted measured image, the method including obtaining (a) an input target image associated with a reference design pattern, and (b) a reference measured image associated with a specified design pattern printed on a substrate, wherein the input target image and the reference measured image are non-aligned images; and training, by a hardware computer system and using the input target image, the machine learning model to generate a predicted measured image.